Changes in frost, snow and Baltic sea ice by the end of the twenty-first century based on climate model projections for Europe

Changes in indices related to frost and snow in Europe by the end of the twenty-first century were analyzed based on experiments performed with seven regional climate models (RCMs). All the RCMs regionalized information from the same general circulation model (GCM), applying the IPCC-SRES A2 radiative forcing scenario. In addition, some simulations used SRES B2 radiative forcing and/or boundary conditions provided by an alternative GCM. Ice cover over the Baltic Sea was examined using a statistical model that related the annual maximum extent of ice to wintertime coastal temperatures. Fewer days with frost and snow, shorter frost seasons, a smaller liquid water equivalent of snow, and milder sea ice conditions were produced by all model simulations, irrespective of the forcing scenario and the driving GCM. The projected changes have implications across a diverse range of human activities. Details of the projections were subject to differences in RCM design, deviations between the boundary conditions of the driving GCMs, uncertainties in future emissions and random effects due to internal climate variability. A larger number of GCMs as drivers of the RCMs would most likely have resulted in somewhat wider ranges in the frost, snow and sea ice estimates than those presented in this paper.     

GCM-based regional temperature and precipitation change estimates for Europe under four SRES scenarios applying a super-ensemble pattern-scaling method

Seasonal GCM-based temperature and precipitation projections for the end of the 21st century are presented for five European regions; projections are compared with corresponding estimates given by the PRUDENCE RCMs. For most of the six global GCMs studied, only responses to the SRES A2 and B2 forcing scenarios are available. To formulate projections for the A1FI and B1 forcing scenarios, a super-ensemble pattern-scaling technique has been developed. This method uses linear regression to represent the relationship between the local GCM-simulated response and the global mean temperature change simulated by a simple climate model. The method has several advantages: e.g., the noise caused by internal variability is reduced, and the information provided by GCM runs performed with various forcing scenarios is utilized effectively. The super-ensemble method proved especially useful when only one A2 and one B2 simulation is available for an individual GCM. Next, 95% probability intervals were constructed for regional temperature and precipitation change, separately for the four forcing scenarios, by fitting a normal distribution to the set of projections calculated by the GCMs. For the high-end of the A1FI uncertainty interval, temperature increases close to 10°C could be expected in the southern European summer and northern European winter. Conversely, the low-end warming estimates for the B1 scenario are ~ 1°C. The uncertainty intervals of precipitation change are quite broad, but the mean estimate is one of a marked increase in the north in winter and a drastic reduction in the south in summer. In the RCM simulations driven by a single global model, the spread of the temperature and precipitation projections tends to be smaller than that in the GCM simulations, but it is possible to reduce this disparity by employing several driving models for all RCMs. In the present suite of simulations, the difference between the mean GCM and RCM projections is fairly small, regardless of the number or driving models applied.     

Climate change projections of the North American Regional Climate Change Assessment Program (NARCCAP)

We investigate major results of the NARCCAP multiple regional climate model (RCM) experiments driven by multiple global climate models (GCMs) regarding climate change for seasonal temperature and precipitation over North America. We focus on two major questions: How do the RCM simulated climate changes differ from those of the parent GCMs and thus affect our perception of climate change over North America, and how important are the relative contributions of RCMs and GCMs to the uncertainty (variance explained) for different seasons and variables? The RCMs tend to produce stronger climate changes for precipitation: larger increases in the northern part of the domain in winter and greater decreases across a swath of the central part in summer, compared to the four GCMs driving the regional models as well as to the full set of CMIP3 GCM results. We pose some possible process-level mechanisms for the difference in intensity of change, particularly for summer. Detailed process-level studies will be necessary to establish mechanisms and credibility of these results. The GCMs explain more variance for winter temperature and the RCMs for summer temperature. The same is true for precipitation patterns. Thus, we recommend that future RCM-GCM experiments over this region include a balanced number of GCMs and RCMs.     

