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The step-mountain eta coordinate model: Further developments of the convection, viscous sublayer, and turbulence closure schemes
Abstract
The step-mountain eta model has shown a surprising skill in forecasting severe storms. Much of the credit for this should be given to the Betts and Miller (hereafter referred to as BM) convection scheme and the Mellor-Yamada (hereafter referred to as MY) planetary boundary layer (PBL) formulation. However, the eta model was occasionally producing heavy spurious precipitation over warm water, as well as widely spread light precipitation over oceans. In addition, the convective forcing, particularly the shallow one, could lead to negative entropy changes. As the possible causes of the problems, the convection scheme, the processes at the air-water interface, and the MY level 2 and level 2.5 PBL schemes were reexamined. A major revision of the BM scheme was made, a new marine viscous sublayer scheme was designed, and the MY schemes were returned. The MY level 2.5 turbulent kinetic energy (TKE) is initialized from above in the PBL, so that excessive TKE is dissipated at most places during the PBL spinup. The method for calculating the MY level 2.5 master length scale was rectified. To demonstrate the effects of the new schemes for the deep convection and the viscous sublayer, tests were made using two summer cases: one with heavy spurious precipitation, and another with a successful 36-h forecast of a tropical storm. The new schemes had dramatic positive impacts on the case with the spurious precipitation. The results were also favorable in the tropical storm case. The developments presented here were incorporated into the eta model in 1990. The details of further research will be reported elsewhere. The eta model became operational at the National Meteorological Center, Washington, D.C., in June 1993. 60 refs., 8 figs.
... These changes reduced the overly energetic convection and improved the simulation of surface heat fluxes, precipitation, and extreme rain and temperature events. Koh and Fonseca (2016) developed a cloud diagnostic scheme, hereafter KF scheme, for use in a cumulus convection parameterization scheme of adjustment type such as the Betts-Miller-Janjic (BMJ) scheme (Betts & Miller, 1986;Janjic, 1994). They applied their scheme to the WRF model. ...
... The explicit clouds are represented by the Ferrier cloud microphysics scheme (Ferrier et al., 2002), which considers different types of hydrometeors. The convective parameterization scheme is the modified BMJ scheme (Betts & Miller, 1986;Janjic, 1994). ...
... In other words, EtaR-CMX should be more capable of capturing extreme rainfall events. The convective relaxation time , which is an adjustment time representative of the convective and unresolved mesoscale processes (Betts & Miller, 1986;Janjic, 1994), used in the four experiments was 3250 s (∼54 min). Several tests involving modifications in the relaxation time were realized; however, the changes showed little sensitivity in the production of total precipitation. ...
Convective clouds play an important role in the local energy budget by directly interacting with solar and terrestrial radiation. However, radiation parameterization schemes of atmospheric models generally consider clouds produced from microphysics schemes or some other grid saturation criteria. Deep convective parameterization schemes tend to rain out the convective cloud before the radiation scheme perceives its water load. This may be a source of the positive bias of the incoming solar radiation at the surface. The objective of this work is to include the effects of deep convective clouds in the radiation scheme of the regional Eta model and to evaluate the impacts on the net radiative energy and other meteorological variables. The radiation scheme is the Rapid Radiative Transfer Model. The work is developed in four stages. The positive bias in the incoming solar radiation was diagnosed in the first stage. In the second stage, the parameters of the convective parameterization scheme were modified to increase convective precipitation. In the third stage, the parameters of the microphysics scheme were modified to increase explicit clouds. In the fourth and last stage, in addition to the previous modifications, the condensates from the convective parameterization were input into the radiation scheme. The runs were performed for a period of one summer rainy month with intense convective activity over South America. Including deep convective cloud condensates into the radiation scheme improved the cloud cover, the diurnal cycle of the surface net radiation, and the 2‐m temperature. However, the reduction of the net radiation at the surface caused the reduction of the available energy for convective instability and, consequently, the precipitation reduction. The results show the importance of including cumulus cloud water load in the radiative scheme for bias reduction in the radiative energy components.
... Then, the microphysics option was fixed with the best scheme, and the longwave radiation option was changed from RRTMG to Goddard, 45,46) RRTM 47) and FLG. 48,49) Similar processes were performed for cumulus with BMJ, 35) Grell 3D 50,51) and New SAS, 52) and for PBL with YSU, 53) MYJ, 35) QNSE, 54) ACM2, 55) MYNN3, 32,33) UW 56) and GBM. 57) The surface layer was changed by following PBL, because its selection is briefly dependent on the PBL. ...
... Then, the microphysics option was fixed with the best scheme, and the longwave radiation option was changed from RRTMG to Goddard, 45,46) RRTM 47) and FLG. 48,49) Similar processes were performed for cumulus with BMJ, 35) Grell 3D 50,51) and New SAS, 52) and for PBL with YSU, 53) MYJ, 35) QNSE, 54) ACM2, 55) MYNN3, 32,33) UW 56) and GBM. 57) The surface layer was changed by following PBL, because its selection is briefly dependent on the PBL. ...
... RRTMG (Same as RRTMG of longwave radiation) FLG (Same as FLG of longwave radiation) Cumulus KF 38) Contains the large-scale convection process with time scale of downdrafts or convective available potential energy (CAPE). BMJ 35) Suitable for representing tropical cyclones and heavy rain. Grill 3D 50,51) Introduces the ensemble forecasting method and data assimilation technique. ...
Many Photovoltaic (PV) systems are connected to electric power grids, and the grids get risk of instability due to the fluctuations of PV output. Numerical Weather Prediction (NWP) models are used for forecasting the solar irradiance and proper grid management. NWPs usually have many physical parameterization options, and appropriate schemes of the options should be selected for accurate forecasting. The options should be changed by regional and climatic conditions and other factors. The target country is Thailand which is in the tropics. At there, cumulus and cumulonimbus appear frequently, and their behavior makes weather forecasting difficult. The optimal combination of schemes in the tropics is found through the sensitivity analysis of the options. By the optimization, the forecasting accuracy increases from 0.773 to 0.814 in correlation coefficient with the observation. It’s also found that contributions of surface layer and planetary boundary layer processes are significant for improvement of accuracy.
... Coastal regions are among the most susceptible areas to bear the impacts of the frequent storms. Ref. [7] conducted an analysis of a significant rainfall event that occurred on [17][18] March 2013, impacting the coastal regions of São Paulo and Rio de Janeiro, as well as the mountainous region of Rio de Janeiro, Brazil. This extreme event was caused by the passage of a cold front accompanied by strong winds at lower altitudes. ...
... Physical processes within the planetary boundary layer were represented using three distinct schemes: MYJ [18], which employs the Mellor-Yamada second-order closure turbulence model, accounting for turbulence in both steady and non-steady states, thereby suitable for a broad spectrum of meteorological conditions; YSU [23], a first-order parameterization utilizing a non-local mixing profile to depict turbulence within the planetary boundary layer, recognized for its effectiveness in modeling turbulence within thicker atmospheric layers, particularly beneficial for simulating free convection and stable conditions; lastly, MY-NN3 [33], an advanced third-order closure turbulence scheme that resolves prognostic equations for turbulent kinetic energy and its third-order fluxes. ...
This study assesses the performance of the Weather Research and Forecasting (WRF) model using a high-resolution spatial grid (1 km) with various combinations of physical parameterization packages to simulate a severe event in August 2021 in the southeastern Brazilian coast. After determining the optimal set of physical parameterizations for representing wind patterns during this event, a year-long evaluation was conducted, covering forecast horizons of 24, 48, and 72 h. The simulation results were compared with observational wind data from four weather stations. The findings highlight variations in the efficacy of different physical parameterization sets, with certain sets encountering challenges in accurately depicting the peak of the severe event. The most favorable results were achieved using a combination of Tiedtke (cumulus), Thompson (microphysics), TKE (boundary layer), Monin-Obukhov (surface layer), Unified-NOAH (land surface), and RRTMG (shortwave and longwave radiation). Over the one-year forecasting period, the WRF model effectively represented the overall wind pattern, including forecasts up to three days in advance (72-h forecast horizon). Generally, the statistical metrics indicate robust model performance, even for the 72-h forecast horizon, with correlation coefficients consistently exceeding 0.60 at all analyzed points. While the model proficiently captured wind distribution, it tended to overestimate northeast wind speed and gust intensities. Notably, forecast accuracy decreased as stations approached the ocean, exemplified by the ATPM station.
... 베타표류는 지향류와 함 께, 열대저기압의 이동 방향과 이동 속도를 결정하는 매우 중요한 요소이다 (Wang et al., 1998;Chan, 2005 (Ooyama, 1969;Chan and Williams, 1987;Bender et al., 1993;Williams and Chan, 1994;Wu and Wang, 2000;Magnusson et al., 2019;Chen et al., 2023). 특히, 이상적인 초기 조건 의 수치 실험을 통하여 베타표류의 이론적인 연구가 많이 수행되었으며, 다양한 배경 조건에 따른 베타자 이어의 특성을 분석한 연구가 활발히 이루어졌다 (Chan and Williams, 1987;Fionrino and Elsberry, 1989;Smith et al., 1990;Nam and Cheong, 2020 (Rosenthal, 1971;Landman et al., 2005;Goswami and Mohapatra, 2013 (Chan and Williams, 1987;Fiorino and Elsberry, 1989;Cheong et al., 2023 (Hong and Lim, 2006)을 사용하였으며, 적운 모 수화는 Kain-Fritsch 방법 (Kain, 2004), 행성경계층 모 수화는 Mellor-Yamada-Janjic 방법 (Janjic, 1994), 그 리고 지표층 모수화는 Eta surface layer 방법 (Janjic, 1994;1996;2002) (Fiorino and Elsberry, 1989;Lee et al., 2014;Cheong et al., 2023). ...
