A regional climate model downscaling projection of China future climate change

Climate changes over China from the present (1990–1999) to future (2046–2055) under the A1FI (fossil fuel intensive) and A1B (balanced) emission scenarios are projected using the Regional Climate Model version 3 (RegCM3) nests with the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM). For the present climate, RegCM3 downscaling corrects several major deficiencies in the driving CCSM, especially the wet and cold biases over the Sichuan Basin. As compared with CCSM, RegCM3 produces systematic higher spatial pattern correlation coefficients with observations for precipitation and surface air temperature except during winter. The projected future precipitation changes differ largely between CCSM and RegCM3, with strong regional and seasonal dependence. The RegCM3 downscaling produces larger regional precipitation trends (both decreases and increases) than the driving CCSM. Contrast to substantial trend differences projected by CCSM, RegCM3 produces similar precipitation spatial patterns under different scenarios except autumn. Surface air temperature is projected to consistently increase by both CCSM and RegCM3, with greater warming under A1FI than A1B. The result demonstrates that different scenarios can induce large uncertainties even with the same RCM-GCM nesting system. Largest temperature increases are projected in the Tibetan Plateau during winter and high-latitude areas in the northern China during summer under both scenarios. This indicates that high elevation and northern regions are more vulnerable to climate change. Notable discrepancies for precipitation and surface air temperature simulated by RegCM3 with the driving conditions of CCSM versus the model for interdisciplinary research on climate under the same A1B scenario further complicated the uncertainty issue. The geographic distributions for precipitation difference among various simulations are very similar between the present and future climate with very high spatial pattern correlation coefficients. The result suggests that the model present climate biases are systematically propagate into the future climate projections. The impacts of the model present biases on projected future trends are, however, highly nonlinear and regional specific, and thus cannot be simply removed by a linear method. A model with more realistic present climate simulations is anticipated to yield future climate projections with higher credibility.     

Present-day and future precipitation in the Baltic Sea region as simulated in a suite of regional climate models

Here we investigate simulated changes in the precipitation climate over the Baltic Sea and surrounding land areas for the period 2071–2100 as compared to 1961–1990. We analyze precipitation in 10 regional climate models taking part in the European PRUDENCE project. Forced by the same global driving climate model, the mean of the regional climate model simulations captures the observed climatological precipitation over the Baltic Sea runoff land area to within 15% in each month, while single regional models have errors up to 25%. In the future climate, the precipitation is projected to increase in the Baltic Sea area, especially during winter. During summer increased precipitation in the north is contrasted with a decrease in the south of this region. Over the Baltic Sea itself the future change in the seasonal cycle of precipitation is markedly different in the regional climate model simulations. We show that the sea surface temperatures have a profound impact on the simulated hydrological cycle over the Baltic Sea. The driving global climate model used in the common experiment projects a very strong regional increase in summertime sea surface temperature, leading to a significant increase in precipitation. In addition to the common experiment some regional models have been forced by either a different set of Baltic Sea surface temperatures, lateral boundary conditions from another global climate model, a different emission scenario, or different initial conditions. We make use of the large number of experiments in the PRUDENCE project, providing an ensemble consisting of more than 25 realizations of climate change, to illustrate sources of uncertainties in climate change projections.     

Consistency of observed winter precipitation trends in northern Europe with regional climate change projections

Often it is claimed that the recent changes in northern European climate are at least partly anthropogenic even though a human influence has not yet been successfully detected. Hence we investigate whether the recent changes are consistent with regional climate change projections. Therefore, trends in winter (DJF) mean precipitation in northern Europe are compared to human induced changes as predicted by a set of four regional climate model simulations. The patterns of recent trends and predicted changes match reasonably well as indicated by pattern correlation and the similarity is very likely not random. However, the model projections generally underestimate the recent change in winter precipitation. That is, the signal-to-noise ratio of the anthropogenic precipitation change is either rather low or the presently used simulations are significantly flawed in their ability to project changes into the future. European trends contain large signals related to the North Atlantic Oscillation (NAO), of which a major unknown part may be unrelated to the anthropogenic signal. Therefore, we also examine the consistency of recent and projected changes after subtracting the NAO signal in both the observations and in the projections. It turns out that even after the removal of the NAO signal, the pattern of trends in the observations is similar to those projected by the models. At the same time, the magnitude of the trends is considerably reduced and closer to the magnitude of the change in the projections.     