Recent Near-surface Temperature Trends in the Antarctic Peninsula from Observed,Reanalysis and Regional Climate Model Data

This study investigates the recent near-surface temperature trends over the Antarctic Peninsula.We make use of available surface observations,ECMWF’s ERA5 and its predecessor ERA-Interim,as well as numerical simulations,allowing us to contrast different data sources.We use hindcast simulations performed with Polar-WRF over the Antarctic Peninsula on a nested domain configuration at 45 km(PWRF-45)and 15 km(PWRF-15)spatial resolutions for the period 1991?2015.In addition,we include hindcast simulations of KNMI-RACMO21P obtained from the CORDEX-Antarctica domain(~50 km)for further comparisons.Results show that there is a marked windward warming trend except during summer.This windward warming trend is particularly notable in the autumn season and likely to be associated with the recent deepening of the Amundsen/Bellingshausen Sea low and warm advection towards the Antarctic Peninsula.On the other hand,an overall summer cooling is characterized by the strengthening of the Weddell Sea low as well as an anticyclonic trend over the Amundsen Sea accompanied by northward winds.The persistent cooling trend observed at the Larsen Ice Shelf station is not captured by ERA-Interim,whereas hindcast simulations indicate that there is a clear pattern of windward warming and leeward cooling.Furthermore,larger temporal correlations and lower differences exhibited by PWRF-15 illustrate the existence of the added value in the higher spatial resolution simulation.     

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.     

Object-based tracking of precipitation systems in western Canada: the importance of temporal resolution of source data

Object-based algorithm provides additional spatiotemporal information of precipitation, besides traditional aspects such as amount and intensity. Using the Method for Object-based Diagnostic Evaluation with Time Dimension (MODE-TD, or MTD), precipitation features in western Canada have been analyzed comprehensively based on the Canadian Precipitation Analysis, North American Regional Reanalysis, Multi-Source Weighted-Ensemble Precipitation, and a convection-permitting climate model. We found light precipitation occurs frequently in the interior valleys of western Canada while moderate to heavy precipitation is rare there. The size of maritime precipitation system near the coast is similar to the continental precipitation system on the Prairies for moderate to heavy precipitation while light precipitation on the Prairies is larger in size than that occurs near the coast. For temporal features, moderate to heavy precipitation lasts longer than light precipitation over the Pacific coast, and precipitation systems on the Prairies generally move faster than the coastal precipitation. For annual cycle, the west coast has more precipitation events in cold seasons while more precipitation events are identified in warm seasons on the Prairies due to vigorous convection activities. Using two control experiments, the way how the spatiotemporal resolution of source data influences the MTD results has been examined. Overall, the spatial resolution of source data has little influence on MTD results. However, MTD driven by dataset with coarse temporal resolution tend to identify precipitation systems with relatively large size and slow propagation speed. This kind of precipitation systems normally have short track length and relatively long lifetime. For a typical precipitation system (0.7 \(\sim \) 2 \(\times \) 10\(^{4}\) km\(^{2}\) in size) in western Canada, the maximum propagation speed that can be identified by 6-h data is approximately 25 km h\(^{-1}\), 33 km h\(^{-1}\) for 3-h, and 100 km h\(^{-1}\) for hourly dataset. Since the propagation speed of precipitation systems in North America is basically between 0 and 80 km h\(^{-1}\), we argue that precipitation features can be identified properly by MTD only when dataset with hourly or higher temporal resolution is used.

     

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.     

Atmospheric circulation in regional climate models over Central Europe: links to surface air temperature and the influence of driving data