... 베타표류는 지향류와 함 께, 열대저기압의 이동 방향과 이동 속도를 결정하는 매우 중요한 요소이다 (Wang et al., 1998;Chan, 2005 (Ooyama, 1969;Chan and Williams, 1987;Bender et al., 1993;Williams and Chan, 1994;Wu and Wang, 2000;Magnusson et al., 2019;Chen et al., 2023). 특히, 이상적인 초기 조건 의 수치 실험을 통하여 베타표류의 이론적인 연구가 많이 수행되었으며, 다양한 배경 조건에 따른 베타자 이어의 특성을 분석한 연구가 활발히 이루어졌다 (Chan and Williams, 1987;Fionrino and Elsberry, 1989;Smith et al., 1990;Nam and Cheong, 2020 (Rosenthal, 1971;Landman et al., 2005;Goswami and Mohapatra, 2013 (Chan and Williams, 1987;Fiorino and Elsberry, 1989;Cheong et al., 2023 (Hong and Lim, 2006)을 사용하였으며, 적운 모 수화는 Kain-Fritsch 방법 (Kain, 2004), 행성경계층 모 수화는 Mellor-Yamada-Janjic 방법 (Janjic, 1994), 그 리고 지표층 모수화는 Eta surface layer 방법 (Janjic, 1994;1996;2002) (Fiorino and Elsberry, 1989;Lee et al., 2014;Cheong et al., 2023). ...
This paper investigates the sensitivities of track and beta-gyre of idealized tropical cyclones to various horizontal domain configurations of a limited-area numerical weather prediction (NWP) model. The idealized initial conditions of the model consist of a three-dimensional axisymmetric bogus vortex generated by empirical functions and the surrounding atmosphere using tropical mean soundings. The background flow is not considered in this study to focus on the effect of the model configurations on the idealized tropical cyclones. The Weather Research and Forecasting (WRF) model is used as the limited-area NWP model to perform sensitivity tests of the idealized tropical cyclones for different horizontal domain sizes and resolutions. To extract beta-gyre from the wind field of simulated tropical cyclones, a limited-area version of the double-Fourier series (DFS) high-order filter is employed. It is found that structure and intensity of the beta-gyre become weak with decreasing size of the horizontal domain, which results in differences in tropical cyclone tracks. When the domain size is set as 3,000 kmX3,000 km which is the smallest domain in our experiments, the westward wind component of ventilation flow is significantly decreased, and the tropical cyclone track is biased to the east compared with other experiments. This result implies that tropical cyclone tracks are not simulated properly with too small horizontal domains that cannot cover the entire flow field associated with tropical cyclones. On the other hand, the sensitivity is very small between 5,000 kmX5,000 km and 6,000 kmX6,000 km domains. Tracks of the idealized tropical cyclones are significantly biased to the west as the horizontal resolution decreases. The size and intensity of beta-gyre are also found to increase and strengthen for decreased resolution.
... The main physical parameterisations considered for the WRF run are the following: The Thompson scheme [24] was employed as a microphysics scheme; the Mellor-Yamada-Janjic turbulence kinetic energy scheme [25] was used as the boundary layer scheme, and the Dudhia scheme [26] and rapid radiative transfer model (RRTM) [27] were applied as shortwave and longwave radiative schemes, respectively. ...
The accurate prediction of heavy precipitation in convective environments is crucial because such events, often occurring in Italy during the summer and fall seasons, can be a threat for people and properties. In this paper, we analyse the impact of satellite-derived surface-rainfall-rate data assimilation on the Weather Research and Forecasting (WRF) model’s precipitation prediction, considering 15 days in summer 2022 and 17 days in fall 2022, where moderate to intense precipitation was observed over Italy. A 3DVar realised at CNR-ISAC (National Research Council of Italy, Institute of Atmospheric Sciences and Climate) is used to assimilate two different satellite-derived rain rate products, both exploiting geostationary (GEO), infrared (IR), and low-Earth-orbit (LEO) microwave (MW) measurements: One is based on an artificial neural network (NN), and the other one is the operational P-IN-SEVIRI-PMW product (H60), delivered in near-real time by the EUMETSAT HSAF (Satellite Application Facility in Support of Operational Hydrology and Water Management). The forecast is verified in two periods: the hours from 1 to 4 (1–4 h phase) and the hours from 3 to 6 (3–6 h phase) after the assimilation. The results show that the rain rate assimilation improves the precipitation forecast in both seasons and for both forecast phases, even if the improvement in the 3–6 h phase is found mainly in summer. The assimilation of H60 produces a high number of false alarms, which has a negative impact on the forecast, especially for intense events (30 mm/3 h). The assimilation of the NN rain rate gives more balanced predictions, improving the control forecast without significantly increasing false alarms.
... Therefore, this paper focuses on studying the impact of microphysical processes, planet boundary layer scheme, and cumulus parameterizations in the WRF model on rainfall simulation. Among them, YSU scheme and Mellor-Yamada-Janjic (MYJ) scheme are two typical planet boundary layer schemes (Janjic 1994). Microphysical schemes Purdue-Lin (Lin) and Single-Moment6 (WSM6) are two widely used schemes in the WRF model. ...
Based on numerical weather prediction model Weather Research and Forecasting (WRF) and Hydrologic Modeling System (HEC-HMS), a coupling model is constructed in Taihang Piedmont basin. The WRF model parameter scheme combinations composed of microphysics, planetary boundary layers, and cumulus parameterizations suitable for the study area are optimized. In both time and space, we tested the effects of the WRF model by a multi-index evaluation system composed of relative error, root meantime square error, probability of detection, false alarm ratio, and critical success index and established this system in two stages. A multi-attribute decision-making model based on Technique for Order Preference by Similarity to an Ideal Solution and grey correlation degree is proposed to optimize each parameter scheme. Among 18 parameter scheme combinations, Mellor-Yamada-Janjic, Grell-Devinji, Purdue-Lin, Betts-Miller-Janjić, and Single-Moment6 are ideal choices according to the simulation performance in both time and space. Using the unidirectional coupling method, the rolling rainfall forecast results of the WRF model in the 24 h and 48 h forecast periods are input to HEC-HMS hydrological model to simulate three typical floods. The coupling simulation results are better than the traditional forecast method, and it prolongs the flood forecast period of the Taihang Piedmont basin.
... The revised Monin- Obukhov similarity scheme was used, as it has been shown to simulate the surface fluxes well in all stability regimes in the study region (Hari Prasad et al., 2016). The other physics parameterizations include the Dudhia scheme for short-wave radiation (Dudhia, 1989) and rapid radiative transfer model (RRTM) scheme for long-wave radiation (Mlawer et al., 1997), WSM6 scheme for microphysics, and the Betts-Miller-Janjic (BMJ) scheme for convection (Janjic, 1994). No cumulus parameterization was used in the third and fourth domains. ...
Horizontal convective rolls (HCR) are sub-mesoscale motions that influence the transport of heat, momentum, and pollutants within the boundary layer. In this work, a high-resolution (0.666 km) Weather Research and Forecasting (WRF) model is employed to simulate the structure of the HCRs over Kalpakkam along the southeast coast of India. The sensitivity of HCR simulation to model land surface physics is studied with two land surface models (LSM), (i) Noah and (ii) Noah multi-parameterization (NMP), for three selected days (15 April 2013, 07 May 2015, 28 March 2018) during summer synoptic conditions. On all three selected days, the boundary layer rolls formed over a period of about 2–3 h in the morning under moderate winds (4–5.0 m/s), moderate vertical wind shear (2.4–3.5 m/s) in the lower atmosphere, and slightly unstable conditions [gradient Richardson number (RiG) −4.5 to −5.0] in both simulations and observations, indicating that thermal instability is the chief mechanism in their development. Simulated mean surface meteorological parameters by NMP were found to be in better agreement with observations than Noah. Results suggest that the LSMs mainly affected the simulated turbulent roll structure in terms of updraft cores and their horizontal and vertical extent by variation in simulated surface energy fluxes, boundary layer structure, wind shear, and stability. The structure of simulated HCRs is better represented by NMP due to the improvements in the flux distribution and surface properties. Simulations using the FLEXPART dispersion model for a hypothetical case of tracer release indicated an uneven spatial concentration pattern due to upward and downward motions in the region of HCRs. The stronger winds and stronger flow convergence in Noah and higher heat flux and more unstable conditions in NMP led to differences in the simulated tracer concentrations in the two cases.
... Simulations are conducted with the physics schemes identified by previous studies over the Southeast coast (Hariprasad et al. 2014;Hari Prasad et al. 2016;Srinivas et al. 2016). The selected physics parameterizations include the Dudhia scheme for short wave radiation (Dudhia 1989) and RRTM scheme for long wave radiation (Mlawer et al. 1997), Lin scheme for microphysics (Lin et al. 1983), MM5 surface layer similarity scheme for surface layer physics, Noah LSM for the land surface, YSU first order scheme (Hong et al. 2006) for PBL turbulence and BMJ scheme for convection (Janjic 1994) in the first and second domains (d01, d02). The land use /land cover is specified from MODIS data and terrain elevation and soil types are defined from the USGS and FAO data sets respectively. ...
