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A Climate Change Simulation Starting From 1935
Abstract and Figures
Due to restrictions in the available computing resources and a lack of suitable observational data, transient climate change experiments with global coupled ocean-atmosphere models have been started from an initial state at equilibrium with the present day forcing. The historical development of greenhouse gas forcing from the onset of industrialization until the present has therefore been neglected. Studies with simplified models have shown that this cold start error leads to a serious underestimation of the anthropogenic global warming. In the present study, a 150-year integration has been carried out with a global coupled ocean-atmosphere model starting from the greenhouse gas concentration observed in 1935, i.e., at an early time of industrialization. The model was forced with observed greenhouse gas concentrations up to 1985, and with the equivalent C02 concentrations stipulated in Scenario A (Business as Usual) of the Intergovernmental Panel on Climate Change from 1985 to 2085. The early starting date alleviates some of the cold start problems. The global mean near surface temperature change in 2085 is about 0.3 K (ca. 10%) higher in the early industrialization experiment than in an integration with the same model and identical Scenario A greenhouse gas forcing, but with a start date in 1985. Comparisons between the experiments with early and late start dates show considerable differences in the amplitude of the regional climate change patterns, particularly for sea level. The early industrialization experiment can be used to obtain a first estimate of the detection time for a greenhouse-gas-induced near-surface temperature signal. Detection time estimates are obtained using globally and zonally averaged data from the experiment and a long control run, as well as principal component time series describing the evolution of the dominant signal and noise modes. The latter approach yields the earliest detection time (in the decade 1990–2000) for the time-evolving near-surface temperature signal. For global-mean temperatures or for temperatures averaged between 45N and 45S, the signal detection times are in the decades 2015–2025 and 2005–2015, respectively. The reduction of the cold start error in the early industrialization experiment makes it possible to separate the near-surface temperature signal from the noise about one decade earlier than in the experiment starting in 1985. We stress that these detection times are only valid in the context of the coupled model's internally-generated natural variability, which possibly underestimates low frequency fluctuations and does not incorporate the variance associated with changes in external forcing factors, such as anthropogenic sulfate aerosols, solar variability or volcanic dust.
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... T21), and then provided as prescribed lower boundary conditions for an integration in a highresolution (e.g. T106) atmospheric model (CUBASCH et al. 1995). The equilibrium response of the high resolution model run is taken as a regional climate estimate. ...
... Such patterns can be derived from climate models. For instance, experiments with climate models (e.g., Cubasch et al., 1995) indicate that the ongoing increase of greenhouse gas concentrations in the atmosphere will lead to a general warming of the air near to the surface, with stronger warming over the continents and delayed warming over the ocean; the delay is, according to the model, particularly evident over the northwestern part of the North Atlantic. Figure 8 displays the warming as calculated by the climate model after 100 years of continuous increase (about 1% per year) of the CO 2 concentration. ...
Climate is largely determined by the fluid flows in the atmosphere and oceans. These flows are governed by the laws of fluid dynamics and thermodynamics. These laws are partial differential equations that represent the conservation of mass, momentum, energy and other quantities.1 If we could solve these equations, with the right initial and boundary conditions, then we would have the answers to all the pressing questions of the current climate debate. This, however, is not possible. Even if there were a unique set of such equations the only consensus about them is that they are highly and multiply nonlinear. They couple processes across all scales, from the planetary scales of wind and current systems to the micro-scales of molecular diffusion. The resulting flow is turbulent, with everything depending on everything else. It is also impossible to know the exact initial and boundary conditions, such as the exact shape of the continents or the details of human land use.