Projected Changes in Surface Air Temperature and Surface Wind in the Gulf of St. Lawrence

Abstract

The impacts of climate change on surface air temperature (SAT) and winds in the Gulf of St. Lawrence (GSL) are investigated by performing simulations from 1970 to 2099 with the Canadian Regional Climate Model (CRCM), driven by a five-member ensemble. Three members are from Canadian Global Climate Model (CGCM3) simulations following scenario A1B from the Intergovernmental Panel on Climate Change (IPCC); one member is from the Community Climate System Model, version 3 (CCSM3) simulation, also following the A1B scenario; and one member is from the CCSM4 (version 4) simulation following the Representative Concentration Pathway (RCP8.5) scenario. Compared with North America Regional Reanalysis (NARR) data, it is shown that CRCM can reproduce the observed SAT spatial patterns; for example, both CRCM simulations and NARR data show a warm SAT tongue along the eastern Gulf; CRCM simulations also capture the dominant northwesterly winds in January and the southwesterly winds in July. In terms of future climate scenarios, the spatial patterns of SAT show plausible seasonal variations. In January, the warming is 3°–3.5°C in the northern Gulf and 2.5°–3°C near Cabot Strait during 2040–2069, whereas the warming is more uniform during 2070–2099, with SAT increases of 4°–5°C. In summer, the warming gradually decreases from the western side of the GSL to the eastern side because of the different heat capacities between land and water. Moreover, the January winds increase by 0.2–0.4?m?s^?1 during 2040–2069, related to weakening stability in the atmospheric planetary boundary layer. However, during 2070–2099, the winds decrease by 0.2–0.4?m?s^?1 over the western Gulf, reflecting the northeastward shift in northwest Atlantic storm tracks. In July, enhanced baroclinicity along the east coast of North America dominates the wind changes, with increases of 0.2–0.4?m?s^?1. On average, the variance for the SAT changes is about 10% of the SAT increase, and the variance for projected wind changes is the same magnitude as the projected changes, suggesting uncertainty in the latter.     

Past and future changes in climate and hydrological indicators in the US Northeast

To assess the influence of global climate change at the regional scale, we examine past and future changes in key climate, hydrological, and biophysical indicators across the US Northeast (NE). We first consider the extent to which simulations of twentieth century climate from nine atmosphere-ocean general circulation models (AOGCMs) are able to reproduce observed changes in these indicators. We then evaluate projected future trends in primary climate characteristics and indicators of change, including seasonal temperatures, rainfall and drought, snow cover, soil moisture, streamflow, and changes in biometeorological indicators that depend on threshold or accumulated temperatures such as growing season, frost days, and Spring Indices (SI). Changes in indicators for which temperature-related signals have already been observed (seasonal warming patterns, advances in high-spring streamflow, decreases in snow depth, extended growing seasons, earlier bloom dates) are generally reproduced by past model simulations and are projected to continue in the future. Other indicators for which trends have not yet been observed also show projected future changes consistent with a warmer climate (shrinking snow cover, more frequent droughts, and extended low-flow periods in summer). The magnitude of temperature-driven trends in the future are generally projected to be higher under the Special Report on Emission Scenarios (SRES) mid-high (A2) and higher (A1FI) emissions scenarios than under the lower (B1) scenario. These results provide confidence regarding the direction of many regional climate trends, and highlight the fundamental role of future emissions in determining the potential magnitude of changes we can expect over the coming century.

