Max Planck Institute For Meteorology Research Articles

Regional dynamical downscaling over West Africa: model evaluation and comparison of wet and dry years

In this study, a 25-year regional climate model run over West Africa is evaluated and examined with respect to causes of interannual rainfall variability related to the West African Monsoon. West African rainfall has been subject to strong interannual and decadal variability throughout the past 50 years. Known driving forces for this variability are large-scale changes in Atlantic sea surface temperatures (SSTs), variability due to global atmospheric circulation changes, like for instance variability related to El Nino-Southern Oscillation, but also regional and local-scale changes in land use and vegetation cover. The interaction of these impact factors with West African synoptic and subsynoptic processes is still not completely understood. One reason for this lack of knowledge is that basic features of West African climate, including the African Easterly Jet (AEJ), African Easterly Waves (AEWs) as well as monsoon dynamics, are very complex multiscale phenomena. Climate modeling in West Africa requires the ability to simulate these effects, which can only be achieved by mesoscale atmospheric models. Using the regional climate model REMO from the Max-Planck Institute for Meteorology in Hamburg, a 25-year dynamical downscaling study was undertaken in order to evaluate a tool, which will then be used for the examination of causes of rainfall variability in West Africa. The model was used on a 0.5° grid over North Africa northward of 15°S. The model evaluation leads to some confidence in the reliability of the modeled climate. A detailed examination of composites of selected wet and dry years in the Guinean coast region elucidates the role of SST forcing and external atmospheric forcing for interannual rainfall variability. In general, abundant monsoonal rainfall comes along with warm tropical Atlantic SSTs, enhanced latent heat fluxes from the ocean to the atmosphere and stronger surface wind convergence near the Guinean Coast. This is accompanied by large-scale dynamical changes in strength and direction of both the Tropical Easterly Jet (TEJ) over the Indian Ocean and the Subtropical Jet (STJ) over the Near East and the Caucasian region.

MEETING SUMMARIES

The Coupled Model Intercomparison Project (CMIP) involves study and intercomparison of multimodel simulations of present and future climate. The simulations of the future use idealized forcing in which CO, increase is compounded 1% yr(-1) until it doubles (near year 70) with global coupled models that contain, typically, components representing atmosphere, ocean, sea ice, and land surface. Results from CMIP diagnostic sub-projects were presented at the Second CMIP Workshop held at the Max Planck Institute for Meteorology in Hamburg, Germany, in September 2003. Significant progress in diagnosing and understanding results from global coupled models has been made since the time of the First CMIP Workshop in Melbourne, Australia, in 1998. For example, the issue of flux adjustment is slowly fading as more and more models obtain stable multicentury surface climates without them. El Nino variability, usually about half the observed amplitude in the previous generation of coupled models, is now more accurately simulated in the present generation of global coupled models, though there are still biases in simulating the patterns of maximum variability. Typical resolutions of atmospheric component models contained in coupled models are now usually around 2.5degrees latitude-longitude, with the ocean components often having about twice the atmospheric model resolution, with even higher resolution in the equatorial Tropics. Some new-generation coupled models have atmospheric resolutions of around 1.5degrees latitude - longitude. Modeling groups now routinely run the CMIP control and 1% CO2 simulations in addition to twentieth- and twenty-first-century climate simulations with a variety of forcings e.g., volcanoes, solar variability, anthropogenic sulfate aerosols, ozone, and greenhouse gases, with the anthropogenic forcings for future climate as well. However, persistent systematic errors noted in previous generations of global coupled models are still present in the current generation (e.g., overextensive equatorial Pacific cold tongue, double ITCZ). This points to the next challenge for the global coupled climate modeling community. Planning and commencement of the Intergovernmental Panel on Climate Change Fourth Assessment Report (AR4) has prompted rapid coupled model development, which is leading to an expanded CMIP-like activity to collect and analyze results for the control, 1% CO2, and twentieth-, twenty-first, and twenty-second-century simulations performed for the AR4. The international climate community is encouraged to become involved in this analysis effort.

