Daily rainfall trend in the Valencia Region of Spain

Summary ?We have analyzed daily rainfall trends throughout the second half of the 20^th century in the western Mediterranean basin (Valencia Region, E of Spain). The area is characterized by high torrentiality, and during the second half of the 20^th century some of the highest daily rainfall values in the Mediterranean basin have been recorded. In this area, mean annual rainfall varies between 500 and 300 mm and is overwhelmingly dependent on just a few days of rain. Daily maximum rainfall varies on average from 120 mm day⁻¹ to 50 mm day⁻¹, and represents a mean of 17% (coastland) to 9% (inland) of annual rainfall. The 10 days in each year with the heaviest rainfall (called “higher events”) provide over 50% of the annual rainfall and can reach more than 400 mm on average. We compared the annual rainfall trend and the trend of higher and minor events defined by percentiles, both in volume and variability. We, therefore, tested whether annual rainfall changes depend on the trend of the higher (rainfall) events. To overlap spatial distribution of trends (i.e.: positive, no significant and negative trends) we have used cross-tab analysis. The results confirm the hypothesis that annual rainfall changes depend on changes found in just a few rainy events. Furthermore, in spite of their negative trend, higher events have increased their contribution to annual rainfall. As a consequence, although torrential events may have diminished in magnitude, future scenarios seem to be controlled by a limited number of rainy events which will become more and more variable year on year. The high spatial density of data used in this work, (97 observatories per 24.000 km², overall mean 1 observatory per 200 km²), suggests to us that extreme caution should be applied when analyzing regional and sub-regional changes in rainfall using GCM output, especially in areas of high torrentiality. Received August 1, 2002; revised November 11, 2002; accepted December 1, 2002 Published online May 19, 2003     

A multi-model ensemble of downscaled spatial climate change scenarios for the Dommel catchment, Western Europe

Regional or local scale hydrological impact studies require high resolution climate change scenarios which should incorporate some assessment of uncertainties in future climate projections. This paper describes a method used to produce a multi-model ensemble of multivariate weather simulations including spatial–temporal rainfall scenarios and single-site temperature and potential evapotranspiration scenarios for hydrological impact assessment in the Dommel catchment (1,350 km²) in The Netherlands and Belgium. A multi-site stochastic rainfall model combined with a rainfall conditioned weather generator have been used for the first time with the change factor approach to downscale projections of change derived from eight Regional Climate Model (RCM) experiments for the SRES A2 emission scenario for the period 2071–2100. For winter, all downscaled scenarios show an increase in mean daily precipitation (catchment average change of +9% to +40%) and typically an increase in the proportion of wet days, while for summer a decrease in mean daily precipitation (−16% to −57%) and proportion of wet days is projected. The range of projected mean temperature is 7.7°C to 9.1°C for winter and 19.9°C to 23.3°C for summer, relative to means for the control period (1961–1990) of 3.8°C and 16.8°C, respectively. Mean annual potential evapotranspiration is projected to increase by between +17% and +36%. The magnitude and seasonal distribution of changes in the downscaled climate change projections are strongly influenced by the General Circulation Model (GCM) providing boundary conditions for the RCM experiments. Therefore, a multi-model ensemble of climate change scenarios based on different RCMs and GCMs provides more robust estimates of precipitation, temperature and evapotranspiration for hydrological impact assessments, at both regional and local scale.     

Recent trends in observed temperature and precipitation extremes in the Yangtze River basin,China