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IPCC第六次评估报告中的《图集》

决策者和公众正在越来越多地关注气候变化带来的影响,而这需要更加丰富的、区域尺度上的当前和未来气候状况的精细信息.《图集》与IPCC第六次评估报告(AR6)第一工作组(WGI)报告中其他章节相协调,评估区域气候变化的观测、归因、预估的基本信息,并建立了在线交互图集系统.《图集》包含图集章节和交互图集两部分:图集章节基于新...     

Multi-year variability or unidirectional trends? Mapping long-term precipitation and temperature changes in continental Southeast Asia using PRECIS regional climate model

The subject of change detection in climate time series has recently received greater interest as the perception of a human-induced change in the climate is now widely accepted. However, changes in regional precipitation and temperature remain uncertain. This study characterizes projected fine-scale changes in precipitation and temperature in continental Southeast Asia over the period 1960?C2049. Twenty four annual variables were derived from grid-based daily precipitation and temperature produced by the PRECIS regional climate model under A2 and B2 scenarios. These time series, capturing precipitation intensities (classified as low, medium and high), seasonality and extremes in precipitation and temperature, were subjected to the modified Mann-Kendall trend detection test accounting for long-term persistence. The results indicate that temperature increases over the whole region with steeper trends in higher latitudes. Increases in annual precipitation, mainly restricted to Myanmar and the Gulf of Thailand, result from increases in high precipitation during the wet season. Decreases are observed mainly over the sea and caused by a reduction of low precipitation. Changes in the occurrence of the monsoon affect the low-latitude sea areas only. By showing that significant precipitation change are minor over land areas, these results challenge most of the previous studies that suggested significant precipitation changes over Southeast Asia, often mixing up multi-decadal variability and long-term unidirectional trends. Significant changes in precipitation and temperature may induce higher agricultural yields as steepest temperature and precipitation increases will predominantly affect the coldest and driest land areas of the region.     

Impact of doubled CO2 on the interaction between the global and regional water cycles in four study regions

Results from a suite of 30-year simulations (after spin-up) of the fully coupled Community Climate System Model version 2.0.1 are analyzed to examine the impact of doubling CO₂ on interactions between the global water cycle and the regional water cycles of four similar-size, but hydrologically and thermally different study regions (the Yukon, Ob, St Lawrence, and Colorado river basins and their adjacent land). A heuristic evaluation based on published climatological data shows that the model generally produces acceptable results for the control 1× CO₂ concentration, except for mountainous regions where it performs like other modern climate models. After doubling CO₂, the Northern Hemisphere receives significantly (95% confidence level) more moisture from the Southern Hemisphere during the boreal summer than under 1× CO₂ conditions, and the phase of the annual cycle of net moisture transport to areas north of 60°N shifts to a month later than in the reference simulation. Precipitation and evapotranspiration in the doubled CO₂ simulation increase for the Yukon, Ob, and St Lawrence, but decrease, on average, for the Colorado region compared to the reference simulation. For all regions, interaction between global and regional water cycles increases under doubled CO₂, because the amount of moisture entering and leaving the regions increases in the warmer climate. The degree of change in this interaction depends on region and season, and is related to slight shifts in the position/strength of semi-permanent highs and lows for the Yukon, Ob, and St Lawrence; in the Colorado region, higher temperatures associated with doubling CO₂ and the anticyclone located over the region increase the persistence of dry conditions.     

Regional climate change patterns identified by cluster analysis

Climate change caused by anthropogenic greenhouse emissions leads to impacts on a global and a regional scale. A quantitative picture of the projected changes on a regional scale can help to decide on appropriate mitigation and adaptation measures. In the past, regional climate change results have often been presented on rectangular areas. But climate is not bound to a rectangular shape and each climate variable shows a distinct pattern of change. Therefore, the regions over which the simulated climate change results are aggregated should be based on the variable(s) of interest, on current mean climate as well as on the projected future changes. A cluster analysis algorithm is used here to define regions encompassing a similar mean climate and similar projected changes. The number and the size of the regions depend on the variable(s) of interest, the local climate pattern and on the uncertainty introduced by model disagreement. The new regions defined by the cluster analysis algorithm include information about regional climatic features which can be of a rather small scale. Comparing the regions used so far for large scale regional climate change studies and the new regions it can be shown that the spacial uncertainty of the projected changes of different climate variables is reduced significantly, i.e. both the mean climate and the expected changes are more consistent within one region and therefore more representative for local impacts.     