The study examines simulation of atmospheric circulation, represented by circulation indices (flow direction, strength and vorticity), and links between circulation and daily surface air temperatures in regional climate models (RCMs) over Central Europe. We explore control simulations of five high-resolution RCMs from the ENSEMBLES project driven by re-analysis (ERA-40) and the same global climate model (ECHAM5 GCM) plus of one RCM (RCA) driven by different GCMs. The aims are to (1) identify errors in RCM-simulated distributions of circulation indices in individual seasons, (2) identify errors in simulated temperatures under particular circulation indices, and (3) compare performance of individual RCMs with respect to the driving data. Although most of the RCMs qualitatively reflect observed distributions of the airflow indices, each produces distributions significantly different from the observations. General biases include overestimation of the frequency of strong flow days and of strong cyclonic vorticity. Some circulation biases obviously propagate from the driving data. ECHAM5 and all simulations driven by ECHAM5 underestimate frequency of easterly flow, mainly in summer. Except for HIRHAM, however, all RCMs driven by ECHAM5 improve on the driving GCM in simulating atmospheric circulation. The influence on circulation characteristics in the nested RCM differs between GCMs, as demonstrated in a set of RCA simulations with different driving data. The driving data control on circulation in RCA is particularly weak for the BCM GCM, in which case RCA substantially modifies (but does not improve) the circulation from the driving data in both winter and summer. Those RCMs with the most distorted atmospheric circulation are HIRHAM driven by ECHAM5 and RCA driven by BCM. Relatively strong relationships between circulation indices and surface air temperatures were found in the observed data for Central Europe. The links differ by season and are usually stronger for daily maxima than minima. RCMs qualitatively reproduce these relationships. Effects of the driving model biases were found on RCMs’ performance in reproducing not only atmospheric circulation but also the links to surface temperature. However, the RCM formulation appears to be more important than the driving data in representing the latter. Differences of the circulation-to-temperature links among the RCA simulations are smaller and the links tend to be more realistic compared to the driving GCMs.     

High resolution regional climate model simulations for Germany: part I—validation

A five-member ensemble of regional climate model (RCM) simulations for Europe, with a high resolution nest over Germany, is analysed in a two-part paper: Part I (the current paper) presents the performance of the models for the control period, and Part II presents results for near future climate changes. Two different RCMs, CLM and WRF, were used to dynamically downscale simulations with the ECHAM5 and CCCma3 global climate models (GCMs), as well as the ERA40-reanalysis for validation purposes. Three realisations of ECHAM5 and one with CCCma3 were downscaled with CLM, and additionally one realisation of ECHAM5 with WRF. An approach of double nesting was used, first to an approximately 50 km resolution for entire Europe and then to a domain of approximately 7 km covering Germany and its near surroundings. Comparisons of the fine nest simulations are made to earlier high resolution simulations for the region with the RCM REMO for two ECHAM5 realisations. Biases from the GCMs are generally carried over to the RCMs, which can then reduce or worsen the biases. The bias of the coarse nest is carried over to the fine nest but does not change in amplitude, i.e. the fine nest does not add additional mean bias to the simulations. The spatial pattern of the wet bias over central Europe is similar for all CLM simulations, and leads to a stronger bias in the fine nest simulations compared to that of WRF and REMO. The wet bias in the CLM model is found to be due to a too frequent drizzle, but for higher intensities the distributions are well simulated with both CLM and WRF at the 50 and 7 km resolutions. Also the spatial distributions are close to high resolution gridded observations. The REMO model has low biases in the domain averages over Germany and no drizzle problem, but has a shift in the mean precipitation patterns and a strong overestimation of higher intensities. The GCMs perform well in simulating the intensity distribution of precipitation at their own resolution, but the RCMs add value to the distributions when compared to observations at the fine nest resolution.     

Modeling Study of Foehn Wind Events in Antarctic Peninsula with WRF Forced by CCSM

Significant changes have occurred in the Antarctic Peninsula (AP) including warmer temperatures, accelerated melting of glaciers, and breakup of ice shelves. This study uses the Weather Research and Forecasting model (WRF) forced by the Community Climate System Model 4 (CCSM) simulations to study foehn wind warming in AP. Weather systems responsible for generating the foehn events are two cyclonic systems that move toward and/or cross over AP. WRF simulates the movement of cyclonic systems and the resulting foehn wind warming that is absent in CCSM. It is found that the warming extent along a transect across the central AP toward Larsen C Ice Shelf (LCIS) varies during the simulation period and the maximum warming moves from near the base of leeward slopes to over 40 km away extending toward the attached LCIS. Our analysis suggests that the foehn wind warming is negatively correlated with the incoming air temperature and the mountain top temperature during periods without significant precipitation, in which isentropic drawdown is the dominant heating mechanism. On the other hand, when significant precipitation occurs along the windward side of AP, latent heating is the major heating mechanism evidenced by positive relations between the foehn wind warming and 1) incoming air temperature, 2) windward precipitation, and 3) latent heating. Foehn wind warming caused by isentropic drawdown also tends to be stronger than that caused by latent heating. Comparison of WRF simulations forced by original and corrected CCSM data indicates that foehn wind warming is stronger in the original CCSM forced simulation when no significant windward precipitation is present. The foehn wind warming becomes weaker in both simulations when there is significant windward precipitation. This suggests that model’s ability to resolve the foehn warming varies with the forcing data, but the precipitation impact on the leeward warming is consistent.     