Summary The present study is an analysis of the observed extreme temperature and precipitation trends over Yangtze from 1960 to 2002 on the basis of the daily data from 108 meteorological stations. The intention is to identify whether or not the frequency or intensity of extreme events has increased with climate warming over Yangtze River basin in the last 40 years. Both the Mann-Kendall (MK) trend test and simple linear regression were utilized to detect monotonic trends in annual and seasonal extremes. Trend tests reveal that the annual and seasonal mean maximum and minimum temperature trend is characterized by a positive trend and that the strongest trend is found in the winter mean minimum in the Yangtze. However, the observed significant trend on the upper Yangtze reaches is less than that found on the middle and lower Yangtze reaches and for the mean maximum is much less than that of the mean minimum. From the basin-wide point of view, significant increasing trends are observed in 1-day extreme temperature in summer and winter minimum, but there is no significant trend for 1-day maximum temperature. Moreover, the number of cold days ≤0 °C and ≤10 °C shows significant decrease, while the number of hot days (daily value ≥35 °C) shows only a minor decrease. The upward trends found in the winter minimum temperature in both the mean and the extreme value provide evidence of the warming-up of winter and of the weakening of temperature extremes in the Yangtze in last few decades. The monsoon climate implies that precipitation amount peaks in summer as does the occurrence of heavy rainfall events. While the trend test has revealed a significant trend in summer rainfall, no statistically significant change was observed in heavy rain intensity. The 1-day, 3-day and 7-day extremes show only a minor increase from a basin-wide point of view. However, a significant positive trend was found for the number of rainstorm days (daily rainfall ≥50 mm). The increase of rainstorm frequency, rather than intensity, on the middle and lower reaches contributes most to the positive trend in summer precipitation in the Yangtze.     

Super-ensemble of three RCMs for climate projection over East Asia and Taiwan

Runs of three regional climate models (RCMs) dynamically downscaling the outputs of atmosphere?Cocean coupling general circulation models (AOGCMs) are studied. These RCMs are NCAR-MM5, NCEP-RSM (Regional Spectral Model), and Purdue-PRM (Purdue Regional Model). A useful approach is developed to compare the variability, error, and spatial distribution of model-simulated results with respect to the Climatic Research Unit (CRU) datasets over East Asia and seven sub-regions during the 1990s. The results show that NCEP-RSM outperforms the other two in meeting criteria selected on evaluating the model performance. Furthermore, three super-ensemble approaches are tested on merging RCMs?? outputs. The inverse of the square error summation (ISES) method is selected as a suitable method with a generally good performance during the verification period. The projected future climate changes by ISES indicate larger temperature increases over high-latitude continent and smaller over low-latitude maritime areas. Rainfall will increase in summer over the central simulation domain, i.e. the eastern China, but decrease in winter, which are clearly linked to the variation in the synoptic airflows. Also, a more frequent occurrence of extreme rainfall events than what happened in the 1990s is projected. The projection over Taiwan suggests strong warming in summer, followed by autumn, winter, and spring. The interaction between the synoptic flow and the local terrain affects significantly the changes in precipitation. In general, larger change of the variability of rainfall will be over areas with lesser rainfall in the future, while lesser change will be over areas with more projected rainfall.     

Projections of Extreme Rainfall in Hong Kong in the 21st Century

The possible changes in the frequency of extreme rainfall events in Hong Kong in the 21st century wereinvestigated by statistically downscaling 30 sets of the daily global climate model projections (involvinga combination of 12 models and 3 greenhouse gas emission scenarios,namely,A2,A1B,and B1) of theFourth Assessment Report of the Intergovernmental Panel on Climate Change.To cater for the intermittentand skewed character of the daily rainfall,multiple stepwise logistic regression and multiple stepwise linearregression were employed to develop the downscaling models for predicting rainfall occurrence and rainfallamount,respectively.Verification of the simulation of the 1971-2000 climate reveals that the models ingeneral have an acceptable skill in reproducing past statistics of extreme rainfall events in Hong Kong.Theprojection results suggest that,in the 21st century,the annual number of rain days in Hong Kong is expectedto decrease while the daily rainfall intensity will increase,concurrent with the expected increase in annualrainfall.Based on the multi-model scenario ensemble mean,the annual number of rain day is expected todrop from 104 days in 1980-1999 to about 77 days in 2090-2099.For extreme rainfall events,about 90% ofthe model-scenario combinations indicate an increase in the annual number of days with daily rainfall 100mm (R100) towards the end of the 21st century.The mean number of R100 is expected to increase from 3.5days in 1980-1999 to about 5.3 days in 2090-2099.The projected changes in other extreme rainfall indicesalso suggest that the rainfall in Hong Kong in the 21st century may also become more extreme with moreuneven distributions of wet and dry periods.While most of the model-emission scenarios in general projectconsistent trends in the change of rainfall extremes in the 21st century,there is a large divergence in theprojections among different model/emission scenarios.This reflects that there are still large uncertainties inmodel simulations of future extreme rainfall events.     