This study aims to examine the recirculation effect of land and sea breeze flows on atmospheric releases from Chennai and Kalpakkam stations in Southeast coast of India using the WRF and FLEXPART models. High-resolution (2 km) simulations conducted with WRF for 4–6 April 2016 and 13–16 July 2016 showed development of sea breeze circulation under strong land–sea temperature contrast across the coast during daytime. Simulations conducted with FLEXPART in two scenarios of (1) 24 h continuous release, (2) release during sea breeze hours for SO2 from industrial sources at Manali in Chennai and routine low-level Ar-41 from a nuclear power reactor at Kalpakkam stations for 5 April and 14 July indicated considerable differences in SO2/Ar-41 concentrations in the two simulation cases. The simulated plume for 24 h release case showed wide dispersion pattern during flow transition compared to the case in which release is confined to onshore sea breeze hours. The recirculation effect is confirmed from low recirculation factor (0.1–0.3), simulated plume trajectory and particle distributions in the 24 h release case. The simulated SO2 concentrations are about 21 µg/m³ to 2 µg/m³ higher from release location to ~ 20 km in the 24 h release case compared to the release case during sea breeze. Simulated SO2 and Ar-41 concentration/doses at monitor locations during the flow transition period indicated better comparison with monitor data by 24-h release case compared to the release case during sea breeze. Although both simulations underestimated the concentration/dose due to stronger simulated winds, the 24 h release case produced higher concentration/cloud gamma dose by representing the recirculation effect. Overall, simulations suggest that the recirculation effect can lead to increase in the concentration /dose over land by 40% during the wind transition period at the coast.
... Therefore, this paper focuses on studying the impact of microphysical processes, planet boundary layer scheme, and cumulus parameterizations in the WRF model on rainfall simulation. Among them, Yonsei University (YSU) scheme and Mellor-Yamada-Janjic (MYJ) scheme are two typical planet boundary layer schemes (Janjic, 1994). Microphysical schemes Purdue-Lin (Lin) and Single-Moment6 (WSM6) are two widely used schemes in the WRF model. ...
Based on numerical weather prediction model Weather Research and Forecasting (WRF) and Hydrologic Modeling System (HEC-HMS), a coupling model is constructed in Taihang Piedmont basin. The WRF model parameter scheme combinations composed of microphysics, planetary boundary layers (PBL), and cumulus parameterizations suitable for the study area are optimized. In both time and space, we tested the effects of the WRF model by a multi-index evaluation system composed of relative error (RE), root meantime square error (RMSE), probability of detection (POD), false alarm ratio (FAR), critical success index (CSI) and established this system in two stages. A multi-attribute decision-making model based on TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) and grey correlation degree is proposed to optimize each parameter scheme. Among eighteen parameter scheme combinations, Mellor-Yamada-Janjic (MYJ), Grell-Devinji (GD), Purdue-Lin (Lin), Mellor-Yamada-Janjic (MYJ), Betts-Miller-Janjić (BMJ), Single-Moment6(WSM6) are ideal choices according to the simulation performance in both time and space. Using the unidirectional coupling method, the rolling rainfall forecast results of the WRF model in the 24h and 48h forecast periods are input to HEC-HMS hydrological model to simulate three typical floods. The coupling simulation results are better than the traditional forecast method, and it prolongs the flood forecast period of the Taihang Piedmont basin.
... WSM6 (Hong and Lim, 2006) Cumulus Betts-Miller-Janjic (Janjić, 1994;2000) Planetary boundary layer Mellor-Yamada Nakanishi and Niino L2.5 (Nakanishi and Niino, 2006) Longwave radiation RRTMG (Iacono et al., 2008) Shortwave radiation RRTMG (shortwave) (Iacono et al., 2008) Surface layer Monin-Obukhov (Janjic Eta) (Monin and Obukhov, 1954;Janjic, 1996) Land-atmosphere interaction Noah land surface model (Chen and Dudhia, 2001;Tewari et al., 2004) The atmospheric initial and boundary conditions were built from the Climate Forecast System Version 2 (CFSv2) reanalysis (Saha et al., 2014). CFSv2 has atmospheric variables at 39 vertical pressure levels with a horizontal resolution of 0.5 • , while the surface variables have a horizontal resolution of approximately 0.2 • , with 6 hr of temporal resolution. ...
Hydrostatic adjustment and vertical mixing are the two main mechanisms used to describe the stability of the marine atmospheric boundary layer (MABL) in oceanic regions with intense horizontal temperature gradients. To analyze the occurrence of these mechanisms, we performed simulations using an active coupled regional ocean–atmosphere numerical model in the southwestern Atlantic Ocean (SWA) region in October 2014 in the presence of an atmospheric frontal system. A novel in‐situ dataset was sampled by radiosondes in the Brazil–Malvinas Confluence (BMC) region and used with the model dataset. The vertical mixing mechanism and a prefrontal warm‐air temperature advection were identified, which modulated the shallower and more stable MABL. The hydrostatic adjustment mechanism was not evident because of the near‐surface wind convergence field modification caused by the large‐scale atmospheric system observed in our experiment. The coupled model simulation presented good agreement compared to in‐situ and satellite data. This contribution to the knowledge of the ocean–atmosphere interaction processes at the SWA reinforced that coupled models can be a helpful tool to investigate the air–sea interactions and physical mechanisms that explain MABL stability.
... Though there are many differences between the MYNN boundary layer scheme and the more commonly used Mellor-Yamada-Janjic TKE closure scheme (MYJ; Janjic 1990Janjic , 1994, the primary difference is that the former uses effects of stability on the turbulent length scale and closure constants that are obtained from LESs. This leads to an improved representation of TKE over a larger range of stability regimes. ...
The distribution of turbulent kinetic energy (TKE) and its budget terms is estimated in simulated tropical cyclones (TCs) of various intensities. Each simulated TC is subject to storm motion, wind shear, and oceanic coupling. Different storm intensities are achieved through different ocean profiles in the model initialization. For each oceanic profile, the atmospheric simulations are performed with and without TKE advection. In all simulations, the TKE is maximized at low levels (i.e., below 1 km) and ∼0.5 km radially inward of the azimuthal‐mean radius of maximum wind speed at 1‐km height. As in a previous study, the axisymmetric TKE decreases with height in the eyewall, but more abruptly in simulations without TKE advection. The largest TKE budget terms are shear generation and dissipation, though variability in vertical turbulent transport and buoyancy production affect the change in the azimuthal‐mean TKE distribution. The general relationships between the TKE budget terms are consistent across different radii, regardless of storm intensity. In terms of the asymmetric distribution in the eyewall, TKE is maximized in the front‐left quadrant where the sea surface temperature (SST) is highest and is minimized in the rear‐right quadrant where the SST is the lowest. In the category‐5 simulation, the height of the TKE maximum varies significantly in the eyewall between quadrants and is between ∼400 m in the rear‐right quadrant and ∼1,000 m in the front‐left quadrant. When TKE advection is included in the simulations, the maximum eyewall TKE values are downwind compared to the simulations without TKE advection.
... As variáveis prognosticadas são temperatura, vento horizontal, umidade específica, pressão à superfície, energia cinética turbulenta e hidrometeoros de nuvens. A precipitação convectiva é produzida pelo esquema Betts-Miller-Janjic (Betts & Miller, 1986;Janjic, 1994). Os processos de superfície são resolvidos pelo esquema Chen et al. (1997) e possui quatro níveis de solo. ...
Comparisons of Eta 5 km mesoscale model forecasts against observations in Cunha, Curucutu, Itanhaém, Paraibuna, Picinguaba, Santa Virgínia e São José dos Campos, located in Serra do Mar (SP) region, is carried out for 2008. The 2 m temperature, station level pressure, winds at 10 m and precipitation are evaluated for the 24 h, 48 h and 72 h forecasts. The results show that the atmospheric pressure was systematically underestimated (overestimated) in Paraibuna and Picinguaba (Cunha and Curucutu), due to differences between the model's altitude and the real station altitude, although its diurnal cycle is well predicted, with two maximum (0 and 12 Z) and two minimum (6 and 18 Z), as observed. For atmospheric pressure, model's performance is better at the 48 h forecast. The temperature's diurnal cycle is very well predicted. The temporal correlation between forecasts and observations are very high, varying from 73 to 91%. In some locations it was observed that temperature was overestimated (near 3ºC in Curucutu and Santa Virgínia and 2ºC in Itanhaém), and that it was a systematic error. The temperature forecasted 24 h in advance is superior than the other forecasts. In general the model shows a tendency of underestimate (overestimate) the frequence of occurrence of calm (strong) winds. The wind direction is the most difficult variable to forecast due probably to the differences between model's topography and the real topography. Although the model shows the characteristic turning of the wind during the day caused by the daily warming. The total monthly precipitation is well predicted, although in Itanhaém, Paraibuna and mainly in Picinguaba the values are overestimated. The frequence of occurrence of rainy events (total daily precipitation < 0,3 mm) is overestimated by the model, although it is the best predicted category, with higher ETS, BIAS and Hit. The analyses shows that one of the model's source of error is related to its topography.
... It is expected to have different results in terms of wind filed when different parameterizations are used. (Janjic 1994) Land Surface Unified Noah land-surface model (Ek et al. 2003) Longwave Radiation RRTM scheme (Mlawer et al. 1997) Shortwave Radiation Dudhia scheme (Dudhia 1989) Microphysics WRF Single-Moment 6-class scheme (Hong and Lim 2006) Here, physical parameterizations are selected based on several previous studies in the study area (Ghafarian et al. 2019;Gholami et al. 2021). Details of the model configuration and selected parameterizations are presented in Table 1. ...
The aim of this study is the evaluation of sources of wind energy in coastal and offshore regions of the Persian Gulf and Oman Sea. A series of simulations by the Weather Research and Forecasting (WRF) model and the Cross-Calibrated Multi-Platform (CCMP) satellite data were used and compared against the observed data during the period 2013–2017. Results indicate overestimation by the WRF model in most of the stations and underestimation of wind speed by the CCMP for relatively strong winds. Maximum and minimum wind speeds in the Persian Gulf occur in its southeastern and northwestern parts, respectively. Maximum wind speed over the Oman Sea occurs in its northeastern, central, and southeastern parts. Maximum extractable wind energy is from the Oman Sea, especially in the eastern parts and also, in some parts of the Sultanate of Oman coastal area.