Sub-Saharan Northern African climate at the end of the twenty-first century: forcing factors and climate change processes

A regional climate model, the Weather Research and Forecasting (WRF) Model, is forced with increased atmospheric CO₂ and anomalous SSTs and lateral boundary conditions derived from nine coupled atmosphere–ocean general circulation models to produce an ensemble set of nine future climate simulations for northern Africa at the end of the twenty-first century. A well validated control simulation, agreement among ensemble members, and a physical understanding of the future climate change enhance confidence in the predictions. The regional model ensembles produce consistent precipitation projections over much of northern tropical Africa. A moisture budget analysis is used to identify the circulation changes that support future precipitation anomalies. The projected midsummer drought over the Guinean Coast region is related partly to weakened monsoon flow. Since the rainfall maximum demonstrates a southward bias in the control simulation in July–August, this may be indicative of future summer drying over the Sahel. Wetter conditions in late summer over the Sahel are associated with enhanced moisture transport by the West African westerly jet, a strengthening of the jet itself, and moisture transport from the Mediterranean. Severe drought in East Africa during August and September is accompanied by a weakened Indian monsoon and Somali jet. Simulations with projected and idealized SST forcing suggest that overall SST warming in part supports this regional model ensemble agreement, although changes in SST gradients are important over West Africa in spring and fall. Simulations which isolate the role of individual climate forcings suggest that the spatial distribution of the rainfall predictions is controlled by the anomalous SST and lateral boundary conditions, while CO₂ forcing within the regional model domain plays an important secondary role and generally produces wetter conditions.     

Uncertainties in projected impacts of climate change on European agriculture and terrestrial ecosystems based on scenarios from regional climate models

The uncertainties and sources of variation in projected impacts of climate change on agriculture and terrestrial ecosystems depend not only on the emission scenarios and climate models used for projecting future climates, but also on the impact models used, and the local soil and climatic conditions of the managed or unmanaged ecosystems under study. We addressed these uncertainties by applying different impact models at site, regional and continental scales, and by separating the variation in simulated relative changes in ecosystem performance into the different sources of uncertainty and variation using analyses of variance. The crop and ecosystem models used output from a range of global and regional climate models (GCMs and RCMs) projecting climate change over Europe between 1961–1990 and 2071–2100 under the IPCC SRES scenarios. The projected impacts on productivity of crops and ecosystems included the direct effects of increased CO₂ concentration on photosynthesis. The variation in simulated results attributed to differences between the climate models were, in all cases, smaller than the variation attributed to either emission scenarios or local conditions. The methods used for applying the climate model outputs played a larger role than the choice of the GCM or RCM. The thermal suitability for grain maize cultivation in Europe was estimated to expand by 30–50% across all SRES emissions scenarios. Strong increases in net primary productivity (NPP) (35–54%) were projected in northern European ecosystems as a result of a longer growing season and higher CO₂ concentrations. Changing water balance dominated the projected responses of southern European ecosystems, with NPP declining or increasing only slightly relative to present-day conditions. Both site and continental scale models showed large increases in yield of rain-fed winter wheat for northern Europe, with smaller increases or even decreases in southern Europe. Site-based, regional and continental scale models showed large spatial variations in the response of nitrate leaching from winter wheat cultivation to projected climate change due to strong interactions with soils and climate. The variation in simulated impacts was smaller between scenarios based on RCMs nested within the same GCM than between scenarios based on different GCMs or between emission scenarios.     