In recent years, the impact of global warming has raised public concern over the precipitation-induced geological hazards, water security and energy security in the Yalong River Basin (YRB). Therefore, it is advisable to identify the variations of future precipitation, hydrology and hydropower generation under the joint impact of global warming and the operation of local hydropower reservoirs. To this end, the ensemble mean of the bias corrected NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) climate projections downscaled from 10 global climate models (GCMs) was applied to seven precipitation indices proposed by the Expert Team on Climate Change Detection and Indices (ETCCDI) and the ensemble of two distributed hydrologic models (VIC and CREST) under the global warming of 1.5℃ and 2℃. Reservoir operation based on actual operation rules and the hydropower optimization model were explicitly included in the routing module to represent the impact of the local hydropower reservoirs, respectively. The future natural runoff is likely to increase under RCP8.5, decrease under RCP4.5, and see a larger daily variability under both. The local hydropower reservoirs can effectively mitigate the negative climate impact on the basin hydrology, and the basin is expected to see increased dry-season runoff, decreased wet-season runoff, and lower daily variability of runoff under all scenarios as compared to the baseline period. The future hydropower generation of the YRB is consistent with the variation of future runoff, and reservoir operation with hydropower optimized rules can produce about 5% electricity more than the current actual operation rules, highlighting the potential need to adapt the current operation rules to future climate conditions. Our framework and findings are expected to provide instructive information for water resources management not only in the YRB but also in different regions worldwide.
The cryosphere comprises all the frozen water and soil on the surface of the Earth. Mass Balance of the Cryosphere focuses on two key components of this environment: land ice (in the form of ice sheets, caps and glaciers) and sea ice. These components have been identified as important indicators of both short and long term climate change. Early chapters cover the theory behind field-based and satellite observations, and modelling of mass balance, providing a thorough grounding in all the concepts and issues presented later in the book. Later chapters review our current understanding of the present and predicted future mass balance of the cryosphere. This is an important reference for all scientists working in the fields of climate change, environmental sciences and glaciology. It is written by leading authors in the field, and is fully integrated to provide a coherent, cross-referenced and consistent exposition on the subject.
The cryosphere comprises all the frozen water and soil on the surface of the Earth. Mass Balance of the Cryosphere focuses on two key components of this environment: land ice (in the form of ice sheets, caps and glaciers) and sea ice. These components have been identified as important indicators of both short and long term climate change. Early chapters cover the theory behind field-based and satellite observations, and modelling of mass balance, providing a thorough grounding in all the concepts and issues presented later in the book. Later chapters review our current understanding of the present and predicted future mass balance of the cryosphere. This is an important reference for all scientists working in the fields of climate change, environmental sciences and glaciology. It is written by leading authors in the field, and is fully integrated to provide a coherent, cross-referenced and consistent exposition on the subject.
A 3-d baroclinic coupled ice–ocean model, applied to the connected marginal seas, North Seaand Baltic Sea, was used to investigate the seasonal cycle of both heat content of the watercolumn and atmosphere–ocean heat exchange throughout the seasonal cycle. Case studies werecarried out to investigate, quantify and inter-compare the intra-annual sensitivity of the thermalstate of both marginal seas in response to changes in wind forcing, air temperature and freshwater runoff. The prescribed changes in model forcing were well within the range of the observedvariability. A simulation for a representative reference case (1984–84) served to quantifypredicted anomalies. Reducing the fresh water runoff for both seas by 30% resulted in asurprisingly small response in the heat content which was one order of magnitude smaller ascompared to the applied change in wind forcing. A reduction of the air temperature by 2°C causeda decrease of the heat content throughout the seasonal cycle in the order of 30%. In contrast to achange in air temperature a reduction of 30% in wind stress yielded distinct seasonal differencesin the oceanic response. The most significant wind induced changes occurred during autumn andwinter in the Baltic Sea and in the North Sea. A reduced wind forcing led to a larger oceanic heatcontent in winter as a consequence of a reduced winter convection and an intensification of thewinter thermocline in the freshwater dominated Baltic. In the Baltic Proper, with its perennialthermo-haline stratification, predicted temperature changes of intermediate waters were severaltimes higher than sea surface temperature changes. Compared with the North Sea, the Balticshowed a much higher sensitivity in response of the heat content to changes in the wind forcing.However, the opposite is true for the heat flux from the water to the atmosphere during the coolingperiod. Here the sensitivity of the North Sea is much higher than that of the Baltic Sea. This iscaused by the fact that advective heat flux changes and atmospheric heat flux changes are workingin the same direction in the Baltic Sea and acting in opposite direction in the North Sea. Resultsof this sensitivity study suggest that future studies on an inter-annual sensitivity should be conductedwith a coupled atmosphere–ocean model. DOI: 10.1034/j.1600-0870.1992.00006.x