Projection of Extreme Temperatures in Hong Kong in the 21st Century

The possible changes in the frequency of extreme temperature events in Hong Kong in the 21st century were investigated by statistically downscaling 26 sets of the daily global climate model projections (a combination of 11 models and 3 greenhouse gas emission scenarios, namely A2, A1B, and B1) of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. The models’ performance in simulating the past climate during 1971–2000 has also been verified and discussed. The verification revealed that the models in general have an acceptable skill in reproducing past statistics of extreme temperature events. Moreover, the models are more skillful in simulating the past climate of the hot nights and cold days than that of the very hot days. The projection results suggested that, in the 21st century, the frequency of occurrence of extremely high temperature events in Hong Kong would increase significantly while that of the extremely low temperature events is expected to drop significantly. Based on the multi-model scenario ensemble mean, the average annual numbers of very hot days and hot nights in Hong Kong are expected to increase significantly from 9 days and 16 nights in 1980–1999 to 89 days and 137 nights respectively in 2090–2099. On the other hand, the average annual number of cold days will drop from 17 days in 1980–1999 to about 1 day in 2090–2099. About 65 percent of the model-scenario combinations indicate that there will be on average less than one cold day in 2090–2099. While all the model-emission scenarios in general have projected consistent trends in the change of temperature extremes in the 21st century, there is a large divergence in the projections between difierent model/emission scenarios. This reflects that there are still large uncertainties in the model simulation of the future climate of extreme temperature events.     

Climate change projections for the Texas High Plains and Rolling Plains

Potential changes in future climate in the Texas Plains region were investigated in the context of agriculture by analyzing three climate model projections under the A2 climate scenario (medium–high emission scenario). Spatially downscaled historic (1971–2000) and future (2041–2070) climate datasets (rainfall and temperature) were downloaded from the North American Regional Climate Change Assessment Program (NARCCAP). Climate variables predicted by three regional climate models (RCMs) namely the Regional Climate Model Version3–Geophysical Fluid Dynamics Laboratory (RCM3-GFDL), Regional Climate Model Version3–Third Generation Coupled Global Climate Model (RCM3-CGCM3), and Canadian Regional Climate Model–Community Climate System Model (CRCM-CCSM) were evaluated in this study. Gaussian and Gamma distribution mapping techniques were employed to remove the bias in temperature and rainfall data, respectively. Both the minimum and maximum temperatures across the study region in the future showed an upward trend, with the temperatures increasing in the range of 1.9 to 2.9 °C and 2.0 to 3.2 °C, respectively. All three climate models predicted a decline in rainfall within a range of 30 to 127 mm in majority of counties across the study region. In addition, they predicted an increase in the intensity of extreme rainfall events in the future. The frost-free season as predicted by the three models showed an increase by 2.6–3.4 weeks across the region, and the number of frost days declined by 17.9 to 30 %. Overall, these projections indicate considerable changes to the climate in the Texas Plains region in the future, and these changes could potentially impact agriculture in this region.

     

Recent changes in dry spell and extreme rainfall events in Ethiopia

Summary This paper assesses recent changes in extremes of seasonal rainfall in Ethiopia based on daily rainfall data for 11 key stations over the period 1965–2002. The seasons considered are Kiremt (‘main rains’, June–September) and Belg (‘small rains’, February/March–May). The Mann-Kendall and linear regression trend tests show decreasing trends in the Kiremt and the Belg extreme intensity and maximum consecutive 5-day rains over eastern, southwestern and southern parts of Ethiopia whereas no trends are found in the remaining part of Ethiopia. In general, no trends are found in the yearly maximum length of Kiremt and Belg dry spells (days with rainfall below 1 mm) over Ethiopia.     