Winter weather regimes over the Mediterranean region: their role for the regional climate and projected changes in the twenty-first century

The winter time weather variability over the Mediterranean is studied in relation to the prevailing weather regimes (WRs) over the region. Using daily geopotential heights at 700 hPa from the ECMWF ERA40 Reanalysis Project and Cluster Analysis, four WRs are identified, in increasing order of frequency of occurrence, as cyclonic (22.0 %), zonal (24.8 %), meridional (25.2 %) and anticyclonic (28.0 %). The surface climate, cloud distribution and radiation patterns associated with these winter WRs are deduced from satellite (ISCCP) and other observational (E-OBS, ERA40) datasets. The LMDz atmosphere–ocean regional climate model is able to simulate successfully the same four Mediterranean weather regimes and reproduce the associated surface and atmospheric conditions for the present climate (1961–1990). Both observational- and LMDz-based computations show that the four Mediterranean weather regimes control the region’s weather and climate conditions during winter, exhibiting significant differences between them as for temperature, precipitation, cloudiness and radiation distributions within the region. Projections (2021–2050) of the winter Mediterranean weather and climate are obtained using the LMDz model and analysed in relation to the simulated changes in the four WRs. According to the SRES A1B emission scenario, a significant warming (between 2 and 4 °C) is projected to occur in the region, along with a precipitation decrease by 10–20 % in southern Europe, Mediterranean Sea and North Africa, against a 10 % precipitation increase in northern European areas. The projected changes in temperature and precipitation in the Mediterranean are explained by the model-predicted changes in the frequency of occurrence as well as in the intra-seasonal variability of the regional weather regimes. The anticyclonic configuration is projected to become more recurrent, contributing to the decreased precipitation over most of the basin, while the cyclonic and zonal ones become more sporadic, resulting in more days with below normal precipitation over most of the basin, and on the eastern part of the region, respectively. The changes in frequency and intra-seasonal variability highlights the usefulness of dynamics versus statistical downscaling techniques for climate change studies.     

Projection of Water Availability in the Miyun Watershed from an RCM Simulation

Based on a high-resolution regional climate model (RegCM3) simulation over East Asia, future climate changes over the Miyun Reservoir in the 21st century under the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B scenario are analyzed. The model simulation extends from 1951 to 2100 at a grid spacing of 25 km and is one-way nested within a global model of MIROC3.2_ hires (the Model for Interdisciplinary Research on Climate). The focus of the analysis is on the Watershed of Miyun Reservoir, the main water supply for Beijing in northern China. The results show that RegCM3 reproduces the observed temperature well but it overestimates precipitation over the region. Significant warming in the 21st century is simulated in the annual mean, December-January-February (DJF) and June-July-August (JJA), although with differences concerning the spatial distribution and magnitude. Changes in precipitation for the annual mean, DJF, and JJA also show differences. A prevailing increase of precipitation in DJF and a decrease of it in JJA is projected over the region, while little change in the annual mean is projected. Changes of the difference between precipitation and evapotranspiration to measure the potential water availability are also presented in the paper.     

Competition of NAO regime changes and increasing greenhouse gases and aerosols with respect to Arctic climate projections

Regional magnitudes and patterns of Arctic winter climate changes in consequence of regime changes of the North Atlantic Oscillation (NAO) are analyzed using a regional atmospheric climate model. The regional model has been driven with data of positive and negative NAO phases from a control simulation as well as from a time-dependent greenhouse gas and aerosol scenario simulation. Both global model simulations include a quite realistic interannual variability of the NAO with pronounced decadal regime changes and no or rather weak long-term NAO trends. The results indicate that the effects of NAO regime changes on Arctic winter temperatures and precipitation are regionally significant over most of northwestern Eurasia and parts of Greenland. In this regard, mean winter temperature variations of up to 6 K may occur over northern Europe. Precipitation and synoptic variability are also regionally modified by NAO regime changes, but not as significantly as temperatures. However, the climate changes associated with the NAO are in some regions clearly stronger than those attributed to enhanced greenhouse gases and aerosols, indicating that projected global changes of the atmospheric composition and internal circulation changes are competing with each other in their importance for the Arctic climate evolution in the near future. The knowledge of the future NAO trend on decadal and longer time scales appears to be vitally important in terms of a regional assessment of climate scenarios for the Arctic.     

