Interannual variability associated with ENSO: present and future climate projections of RegCM4 for South America-CORDEX domain

Interannual variability over South America (SA) is mainly controlled by the El Niño-Southern Oscillation (ENSO) phenomenon. This study investigates the ENSO precipitation signal during austral spring (September–October–November-SON) over SA. Three global circulation models-GCMs-(MPI, GFDL and HadGEM2) are used for RegCM4 (Regional Climate Model version 4) downscaling of the present (1975–2005) near-future (2020–2050) and far-future (2070–2098) climates using two greenhouse gas stabilization scenarios (RCP4.5 and RCP8.5). For the present climate, only HadGEM2 simulates a frequency of El Niño (EN) and La Niña (LN) years similar to the observations. In terms of ENSO frequency changes, only in the far-future RCP8.5 climate there is greater agreement among GCMs, indicating an increase (decrease) of EN (LN) years. In the present climate, validation indicates that only the RegCM4 ensemble mean provides acceptable precipitation biases (smaller than ±20 %) in the two investigated regions. In this period, the GCMs and RegCM4 agree on the relationship between ENSO and precipitation in SA, i.e., both are able to capture the observed regions of positive/negative rainfall anomalies during EN years, with RegCM4 improving on the GCMs’ signal over southeastern SA. For the near and far future climates, in general, the projections indicate an increase (decrease) of precipitation over southeastern SA (northern-northeastern SA). However, the relationship between ENSO and rainfall in most of RegCM4 and GCM members is weaker in the near and far future climates than in the present day climate. This is likely connected with the GCMs’ projection of the more intense ENSO signal displaced to the central basin of Pacific Ocean in the far future compared to present climate.     

Present and future climatologies in the phase I CREMA experiment

We provide an overall assessment of the surface air temperature and precipitation present day (1976–2005) and future (2070–2099) ensemble climatologies in the Phase I CREMA experiment. This consists of simulations performed with different configurations (physics schemes) of the ICTP regional model RegCM4 over five CORDEX domains (Africa, Mediterranean, Central America, South America, South Asia), driven by different combinations of three global climate models (GCMs) and two greenhouse gas (GHG) representative concentration pathways (RCP8.5 and RCP4.5). The biases (1976–2005) in the driving and nested model ensembles compared to observations show a high degree of spatial variability and, when comparing GCMs and RegCM4, similar magnitudes and more similarity for precipitation than for temperature. The large scale patterns of change (2070–2099 minus 1976–2005) are broadly consistent across the GCM and RegCM4 ensembles and with previous analyses of GCM projections, indicating that the GCMs selected in the CREMA experiment are representative of the more general behavior of current GCMs. The RegCM4, however, shows a lower climate sensitivity (reduced warming) than the driving GCMs, especially when using the CLM land surface scheme. While the broad patterns of precipitation change are consistent across the GCM and RegCM4 ensembles, greater differences are found at sub-regional scales over the various domains, evidently tied to the representation of local processes. This paper serves to provide a reference view of the behavior of the CREMA ensemble, while more detailed and process-based analysis of individual domains is left to companion papers of this special issue.     

Hydrologic Sensitivity of Global Rivers to Climate Change

Climate predictions from four state-of-the-art general circulation models (GCMs) were used to assess the hydrologic sensitivity to climate change of nine large, continental river basins (Amazon, Amur, Mackenzie, Mekong, Mississippi, Severnaya Dvina, Xi, Yellow, Yenisei). The four climate models (HCCPR-CM2, HCCPR-CM3, MPI-ECHAM4, and DOE-PCM3) all predicted transient climate response to changing greenhouse gas concentrations, and incorporated modern land surface parameterizations. Model-predicted monthly average precipitation and temperature changes were downscaled to the river basin level using model increments (transient minus control) to adjust for GCM bias. The variable infiltration capacity (VIC) macroscale hydrological model (MHM) was used to calculate the corresponding changes in hydrologic fluxes (especially streamflow and evapotranspiration) and moisture storages. Hydrologic model simulations were performed for decades centered on 2025 and 2045. In addition, a sensitivity study was performed in which temperature and precipitation were increased independently by 2 °C and 10%, respectively, during each of four seasons. All GCMs predict a warming for all nine basins, with the greatest warming predicted to occur during the winter months in the highest latitudes. Precipitation generally increases, but the monthly precipitation signal varies more between the models than does temperature. The largest changes in the hydrological cycle are predicted for the snow-dominated basins of mid to higher latitudes. This results in part from the greater amount of warming predicted for these regions, but more importantly, because of the important role of snow in the water balance. Because the snow pack integrates the effects of climate change over a period of months, the largest changes occur in early to mid spring when snow melt occurs. The climate change responses are somewhat different for the coldest snow dominated basins than for those with more transitional snow regimes. In the coldest basins, the response to warming is an increase of the spring streamflow peak, whereas for the transitional basins spring runoff decreases. Instead, the transitional basins have large increases in winter streamflows. The hydrological response of most tropical and mid-latitude basins to the warmer and somewhat wetter conditions predicted by the GCMs is a reduction in annual streamflow, although again, considerable disagreement exists among the different GCMs. In contrast, for the high-latitude basins increases in annual flow volume are predicted in most cases.     