Dynamical downscaling: Fundamental issues from an NWP point of view and recommendations

Dynamical downscaling has been recognized as a useful tool not only for the climate community, but also for associated application communities such as the environmental and hydrological societies. Although climate projection data are available in lower-resolution general circulation models (GCMs), higher-resolution climate projections using regional climate models (RCMs) have been obtained over various regions of the globe. Various model outputs from RCMs with a high resolution of even as high as a few km have become available with heavy weight on applications. However, from a scientific point of view in numerical atmospheric modeling, it is not clear how to objectively judge the degree of added value in the RCM output against the corresponding GCM results. A key factor responsible for skepticism is based on the fundamental limitations in the nesting approach between GCMs and RCMs. In this article, we review the current status of the dynamical downscaling for climate prediction, focusing on basic assumptions that are scrutinized from a numerical weather prediction (NWP) point of view. Uncertainties in downscaling due to the inconsistencies in the physics packages between GCMs and RCMs were revealed. Recommendations on how to tackle the ultimate goal of dynamical downscaling were also described.     

Assessing climate change impacts on hydrology from an ensemble of regional climate models,model scales and linking methods – a case study on the Lule River basin

This paper investigates how using different regional climate model (RCM) simulations affects climate change impacts on hydrology in northern Europe using an offline hydrological model. Climate change scenarios from an ensemble of seven RCMs, two global climate models (GCMs), two global emissions scenarios and two RCMs of varying resolution were used. A total of 15 climate change simulations were included in studies on the Lule River basin in Northern Sweden. Two different approaches to transfer climate change from the RCMs to hydrological models were tested. A rudimentary estimate of change in hydropower potential on the Lule River due to climate change was also made. The results indicate an overall increase in river flow, earlier spring peak flows and an increase in hydropower potential. The two approaches for transferring the signal of climate change to the hydrological impacts model gave similar mean results, but considerably different seasonal dynamics, a result that is highly relevant for other types of climate change impacts studies.     

The WAMME regional model intercomparison study

Results from five regional climate models (RCMs) participating in the West African Monsoon Modeling and Evaluation (WAMME) initiative are analyzed. The RCMs were driven by boundary conditions from National Center for Environmental Prediction reanalysis II data sets and observed sea-surface temperatures (SST) over four May–October seasons, (2000 and 2003–2005). In addition, the simulations were repeated with two of the RCMs, except that lateral boundary conditions were derived from a continuous global climate model (GCM) simulation forced with observed SST data. RCM and GCM simulations of precipitation, surface air temperature and circulation are compared to each other and to observational evidence. Results demonstrate a range of RCM skill in representing the mean summer climate and the timing of monsoon onset. Four of the five models generate positive precipitation biases and all simulate negative surface air temperature biases over broad areas. RCM spatial patterns of June–September mean precipitation over the Sahel achieve spatial correlations with observational analyses of about 0.90, but within two areas south of 10°N the correlations average only about 0.44. The mean spatial correlation coefficient between RCM and observed surface air temperature over West Africa is 0.88. RCMs show a range of skill in simulating seasonal mean zonal wind and meridional moisture advection and two RCMs overestimate moisture convergence over West Africa. The 0.5° computing grid enables three RCMs to detect local minima related to high topography in seasonal mean meridional moisture advection. Sensitivity to lateral boundary conditions differs between the two RCMs for which this was assessed. The benefits of dynamic downscaling the GCM seasonal climate prediction are analyzed and discussed.     