Climate Change on Newfoundland and Labrador Shelves: Results From a Regional Downscaled Ocean and Sea-Ice Model Under an A1B Forcing Scenario 2011–2069

Climate change may affect ocean and ice conditions in coastal oceans and thus have significant impacts on coastal infrastructure, marine navigation, and marine ecosystems. In this study a three-dimensional ice–ocean model is developed to examine likely changes of ocean and ice conditions over the Newfoundland and Labrador Shelves in response to climate change. The model is configured with a horizontal grid of approximately 7?km and a vertical grid of 46 levels and is run from 1979 to 2069. The projection period is 2011 to 2069 under a median emission scenario A1B used by the Intergovernmental Panel on Climate Change. For the projection period, the surface atmospheric forcing fields used are from the Canadian Regional Climate Model over the North Atlantic. The open boundary conditions come from the Canadian Global Climate Model, Version 3 (CGCM3), adjusted for the 1981–2010 mean of the Simple Ocean Data Assimilation model output. The simulated fields over the 1981–2010 period have patterns consistent with observations. Over the Newfoundland and Labrador Shelves during the projection period, the model shows general trends of warming, freshening, and decreasing ice. From 2011 to 2069, the model projects that under A1B sea surface temperature will increase by 1.4°C; bottom temperature will increase by 1.6°C; sea surface salinity will decrease by 0.7; bottom salinity will decrease by 0.3; and sea-ice extent will decrease by 70%. The sea level will rise by 0.11?m at the St. John's tide-gauge station because of oceanographic change, and the freshwater transport of the Labrador Current will double as a result of freshening. The regional ice–ocean model reproduces more realistic present climate conditions and projects considerably different future climate conditions than CGCM3.     

Impacts of bias correction of lateral boundary conditions on regional climate projections in West Africa

Biases existing in the lateral boundary conditions (LBCs) influence climate simulations in regional climate models (RCMs). Correcting the biases in global climate model (GCM)-produced LBCs before running RCMs was proposed in previous studies as a possible way to reduce the GCM-related model dependence of future climate projections using RCMs. In this study the ICTP Regional Climate Model Version 4 (RegCM4) is used to investigate the impact of LBC bias correction on projected future changes of regional climate in West Africa. To accomplish this, two types of present versus future simulations are conducted using RegCM4: a control type where both the present and future LBCs are derived directly from the GCM output (as is done in most regional climate downscaling studies); an experiment type where the present-day LBCs are from reanalysis data and future LBCs are derived by combining the reanalysis data and the GCM-projected LBC changes. For each type of simulations, three different sets of LBCs are experimented on: 6-hourly synoptic forcing directly from the reanalysis or GCM, 6-hourly data interpolated from monthly climatology (without diurnal cycle), and 6-hourly data interpolated from the month-specific climatology of diurnal cycles. It is found that the simulations using different LBCs produce similar present-day summer rainfall patterns, but the predicted future changes differ significantly depending on how the LBC bias correction is treated. Specifically, both the bias correction applied at the synoptic scale and the bias correction applied to the monthly interpolated LBCs without diurnal cycle produce a spurious drying signal caused by physical inconsistency in the corrected future LBCs. Interpolated monthly LBCs with diurnal cycle alleviate the problem to a large extent. These results suggest that using bias-corrected LBCs to drive regional climate models may not guarantee reliable future projections although reasonable present climate can be simulated. Physical inconsistencies may be contained in the bias-corrected LBCs, increasing the uncertainties of RCM-produced future projections.     