作物生长对流域水文过程与区域气候的影响

利用区域气候模式RegCM3以及考虑作物生长过程的耦合模式RegCM3_CERES对东亚区域进行20年模拟,研究作物生长对流域水文过程与区域气候的影响。结果表明：考虑作物生长过程的耦合模式模拟海河流域、松花江流域、珠江流域多年平均降水效果明显改进,在除黑河流域外的各流域模拟的温度负偏差有所减小,其中在海河流域、淮河流域的夏季改进尤为明显。各流域夏季（6、7、8月）月蒸散量最高,其中长江流域、海河流域、淮河流域、珠江流域的夏季月蒸散量基本上在100 mm左右,并且七大流域蒸散发的季节变化趋势跟总降水基本一致。多数流域考虑作物生长过程的耦合模式模拟得出蒸散发减少且进入的水汽增加,导致局地水循环率减小;黑河流域与黄河流域降水有所增加,其他流域均有不同程度的减小。针对长江流域,比较耦合模式RegCM3_CERES与模式RegCM3模拟结果显示,叶面积指数减少1.20 m²/m²,根区土壤湿度增加0.01 m³/m³,进而导致潜热通量下降1.34 W/m²（其中在四川盆地地区减少16.00 W/m²左右）,感热通量增加2.04 W/m²,从而影响到降水和气温。     

Uncertainty assessments of climate change projections over South America

This paper assesses the uncertainties involved in the projections of seasonal temperature and precipitation changes over South America in the twenty-first century. Climate simulations generated by 24 general circulation models are weighted according to the reliability ensemble averaging (REA) approach. The results show that the REA mean temperature change is slightly smaller over South America compared to the simple ensemble mean. Higher reliability in the temperature projections is found over the La Plata basin, and a larger uncertainty range is located in the Amazon. A temperature increase exceeding 2 °C is found to have a very likely (>90 %) probability of occurrence for the entire South American continent in all seasons, and a more likely than not (>50 %) probability of exceeding 4 °C by the end of this century is found over northwest South America, the Amazon Basin, and Northeast Brazil. For precipitation, the projected changes have the same magnitude as the uncertainty range and are comparable to natural variability.     

Seasonal changes of the South American monsoon system during the Mid-Holocene in the CMIP5 simulations

The South American Monsoon System (SAMS) is a major climatic feature of South America, and its domain extends from Amazon to La Plata basin. The SAMS region is vulnerable to variations of climate and precipitation patterns, which could impact economic activities and lead to potential societal consequences. In the face of a warming future scenario, the importance of the study of the past climate with numerical simulations is to evaluate the climate models and to assure the reliability of future projections. Here we investigate the Mid-Holocene SAMS, evaluating changes in strength, life cycle and associated dynamical mechanisms in ten Earth System Models simulations. Our results show that the SAMS was weaker in the Mid-Holocene than in the pre-industrial climate in December–January–February (DJF), but stronger in September–October–November (SON). This is probably a consequence of insolation variations in the Mid-Holocene, which contributed to changes in the moisture flux from the Atlantic Ocean to the continent, the strength of the upper-level atmospheric circulation, and the amount of precipitation over the SAMS region. Moreover, we suggest that the life cycle of the SAMS was altered during the Mid-Holocene, with an earlier onset and demise. Our results also indicate that Mid-Holocene SAMS changes are connected to precipitation variations near Northeast Brazil, in a dipole configuration of precipitation between western Amazon and Northeast Brazil, due to the influence of the Walker cell. Finally, this study highlights a need for improvement of the numerical models to better simulate the amount of precipitation over South America and the upper-level circulation over western Amazon in SON, which are crucial factors for a more realistic representation of the SAMS.     

