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Panels (a) and (b) are similar to (a) and (b) but for the Western United States and Mexico region. Equal weight and unequal weight schemes are used for (a) and (b), respectively; (c) and (d) are similar to (a) and (b) but for the trend in winter (December to February) precipitation; and (e) and (f) are similar to (c) and (d) but for the Mediterranean region
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This study compares two methods of multimodel averaging for the future projection of precipitation based on the classically defined absolute and relative climate changes. In the relative change scheme, the multimodel average of the percentage changes in precipitation is multiplied by the observed present climate to form the future projection; this...
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... draw additional motivation, Figure 1(a) shows the area-averaged summer (July to September) pre- cipitation versus the ratio of summer to annual pre- cipitation for a box in Southwest United States (indi- cated in Figure 3(a)) as simulated by CMIP3 models. ...
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... R j is a function of space, the impact of unequal weighting varies from one region to another.) For example, Figure 3(a) and (b) shows the detail of the trend of annual precipitation for Western United States and Northern Mexico based on the equal and unequal weight schemes, respectively. While both indicate drying in the Southwest United States (Seager et al., 2007), with the unequal weight scheme the reduction of precipitation is projected to be less severe for Arizona but more severe for part of Texas. ...
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... both indicate drying in the Southwest United States (Seager et al., 2007), with the unequal weight scheme the reduction of precipitation is projected to be less severe for Arizona but more severe for part of Texas. Over the black box in Figure 3(a), the projected reduction of rainfall is 40 mm/year from the unequal weight scheme, compared to 55 mm/year from the equal weight scheme. This difference may be large enough to have implications for local stake holders. ...
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... notable differences exist in the regional trend pat- terns. The trends in winter precipitation over the West- ern United States produced by the two schemes are compared in Figure 3(c) and (d). The shift of drying from Southwest United States to Texas produced by the unequal weight scheme is similar to the annual mean in Figure 3 e) and (f) shows the equal weight and unequal weight (relative change) results for the change in winter precipitation over the Mediterranean region (see Mariotti et al. (2008) for further background on the hydrological changes in this region). ...
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... trends in winter precipitation over the West- ern United States produced by the two schemes are compared in Figure 3(c) and (d). The shift of drying from Southwest United States to Texas produced by the unequal weight scheme is similar to the annual mean in Figure 3 e) and (f) shows the equal weight and unequal weight (relative change) results for the change in winter precipitation over the Mediterranean region (see Mariotti et al. (2008) for further background on the hydrological changes in this region). Just like Southwest United States, the unequal weight scheme not only preserves the large-scale pat- tern but also leads to some differences in the regional detail of the change. ...
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... Though the combined forecast formed by giving equal weights to each of the individual forecasts is acceptable for illustrative purposes (Elliott, 2011;Zounemat-Kermani et al., 2021). However, accumulating evidence suggests that one would want to give more weight to the set of forecasts that appear to have fewer (mean square) errors (Baker and Huang, 2012). Therefore, the Lagrange multiplier method (Yu et al., 2009) was used in this paper to establish the EML model, which has been widely applied and proven to be reliable (Yu et al., 2007;Yu et al., 2010). ...
... Focusing on North America, hydroclimate variability has been extensively studied from both observational and modeling analyses, including a number of studies for the Great Plains of the central United States during the warm season (e.g., Trenberth and Guillemot 1996;Barlow et al. 2001;Schubert et al. 2004;Ruiz-Barradas andNigam 2005, 2006;Feng et al. 2016) and for the western United States (Guan et al. 2010;Dettinger 2011;Baker andHuang 2012, 2014;Gershunov et al. 2017;Massoud et al. 2020a;McKinnon and Deser 2021). In this context, Cook and Seager (2013) noted a shift in the seasonality of the North American monsoon to late summer under global warming based on projections in CMIP5 models. ...
Observation-based climate model evaluation and future projections help policymakers in developing action plans for efficient management of water resources and mitigation of the impacts of hazardous extremes. Apart from this socioeconomic importance, the scientific value cannot be overstated, especially in light of the upcoming Fifth U.S. National Climate Assessment (NCA) report. In this study, we evaluate the realism of hydroclimate variability in the historical simulations of a suite of coupled general circulation models (CGCMs) participating in the Sixth and Fifth phases of the Coupled Model Intercomparison Project (CMIP6 and CMIP5). Our results demonstrate systematic biases in the simulated seasonal precipitation – most prominently, wet bias over the mountainous West in winter, and dry bias over the Central Plains in summer. A distinctive feature of this work is our focus on the examination of the atmospheric water budget, in particular, the relative importance of remote and local contributions – convergence of moisture fluxes and local land surface processes (evapotranspiration) respectively – in helping produce precipitation. This diagnosis reveals that the leading contribution of the remote influence in winter is overestimated by the CMIP6 multi-model mean (MMM), whereas the local influence which is more influential in summer is underestimated. Our results aid in understanding the drivers of seasonal precipitation over the U.S., where precipitation will likely increase by the end of the century but with significant model disagreement for the summer and fall. In support of ongoing NCA efforts, our study aims to contribute a comprehensive, regional-level analysis of the moisture budget and emphasizes the importance of realistically simulating its major components in CGCMs.