Net accumulation of the Greenland ice sheet: High resolution modeling of climate changes

High‐resolution (50 km) climate change simulations for an area covering the entire Arctic have been conducted with the regional climate model (RCM) HIRHAM. The experiments were forced at the lateral boundary by large‐scale atmospheric conditions from transient climate change scenario simulations performed with the Max Planck Institute for Meteorology coupled ocean atmosphere general circulation model (OAGCM) ECHAM4/OPYC3 with a resolution of ∼300 km. The emission scenarios used were the IPCC SRES [Nakicenovic, 2000] marker scenarios A2 and B2. Three 30‐year time slice experiments were conducted with HIRHAM for periods representing present‐day (1961–1990) and the future (2071–2100) in the two scenarios. We find that due to a much better representation of the surface topography in the RCM, the geographical distribution of present‐day accumulation rates simulated by the RCM represents a substantial improvement compared to the driving OAGCM. Estimates of the regional net balance are also better represented by the RCM. In the future climate the net balance for the Greenland Ice Sheet is reduced in all the simulation, but discrepancies between the amounts when based on ECHAM4/OPYC3 and HIRHAM are found. In both scenarios, the estimated melt rates are larger in HIRHAM than in the driving model.

Impact of horizontal resolution on the simulation of seasonal climate in the Atlantic/European area for present and future times

The climate response to increasing levels of atmospheric greenhouse gases, prescribed according to the Intergovernmental Panel on Climate Change (IPCC) scenario IS92a, is studied in 2 model simulations. One is a transient response experiment performed with a medium resolution (T42) coupled general circulation model of the atmosphere and ocean (ECHAM4/OPYC) developed at the Max Planck Institute for Meteorology. The other one is a time-slice experiment with the high resolu- tion (T106) ECHAM4 model forced with monthly sea-surface temperatures and sea-ice from the coupled model. For two 30 yr time-slices, representing the present-day climate (1970-1999) and the future climate with an effective doubling of carbon dioxide (2060-2099), the seasonal mean climate statistics obtained from the 2 experiments in the Atlantic/European area are compared with each other and, for the simulations of the present-day climate, with observational data in order to evaluate the impact of the model's horizontal resolution on the simulation of regional climate change as well as on the quality of the simulation of regional climate. As the region of special interest, the Atlantic/European area is chosen. The model's horizontal resolution has a noticeable impact on the assessment of anthropogenic climate change as well as on the quality of the climate simulation at a local level, while at a regional level, that is considering the entire Atlantic/European area, the effect of the horizontal resolution is considerably reduced. The level of uncertainty related to the horizontal resolution actually falls with the range of uncertainty caused by the internal model variability obtained from ensembles of climate predictions. The level of uncertainty at a given location is very small for the near-surface temperature but somewhat higher for the sea-level pressure, in particular in autumn and winter, and relatively high for precipitation, with a marked maximum in summer. While the uncertainties in autumn and winter are mainly accounted for by the marked impact of the horizontal resolution on the dynamical aspects of the model, the high level of un- certainty in summer is related to the pronounced effect of the horizontal resolution on the model's physical parameterizations.

Climate change impacts on runoff in Sweden-assessments by global climate models, dynamical downscaling and hydrological modelling

The Swedish regional climate modelling programme, SWECLIM, started in 1997 with the main goal being to produce regional climate change scenarios over the Nordic area on a time scale of 50 to 100 yr. An additional goal is to produce water resources scenarios with a focus on hydropower production, dam safety, water supply and environmental aspects of water resources. The scenarios are produced by a combination of global climate models (GCMs), regional climate models and hydrological runoff models. The GCM simulations used thus far are 10 yr time slices from 2 different GCMs, UKMO HadCM2 from the Hadley Centre and the ECHAM4/OPYC3 of the Max Planck Institute for Meteorology. The regional climate model is a modified version of the international HIRLAM forecast model and the hydrological model is the HBV model developed at the Swedish Meteorological and Hydrological Institute. Scenarios of river runoff have been simulated for 6 selected basins covering the major climate regions in Sweden. Changes in runoff totals, runoff regimes and extreme values have been analysed with a focus on the uncertainties introduced by the choice of GCM and routines for estimation of evapotranspiration in the hydrological model. It is further shown how these choices affect the statistical return periods of future extremes in a design situation.