The term “downscaling” describes a procedure in which information about a process with a certain characteristic scale is derived from other processes with larger scales. The present paper identifies a relationship between the main components of the North Atlantic air-pressure anomalies at sea-level (characteristic length-scale > 1000 km) and the sea level anomalies at several Baltic Sea gauges (10 km−100 km) in winter. Monthly means from 20 observed winters are used to fit a statistical model that describes the dependence between both parameters. Further observations from this century are used to validate this model, which is able to estimate sea level anomalies from the air-pressure field to a good level of approximation. Sea level anomalies with periods from months to decades are reproduced well. As main forcing for the sea level anomalies, wind-stress with a strong zonal component is identified. For the past 89 years, we found that a slight decrease of mean sea level was induced by air-pressure. A slight increase is found when air-pressure from a GCM “greenhouse” experiment is downscaled. DOI: 10.1034/j.1600-0870.1996.t01-1-00008.x
A relationship between observed variability in large-scale climate and salinity in the GermanBight is sought using a multivariate statistical approach. It is found that on an annual timescale,90% of the observed salinity variability is in-phase and correlated with a lag of several monthsto large-scale air pressure. The statistical model is used to estimate annual salinity anomaliesfrom large-scale air pressure back to 1900. The correlations between estimated and observedsalinities range from r=0.4 to r=0.7, depending on the position. It is shown that advectiveprecipitation is the mechanism that links air pressure and salinity anomalies. Advection ofAtlantic Water has only a minor impact on the annula mean in the examined coastal zone. Ifair pressure data from a climate change experiment is used as predictor, a slight drop of themean salinity level in the range of 0.2 to 0.3 psu is predicted for the near future. DOI: 10.1034/j.1600-0870.1998.00012.x
Die Strahlung der Sonne ist Energiequelle für alle meteorologischen und biologischen Prozesse des Systems Erde-Atmosphäre und damit unverzichtbar für irdisches Leben. UV-Strahlung kann jedoch, obwohl ihr Spektralbereich nur wenige Prozent der solaren Energie ausmacht, Schäden an biologischen Zellen sowie photochemische Prozesse (Bd. 1A, Kap. 3.2) hervorrufen. Wegen dieser Wirkungen spielt die UV-Strahlung für die Umwelt eine besondere Rolle.
Observational datasets are analyzed in four steps to provide a comprehensive view of climate and climate variability in Europe. The first step towards an overall description of climate is the analysis of the spatial distributions of means and variances of basic climate elements (surface air temperature, sea level pressure, and precipitation). The second step identifies the chmate generating dynamical processes; here, cyclone paths and storm tracks provide climatologies from quantitative Lagrangian and Eulerian analyses of weather data; Grosswetterlagen and climate zones, on the other hand, represent climatologies based on qualitative patterns (regimes) embedding the chmate into its geographical and biospheric environment. A third step of analysis is necessary because these climatologies indicate recent climate changes at the end of the last century. This is documented in terms of the spatial distribution of time averaged climate elements and of various measures of their variability (see preceding steps). The fourth step evaluates the causes of the observed trends, analyzing the effects of external forcing (volcanism, solar, and anthropogenic) by empirical methods.
A strategy using statistically optimal fingerprints to detect anthropogenic climate change is outlined and applied to near-surface temperature trends. The components of this strategy include observations, information about natural climate variability, and a {open_quotes}guess pattern{close_quotes} representing the expected time-space pattern of anthropogenic climate change. The expected anthropogenic climate change is identified through projection of the observations onto an appropriate optimal fingerprint, yielding a scalar-detection variable. The statistically optimal fingerprint is obtained by weighting the components of the guess pattern (truncated to some small-dimensional space) toward low-noise directions. The null hypothesis that the observed climate change is part of natural climate variability is then tested. This strategy is applied to detecting a greenhouse-gas-induced climate change in the spatial pattern of near surface temperature trends defined for time intervals of 15-30 years. The expected pattern of climate change is derived from a transient simulation with a coupled ocean-atmosphere general circulation model. Global gridded near-surface temperature observations are used to represent the observed climate change. Information on the natural variability needed to establish the statistics of the detection variable is extracted from long control simulations of coupled ocean-atmosphere models and, additionally, from the observations themselves (from which an estimated greenhouse warming signal has been removed). While the model control simulations contain only variability caused by the internal dynamics of the atmosphere-ocean system, the observations additionally contain the response to various external forcings. The resulting estimate of climate noise has large uncertainties but is qualitatively the best the authors can presently offer. 71 refs., 12 figs., 14 tabs.