Changes in extremes and hydroclimatic regimes in the CREMA ensemble projections

We analyze changes of four extreme hydroclimatic indices in the RCP8.5 projections of the Phase I CREMA experiment, which includes 21st century projections over 5 CORDEX domains (Africa, Central America, South America, South Asia, Mediterranean) with the ICTP regional model RegCM4 driven by three CMIP5 global models. The indices are: Heat Wave Day Index (HWD), Maximum Consecutive Dry Day index (CDD), fraction of precipitation above the 95th intensity percentile (R95) and Hydroclimatic Intensity index (HY-INT). Comparison with coarse (GPCP) and high (TRMM) resolution daily precipitation data for the present day conditions shows that the precipitation intensity distributions from the GCMs are close to the GPCP data, while the RegCM4 ones are closer to TRMM, illustrating the added value of the increased resolution of the regional model. All global and regional model simulations project predominant increases in HWD, CDD, R95 and HY-INT, implying a regime shift towards more intense, less frequent rain events and increasing risk of heat wave, drought and flood with global warming. However, the magnitudes of the changes are generally larger in the global than the regional models, likely because of the relatively low “climate sensitivity” of the RegCM4, especially when using the CLM land surface scheme. In addition, pronounced regional differences in the change signals are found. The data from these simulations are available for use in impact assessment studies.     

土地利用变化对长江流域气候及水文过程影响的敏感性研究

使用区域气候模式(RegCM3)和大尺度汇流模型(LRM), 研究土地利用/植被覆盖变化对长江流域气候及水文过程的影响。RegCM3嵌套于欧洲数值预报中心 (ECMWF) 再分析资料ERA40, 分别进行了中国区域在实际植被和理想植被分布情况下两个各15年 (1987～2001年) 时间长度的积分试验。随后, RegCM3 两个试验的输出径流结果分别用来驱动LRM, 研究土地利用/植被覆盖变化对长江流域河川径流的影响。研究结果指出, 中国当代土地利用变化对长江流域降水、蒸散发、径流深及河川径流等水文气候要素的改变较大, 对气温的改变并不明显。土地利用变化引起长江干流河川径流量在夏季(6～8月)有所增加, 并且越向下游增加幅度越大, 其中大通站径流量增加接近15%。总体而言, 土地利用改变加剧了长江流域夏季水循环过程, 使得夏季长江中下游地区降水增多, 径流增大。     

Sensitivity evaluation of the different physical parameterizations schemes in regional climate model RegCM4.5 for simulation of air temperature and precipitation over North and West of Iran

In this research the dynamic downscaling method by Regional Climate Model (RegCM4.5) was used to assess the performance and sensitivity of seasonal simulated North and West of Iran (NI&WI) climate factors to different convection schemes, and transforms the large-scale simulated climate variables into land surface states over the North of Iran (NI) and West of Iran (WI). A 30-year (1986–2015) numerical integration simulation of climate over NI&WI was conducted using the regional climate model RegCM4.5 nested in one-way ERA-Interim reanalysis data. The Grell, Kuo and MIT-Emanuel cumulus convection with Holtslag and University of Washington (UW) planetary boundary layer (PBL) parameterization schemes were applied in the running of RegCM4.5 to test their capability in simulating precipitation and temperature in winter-spring (January–April) over NI and WI. The results demonstrated that the RegCM4.5 model has a good potential for simulating the variables and trend of surface temperature over the NI and WI region. Magnitude of the model bias for land surface temperature over different regions of Iran varies by convection parameterization schemes. In most cases, the root mean square error between post-processed simulated seasonal average temperature and observation value was less than 1 °C, but there is a systematic “cold bias”. In general, with respect to land surface temperature simulations, a better performance is obtained when using post-processing model’s data with Holtslag PBL-Grell and Holtslag PBL-Kuo configuration schemes, compared to the other simulations, over the NI&WI region. Also, the UW PBL convection schemes show a relatively excellent spatial correlations and normalized standard deviations closer to 1 for thirty-year seasonal land surface temperature anomalies over the entire NI&WI region. However, the simulation accuracy of model for precipitation is not as optimal as for temperature. The dominant feature in model simulations is a dry bias with the largest average value (∼1.04 mm/day) over NI region, while the lowest mean bias precipitation (∼−0.47 mm/day), mainly located in WI region. In the comparison of six configuration convection schemes, the Emanuel scheme has been proven to be the most accurate for simulating winter-spring seasonal mean precipitation over NI&WI region. The accuracy of the scheme also showed great difference in simulated station interpolation of precipitation, which urges the improvement for the simulation capability of spatial distribution of precipitation. In general, for seasonal variation of precipitation, the Emanuel convection with two (Holtslag, UW) PBL configuration schemes outperforms with a good correlation score between 0.7−0.8 and normalized standard deviations closer to 1.     