Projected Climate Change in the Northwestern Arid Regions of China: An Ensemble of Regional Climate Model Simulations

The projected temperature and precipitationchange under different emissions scenarios using Coupled Model Intercomparison Project Phase 5 models over the northwestern arid regions of China(NWAC) were analyzed using the ensemble of three high-resolution dynamical downscaling simulations: the simulation of the Regional Climate Model version 4.0(Reg CM4) forced by the Beijing Climate Center Climate System Model version 1.1(BCC_CSM1.1); the Hadley Centre Global Environmental Model version 3 regional climate model(Had GEM3-RA) forced by the Atmosphere-Ocean coupled Had GEM version 2(Had GEM2-AO); and the Weather Research and Forecasting(WRF) model forced by the Norwegian community Earth System Model(Nor ESM1-M). Model validation indicated that the multimodel simulations reproduce the spatial and temporal distribution of temperature and precipitation well. The temperature is projected to increase over NWAC under both the 4.5 and 8.5 Representative Concentration Pathways scenarios(RCP4.5 and RCP8.5, respectively) in the middle of the 21 st century, but the warming trend is larger under the RCP8.5 scenario. Precipitation shows a significant increasing trend in spring and winter under both RCP4.5 and RCP8.5; but in summer, precipitation is projected to decrease in the Tarim Basin and Junggar Basin. The regional averaged temperature and precipitation show increasing trends in the future over NWAC; meanwhile, the large variability of the winter mean temperature and precipitation may induce more extreme cold events and intense snowfall events in these regions in the future.     

Zonal winds and southeast Australian rainfall in global and regional climate models

Southeast Australia is a region of high rainfall variability related to major climate drivers, with a long-term declining trend in cool-season rainfall. Projections of future rainfall trends are uncertain in this region, despite projected southward shifts in the subtropical ridge and mid-latitude westerlies. This appears to be related to a poor representation of the spatial relationships between rainfall variability and zonal wind patterns across southeast Australia in the latest Coupled Model Intercomparison Project ensemble, particularly in the areas where weather systems embedded in the mid-latitude westerlies are the main source of cool-season rainfall. Downscaling with regional climate models offers improvements in the mean rainfall climatology, and shows some ability to correct for poor modelled relationships between rainfall and zonal winds along the east coast of Australia. However, it provides only minor improvements to these relationships in southeast Australia, despite the improved representation of topographic features. These results suggest that both global and regional climate models may fail to translate projected circulation changes into their likely rainfall impacts in southeast Australia.     

Future projections and uncertainty assessment of extreme rainfall intensity in the United States from an ensemble of climate models

Changes in climate are expected to lead to changes in the characteristics extreme rainfall frequency and intensity. In this study, we propose an integrated approach to explore potential changes in intensity-duration-frequency (IDF) relationships. The approach incorporates uncertainties due to both the short simulation periods of regional climate models (RCMs) and the differences in IDF curves derived from multiple RCMs in the North American Regional Climate Change Assessment Program (NARCCAP). The approach combines the likelihood of individual RCMs according to the goodness of fit between the extreme rainfall intensities from the RCMs’ historic runs and those from the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) data set and Bayesian model averaging (BMA) to assess uncertainty in IDF predictions. We also partition overall uncertainties into within-model uncertainty and among-model uncertainty. Results illustrate that among-model uncertainty is the dominant source of the overall uncertainty in simulating extreme rainfall for multiple locations in the U.S., pointing to the difficulty of predicting future climate, especially extreme rainfall regimes. For all locations a more intense extreme rainfall occurs in future climate; however the rate of increase varies among locations.     

Changes in extreme wind speeds in NW Europe simulated by generalized linear models