... In terms of physical parameterization, we tested five convection schemes: Kain-Fritsch (KFETA;Kain, 2004), New-Tiedtke (NTIEDTKE; Zhang & Wang, 2017), New-Simplied Arakawa-Schubert (NSAS; Han & Pan, 2011), Betts-Miller-Janjic (BMJ;Betts, 1986;Betts & Miller, 1986;Janjíc, 1994), and Zhang-McFarlane (CAMZM; Zhang & McFarlane, 1995). We refer to H21 for a description of their main features. ...
... Multi-Scale Kain-Fritsch Scheme (Multi-scale KF) is based on KF but modified for different spatial scales (Zheng et al., 2016). In Betts-Miller-Janjic (BMJ) scheme, change in entropy, mean temperature and precipitation rate is incorporated (Janjic, 1990(Janjic, , 1994(Janjic, , 2000 for the deep convection profile. In Grell-Devenyi Ensemble Scheme, Grell and Devenyi (2002) University (YSU) PBL (Hong et al., 2006), Mellor Yamada-Janjic (MYJ) (Janjic, 1990(Janjic, , 2002, Bougeault-Lacarrere (Bougeault and Lacarrere, 1989), University of Washington (UW) (Bretherton and Park (2009). ...
A study of electrical and lightning properties of the premonsoon thunderclouds is carried out over the Northeastern and Eastern parts of India with the following objectives (i) To investigate the regional variation of the electrical and lightning properties of thunderclouds, in association with their cloud top temperature, vertical structure and cloud microphysical properties, (ii) To simulate the lightning and associated cloud microphysical, dynamical and thermodynamical properties of thunderclouds, (iii) To investigate the optimum atmospheric stability indices for detection of thundercloud day. For the present study, ground observations are carried out at Kohima (25.67o N, 94.08o E) in the Northeastern India and at Rampurhat (24.17° N, 87.78° E) in Eastern India. Kohima and Rampurhat are situated at an altitude of 1500 m and 40 m from the mean sea level respectively. The present study is a comprehensive multi-sensor approach. The observations from the ground-based electric field mills (EFM-100) and lightning detectors (LD-350) are utilized in synergy with the satellite onboard radiance observations from INSAT-3D. Apart from this, the observations, from Global Precipitation Measurement (GPM) and CloudSat satellites are also utilized to study the characteristics of vertical structure of reflectivity and cloud microphysics. Simulation study is carried out with the help of Weather Research and Forecasting (WRF) model.
The electrical and lightning observations reveal that, Kohima experiences more number of, thunderclouds, albeit of smaller size, compared to Rampurhat. Over Rampurhat, there is a relatively strong diurnal cycle of the occurrence of thunderclouds compared to Kohima. The electric field observations show larger values of step change in electric field (±ΔE) over Rampurhat compared to Kohima, which appeaently suggest larger charge transfer over Rampurhat. The lightning type distribution from the LD-350 shows significant regional variation in lightning characteristics, which signify the variability in the charge structure of the thunderclouds. Overall percentage occurrence of Cloud-to-Ground (CG) lightning is more over Kohima compared to Rampurhat. On the contrary, occurrence of Intra-Cloud (IC) lightning is more over Rampurhat compared to Kohima. It is also observed that, over both the stations, the occurrence of –CG lightning is more compared to +CG lightning. Overall, negatives discharges dominated over Kohima, whereas the opposite is observed over Rampurhat. The prevalence of positive as well as negative discharge from the thunderclouds suggests the presence of tripole charge structure of the thunderclouds over both the stations, with distinct characteristics. The result is broadly in agreement with the EFM-100 observations. The thunderclouds over Rampurhat are associated with higher lightning flash density compared to Kohima, suggesting that, the thunderclouds over Rampurhat are more severe compared to Kohima. Satellite radiance observations shows thunderclouds with colder clouds over Rampurhat compared to Kohima. Thunderclouds over Rampurhat are associated with stronger mixed phase processes compared to Kohima.
The simulation of thundercloud lightning and associated cloud and atmospheric properties is carried out with the help of WRF model in the month of April. It is found that, over both the region, though up to the median value, the simulated CG flash density are reasonably in good agreement with the observations, but over both the regions, the model simulation is not able to capture the extreme CG flash density. Nevertheless, the regional variability of the CG flash density is well captured by WRF simulation, with higher flash density over Rampurhat compared to Kohima, consistent with the observations. Simulation is able to capture the strong and weak diurnal variation of thundercloud occurrence over Rampurhat and Kohima respectively. The results also suggest that the performance of simulation of space-time evolution is better over Rampurhat compared to Kohima, suggesting more challenge to forecast the impending thunderclouds over the Northeastern part of India. The mean values of ice, graupel and cloud water mixing ratio are higher in the mixed phase region over Rampurhat compared to Kohima, suggesting a prevalence of stronger microphysical processes in the mixed phase region, a favorable condition for the lightning, consistent with the observations. The simulation results are able to capture the regional variation of total wind shear, with higher value over Rampurhat compared to Kohima. The performance of six stability indices namely, Lifting index (LI), K-Index, Total Total (TT) index, Severe Weather Threat (SWEAT) index, Convective Available Potential Energy (CAPE) and Convective Inhibition (CIN) were analyzed to find the optimum stability index to detect the thundercloud days over each region. Over Kohima, the optimum stability index TT ≥ 38o C shows the best skill scores, whereas over Rampurhat, the optimum stability index CAPE ≥1680 J kg-1 shows the best skill scores. The overall performance of the optimum stability indices were found to be better over Rampurhat compared to Kohima.
Overall, the present study provides a comprehensive understanding of the regional variability of the electrical and lightning properties of thunderclouds and associated microphysical, dynamical and thermodynamical properties over the Northeastern and Eastern parts of India. The simulated results are reasonably in good agreement with the observations. The present study will help to address the issues related to the lightning hazards and their mitigation in a better way.
Consequences of the mesoscale Thermal FeedBack (TFB) on the ocean dynamics are studied in the South‐East Pacific (SEP) using a high‐resolution regional ocean–atmosphere coupled model. Three simulations are compared: the first one is a fully coupled simulation. In the second one, the TFB has been removed with an online smoothing of the Sea Surface Temperature (SST) conditions used by the atmosphere. In the third one, to disentangle the impact of the nearshore and the offshore TFB, the smoothing is only applied in the offshore region. In the SEP, the coastal upwelling cold tongue constitutes a permanent mesoscale SST pattern. We show that this SST pattern alters the coastal wind structure, reducing the coastal upwelling‐favorable wind intensity. So, the nearshore TFB reduces the coastal surface current and the vertical velocities. As a result, the Eddy Kinetic Energy (EKE) generation by baroclinic conversion is also weakened. In the offshore region, on the contrary, the oceanic mean state is not affected by the TFB and only the EKE is weakened. Composites above the coherent eddies show that the heat flux response to the mesoscale SST anomalies is responsible for the mesoscale activity weakening over the whole studied area. Although the wind response to the SST anomalies has a very weak mean impact on the EKE generation through wind work, we show that it strongly modifies the mean oceanic vertical velocity anomalies over the coherent eddies.
Forecasting rainfall is essential for warning of issues and mitigating natural disasters. For this purpose, employing numerical weather models, even with their uncertainties, can generate reliable forecasts and guide decision-makers. The accuracy of a numerical model can be verified using statistical tools, and it is an essential procedure that needs to be made operationally, aiming to increase the forecasts' reliability. Numerical precipitation forecasts for the mountainous region of Rio de Janeiro, Brazil, were performed using the Weather Research & Forecasting model, configured with three spatial resolution grids of 9, 3, and 1 km, and combining different parameterizations for five physical processes: cloud microphysics, cumulus, planetary boundary layer, surface layer, and land surface. The period of interest was January 11th–12th, 2011, when significant rainfall accumulations originated the fatal natural hazards in Brazil. Analyses of the spatial distribution of rainfall and its temporal evolution were performed to evaluate the predictions from the quantitative and qualitative approaches. The results showed that the Kessler (cloud microphysics), MYNN3 (planetary boundary layer), Grell-Freitas, Betts-Miller-Janjic (cumulus) parameterizations, and the two highest resolution grids (at times, one was better than the other) had predicted the highest rainfall accumulations. From the initial results, this work reinforces the importance of forecast verification, especially considering different physical parameterizations and spatial resolutions since they can strongly influence the results. Also, it corroborates the importance of local numerical forecasts studies aiming to identify the best numerical configurations to forecast heavy rainfall events to alert decision-makers to the possibility of a natural hazard.
Prediction of thunderstorms with accurate space–time-intensity is still a challenging task in the tropical region. This paper examines the development of a pre-monsoon thunderstorm over a coastal urban city with an advanced 205 MHz VHF radar, and simulates the moist thermodynamical processes with the help of Weather Research and Forecasting model. The state-of-the-art VHF radar has been utilized to explore the dynamical features of the storm that occurred over Cochin, India on a typical pre-monsoon day. The thermodynamical processes have been simulated with different sets of microphysics-, cumulus-, and boundary layer- parameterization schemes. The performance of each combination of various parameterization schemes is examined in terms of correlation and standard deviation with the observations. Out of the 42 various combinations, it is found that the combination of Thompson microphysics-, Grell Freitas Ensemble cumulus-, and Meller Yamada Janjic planetary boundary layer- schemes is able to reproduce the moist thermodynamics better when compared with ground observations involving automatic weather station (AWS) and the VHF radar. The WRF model simulates the preconditioning of the atmosphere, mid-level blocking and release of convective instability, and moisture convergence in a reasonable manner. The identified physics suite is able to predict the storm development realistically and the study offers a reliable prospect of real-time prediction of thunderstorms over this region with the WRF model.