Very High-Resolution Regional Climate Simulations over Scandinavia—Present Climate

The hydrological cycle on a regional scale is poorly represented with a present-day coarse resolution general circulation model (GCM). With a dynamical downscaling technique, in which a regional higher-resolution climate model (RCM) is nested into the GCM, this starts to become feasible. Here the authors go one step further with a double nesting approach, applying an RCM at 19-km horizontal resolution nested into an RCM at 57-km resolution over an area covering the Scandinavian Peninsula. A 9-yr-long time-slice simulation is performed with the driving boundary conditions taken from a fully coupled ocean–atmosphere GCM experiment, the recently completed ECHAM4/OPYC3 control simulation performed by the Max Planck Institute for Meteorology in Hamburg. With increasing resolution, local effects playing a significant role in the hydrological budget become better and better resolved and are more realistically simulated. It is found in particular that in mountainous regions the high-resolution simulation shows improvements in the simulation of hydrologically relevant fields such as runoff and snow cover. Also, the distribution of precipitation on different intensity classes is most realistically simulated in the high-resolution simulation. It does, however, inherit certain large-scale systematic errors from the driving GCM. In many cases these errors increase with increasing resolution. Model verification of near-surface temperature and precipitation is made using a new gridded climatology based on a high-density station network for the Scandinavian countries compiled for the present study. The simulated runoff is compared with observed data from Sweden extracted from a Swedish climatological atlas. These runoff data indicate that the precipitation analyses are underestimating the true precipitation by as much as 96% on an annual basis in the most mountainous region of Sweden. This fact as well as estimates of the underestimation in other areas of Scandinavia make the high-resolution RCM simulations appear more realistic.

ENSO dynamics and seasonal cycle in the tropical Pacific as simulated by the ECHAM4/OPYC3 coupled general circulation model

The new version of the atmospheric general circulation model (AGCM), ECHAM4, at the Max Planck Institute for Meteorology, Hamburg, has been coupled to the OPYC3 isopycnic global ocean general circulation and sea ice model in a multi-century present-day climate simulation. Non-seasonal constant flux adjustment for heat and freshwater was employed to ensure a long-term annual mean state close to present-day climatology. This study examines the simulated upper ocean seasonal cycle and interannual variability in the tropical Pacific for the first 100 years. The coupled model’s seasonal cycle of tropical Pacific SSTs is satisfactory with respect to both the warm pool variation and the Central and Eastern Pacific, with significant errors only in the cold tongue around April. The cold phase cold tongue extent and strength is as observed, and for this the heat flux adjustment does not play a decisive role. A well-established South Pacific convergence zone is characteristic for the new AGCM version. Apart from extending the southeast trades seasonal maximum to midbasin, wind stress pattern and strength are captured. Overall the subsurface structure is consistent with the observed, with a pronounced thermocline at about 150 m depth in the west and rising to the surface from 160 °W to 100 °W. The current system is better resolved than in some previous global models and, on the whole, has the expected shape. The equatorial undercurrent is correctly positioned but the core is only half as strong as observed. The north equatorial current and counter-current also have reduced maximum speeds but the April minimum is captured. As with the companion publication from Roeckner et al. this study finds pronounced tropical Eastern and Central Pacific interannual variability. Simulated and observed NINO3 sea surface temperature (SST) variability is represented by a single, rather broadband, maximum of power spectral density, centered on about 28 months for the simulation and four years for the observations. For simulation and observations, SST, windstress, and upper ocean heat content each exhibit a single dominant large-scale amplitude and phase pattern, suggesting that the model captures the essential dynamics. The amplitude of the essentially standing oscillation in SST in the NINO3 region attains the observed strength, but is weaker at the eastern boundary. Anomalies of upper ocean heat content show off-equatorial westward and equatorial eastward propagation, the latter’s arrival in the east of the basin coinciding with the SST anomalies. Equatorial wind stress anomalies near the date line provide the appropriate forcing and clearly form a response to the anomalous SST.