Summary We investigate the capability of generalized linear models (GLMs) to simulate sequences of daily maximum wind speed (DMWS), at a selection of locations in NW Europe. Models involving both the gamma and Weibull distributions have been fitted to the NCEP reanalysis data for the period 1958–1998. In simulations, these models successfully reproduce the observed increasing trends up to 0.3 m/s per decade in coastal or oceanic locations for the wintertime and the decreasing trends down to –0.2 m/s per decade in inland Europe for the summertime. Annually extreme winds exhibit an increasing tendency (with median estimates up to 0.6 m/s per decade) at the studied locations. The gamma model slightly overestimates the upper percentiles of the wind speed distribution, but reproduces trends better than the Weibull model. In both the NCEP data and GLM simulations, local extreme DMWS events (defined in terms of threshold exceedances) have increased dramatically in frequency during winter; decreasing trends are more common in summer. The NCEP data indicate similar trends in the frequencies of large-scale windy events (defined via simultaneous exceedances at 2 or more locations). Overall, these events have increased in number; at the scale of the North Sea basin, their number may have changed from 3–5 days per year during the earlier decades, to 5–7 days per year during later decades based on observational estimates. An increase in the frequency of large-scale extreme winter storms is implied. The GLMs underestimate these large-scale event frequencies, and provide imprecise estimates of the corresponding secular trends. These problems could be rectified by using a better representation of spatial dependence. The present results suggest that GLMs offer a useful tool to study local climate extremes in the context of changing climate distributions; they also provide some pointers towards improving the representation of extremes at a regional scale.     

A study on combining global and regional climate model results for generating climate scenarios of temperature and precipitation for the Netherlands

Climate scenarios for the Netherlands are constructed by combining information from global and regional climate models employing a simplified, conceptual framework of three sources (levels) of uncertainty impacting on predictions of the local climate. In this framework, the first level of uncertainty is determined by the global radiation balance, resulting in a range of the projected changes in the global mean temperature. On the regional (1,000–5,000 km) scale, the response of the atmospheric circulation determines the second important level of uncertainty. The third level of uncertainty, acting mainly on a local scale of 10 (and less) to 1,000 km, is related to the small-scale processes, like for example those acting in atmospheric convection, clouds and atmospheric meso-scale circulations—processes that play an important role in extreme events which are highly relevant for society. Global climate models (GCMs) are the main tools to quantify the first two levels of uncertainty, while high resolution regional climate models (RCMs) are more suitable to quantify the third level. Along these lines, results of an ensemble of RCMs, driven by only two GCM boundaries and therefore spanning only a rather narrow range in future climate predictions, are rescaled to obtain a broader uncertainty range. The rescaling is done by first disentangling the climate change response in the RCM simulations into a part related to the circulation, and a residual part which is related to the global temperature rise. Second, these responses are rescaled using the range of the predictions of global temperature change and circulation change from five GCMs. These GCMs have been selected on their ability to simulate the present-day circulation, in particular over Europe. For the seasonal means, the rescaled RCM results obey the range in the GCM ensemble using a high and low emission scenario. Thus, the rescaled RCM results are consistent with the GCM results for the means, while adding information on the small scales and the extremes. The method can be interpreted as a combined statistical–dynamical downscaling approach, with the statistical relations based on regional model output.     

Climate change scenarios of precipitation extremes in Central Europe from ENSEMBLES regional climate models

The study examines future scenarios of precipitation extremes over Central Europe in an ensemble of 12 regional climate model (RCM) simulations with the 25-km resolution, carried out within the European project ENSEMBLES. We apply the region-of-influence method as a pooling scheme when estimating distributions of extremes, which consists in incorporating data from a ‘region’ (set of gridboxes) when fitting an extreme value distribution in any single gridbox. The method reduces random variations in the estimates of parameters of the extreme value distribution that result from large spatial variability of heavy precipitation. Although spatial patterns differ among the models, most RCMs simulate increases in high quantiles of precipitation amounts when averaged over the area for the late-twenty-first century (2070–2099) climate in both winter and summer. The sign as well as the magnitude of the projected change vary only little for individual parts of the distribution of daily precipitation in winter. In summer, on the other hand, the projected changes increase with the quantile of the distribution in all RCMs, and they are negative (positive) for parts of the distribution below (above) the 98% quantile if averaged over the RCMs. The increases in precipitation extremes in summer are projected in spite of a pronounced drying in most RCMs. Although a rather general qualitative agreement of the models concerning the projected changes of precipitation extremes is found in both winter and summer, the uncertainties in climate change scenarios remain large and would likely further increase considerably if a more complete ensemble of RCM simulations driven by a larger suite of global models and with a range of possible scenarios of the radiative forcing is available.     