This study assesses the performance of the Weather Research and Forecasting (WRF) model using a high-resolution spatial grid (1 km) with various combinations of physical parameterization packages to simulate a severe event in August 2021 in the southeastern Brazilian coast. After determining the optimal set of physical parameterizations for representing wind patterns during this event, a year-long evaluation was conducted, covering forecast horizons of 24, 48, and 72 hours. The simulation results were compared with observational wind data from four weather stations. The findings highlight variations in the efficacy of different physical parameterization sets, with certain sets encountering challenges in accurately depicting the peak of the severe event. The most favorable results were achieved using a combination of Tiedtke (cumulus), Thompson (microphysics), TKE (boundary layer), Monin-Obukhov (surface layer), Unified-NOAH (land surface), and RRTMG (shortwave and longwave radiation). Over the one-year forecasting period, the WRF model effectively represented the overall wind pattern, including forecasts up to three days in advance (72-hour forecast horizon). Generally, the statistical metrics indicate robust model performance, even for the 72-hour forecast horizon, with correlation coefficients consistently exceeding 0.60 at all analyzed points. While the model proficiently captured wind distribution, it tended to overestimate northeast wind speed and gust intensities. Notably, forecast accuracy decreased as stations approached the ocean, exemplified by the ATPM station.
An eight-year satellite observation dataset reveals that sulfate aerosols significantly influence the vertical structure of precipitation and latent heat (LH) in the Beijing-Tianjin-Hebei (BTH) region during summer. In this period, prevalent sulfate aerosols combine with warm, humid southerly winds and elevated convective available potential energy (CAPE), influencing precipitation dynamics. Under polluted conditions with specific CAPE and precipitation top temperature (PTT) ranges, precipitation particles experience accelerated growth within the mixed-phase layer, delineated by the -5°C to 2°C isotherms, compared to pristine environments. This results in a marked increase in both the intensity and height at which the maximum LH is released. Subsequent analysis reveals that hygroscopic sulfate aerosols, acting as cloud condensation nuclei (CCN), amplify the collision-coalescence process within the mixed layer amid high cloud water content, propelling rapid precipitation particle growth and elevating the PTT. This warming effect surpasses the cooling contribution from robust CAPE, culminating in a net elevation of PTT under polluted scenarios compared to pristine ones. Additionally, quantification of PTT sensitivity to both CAPE and aerosol optical depth (AOD) unveils a high consistency between satellite-detected PTT responses to CAPE and those predicted by cloud-resolving model simulations. The study deduces that the role of aerosols as CCN in either invigorating or diminishing the collision-coalescence process is contingent on the available cloud water.
Simulation of stronger convergence of angular momentum in the boundary layer by the turbulent kinetic energy planetary boundary layer (PBL) schemes causes faster spin-up of the tropical cyclone (TC) vortex. We have conducted two experiments using local turbulent kinetic energy-based PBL parameterization schemes viz. Mellor-Yamada-Janjic (MYJ) and Bougeault-Lacarrere (Boulac) schemes have been used to analyze their impacts on the simulation of three TCs formed over the North Indian Ocean. The high-resolution (2 km) reanalysis has been developed by 6 hourly cyclic data assimilation using the Weather Research and Forecasting model (WRF) and data assimilation (WRFDA). The impact of PBL schemes has been investigated by comparing the developed reanalysis with the observations and IMD reanalysis. MYJ experiment showed lower bias in the simulation of genesis stage winds, variation in minimum sea level pressure, and rainfall distribution compared to the Boulac experiment. For TC Fani, Boulac experiments have more bias in the simulation of potential temperature at the lower troposphere. The Boulac experiment captured the high wind speed at the maximum intensity (MI) stage and the drastic increment in wind speed during the rapid intensification (RI). Both the schemes overestimated the RI of TC Fani. Whereas, for post-monsoon TCs Luban and Ockhi, the RI was more precisely captured by the Boulac experiment compared to the MYJ experiment. The successful simulation of intense wind speed at the MI stages by the Boulac experiment is attributed to the simulation of higher moisture flux and stronger updraft in the Boulac experiment.
The accuracy of the Weather Research and Forecasting Model (WRF) can be affected by multiple factors, including domain resolution, geostatic data, and model configuration. This study examined the sensitivity of simulated seasonal temperature to different geostatic data, horizontal domain resolutions, and configurations in Northeast Iran. During the investigation, the WRF model utilized Asymmetric Convective Model version 2 (ACM2) planetary boundary layer, WRF-single-moment-microphysics classes 6 (WSM6) Microphysic, Geophysical Fluid Dynamics Laboratory (GFDL) Long-wave/short-wave radiation parameterization schemes, and Climate Forecast System version2 (CFSV2) initial and boundary conditions from Nov 2019 to Feb 2020. The default (States Geological Survey (USGS)/ Moderate Resolution Imaging Spectroradiometer (MODIS)) and high-resolution (ASTER/Copernicus) geostatic data and inner domain resolutions 3 and 6 km were set for model simulation. The results revealed that following the physical configuration, the model simulation’s highest sensitivity was associated with the domain resolution and geostatic data. Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) had approximately similar results in the 6 km domain for both geostatic data, but the Mean Bias (MB) showed a cold Bias. The MB results were warmer when the horizontal resolution increased from 6 to 3 km. To obtain reliable temperature simulation, WRF was more sensitive to horizontal domain resolution than geostatic data. However, the accuracy of geostatic data affected the distribution of temperature patterns. A greater error appeared in the lower horizontal domain resolution (6 km) and low-resolution geostatic data (default), especially in complex terrains.
Strong wind events can cause severe economic loss and societal impacts. Peak winds over Wyoming and Colorado occur during the wintertime months, and in the first part of this two-part series, it was shown that the High-Resolution Rapid Refresh (HRRR) model displays large negative biases with respect to strong wind events. In this part of the study, we address two questions: 1) does increasing the horizontal resolution improve the representation of strong wind events over this region, and 2) are the biases in HRRR-forecasted winds related to the selected planetary boundary layer (PBL), surface layer (SL), and/or land surface model (LSM) parameterizations? We conduct Weather Research and Forecasting (WRF) Model simulations to address these two main questions. Increasing the horizontal resolution leads to a small improvement in the simulation of strong wind speeds over the complex terrain of Wyoming and Colorado. In general, changes in the PBL, SL, and LSM parameterizations show much larger changes in simulated wind speeds compared to increasing the model resolution alone. Specifically, changing from the Mellor–Yamada–Nakanishi–Niino scheme to the Mellor–Yamada–Janjić PBL and SL schemes results in nearly no change in the r ² values, but there is a decrease in the magnitude of the strong wind speed bias (from −12.52 to −10.16 m s ⁻¹ ). We attribute these differences to differences in the diagnosis of surface wind speeds and mixing in the boundary layer. Further analysis is conducted to determine the value of 1-km forecasts of strong winds compared with wind speed diagnostics commonly used by the National Weather Service.
Significance Statement
Motivated by prior studies showing low skill in the prediction of strong winds using state-of-the-art weather forecast models, in this study, we aim to investigate two questions: 1) does increasing the horizontal resolution improve the prediction of strong wind events over the complex terrain of Wyoming and Colorado, and 2) are the biases in High-Resolution Rapid Refresh (HRRR) forecasted winds related to the selected planetary boundary layer, surface layer, and/or land surface model parameterizations? We find that increasing the horizontal resolution provides a slight improvement in the prediction of strong winds. Further, considerable improvement in the prediction of strong winds is found for varying boundary layer, surface layer, and land surface parameterizations.
Vertical exchange between the atmospheric boundary layer (ABL) and free troposphere (FT) is a key link in coupling the earth's surface and upper atmosphere. This process is usually quantified by numerical simulations, while its reliability is not well assessed until now. Using space‐time intensified ABL observations, we evaluate the ABL‐FT air mass exchange flux derived from the Weather Research and Forecast (WRF) model. A six‐site sounding experiment is conducted in the North China Plain during the wintertime of 2019. The measured data is processed to provide enough information to derive the vertical exchange flux corresponding to the model‐based result, so that a systematic comparison is conducted. Three physical processes involved in ABL‐FT vertical exchange are quantitatively evaluated, that is, temporal variation of ABL height, advection across the inclined ABL top, and vertical motion at the ABL‐FT interface. Results show that the model‐based and observation‐based fluxes are generally agreed in temporal evolution (R = 0.67, p < 0.01), both characterized by 4–6 days periodicity and diurnal cycle. Their relative mean error was about 45% during the whole study period, mainly stemming from the vertical motion term and the advection crossing term. The model inaccuracy in representing these relevant processes at the ABL top is largely responsible for the discrepancy. Besides, the difference may also be attributed to the observational uncertainty (∼22%) that is caused by the measurement's difficulties in determining ABL spatial variation and acquiring vertical velocity. Through this study, the credibility and limitation of the WRF model in deriving ABL‐FT exchange flux are quantified.
In the framework of the coordinated regional modeling initiative Med-CORDEX (Coordinated Regional Climate Downscaling Experiment), we present an updated version of the regional Earth System Model ENEA-REG designed to downscale, over the Mediterranean basin, the models used in the Coupled Model Intercomparison Project phase 6 (CMIP6). The regional ESM includes coupled atmosphere (WRF), ocean (MITgcm), land (Noah-MP, embedded within WRF), and river (HD) components with spatial resolution of 12 km for the atmosphere, 1/12° for the ocean and 0.5° for the river rooting model. For the present climate, we performed a hindcast (i.e. reanalysis-driven) and a historical simulation (GCM-driven) over the 1980–2014 temporal period. The evaluation shows that the regional ESM reliably reproduces the mean state, spatial and temporal variability of the relevant atmospheric and ocean variables. In addition, we analyze the future evolution (2015–2100) of the Euro-Mediterranean climate under three different scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5), focusing on several relevant essential climate variables and climate indicators for impacts. Among others, results highlight how, for the scenarios SSP2-4.5 and SSP5-8.5, the intensity, frequency and duration of marine heat waves continue to increase until the end of the century and anomalies of up to 2 °C, which are considered extreme at the beginning of this century, will be so frequent to become the norm in less than a hundred years under the SSP5-8.5 scenario. Overall, our results demonstrate the improvement due to the high-resolution air–sea coupling for the representation of high impact events, such as marine heat waves, and sea-level height.