Climate change scenarios over the South American region: an intercomparison of coupled general atmosphere-ocean circulation models

Results of four different coupled atmosphere-ocean general circulation model runs for South America and surrounding oceans are examined. The mean response of the simulated climate system to a gradual increase of greenhouse gases is presented. The transient coupled experiment data provided for the Intergovernmental Panel on Climate Change (IPCC) were the most recent available to us at the time of this study, from the following research centres in Europe and USA: the UK Meteorological Office (UKMO), the Max-Planck Institute for Meteorology (MPI), the Geophysical Fluid Dynamic Laboratory (GFDL) and the National Center for Atmospheric Research (NCAR). The regional performance of the control simulations (with fixed CO2 concentration) is determined by comparing sea-level pressure, near-surface zonal wind, precipitation and surface air temperature from the models, against observed climatological fields. The response of the climate system to the enhanced emission scenarios is established comparing the control experiments with the respective transient experiments around the time of doubling CO2. To assist in estimating likely future climate change in the South American region, only the results of those model experiments with the best control simulation of current climate in the region are considered: the UKMO and MPI models. A maximum warming over the continent and a minimum warming in the extratropical oceans, a slight intensification and southward migration of the subtropical ridge, a deepening of the sub-Antarctic trough, an intensification of the westerly winds, and increasing precipitation in the tropics and in the mid-latitude oceans are the most important potential changes simulated by both models for the increased CO2 scenarios. © 1997 Royal Meteorological Society.

Grid point surface air temperature calculations with a fast turnaround: Combining the results of IMAGE and a GCM

This paper describes a methodology that combines the outputs of (1) the Integrated Model to Assess the Greenhouse Effect (IMAGE Version 1.0) of the Netherlands National Institute of Public Health and Environmental Protection (RIVM) (given a greenhouse gas emission policy, this model can estimate the effects such as global mean surface air temperature change for a wide variety of policies) and (2) ECHAM-1/LSG, the Global Circulation Model (GCM) of the Max-Planck Institute for Meteorology in Hamburg, Germany. The combination enables one to calculate grid point surface air temperature changes for different scenarios with a turnaround time that is much quicker than that for a GCM. The methodology is based upon a geographical pattern of the ratio of grid point temperature change to global mean values during a certain period of the simulation, as calculated by ECHAM-1/LSG for the 1990 Scenarios A and D of the Intergovernmental Panel on Climate Change (IPCC). A procedure, based upon signal-to noise ratios in the outputs, enabled us to estimate where we have confidence in the methodology; this is at about 23% to 83% of the total of 2,048 grid points, depending upon the scenario and the decade in the simulation. It was found that the methodology enabled IMAGE to provide useful estimates of the GCM-predicted grid point temperature changes. These estimates were within 0.5K (0.25K) throughout the 100 years of a given simulation for at least 79% (74%) of the grid points where we are confident in applying the methodology. The temperature ratio pattern from Scenario A enabled IMAGE to provide useful estimates of temperature change within 0.5K (0.25K) in Scenario D for at least 88% (68%) of the grid points where we have confidence; indicating that the methodology is transferable to other scenarios. Tests with the Geophysical Fluid Dynamics Laboratory GCM indicated, however, that a temperature ratio pattern may have to be developed for each GCM. The methodology, using a temperature ratio pattern from the 1990 IPCC Scenario A and involving IMAGE, gave gridded surface air temperature patterns for the 1992 IPCC radiative-forcing Scenarios C and E and the RIVM emission Scenario B; none of these scenarios has been simulated by ECHAM-1/LSG. The simulations reflect the uncertainty range of a future warming.

Downscaling two versions of a general circulation model to estimate local hydroclimatic factors under climate change

Abstract The regional hydroclimatological effect of global climate change has been estimated and compared using a semi-empirical downscaling method with two versions (T21 and T42) of the general circulation model (GCM) developed at the Max Planck Institute for Meteorology, Germany. The comparisons were performed with daily mean temperature and daily precipitation amounts for the continental climate of the state of Nebraska, USA. Both the T21 and the T42 versions resulted in an increase of daily mean temperature under a 2 x C02 climatess. The magnitude of warming was substantially greater for T21 than for T42, except for February and June and at some stations in July where the T42 model suggested greater warming. Both GCMs resulted in a slight decrease in precipitation frequency and an increase in the amount of precipitation on wet days. Here, the T42 model again led to smaller changes. Different locations within Nebraska exhibited somewhat different temperature and precipitation responses with both GCM ve...