Future evolution of extreme precipitation in the Mediterranean

Mediterranean basins can be impacted by severe floods caused by extreme rainfall, and there is a growing awareness about the possible increase in these heavy rainfall events due to climate change. In this study, the climate change impacts on extreme daily precipitation in 102 catchments covering the whole Mediterranean basin are investigated using nonstationary extreme value model applied to annual maximum precipitation in an ensemble of high-resolution regional climate model (RCM) simulations from the Euro-CORDEX experiment. Results indicate contrasted trends, with significant increasing trends in Northern catchments and conversely decreasing trends in Southern catchments. For most cases, the time of signal emergence for these trends is before the year 2000. The same spatial pattern is obtained under the two climate scenarios considered (RCP4.5 and RCP8.5) and in most RCM simulations, suggesting a robust climate change signal. The strongest multi-model agreement concerns the positive trends, which can exceed +?20% by the end of the twenty-first century in some simulations, impacting South France, North Italy, and the Balkans. For these areas, society-relevant strong impacts of such Mediterranean extreme precipitation changes could be expected in particular concerning flood-related damages.     

High resolution regional climate model simulations for Germany: Part II—projected climate changes

The projected climate change signals of a five-member high resolution ensemble, based on two global climate models (GCMs: ECHAM5 and CCCma3) and two regional climate models (RCMs: CLM and WRF) are analysed in this paper (Part II of a two part paper). In Part I the performance of the models for the control period are presented. The RCMs use a two nest procedure over Europe and Germany with a final spatial resolution of 7 km to downscale the GCM simulations for the present (1971–2000) and future A1B scenario (2021–2050) time periods. The ensemble was extended by earlier simulations with the RCM REMO (driven by ECHAM5, two realisations) at a slightly coarser resolution. The climate change signals are evaluated and tested for significance for mean values and the seasonal cycles of temperature and precipitation, as well as for the intensity distribution of precipitation and the numbers of dry days and dry periods. All GCMs project a significant warming over Europe on seasonal and annual scales and the projected warming of the GCMs is retained in both nests of the RCMs, however, with added small variations. The mean warming over Germany of all ensemble members for the fine nest is in the range of 0.8 and 1.3 K with an average of 1.1 K. For mean annual precipitation the climate change signal varies in the range of ?2 to 9 % over Germany within the ensemble. Changes in the number of wet days are projected in the range of ±4 % on the annual scale for the future time period. For the probability distribution of precipitation intensity, a decrease of lower intensities and an increase of moderate and higher intensities is projected by most ensemble members. For the mean values, the results indicate that the projected temperature change signal is caused mainly by the GCM and its initial condition (realisation), with little impact from the RCM. For precipitation, in addition, the RCM affects the climate change signal significantly.     

Geographic Variation in Growing Season Rainfall during three Decades in Nigeria Using Principal Component and Cluster Analyses

Summary  Reports of changes in the seasonal and annual rainfall in Nigeria suggests that a more detailed analyses of the geographic extent of these changes and of their impact on agriculture could be of value. Variation in the growing season (April to September) rainfall from stations across Nigeria was analysed over the 30-yr period, 1960–90. Regression analyses were used to examine long-term trends. Principal component and cluster analyses were used to group stations with similar trends in standardised seasonal rainfall. Mean accumulated standardised seasonal rainfall were used to examine short- and medium-term trends for each of the groups identified. Significant (P ≤ 0.05) decreases in rainy season rainfall were found at 8 stations mostly in the Guinea and arid/semi-arid savannas of northern Nigeria, whereas no station showed significant increases. Examination of the monthly (April through September) rainfall showed that only three – Kano, Sokoto and Potiskum in the arid/semi-arid savanna – of the twenty-three stations used in the analysis had declining rainfall trends for each of the months April to September and subsequently declining seasonal rainfall trends. However, 12 to 15 stations had consistently declining rainfall trends in atleast some but not all the growing season months. However, a similar pattern was not the case in terms of increasing rainfall trends, where only one to three stations had consistently increasing rainfall trends in some but not all of the months from April to September. Stations that showed increasing rainfall trends were in the southern parts of Nigeria. Six groups with similar patterns in standardised seasonal rainfall were identified by Principal Component and Cluster analyses. For most of the groups, the period from 1967 to 1973 was that of consistently below average seasonal rainfall. However, the timing and extent of the decline varied with location. Common to stations in four of the six groups was a negative trend in seasonal rainfall for the period considered. The geographic variation in seasonal rainfall trends has tremendous agricultural significance since there are indications that the reliability of the season is decreasing from the humid forest zone with positive seasonal trends to the arid/semi-arid savanna with significant negative seasonal trends. Received June 24, 1998 Revised December 18, 1998     