Climate change scenarios of heat waves in Central Europe and their uncertainties

The study examines climate change scenarios of Central European heat waves with a focus on related uncertainties in a large ensemble of regional climate model (RCM) simulations from the EURO-CORDEX and ENSEMBLES projects. Historical runs (1970–1999) driven by global climate models (GCMs) are evaluated against the E-OBS gridded data set in the first step. Although the RCMs are found to reproduce the frequency of heat waves quite well, those RCMs with the coarser grid (25 and 50 km) considerably overestimate the frequency of severe heat waves. This deficiency is improved in higher-resolution (12.5 km) EURO-CORDEX RCMs. In the near future (2020–2049), heat waves are projected to be nearly twice as frequent in comparison to the modelled historical period, and the increase is even larger for severe heat waves. Uncertainty originates mainly from the selection of RCMs and GCMs because the increase is similar for all concentration scenarios. For the late twenty-first century (2070–2099), a substantial increase in heat wave frequencies is projected, the magnitude of which depends mainly upon concentration scenario. Three to four heat waves per summer are projected in this period (compared to less than one in the recent climate), and severe heat waves are likely to become a regular phenomenon. This increment is primarily driven by a positive shift of temperature distribution, but changes in its scale and enhanced temporal autocorrelation of temperature also contribute to the projected increase in heat wave frequencies.     

Gradient in the climate change signal of European discharge predicted by a multi-model ensemble

In order to perform hydrological studies on the PRUDENCE regional climate model (RCM) simulations, a special focus was put on the discharge from large river catchments located in northern and central Europe. The discharge was simulated with a simplified land surface (SL) scheme and the Hydrological Discharge (HD) model. The daily fields of precipitation, 2 m temperature and evapotranspiration from the RCM simulations were used as forcing. Therefore the total catchment water balances are constrained by the hydrological cycle of the different RCMs. The validation of the simulated hydrological cycle from the control simulations shows that the multi-model ensemble mean is closer to the observations than each of the models, especially if different catchments and hydrological variables are considered. Therefore, the multi-model ensemble mean can be used to largely reduce the uncertainty that is introduced by a single RCM. This also provides more confidence in the future projections for the multi-model ensemble means. The scenario simulations predict a gradient in the climate change signal over Northern and Central Europe. Common features are the overall warming and the general increase of evapotranspiration. But while in the northern parts the warming will enhance the hydrological cycle leading to an increased discharge, the large warming, especially in the summer, will slow down the hydrological cycle caused by a drying in the central parts of Europe which is accompanied by a reduction of discharge. The comparison of the changes predicted by the multi-model ensemble mean to the changes predicted by the driving GCM indicates that the RCMs can compensate problems that a driving GCM may have with local scale processes or parameterizations.     

Global high resolution versus Limited Area Model climate change projections over Europe: quantifying confidence level from PRUDENCE results

Four high resolution atmospheric general circulation models (GCMs) have been integrated with the standard forcings of the PRUDENCE experiment: IPCC-SRES A2 radiative forcing and Hadley Centre sea surface temperature and sea-ice extent. The response over Europe, calculated as the difference between the 2071–2100 and the 1961–1990 means is compared with the same diagnostic obtained with nine Regional Climate Models (RCM) all driven by the Hadley Centre atmospheric GCM. The seasonal mean response for 2m temperature and precipitation is investigated. For temperature, GCMs and RCMs behave similarly, except that GCMs exhibit a larger spread. However, during summer, the spread of the RCMs—in particular in terms of precipitation—is larger than that of the GCMs. This indicates that the European summer climate is strongly controlled by parameterized physics and/or high-resolution processes. The temperature response is larger than the systematic error. The situation is different for precipitation. The model bias is twice as large as the climate response. The confidence in PRUDENCE results comes from the fact that the models have a similar response to the IPCC-SRES A2 forcing, whereas their systematic errors are more spread. In addition, GCM precipitation response is slightly but significantly different from that of the RCMs.     