Keywords: Offshore wind energy WRF model Wind energy development Ecologically sensitive areas India A B S T R A C T This study focuses on assessing the offshore wind energy potential along the Indian Coast over a 10-year period (2005-2014) using high-resolution data from the simulation of the Weather Research and Forecasting (WRF) model. The predicted wind fields are utilized to identify potential sites, estimate offshore wind technical potential at different depths (ranging from 30 to 200 meters), and develop wind energy blocks within the Indian Exclusive Economic Zone. To ensure environmental protection, environmentally sensitive areas have been excluded from the offshore wind potential sites. The gross technical offshore wind potential was estimated to be 3941 GW within depths of 30-200 meters, excluding environmentally sensitive areas within the 0 to 30-m depth range. High-potential sites have been identified in the coastal states of Gujarat, Maharashtra, Kerala, and Tamil Nadu. The environmental offshore wind potential across these identified sites (feasible OWE sites) along the Indian coast is estimated at 432.34 GW within the 30 to 200-m depth range (at 140 m AGL). According to the report by the Central Electricity Authority (CEA), the predicted offshore wind power has the potential to significantly contribute to the country's total electrical power requirement for 2020-21. This study encourages exploration of offshore wind energy possibilities along the Indian coast and highlights the management challenges at suitable sites, including addressing potential conflicts between offshore wind energy development and other marine uses. The findings of this study can assist in the assessment of offshore wind resources and provide decision-makers with scientific evidence for the development of offshore wind energy in India, while also considering the management and conservation of marine ecosystems.
As an essential moisture transport channel over the Tibetan Plateau (TP), accurate simulation of precipitation over the southeastern TP (SETP) is crucial for downstream moisture transport and water resource assessment. To improve SETP’s precipitation simulation accuracy, a Turbulent Orographic Form Drag (TOFD) scheme, which represents the TOFD effect of subgrid orography on model grids, is employed. The impact of TOFD on cloud and precipitation during the summer monsoon over the SETP is investigated from dynamical and cloud microphysical perspectives. Through comparison with ground observations and satellite precipitation data, TOFD reduces the simulated precipitation bias. Despite reducing moisture transport, TOFD enhances low-level convergence and high-level divergence by influencing the low-level wind, thereby strengthening updraft and cloud and precipitation processes before the slope of SETP. TOFD also increases total precipitation before the slope by promoting heavy precipitation and reducing weak precipitation. However, TOFD diminishes the updraft and cloud and precipitation processes over the slope of SETP by influencing low-level wind. The reduced moisture transport by TOFD leads to decreased precipitation over the slope. Additionally, TOFD reduces total precipitation over the slope by promoting weak precipitation and reducing heavy precipitation. Furthermore, the impact mechanism of TOFD on precipitation depends on the wind speed, which is weakened during weak precipitation period with reduced wind speed and enhanced during heavy precipitation period with increased wind speed. These findings enhance the understanding of the complex terrain's influence on cloud and precipitation and provide a basis for improving cloud and precipitation simulation over the SETP.
The sea breeze is local thermal circulation along the coasts of large water bodies. The breeze occurs due to the different heating of water and land, as a result of different thermal conductivities of these surfaces. Breeze circulation occurs when temperature contrast water-land is well-pronounced, the most favorable conditions for its development being in anticyclonic fields and weak pressure gradient fields. The importance of the phenomenon is defined by its impact on different areas of our life and ecosystems and emphasized by the fact that about 50% of world's population lives and works in coastal strip of 200 km width. The regime of wind is studied with Weather Research and Forecasting (WRF) model for 3 cases of closed breeze cell. The modeled vertical profiles of wind speed, wind direction and vertical wind speed are compared with MFAS sodar data at meteorological observatory in Ahtopol. The comparison model-observations reveals that the used configuration of WRF qualitatively reproduces the observed wind fields, but with shifted in time characteristics, with different vertical scales of breeze cell and with lower vertical wind speed. Measurements for determining horizontal scale of the sea breeze are not available at the studied region, but this parameter (more than 65 km inland in summer) is evaluated based on model results.
The diurnal cycle is often poorly reproduced in global climate model (GCM) simulations, particularly in terms of rainfall frequency and amplitude. While improvements in the regional climate model (RCM) with bias‐corrected boundaries have been reported in previous studies, they assumed that diurnal patterns are simulated correctly by the GCM, potentially leading to inaccuracies in the maximum rainfall timing and magnitude within the RCM domain. Here we provide the first examination of improvements to the diurnal cycle, within a RCM domain, achieved through the use of sophisticated bias‐corrected lateral and lower boundary conditions. Results show that the RCMs with bias‐corrected boundaries generally present improvement in capturing both rainfall timing and magnitude, particularly in northern Australia, where a strong diurnal pattern in rainfall is prevalent. We show that correcting systematic sub‐daily multivariate bias in RCM boundaries improves the diurnal rainfall cycle, which is particularly important in regions where short‐term intense precipitation occurs.
The performances of six surface layer parameterizations in the latest Weather Research and Forecasting Model (WRF Version 4.5) are examined via observations at Yongxing Island, South China Sea. Three short-term simulations and two long-term simulations were carried out, and four statistical indicators were used to quantify the performance of different schemes. The statistical indicators suggested that all the surface schemes had a better accuracy in simulating surface wind than in simulating surface temperature and moisture. Meanwhile, the unresolved precipitation in the WRF model made significant increases in the model biases for all the schemes. Overall, the Global Forecast System surface scheme performed better in simulating surface variables than other schemes on nonrainy days in the study area. The simulation results also demonstrated that the diurnal SST cycle input could lead to remarkable improvements in the accuracy of the simulated surface heat fluxes and the temperature for all the schemes. The daily averaged determination coefficients between the simulation and observation results almost doubled, and the daily averaged root mean square error (RMSE), as well as the relative RMSE, were reduced by approximately half. However, the surface air specific humidity was not sensitive to the diurnal SST cycle, and only small improvements were identified in these simulations with the diurnal SST cycle. Therefore, the calculation module for the surface humidity in the surface schemes needs to be further optimized.
This study investigated the performance of the Weather Research Forecasting (WRF) model at 4‐km horizontal grid spacing in simulating precipitation, 2 m air temperature (T2), snowfall, and lake‐effect snow (October 4–8, 2018) over the Tibetan Plateau (TP). Multiple simulations with different physical parameterization schemes (PPSs), including two planetary boundary layer schemes (Yonsei University and Mellor–Yamada–Janjic), no cumulus and multi‐scale Kain‐Fritsch, two land surface models (Noah and Noah‐MP), and two microphysics schemes (Thompson and Milbrandt), were conducted and compared. Compared with gauge observations, all PPSs simulate mean daily precipitation with mean relative errors (MREs) of 27.7%–53.6%. Besides, spatial correlation coefficients (SCCs) between simulated and observed mean daily precipitation range from 0.56 to 0.71. For simulations of T2, all PPSs perform similarly well, even though the mean cold biases are up to about 3°C. Meanwhile, all PPSs exhibit acceptable performance in simulating spatial distributions of snow depth, snow cover, and snowfall amount, with SCCs of 0.37–0.65 between simulations and observations. However, the WRF simulations significantly overestimate snow depth (∼0.4 cm mean error) and snowfall amount (MREs >372%). The Milbrandt scheme slightly outperforms the other PPSs in simulating snow‐related variable magnitudes. Due to their inaccurate temperature and airflow modeling over the lake surface and its surroundings, none of the WRF simulations well reproduce the characteristics that more snow occurs over the lake and downwind area. Overall, this study provides a useful reference for future convection‐permitting climate modeling of snow or other extreme events when using the WRF model in the TP and other alpine regions.
This study aims to identify the optimal combination of microphysics (MP) and cumulus (CU) parameterization schemes for accurately simulating heavy to violet rainfall events associated with Tropical Cyclones (TCs) and atmospheric disturbances in Thailand using the coupled Weather Research and Forecasting (WRF) and Regional Oceanic Model (ROMS), hereafter referred to as WRF-ROMS. Three CU schemes, namely Betts–Miller–Janjic (BMJ), Grell 3D Ensemble (G3), and Kain–Fritsch (KF), along with three MP schemes, namely Eta (ETA), Purdue Lin (LIN), and WRF Single-moment 3-class (WSM3), are selected for the sensitivity analysis. Seven instances of heavy to violent rainfall in Thailand, occurring during summer season of 2020 and associated with tropical storms and atmospheric disturbances, are simulated using all possible combinations of the chosen physics schemes. The simulated rain intensities are compared against observations from the National Hydroinformatics Data Center. Performance was assessed using the Probability of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI) metrics. The models showed proficiency in predicting light to moderate rainfall, with certain combinations performing better in specific rainfall categories. However, forecasting heavy and violent rainfall proved challenging for all models and lead-time forecasts. Specific combinations, particularly those incorporating the KF scheme, demonstrated superior prediction of heavy to violent rainfall. The FAR values increased with lead-time and rain intensity, and the KF scheme combinations showed improved predictions of intense rainfall with lower FAR values. The CSI values indicated comparable performance between the control model and combination models across light to heavy rain categories, with the KF scheme showing better predictions for longer lead-times. However, accurately predicting intense rainfall remained limited. These findings highlight the need for further improvements, including refining model parameters and exploring advanced techniques to enhance accuracy and skill, particularly for longer-term forecasts. Sub-seasonal to seasonal prediction should be considered to extend forecast capabilities.