Climate change projections over India by a downscaling approach using PRECIS

This study presents a comprehensive assessment of the possible regional climate change over India by using Providing REgional Climates for Impacts Studies (PRECIS), a regional climate model (RCM) developed by Met Office Hadley Centre in the United Kingdom. The lateral boundary data for the simulations were taken from a sub-set of six members sampled from the Hadley Centre’s 17- member Quantified Uncertainty in Model Projections (QUMP) perturbed physics ensemble. The model was run with 25 km × 25 km resolution from the global climate model (GCM) - HadCM3Q at the emission rate of special report on emission scenarios (SRES) A1B scenarios. Based on the model performance, six member ensembles running over a period of 1970-2100 in each experiment were utilized to predict possible range of variations in the future projections for the periods 2020s (2005-2035), 2050s (2035-2065) and 2080s (2065-2095) with respect to the baseline period (1975-2005). The analyses concentrated on maximum temperature, minimum temperature and rainfall over the region. For the whole India, the projections of maximum temperature from all the six models showed an increase within the range 2.5°C to 4.4°C by end of the century with respect to the present day climate simulations. The annual rainfall projections from all the six models indicated a general increase in rainfall being within the range 15-24%. Mann-Kendall trend test was run on time series data of temperatures and rainfall for the whole India and the results from some of the ensemble members indicated significant increasing trends. Such high resolution climate change information may be useful for the researchers to study the future impacts of climate change in terms of extreme events like floods and droughts and formulate various adaptation strategies for the society to cope with future climate change.     

South Asian summer monsoon precipitation variability: Coupled climate model simulations and projections under IPCC AR4

Summary South Asian summer monsoon precipitation and its variability are examined from the outputs of the coupled climate models assessed as part of the Intergovernmental Panel on Climate Change Fourth Assessment. Out of the 22 models examined, 19 are able to capture the maximum rainfall during the summer monsoon period (June through September) with varying amplitude. While two models are unable to reproduce the annual cycle well, one model is unable to simulate the summer monsoon season. The simulated inter-annual variability from the 19 models is examined with respect to the mean precipitation, coefficient of variation, long-term trends and the biennial tendency. The model simulated mean precipitation varies from 500 mm to 900 mm and coefficient of variation from 3 to 13%. While seven models exhibit long-term trends, eight are able to simulate the biennial nature of the monsoon rainfall. Six models, which generate the most realistic 20th century monsoon climate over south Asia, are selected to examine future projections under the doubling CO₂ scenario. Projections reveal a significant increase in mean monsoon precipitation of 8% and a possible extension of the monsoon period based on the multi-model ensemble technique. Extreme excess and deficient monsoons are projected to intensify. The projected increase in precipitation could be attributed to the projected intensification of the heat low over northwest India, the trough of low pressure over the Indo-Gangetic plains, and the land–ocean pressure gradient during the establishment phase of the monsoon. The intensification of these pressure systems could be attributed to the decline in winter/spring snowfall. Furthermore, a decrease of winter snowfall over western Eurasia is also projected along with an increase of winter snowfall over Siberia/eastern Eurasia. This projected dipole snow configuration during winter could imply changes in mid-latitude circulation conducive to subsequent summer monsoon precipitation activity. An increase in precipitable water of 12–16% is projected over major parts of India. A maximum increase of about 20–24% is found over the Arabian Peninsula, adjoining regions of Pakistan, northwest India and Nepal. Although the projected summer monsoon circulation appears to weaken, the projected anomalous flow over the Bay of Bengal (Arabian Sea) will support oceanic moisture convergence towards the southern parts of India and Sri Lanka (northwest India and adjoining regions). The ENSO-Monsoon relationship is also projected to weaken.