Comparisons of Low-Level Circulation Characteristics between ECHAM5/MPI-OM Results and NCEP/NCAR Re-Analysis Data in East Asia

Regional climate models(RCMs) can provide far more precise information than general circulation models(GCMs).However,RCMs depend on GCM results or re-analysis products providing boundary conditions,especially for future climate scenarios.Meanwhile,the capacity of RCMs to reproduce precipitation is strongly connected to its performance on circulation and moisture transport simulations in the low troposphere,which is the key problem with RCMs at present.In the Regional Climate Model Inter-comparison Project for East Asia(RMIP III),the results of ECHAM5/MPI-OM(the European Centre-Hamburg model version 5/Max Planck Institute Ocean Model,simplified as E5OM here) are used to drive RCMs for the past(1978?2000) climate simulation and future(2038?70) climate scenarios.Therefore,it is necessary to test E5OM’s ability to represent atmospheric circulation,which defines the large-scale circulation for RCMs.Here,comparisons between the E5OM results and NCEP/NCAR(simplified as NCEP) re-analysis data in the low troposphere for the years 1978 to 2000 are performed.The results show that E5OM results can generally reproduce atmospheric circulations in the low troposphere.However,differences can be detected in East Asian summer and winter monsoon simulations.For summer,there is an anti-cyclone circulation for the difference of wind vector at 850 hPa in Southeast China,the Indo-China Peninsula,the South China Sea,and the northwestern Pacific.For winter,due to the weaker northwesterly wind in Northeast Asia,the northeasterly wind from the Indo-China Peninsula to Taiwan in E5OM extends northward with greater intensity than that in NCEP.These differences will have a considerable influence on the low level atmospheric circulation and water vapor transport as well as the location and intensity of the precipitation.Therefore,when E5OM results are to be used as initial and boundary conditions to drive RCMs,the differences between NCEP and E5OM should be considered.     

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.     

High-resolution simulations for Vietnam - methodology and evaluation of current climate

To assist the government of Vietnam in its efforts to better understand the impacts of climate change and prioritise its adaptation measures, dynamically downscaled climate change projections were produced across Vietnam. Two Regional Climate Models (RCMs) were used: CSIRO’s variable-resolution Conformal-Cubic Atmospheric Model (CCAM) and the limited-area model Regional Climate Model system version 4.2 (RegCM4.2). First, global CCAM simulations were completed using bias- and variance-corrected sea surface temperatures as well as sea ice concentrations from six Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models. This approach is different from other downscaling approaches as it does not use any atmospheric fields from the GCMs. The global CCAM simulations were then further downscaled to 10 km using CCAM and to 20 km using RegCM4.2. Evaluations of temperature and precipitation for the current climate (1980-2000) were completed using station data as well as various gridded observational datasets. The RCMs were able to reproduce reasonably well most of the important characteristics of observed spatial patterns and annual cycles of temperature. Average and minimum temperatures were well simulated (biases generally less than 1oC), while maximum temperatures had biases of around 1oC. For precipitation, although the RCMs captured the annual cycle, RegCM4.2 was too dry in Oct.-Nov. (-60% bias), while CCAM was too wet in Dec.- Mar. (130% bias). Both models were too dry in summer and too wet in winter (especially in northern Vietnam). The ability of the ensemble simulations to capture current climate increases confidence in the simulations of future climate.     

Simulations of the Indian summer monsoon using a nested regional climate model: domain size experiments

Seasonal simulations of the Indian summer monsoon using a 50-km regional climate model (RCM) are described. Results from three versions of the RCM distinguished by different domain sizes are compared against those of the driving global general circulation model (AGCM). Precipitation over land is 20% larger in the RCMs due to stronger vertical motions arising from finer horizontal resolution. The resulting increase in condensational heating helps to intensify the monsoon trough relative to the AGCM. The RCM precipitation distributions show a strong orographically forced mesoscale component (similar in each version). This component is not present in the AGCM. The RCMs produce two qualitatively realistic intraseasonal oscillations (ISOs) associated respectively with monsoon depressions which propagate northwestward from the Bay of Bengal and repeated northward migrations of the regional tropical convergence zone. The RCM simulations are relatively insensitive to domain size in several respects: (1) the mean bias relative to the AGCM is similar for all three domains; (2) the variability simulated by the RCM is strongly correlated with that of the driving AGCM on both daily and seasonal time scales, even for the largest domain; (3) the mesoscale features and ISOs are not damped by the relative proximity of the lateral boundaries in the version with the smallest domain. Results (1) and (2) contrast strongly with a previous study for Europe carried out with the same model, probably due to inherent differences between mid-latitude and tropical dynamics.