In the past few years during the pre-monsoon season, the Weather Research Forecast model coupled with Electricity (WRF-ELEC) has been used to forecast lightning activities over the North Eastern region of India. The model underestimated the events without lightning data assimilation and forecasted only a few cases. Instead, the model capability was significantly improved by assimilating lightning data. It can predict above 91% with a 0.78 success ratio in the lead-time of one hour. The validations have been done for 67 thunderstorm days with 870 cases. We noticed the model capable of forecasting up to 3–4 h with acceptable accuracy, which worsens after increasing the lead-time further. In addition, we found the WRF-ELEC biased to the places of lightning location once severe lightning activities over specific areas. That means the thunderstorm gets steady from the model though moving forward in reality. This study focused on assessing the capability of WRF-ELEC and found that it can forecast specified locations with actionable lead-time. The overall goal of this work is to show the present capability and limitations of using the WRF-ELEC model that may help to effectively operational lightning and rainfall warning.
The measurements of an urban-rural observation network in Hannover obtained over almost four years were used to analyse a canopy layer urban heat island (UHIUCL). Especially during the summer months, the UHIUCL was pronounced on numerous nights with maximum values of more than 6 K. We have demonstrated that the choice of rural reference station is important to describe a UHIUCL in detail. The time evolution of UHIUCL differed greatly from night to night and four main types could be identified with comparable frequencies of occurrence. The difference between these types was the appearance of the maximum urban heat island intensity during very different times of the night. The main drivers for the development of a specific type were the rural winds and rural temperature changes caused by turbulent mixing within the near-surface inversion.
The selection of physical parameterization schemes for tropical cyclone (TC) forecasts has required a substantial amount of effort. In general, the evaluation of physical parameterization schemes and their combined performance was based solely on the deterministic forecast, which had inherent limitations in representing the overall performance of physical parameterization schemes due to the model uncertainty. This study introduces an uncertainty‐informed framework of evaluating and selecting the combination of physical parameterization schemes for TC forecasts, based on the ensemble forecast that could include the model uncertainty roles. The performance ranking of the scheme combination based on the ensemble mean error is found to be distinct from that based on the deterministic forecast error. Moreover, differences in both ensemble mean errors and ensemble spreads for various scheme combinations highlight the importance of considering two metrics concurrently, that is, via the quality of the forecast distribution as a whole, to assess the forecast performance. Consequently, the ensemble Continuous Ranked Probability Score (eCRPS) is used to quantify the performance of the scheme combinations, and it is demonstrated that the performance is more comprehensive than that in the deterministic context. Finally, the well‐performed scheme combination for the forecasts of six intense TCs is chosen from the evaluated schemes in the context of model uncertainty, based on the overall quality of TC track and intensity forecast distributions.
A comprehensive attempt has been made to simulate the characteristics of monsoon deep depressions (MDD) originating over the Bay of Bengal (BoB) basin, with special emphasis on their rainfall using a coupled ocean–atmospheric model, that is, the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model, and a stand‐alone atmospheric model, that is, the Weather Research and Forecasting (WRF) model, with a lead time of up to 72 hr. It is to be noted that COAWST employs WRF as its atmospheric component, while the Regional Ocean Modeling System (ROMS) is used as the oceanic component. It is found that though the tracks of the four MDDs considered have been reasonably simulated, the intensity was overestimated in both sets of simulations compared to India Meteorological Department (IMD) best estimates. Decomposition of the contributors to rain rate for the composite of the storms in the deep depression (DD) phase revealed that the moisture sources/sinks (Qm) are the major component in modulating the rain rate compared to the cloud sources/sinks. Further analysis of Qm suggested that vertical and horizontal advection of moisture forms the leading contributors to Qm. Validation against Modern Era Retrospective‐Analysis for Research and Analysis (MERRA) reanalysis showed that COAWST captured a more realistic evolution of Qm (specifically vertical advection) compared to its stand‐alone counterpart. Investigation of the composite storm energetics in a vortex‐following control volume showed a scarcity of bulk kinetic energy (volume‐integrated kinetic energy over the control volume) in the later hours of the DD phase in COAWST which led to the dissipation of the storm core, unlike in WRF, where a re‐intensification took place through condensational heating. It is inferred that in spite of the stand‐alone atmospheric model capturing the moisture incursion from the lateral boundaries in the lower levels significantly, the better representation of the vertical structure in COAWST led to more realistic simulations of the storms, increasing the skill in rainfall prediction.
The morphology and grid resolution are important aspects that need to be considered in urban modeling applications, since together with buildings they induce a direct effect on wind and dispersion of pollutants over urban areas. In this study we evaluate high resolution simulations of a multi-layer Urban Canopy Model (UCM) based on Local Climate Zone (LCZ) classification coupled to the Weather Research and Forecasting model with Chemistry (WRF-Chem) in the local meteorological conditions and air quality pollutants of a highly urbanized megacity. This modeling system known as Building Effect Parameterization (BEP) takes into account the buildings vertical and horizontal surfaces effects on the momentum that considerably impact on the lower part of the Urban Boundary Layer (UBL). Simulations of urbanized model (WRFu) were compared against a Noah land surface model (Noah LSM) with no urban physics (WRF) for the same period. It was observed that LCZ classification and urban parameterization coupled to the model have a direct influence in meteorological parameters and pollutant concentrations. Urban simulations of temperature and wind speed showed a major sensitivity to initial and boundary conditions, increasing correlation with observations and reducing bias error. An important aspect found is that emissions drive air quality concentrations despite the improvements in local meteorology.
Improving modeling capacities requires a better understanding of both the physical relationship between the variables and climate models with a higher degree of skill than is currently achieved by Global Climate Models (GCMs). Although Regional Climate Models (RCMs) are commonly used to resolve finer scales, their application is restricted by the inherent systematic biases within the GCM datasets that can be propagated into the RCM simulation through the model input boundaries. Hence, it is advisable to remove the systematic biases in the GCM simulations prior to downscaling, forming improved input boundary conditions for the RCMs. Various mathematical approaches have been formulated to correct such biases. Most of the techniques, however, correct each variable independently leading to physical inconsistencies across the variables in dynamically linked fields. Here, we investigate bias corrections ranging from simple to more complex techniques to correct biases of RCM input boundary conditions. The results show that substantial improvements in model performance are achieved after applying bias correction to the boundaries of RCM. This work identifies that the effectiveness of increasingly sophisticated techniques is able to improve the simulated rainfall characteristics. An RCM with multivariate bias correction, which corrects temporal persistence and inter-variable relationships, better represents extreme events relative to univariate bias correction techniques, which do not account for the physical relationship between the variables.
Abstract Depicting Secondary Eyewall Formation (SEF) and Eyewall Replacement Cycle (ERC) in a numerical model is important for tropical cyclone (TC) forecasting. However, there is no consensus about what resolutions are appropriate to describe SEF/ERC within a full‐physics mesoscale model. In this study, numerical experiments are conducted to examine the impact of the horizontal and vertical resolutions on SEF/ERC. The mesoscale model is configured through nesting to the horizontal grid spacings of 6, 4, 2, 1.33, 0.67‐km, and with 27‐ and 54‐levels on an f‐plane in a quiescent environment. In addition, there are more levels below 1.5‐km to better describe the TC boundary layer (TCBL). The simulations with 6 and 4‐km grid spacings show no obvious SEF/ERC regardless of the number of vertical levels. When the horizontal grid spacings decrease to 2‐km or smaller, the simulations manifest SEF/ERC. These results are supported by a few simulations with the ARW model using similar configurations. Furthermore, the spectra of kinetic energy and vertical velocity from various resolutions confirm that the grid spacings should be smaller than 4‐km to resolve SEF/ERC. The impact of doubling vertical levels on the SEF/ERC is not as significant as doubling the horizontal resolutions. Finally, we discuss the coupling between the balanced/unbalanced flows (above/in the TCBL), and their effect on SEF. It is proposed that the coupled balanced/unbalanced processes that generate the quasi‐steady cooling zone in the primary eyewall and two warming regions inside and beyond the cooling zone are essential for SEF.
In mountainous regions, the height of the atmospheric boundary layer (ABL) plays a crucial role in accurately simulating the wind field. In order to uncover the correlation between the complex terrain and the ABL height, the required samples were obtained via the WRF experiment taking a mountainous region in Southwestern China as the research object. The Pair-Copula decomposition method was then employed to create a trivariate joint distribution model of the atmospheric boundary layer elevation, the terrain elevation, and the surface relief degree based on the samples. The trivariate joint distribution model shows that the ABL field fluctuates more in the regions with higher surface undulation and less in the regions with lower surface undulation. Furthermore, the model can be used to evaluate the probability distribution of the ABL height over the complex terrain where a projected bridge will locate, thereby providing a more reasonable inlet boundary to simulate the wind environment surrounding the bridge. The method presented here for correlating the ABL height with terrain is universal and can be extended to wind field simulation in many regions.