This paper is an up-to-date review of instrumentally-recorded, seasonal, surface temperature change across the land and marine regions of the world during the twentieth century. This is the first part of a two part series. The second part will deal with the interpretation of proxy-climate data in terms of large-scale hemispheric or global-scale temperature averages for the Holocene.
In Part 1, we review the uncertainties associated with combining land and marine instrumental records to produce regional-average series. The surface air temperature of the world has warmed 0.5°C since the middle of the nineteenth century. The warming in the Northern Hemisphere only occurred in winter, spring and autumn. Summers are now no warmer than in the 1860s and 1870s. The same half-degree warming is seen in all seasons in the Southern Hemisphere.
Spatial patterns of temperature anomalies during two warm decades, the 1930s and 1980s, all vary from season to season. Temperatures during the 1980s were by far the warmest in the last 140 years. Though most areas of the world experienced above normal temperatures, the variability from season to season was notable in the Northern Hemisphere where much of the warmth was in winter and spring over northern and central Asia and northwestern North America. Almost all of the Southern Hemisphere was warmer during these years.
This study investigates the seasonal variation of the transient response of a coupled ocean-atmosphere model to a gradual increase (or decrease) of atmospheric carbon dioxide. The model is a general circulation model of the coupled atmosphere-ocean-land surface system with a global computational domain, smoothed geography, and seasonal variation of insolation.It was found that the increase of surface air temperature in response to a gradual increase of atmospheric carbon dioxide is at a maximum over the Arctic Ocean and its surroundings in the late fall and winter. On the other hand, the Arctic warming is at a minimum in summer. In sharp contrast to the situation in the Arctic Ocean, the increase of surface air temperature and its seasonal variation in the circumpolar ocean of the Southern Hemisphere are very small because of the vertical mixing of heat over a deep water column.In response to the gradual increase of atmospheric carbon dioxide, soil moisture is reduced during the June-July-August period over most of the continents in the Northern Hemisphere with the notable exception of the Indian subcontinent, where it increases. The summer reduction of soil moisture in the Northern Hemisphere is relatively large over the region stretching from the northern United States to western Canada, eastern China, southern Europe, Scandinavia, and most of the Russian Republic. During the December-January-February period, soil moisture increases in middle and high latitudes of the Northern Hemisphere. The increase is relatively large over the western portion of the Russian Republic and the central portion of Canada. On the other hand, it is reduced in the subtropics, particularly over Southeast Asia and Mexico.Because of the reduction (or delay) in the warming of the oceanic surface due to the thermal inertia of the oceans, the increase of the moisture supply from the oceans to continents is reduced, thereby contributing to the reduction of both soil moisture and runoff over the continents in middle and high latitudes of the Northern Hemisphere. This mechanism enhances the summer reduction of soil moisture and lessens its increase during winter in these latitudes.The changes in surface air temperature and soil moisture in response to the gradual reduction of atmospheric CO2 are opposite in sign but have seasonal and geographical distributions that are broadly similar to the response to the gradual CO2 increase described above.
Four time-dependent greenhouse warming experiments were performed with the same global coupled atmosphere-ocean model, but with each simulation using initial conditions from different “snapshots” of the control run climate. The radiative forcing — the increase in equivalent CO2 concentrations from 1985–2035 specified in the Intergovernmental Panel on Climate Change (IPCC) scenario A — was identical in all four 50-year integrations. This approach to climate change experiments is called the Monte Carlo technique and is analogous to a similar experimental set-up used in the field of extended range weather forecasting. Despite the limitation of a very small sample size, this approach enables the estimation of both a mean response and the “between-experiment” variability, information which is not available from a single integration. The use of multiple realizations provides insights into the stability of the response, both spatially, seasonally and in terms of different climate variables. The results indicate that the time evolution of the global mean warming signal is strongly dependent on the initial state of the climate system. While the individual members of the ensemble show considerable variation in the pattern and amplitude of near-surface temperature change after 50 years, the ensemble mean climate change pattern closely resembles that obtained in a 100-year integration performed with the same model. In global mean terms, the climate change signals for near surface temperature, the hydrological cycle and sea level significantly exceed the variability among the members of the ensemble. Due to the high internal variability of the modelled climate system, the estimated detection time of the global mean temperature change signal is uncertain by at least one decade. While the ensemble mean surface temperature and sea level fields show regionally significant responses to greenhouse-gas forcing, it is not possible to identify a significant response in the precipitation and soil moisture fields, variables which are spatially noisy and characterized by large variability between the individual integrations.