Downscaling GCM information to regional scales: a non-parametric multivariate regression approach

The multivariate adaptive regression splines (MARS) model was used to capture the observed relationships between sea level pressure (SLP) anomalies over the Euro-Atlantic sector and the winter time (December–February) monthly rainfall at eight sites in Portugal; possible anthropogenic changes of the rainfall in a perturbed future climate were then estimated by using both the observed SLP-rainfall relationships, described by MARS models, and the GCM simulated SLP, taken from the output of the Hadley Centre Transient Climate Change Experiment (UKTR). Also, principal component analysis was carried out to reduce the dimensionality of the SLP data, and to assess the ability of the GCM in simulating the large-scale circulation; the first six principal components were retained as predictors in the MARS model. The MARS model were built up by using the data for 1946–1991 as the training set and that for 1901–1943 as the testing set, showing satisfactory prediction skills. It is concluded that the UKTR control simulation successfully reproduced main features of the large-scale circulation, but the observed relationship between SLP and the regional rainfall was not well preserved. With respect to the 54-year experiment of perturbed run, the MARS estimation of rainfall and the relevant direct GCM rainfall output possess similar multi-annual variations; however, there are substantial differences regarding details; the change in the area mean of winter time mean monthly rainfall in Portugal estimated by MARS (indirect GCM output) is about −12.7 mm per 54-year, and the relevant direct GCM output is −16.9 mm/54-year. This reduction tendency is consistent with previously reported findings respecting rainfall in the Iberian Peninsula, which were based on the MPI (Max-Planck Institute for Meteorology) transient simulations.

Influence of cirrus cloud radiative forcing on climate and climate sensitivity in a general circulation model

Six numerical experiments have been performed with a general circulation model (GCM) to study the influence of high‐level cirrus clouds and global sea surface temperature (SST) perturbations on climate and climate sensitivity. The GCM used in this investigation is the third‐generation ECHAM3 model developed jointly by the Max Planck Institute for Meteorology and the University of Hamburg. It is shown that the model is able to reproduce many features of the observed cloud radiative forcing with considerable skill, such as the annual mean distribution, the response to seasonal forcing, and the response to observed SST variations in the equatorial Pacific. In addition to a reference experiment where the cirrus emissivity is computed as a function of the cloud water content, two sensitivity experiments have been performed in which the cirrus emissivity is either set to zero everywhere above 400 hPa (“transparent cirrus”) or set to 1 (“black cirrus”). These three experiments are repeated identically, except for prescribing a globally uniform SST warming of 4 K. Similar to earlier GCM studies, the changed cloud radiative heating within the troposphere has a profound impact on the model climate. Since the initial radiative forcing introduced by the changed cirrus emissivity is much smaller than the convective or dynamical response, we conclude that the tropical circulation, in particular, is maintained through a positive feedback loop involving cirrus radiative heating, deep cumulus convection, and moisture supply through the large‐scale dynamics. Since this interaction has been identified in at least two other GCMs employing different cumulus parameterizations, it does not crucially depend on the respective closure assumption. Moreover, the radiative‐convective‐dynamical coupling in the tropics is relevant also in the global warming experiment through the increase of cloud water and hence cirrus radiative heating in the warmer atmosphere. It is shown that the spin‐up of the Walker circulation in both the global warming and the increased cirrus emissivity experiments is a result of a selection process which enhances the diabatic heat source through asymmetries of the circulation itself, and the extra differential heating feeds back positively on the circulation. It is also shown that cirrus clouds have a significant influence on the global climate sensitivity of the model. In the climate change experiment with the standard model, the climate sensitivity is 20% higher than in a clear‐sky reference atmosphere because the increase of cirrus emissivity in the warmer atmosphere contributes substantially to the overall positive cloud feedback. In the transparent cirrus model the cloud feedback is negative, and the global sensitivity is reduced by 20% as compared to a clear‐sky reference atmosphere.

Studies Say—Tentatively—That Greenhouse Warming Is Here

Published studies on greenhouse warming have been ambivalent as to whether warming has arrived. Now two independent studies of the climate record have incriminated the green-house effect in global warming, although they fall short of convicting it. Researchers at the Max Planck Institute for Meteorology in Hamburg are confident they have exonerated natural climatic variability, saying the observed global warming seems to large to account for the warming effect. A group from Lawrence Livermore National Laboratory directly implicates greenhouse warming by finding its geographic `fingerprinting` in the climate record of the past century. This article discusses both studies and how the results will affect future concerns in the area of greenhouse warming.