Seasonal rainfall forecasts generated with regional Eta model for the rainy season of the São Francisco River Basin, upstream Hydroeletric Power Plant (HPP) Três Marias in Minas Gerais are evaluated in this work. The use of such forecasts as an input in energy planning models, represent a better management in the generation, transmission and distribution of electricity. However, it is well known that most of the globe, seasonal climate predictability is much reduced, since the effects of boundary conditions to determine the evolution of the average state of the atmosphere compete with internal variability associated with the chaotic instabilities and nonlinear interactions of the atmospheric flow. The forecasts of the Eta-Seasonal-15km model are initiated on days 13 to 17 October, extending until February 28, during the years 2001-2010. The evaluation results indicate that the noise (inter members variability) is higher than the signal (interannual variability), suggesting low reliability of the forecasts for the region during the rainy season. Forecasts of precipitation are underestimated and the Root Mean Square Error of 77.03 mm / month is high, almost twice its standard deviation. Note A high spatial variability of rainfall due to very steep topography, which further reduces the performance of numerical models. A hit rating category of precipitation (IACP), based on the distribution of tertiles, was applied to account for the number of times that the forecasts point to the same category of observed rainfall: rainfall below, within or above the normal range. The IACP for the whole area and during the ten years was low (mean 29%), however in the southern Basin IACP is a bit higher, around 50% to 70% in the Southeast region. The annual review of the forecasts for the entire area indicated that the best model performance occurred in 2005, when conditions ATMS negative in Pacific, near the coast of Peru were persisted in October 2005 and in fact such anomalies occurred through the month of February 2006.
Super cyclonic storm Amphan (2020), formed over the Bay of Bengal, has been forecasted using the mesoscale model WRF to examine the rapid intensification (RI) features in the model forecast. The special surface and upper air weather observational campaigns were arranged from ISRO’s Balasore observatory during the life cycle of Amphan. Along with these observations, forecasts have been validated with the available surface and upper air observations along the east coast of India, the GPM-IMERG rainfall observations, and the ECMWF Reanalysis-5 (ERA-5) reanalysis. The dynamical parameters, viz. low-level convergence, middle tropospheric humidity, and diabatic heating in the middle troposphere, have been compared with reanalysis. It is seen that up to 124-h forecasts of track and intensities have significantly improved And the surface and upper air parameters forecast is reliable for up to 48 h. The study showed that the high SST in the range 30–31 °C along the track of the TC, TCHP range of 60–70 kJ cm−2, ~ 100% Mid-tropospheric relative humidity (MTRH), enhanced diabatic heating in the rainband region. Intense rainfall in the front left quadrant of the system favored the rapid intensification of Amphan. Because of the large size, high shear (10–25 ms−1) is ineffective in hindering the system’s intensification process. The wind variation during the system’s landfall is also well captured, and 24 h forecast agrees with the observed data. The appropriate representation of vertical wind shear required for realistic simulation of axisymmetric, asymmetric, and landfall dynamics, is also evident from campaign observations.
This paper is aimed at performing a group of experiments to evaluate the sensitivity to cumulus and microphysics schemes, as represented in numerical simulations of the Weather Research and Forecasting (WRF) model. The convective schemes of Kain-Fritsch (KF), Betts-Miller-Janjic (BMJ), Grell-Devenyi (GD), Grell-Freita (GF), Grell 3D (G3D), Tiedtke and New Tiedtke (NT) were tested in association with the microphysics schemes of Kessler, Purdue Lin, WSM3, WSM5, WSM6, ETA (Ferrier) and Goddard (totaling forty-nine experiments) in order to identify the combination which best represents the cumulative rainfall distribution in the Paraíba do Sul watershed. In order to evaluate the best performance experiments, they were submitted to statistical tests of bias (BIAS), root mean square error (RMSE), absolute mean error (MAE) and Coefficient of Determination (R2). Results show that combinations WSM5 and GD; Goddard and G3D; Perdue Lin and G3D; WSM5 and G3D form a group of four physical configurations statistically similar and able to predict well the mean rainfall in the Paraiba do Sul watershed. It was noticed also that the cumulus scheme has a greater weight than microphysics in rainfall simulations being GD3 the best performing.
In this article, precipitation in a new regional reanalysis dataset, namely, the East Asia regional reanalysis system (EARS‐CMA) with a 12‐km resolution based on the Weather Research and Forecast (WRF) model, ERA‐Interim, ERA5, TRMM 3B42V7, Climate Prediction Center Morphing Technique (CMORPH) and CN05.1, is compared in 2008–2017. The results show that EARS‐CMA can capture the spatial features and temporal variation in precipitation over East Asia well. Focusing on mainland China, CMORPH performs worse in regard to winter precipitation and dryer areas than TRMM against CN05.1. Although ERA5 behaves better with integrated properties compared with ERA‐Interim and EARS‐CMA over East Asia, EARS‐CMA produces more reliable annual, summer and winter mean precipitation pattern than ERA5 over the subregions dominated by large scales in mainland China, including the Tibetan Plateau and northwestern China, similar to its driving fields, ERA‐Interim. In addition, the improvement from ERA‐Interim to EARS‐CMA can be obtained in reasonably reproducing precipitation seasonality in South China, Indo‐China and southern Japan. Thus, the compatibility of EARS is outstanding in maintaining the advantages of its corresponding driving fields, ERA‐Interim, as well as developing finer small scales. Although slightly behind ERA5 in the subregions affected by tropical systems and monsoons, EARS‐CMA is competitive in acting as reference data for daily, seasonal, annual and interannual precipitation estimations over mainland China.
The Tibetan Plateau and its surrounding mountains have an average elevation of 4,400 m and a glaciated area of \(\sim \)100,000 \(\hbox {km}^{2}\) giving it the name “Third Pole (TP) region”. The TP is the headwater of many major rivers in Asia that provide fresh water to hundreds of millions of people. Climate change is altering the energy and water cycle of the TP at a record pace but the future of this region is highly uncertain due to major challenges in simulating weather and climate processes in this complex area. The Convection-Permitting Third Pole (CPTP) project is a Coordinated Regional Downscaling Experiment (CORDEX) Flagship Pilot Study (FPS) that aims to revolutionize our understanding of climate change impacts on the TP through ensemble-based, kilometer-scale climate modeling. Here we present the experimental design and first results from multi-model, multi-physics ensemble simulations of three case studies. The five participating modeling systems show high performance across a range of meteorological situations and are close to having ”observational quality” in simulating precipitation and near-surface temperature. This is partly due to the large differences between observational datasets in this region, which are the leading source of uncertainty in model evaluations. However, a systematic cold bias above 2000 m exists in most modeling systems. Model physics sensitivity tests performed with the Weather Research and Forecasting (WRF) model show that planetary boundary layer (PBL) physics and microphysics contribute equally to model uncertainties. Additionally, larger domains result in better model performance. We conclude by describing high-priority research needs and the next steps in the CPTP project.
This study, a work used to distinguish the dispersion patterns of air pollutants, is designs particularly NO X because of vehicular and modern sources over a quickly creating metropolitan city, Nagpur (21.15°N, 79.09°E), India, during winter and summer representative months, that is, January and April respectively in 2009. Utilizing the emission variables of industry and various vehicles, 1 km x 1 km high-resolution Gridded Emission Inventory (GEI) has produced over Nagpur city. Here, two PBL schemes form WRF model viz., local (MYJ) and non-local (YSU) schemes considered for obtaining the PBL as well as meteorological parameters. Both the schemes MYJ and YSU representing the boundary layer parameters are reasonably well and measured for generating the input parameter for AERMOD model. During the winter and summer month's fundamentally unique scattering patterns of NO X have been observed. After carefully examining the NO X concentration from the AERMOD model, the reasonable well-by integrated YSU schemes of WRF were found to be superior to the other schemes. The current review advocates the utility of the created GEI of NO X with coupled AERMOD-WRF offline model for air quality appraisal over Nagpur.
This study investigates the mesoscale dynamics involved in the 8–11 October 2008 unseasonably strong African dust episode, during which dust was transported to the Iberian Peninsula (IP). We employ observational datasets and a high‐resolution Weather Research and Forecasting model coupled with Chemistry simulations. The analysis shows that during 0900–1200 UTC 9 October, a mesoscale convective system developed over the Atlas Mountains and resulted in a southwestward propagating convective cold pool outflow on the southern foothills of the Anti‐Atlas, which lifted dust from the source region. Between 1200 and 1800 UTC 9 October, new moist convection was enhanced over the Atlas Mountains due to intensifying confluence among a heat low, moist southwesterly Atlantic sea‐breeze front, and northeasterly flow associated with the convective cold pool near western Algeria. This new moist convection intensified the strength of the convective cold pool outflow and haboob, both of which continued propagating southwestward. At 1200 UTC 10 October, the low‐pressure system migrated poleward on the southern slopes of the Anti‐Atlas Mountains in association with a mountain‐plains solenoidal circulation due to the daytime differential heating between the southern slopes of the Anti‐Atlas and nearby atmosphere. The deepening low‐pressure and strengthening Atlantic sea‐breeze redirected an equatorward advancing dust plume into the poleward direction. The dust plume ultimately crossed the Saharan Atlas Mountains on 11 October and finally impacted the IP.
The projected increase in the frequency of extreme rainfall events with climate change has serious implications for flood risk management. This study developed a novel method to evaluate future flood inundation risk in the Kakehashi River basin, Japan. First, a pseudo global warming (PGW) method and ensemble simulation techniques were combined to develop rainfall projections with different return periods, based on the Weather Research and Forecasting (WRF) model. Second, runoff analyses were performed for the target river basin, and inundation simulations, including levee breaches, were conducted at high spatial resolution (40 × 40 m). Finally, the potential inundation risk for the river basin was estimated. Rainfall simulation results indicated intensification of short-duration heavy rainfall events. The PGW ensemble simulations indicated that extreme rainfall scenarios with long return periods (>1000 years, based on current conditions) are likely to occur more frequently in the future, highlighting the possibility of flood intensification. Regardless of the length of return period, areas with infrequent flooding but large inundation depth and those with more frequent flooding but small inundation depth were classified as high risk. The proposed method provides a baseline framework for future flood risk assessments and the results highlight the importance of incorporating (currently) rare heavy rainfall events in future flood management evaluation and planning.
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