Recent investigations have considered whether it is possible to achieve early detection of greenhouse-gas-induced climate change by observing changes in ocean variables. In this study, we use model data to assess some of the uncertainties involved in estimating when we could expect to detect ocean greenhouse warming signals. We distinguish between detection periods and detection times. As defined here, detection period is the length of a climate time series which must be available in order to detect a given linear trend in the presence of the natural climate variability. Detection period is defined in model years and is independent of reference time and the real time evolution of the signal. Detection time is computed for an actual time-evolving signal from a greenhouse warning experiment and depends on the experiment`s start date. Two sources of uncertainty are considered - those associated with the level of natural variability or noise, and those associated with the time-evolving signals. We analyze the ocean signal and noise for spatially-averaged ocean circulation indices such as ice volume, heat and fresh water fluxes, rate of deep water formation, salinity, temperature, and transport of mass. The signals for these quantities are taken from recent time-dependent greenhouse warming experiments performed by the Hamburg group with a coupled ocean-atmosphere General Circulation Model. The natural variability noise is derived from a 300-year control run performed with the same coupled atmosphere-ocean model and from two long (> 3,000 year) stochastic forcing experiments in which an uncoupled ocean model was forced by white-noise surface flux variations. In the first experiment the stochastic forcing was restricted to the fresh water fluxes, while in the second experiment the ocean model was additionally forced by variations in wind stress and heat fluxes. The mean states and ocean variability are very different in the three natural variability integrations.
The influence of the starting date of model integration on time-dependent projections of greenhou- se-gas-induced climatic charge is assessed with a coupled atmosphere-ocean energy-balance model. It is shown that the starting date effect depends on the rate of for- cing change and on the oceanic thermal inertia. On the other hand, the model results indicate that, for the va- rious cases considered here, reliable projections of green- house-gas-induced climatic change over the next century can be obtained by starting the model integration as late as the year 1960.
The sensitivity of the global ocean circulation to changes in surface heat flux forcing is studied using the Hamburg Large Scale Geostrophic (LSG) ocean circulation model. The simulated mean ocean circulation for appropriately chosen surface forcing fields reproduces the principal water mass properties, residence times, and large-scale transport properties of the observed ocean circulation quite realistically within the constraints of the model resolution. However, rather minor changes in the formulation of the high-latitude air-sea heat flux can produce dramatic changes in the structure of the ocean circulation. These strongly affect the deep-ocean overturning rates and residence times, the oceanic heat transport, and the rate of oceanic uptake of CO2. The sensitivity is largely controlled by the mechanism of deep-water formation in high latitudes. -Authors
The original appraisal of Bolin and Chalonson (1976) is extended by
providing an updated and refined estimate of the direct climatic effect
of anthropogenic SO4(2-) aerosol based on a global 3D numerical
calculation of the sulfate aerosol burden and an empirical calculation
of the optical effect of SO4(2-) aerosol mass concentration. This
estimate is compared to a single burden calculation and calculated
forcings due to the possible influence of cloud condensation nuclei
(CCN) on cloud albedo. The likelihood is demonstrated that aerosol
cooling effects are significant in comparison to current climate forcing
by anthropogenic CO2 and other greenhouse gases. It is concluded that
the change of reflected solar flux due to anthropogenic SO4(2-) averaged
over the Northern Hemisphere is about -1.1 W/sq m, which is comparable
but opposite in sign to the present-day radiative forcing by
anthropogenic CO2, + 1.5 W/sq m.
Book review of the intergovernmental panel on climate change report on global warming and the greenhouse effect. Covers the scientific basis for knowledge of the future climate. Presents chemistry of greenhouse gases and mathematical modelling of the climate system. The book is primarily for government policy makers.