Ocean variability and its influence on the detectability of greenhouse warming signals

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 required in order to detect, at some prescribed significance level, 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 warming 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 heat and fresh water fluxes, rate of deep water formation, salinity, temperature, transport of mass, and ice volume. The signals for these quantities are taken from recent time‐dependent greenhouse warming experiments performed by the Max Planck Institute for Meteorology in Hamburg with a coupled ocean‐atmosphere general circulation model. The time‐dependent greenhouse gas increase in these experiments was specified in accordance with scenario A of the Intergovernmental Panel on Climate Change. The natural variability noise is derived from a 300‐year control run performed with the same coupled atmosphere‐ocean model and from two long (>3000 years) 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. A suite of greenhouse warming simulations with identical forcing but different initial conditions reveals that the signal estimated from these experiments may evolve in noticeably different ways for some ocean variables. The combined signal and noise uncertainties translate into large uncertainties in estimates of detection time. Nevertheless, we find that ocean variables that are highly sensitive indicators of surface conditions, such as convective overturning in the North Atlantic, have shorter signal detection times (35–65 years) than deep‐ocean indicators (≥100 years). We investigate also whether the use of a multivariate detection vector increases the probability of early detection. We find that this can yield detection times of 35–60 years (relative to a 1985 reference date) if signal and noise are projected onto a common “fingerprint” which describes the expected signal direction. Optimization of the signal‐to‐noise ratio by (spatial) rotation of the fingerprint in the direction of low‐noise components of the stochastic forcing experiments noticeably reduces the detection time (to 10–45 years). However, rotation in space alone does not guarantee an improvement of the signal‐to‐noise ratio for a time‐dependent signal. This requires an “optimal fingerprint” strategy in which the detection pattern (fingerprint) is rotated in both space and time.

High resolution simulations of January and July climate over the western Alpine region with a nested Regional Modeling system

High resolution January and July present day climatologies over the central-western Alpine region are simulated with a Regional Climate Model (RegCM) nested within a General Circulation Model (GCM). The RegCM was developed at the National Center for Atmospheric Research (NCAR) and is run at 20 km grid point spacing. The model is driven by output from a “present day” climate simulation performed with the GCM ECHAM3 of the Max Planck Institute for Meteorology (MPI) at T106 resolution (~ 120 km). Five January and July simulations are conducted with the nested RegCM and the results for surface air temperature and precipitation are compared with a gridded observed dataset and a dataset from 99 observing stations throughout the Swiss territory. The driving ECHAM3 simulation reproduces well the position of the northeastern Atlantic jet, but underestimates the jet intensity over the Mediterranean. Precipitation over the Alpine region in the ECHAM3 simulation is close to observed in January but lower than observed in July. Compared to the driving GCM, the nested RegCM produces more precipitation in both seasons, mostly as a result of the stronger model orographic forcing. Average RegCM temperature over the Swiss region is 2–3 degrees higher than observed, while average precipitation is within 30% of observed values. The spatial distribution of precipitation is in general agreement with available gridded observations and the model reproduces the observed elevation dependency of precipitation in the summer. In the winter the simulated elevation of maximum precipitation amounts is lower than observed. Precipitation frequencies are overestimated, while precipitation intensities show a reasonable agreement with observations, especially in the winter. Sensitivity experiments with different cumulus parameterizations, soil moisture initialization and model topography are discussed. Overall, the model performance at the high resolution used here did not deteriorate compared to previous lower resolution experiments.

Water resources of the South Asian region in a warmer atmosphere

The global mean surface temperature may rise by about 0.3° C per decade during the next few decades as a result of anthropogenic greenhouse gas emissions in the earth's atmosphere. The data generated in the greenhouse warming simulations (Business-as-Usual scenario of IPCC) with the climate models developed at Max Planck Institute for Meteorology, Hamburg have been used to assess future plausible hydrological scenario for the South Asian region. The model results indicate enhanced surface warming (2.7°C for summer and 3.6°C for winter) over the land reginos of South Asia during the next hundred years. While there is no significant change in the precipitation over most of the land regions during winter, substantial increase in precipitation is likely to occur during summer. As a result, an increase in soil moisture is likely over central India, Bangladesh and South China during summer but a statistically significant decline in soil moisture is expected over central China in winter. A moderate decrease in surface runoff may occur over large areas of central China during winter while the flood prone areas of NE-India, Bangladesh and South China are likely to have an increase in surface runoff during summer by the end of next century.