... The absolute change for air temperatures and both the absolute and relative changes for streamflow conditions were used to develop future climatic conditions using Eqs. 1, 2, and 3. Although the relative change approach has been widely adopted for estimating projected precipitation in climate change research (Andrishak and Hicks 2008;Navarro-Racines et al. 2020;Eum et al. 2017;Räty et al. 2014;Sunyer et al. 2015), absolute change has also been used in recent years to project future climate scenarios (Hudson and Thompson 2019;Baker and Huang 2012). Since streamflow also depends on temperature, which is projected based on the absolute change, the estimation of projected streamflow with absolute change can add a counter-intuitive perspective to the analysis. ...
Assessing the impact of future climate on the severity of ice jam floods (IJFs) is an essential component of a flood mitigation strategy for many ice jam-prone northern communities. The general circulation model (GCM) outputs are used to derive hydrological conditions under future climate scenarios. Although GCMs are often downscaled to the point of interest, there can still be significant differences between modelled climate scenarios and historically observed climate scenarios. Therefore, the changes between the model simulated baseline and future scenarios are applied to observed baseline values to derive projected future values. In IJF modelling, such projected values are provided as input (boundary conditions) to assess the frequency and severity of future IJF events. Different methods can be used to calculate the climate change signal (difference between model-simulated future vs model-simulated historical conditions), and depending upon the method employed, results can vary. In this study, we evaluate the impact of using different delta change methods (i.e., absolute vs relative) to directly bias-correct the hydrological model output on the assessment of frequency and severity of IJFs under future climate. The method was tested in the Athabasca River at Fort McMurray in western Canada, an ice jam-prone location, to assess the IJF probabilities and intensities in the 2041–2070 period. Our results indicate that there is a notable difference in the projected frequency and severity of IJFs between absolute and relative delta change approaches, suggesting the methods should be carefully selected and results cautiously interpreted.
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Uncertainties in future changes of temperature and precipitation over the homogenous monsoon regions of India are investigated using the CMIP5 and CESM-LE datasets. The uncertainty is partitioned into epistemic (model) and aleatoric (internal variability) components for each season using the RCP8.5 scenario. The uncertainty in temperature change is dominated by epistemic uncertainty that increases over time. The uncertainty in precipitation change shows a more complex picture. Aleatoric uncertainty can remain quite large and comparable to epistemic uncertainty till the latter part of the twenty-first Century especially during the JJA and SON seasons. Much of the rainfall uncertainty is in the more arid Northwest region with the West Central region (part of the core monsoon area) exhibiting lower uncertainties. Considerable increase in rainfall is seen during the SON season indicating an extended monsoon season. During the DJF season aleatoric uncertainty is much larger than epistemic uncertainty over much of the century and shows considerable decadal scale variability. Using the 40-member CESM-LE ensemble to analyze the influence of ensemble size on aleatoric uncertainty we find that low ensemble sizes can lead to an underestimate of the uncertainty.
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Projections of runoff from global multi-model ensembles provide a valuable basis for the estimation of future hydrological extremes. However, projections suffer from uncertainty that originates from different error sources along the modeling chain. Hydrological impact studies have generally partitioned these error sources into global impact and global climate model (GIM and GCM, respectively) uncertainties, neglecting other sources, including scenarios and internal variability. Using a set of GIMs driven by GCMs under different representative concentration pathways (RCPs), this study aims to partition the uncertainty of future flows coming from GIMs, GCMs, RCPs, and internal variability over the CONterminous United States (CONUS). We focus on annual maximum, median, and minimum runoff, analyzed decadally over the twenty-first century. Results indicate that GCMs and GIMs are responsible for the largest fraction of uncertainty over most of the study area, followed by internal variability and to a smaller extent RCPs. To investigate the influence of the ensemble setup on uncertainty, in addition to the full ensemble, three ensemble configurations are studied using fewer GIMs (excluding least credible GIMs in runoff representation and GIMs accounting for vegetation and CO2 dynamics), and excluding intermediate RCPs. Overall, the use of fewer GIMs has a minor impact on uncertainty for low and medium flows, but a substantial impact for high flows. Regardless of the number of pathways considered, RCPs always play a very small role, suggesting that improvement of GCMs and GIMs and more informed ensemble selections can yield a reduction of projected uncertainties.
The twentieth-century climatology and twenty-first-century trend in precipitation P, evaporation E, and P - E for selected semiarid U.S. Southwest and Mediterranean regions are compared between ensembles from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5). The twentieth-century simulations are validated with precipitation from observation and evaporation from reanalysis. It is found that the Special Report on Emissions Scenarios (SRES) A1B simulations in CMIP3 and the simulations with representative concentration pathways (RCPs) 4.5 and 8.5 in CMIP5 produce qualitatively similar seasonal cycles of the twenty-first-century trend in P - E for both semiarid regions. For the southwestern United States, it is characterized by a strong drying trend in spring, a weak moistening trend in summer, a weak drying trend in winter, and an overall drying trend for the annual mean. For the Mediterranean region, a drying trend is simulated for all seasons with an October maximum and July minimum. The consistency between CMIP3 and CMIP5 scenarios indicates that the simulated trend is robust; however, while the trend in P - E is negative in spring for the southwestern United States for all CMIP ensembles, CMIP3 predicts a strongly negative trend in P and minor negative trend in E whereas both CMIP5 scenarios predict a nearly zero trend in P and positive trend in E. For the twentieth-century simulations, the P, E, and P - E of the two model ensembles are statistically indistinguishable for most seasons. This stagnation of the simulated climatology from CMIP3 to CMIP5 implies that the hydroclimatic variable biases have not decreased in the newer generation of models. Notably, over the southwestern United States the CMIP3 models produce too much precipitation in the cold season. This bias remains almost unchanged in CMIP5.