Atmosphere-land surface interactions and their influence on extreme rainfall and potential abrupt climate change over southern Africa

In a changing climate, changes in rainfall variability and, in particular, extreme rainfall events are likely to be highly significant for environmentally vulnerable regions such as southern Africa. It is generally accepted that sea-surface temperatures play an important role in modulating rainfall variability, thus the majority work to date has focused on these mechanisms. However past research suggests that land surface processes are also critical for rainfall variability. In particular, work has suggested that the atmosphere-land surface feedback has been important for past abrupt climate changes, such as those which occurred over the Sahara during the mid-Holocene or, more recently, the prolonged Sahelian drought. Therefore the primary aim of this work is to undertake idealised experiments using both a regional and global climate model, to test the sensitivity of rainfall variability to land surface changes over a location where such abrupt climate changes are projected to occur in the future, namely southern Africa. In one experiment, the desert conditions currently observed over southwestern Africa were extended to cover the entire subcontinent. This is based on past research which suggests a remobilisation of sand dune activity and spatial extent under various scenarios of future anthropogenic global warming. In the second experiment, savanna conditions were imposed over all of southern Africa, representing an increase in vegetation for most areas except the equatorial regions. The results suggest that a decrease in rainfall occurs in the desert run, up to 27% of total rainfall in the regional model (relative to the control), due to a reduction in available moisture, less evaporation, less vertical uplift and therefore higher near surface pressure. This result is consistent across both the regional and global model experiments. Conversely an increase in rainfall occurs in the savanna run, because of an increase in available moisture giving an increase in latent heat and therefore surface temperature, increasing vertical uplift and lowering near surface pressure. These experiments, however, are only preliminary, and form the first stage of a wider study into how the atmosphere-land surface feedback influences rainfall extremes over southern Africa in the past (when surface i.e. vegetation conditions were very different) and in the future under various scenarios of future climate change. Future work will examine how other climate models simulate the atmosphere-land surface feedback, using more realistic vegetation types based on past and future surface conditions.     

A multi-physics ensemble of regional climate change projections over the Iberian Peninsula

This study illustrates the sensitivity of regional climate change projections to the model physics. A single-model (MM5) multi-physics ensemble of regional climate simulations over the Iberian Peninsula for present (1970–1999) and future (2070–2099 under the A2 scenario) periods is assessed. The ensemble comprises eight members resulting from the combination of two options of parameterization schemes for the planetary boundary layer, cumulus and microphysics. All the considered combinations were previously evaluated by comparing hindcasted simulations to observations, none of them providing clearly outlying climates. Thus, the differences among the various ensemble members (spread) in the future projections could be considered as a matter of uncertainty in the change signals (as similarly assumed in multi-model studies). The results highlight the great dependence of the spread on the synoptic conditions driving the regional model. In particular, the spread generally amplifies under the future scenario leading to a large spread accompanying the mean change signals, as large as the magnitude of the mean projected changes and analogous to the spread obtained in multi-model ensembles. Moreover, the sign of the projected change varies depending on the choice of the model physics in many cases. This, together with the fact that the key mechanisms identified for the simulation of the climatology of a given period (either present or future) and those introducing the largest spread in the projected changes differ significantly, make further claims for efforts to better understand and model the parameterized subgrid processes.     

Creating regional climate change scenarios over southern South America for the 2020’s and 2050’s using the pattern scaling technique: validity and limitations

Dynamical downscaling of global climate simulations is the most adequate tool to generate regional projections of climate change. This technique involves at least a present climate simulation and a simulation of a future scenario, usually at the end of the twenty first century. However, regional projections for a variety of scenarios and periods, the 2020s or the 2050s, are often required by the impact community. The pattern scaling technique is used to estimate information on climate change for periods and scenarios not simulated by the regional model. We based our study on regional simulations performed over southern South America for present climate conditions and two emission scenarios at the end of the twenty first century. We used the pattern scaling technique to estimate mean seasonal changes of temperature and precipitation for the 2020s and the 2050s. The validity of the scalability assumptions underlying the pattern scaling technique for estimating near future regional climate change scenarios over southern South America is assessed. The results show that the pattern scaling works well for estimating mean temperature changes for which the regional changes are linearly related to the global mean temperature changes. For precipitation changes, the validity of the scalability assumption is weaker. The errors of estimating precipitation changes are comparable to those inherent to the regional model and to the projected changes themselves.     

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.