中国当代土地利用变化对黄河流域径流影响

使用区域气候模式(RegCM3)和大尺度汇流模型(LRM),研究中国地区土地利用/植被覆盖变化对黄河流域降雨径流过程的影响。RegCM3嵌套于欧洲数值预报中心(ECMWF)再分析资料ERA40,分别进行了中国区域在实际植被和理想植被分布情况下两个各15年(1987～2001年)时间长度的积分试验。随后,RegCM3 两个试验的输出径流结果分别用来驱动LRM。与观测资料的对比分析表明,在实际土地利用状况下,LRM能较好地模拟黄河河川径流的季节和年际变化。研究结果指出,当代土地利用引起了冬季黄河上游部分地区降水减少,中下游地区降水增加;引起夏季整个黄河流域降水的减少。总体来说,当代土地利用变化引起黄河流域年平均降水的减少。对于水文站河川径流量,除了冬春季略有增加外,其他月份河川径流均会减少,并且在9月减少最多。土地利用引起的植被退化造成黄河径流的大幅度减少,并且越向下游减少幅度越大,这可能是引起黄河下游断流的重要原因之一。     

Possible Impacts of Global Warming on the Hydrology of the Ogallala Aquifer Region

The Ogallala or High Plains aquifer provides water for about 20% of the irrigated land in the United States. About 20 km³ (16.6 million acre-feet) of water are withdrawn annually from this aquifer. In general, recharge has not compensated for withdrawals since major irrigation development began in this region in the 1940s. The mining of the Ogallala has been pictured as an analogue to climate change in that many GCMs predict a warmer and drier future for this region. In this paper we attempt to anticipate the possible impacts of climate change on the sustainability of the aquifer as a source of water for irrigation and other purposes in the region. We have applied HUMUS, the Hydrologic Unit Model of the U.S. to the Missouri and Arkansas-White-Red water resource regions that overlie the Ogallala. We have imposed three general circulation model (GISS, UKTR and BMRC) projections of future climate change on this region and simulated the changes that may be induced in water yields (runoff plus lateral flow) and ground water recharge. Each GCM was applied to HUMUS at three levels of global mean temperature (GMT) to represent increasing severity of climate change (a surrogate for time). HUMUS was also run at three levels of atmospheric CO₂ concentration (hereafter denoted by [CO₂]) in order to estimate the impacts of direct CO₂ effects on photosynthesis and evapotranspiration. Since the UKTR and GISS GCMs project increased precipitation in the Missouri basin, water yields increase there. The BMRC GCM predicts sharply decreased precipitation and, hence, reduced water yields. Precipitation reductions are even greater in the Arkansas basin under BMRC as are the consequent water yield losses. GISS and UKTR climates lead to only moderate yield losses in the Arkansas. CO₂-fertilization reverses these losses and yields increase slightly. CO₂ fertilization increases recharge in the base (no climate change) case in both basins. Recharge is reduced under all three GCMs and severities of climate change.     

Potential impact of climate change on the water availability of South Saskatchewan River Basin

The potential hydrologic impact of climatic change on three sub-basins of the South Saskatchewan River Basin (SSRB) within Alberta, namely, Oldman, Bow and Red Deer River basins was investigated using the Modified Interactions Soil-Biosphere-Atmosphere (MISBA) land surface scheme of Kerkhoven and Gan (Advances in Water Resources 29:808–826 2006). The European Centre for Mid-range Weather Forecasts global re-analysis (ERA-40) climate data, Digital Elevation Model of the National Water Research Institute, land cover data and a priori soil parameters from the Ecoclimap global data set were used to drive MISBA to simulate the runoff of SSRB. Four SRES scenarios (A21, A1FI, B21 and B11) of four General Circulation Models (CCSRNIES, CGCM2, ECHAM4 and HadCM3) of IPCC were used to adjust climate data of the 1961–1990 base period (climate normal) to study the effect of climate change on SSRB over three 30-year time periods (2010–2039, 2040–2069, 2070–2099). The model results of MISBA forced under various climate change projections of the four GCMs with respect to the 1961–1990 normal show that SSRB is expected to experience a decrease in future streamflow and snow water equivalent, and an earlier onset of spring runoff despite of projected increasing trends in precipitation over the 21st century. Apparently the projected increase in evaporation loss due to a warmer climate over the 21st century will offset the projected precipitation increase, leading to an overall decreasing trend in the basin runoff of SSRB. Finally, a Gamma probability distribution function was fitted to the mean annual maximum flow and mean annual mean flow data simulated for the Oldman, Bow and Red Deer River Basins by MISBA to statistically quantify the possible range of uncertainties associated with SRES climate scenarios projected by the four GCMs selected for this study.     

Incorporating groundwater dynamics and surface/subsurface runoff mechanisms in regional climate modeling over river basins in China

To improve the capability of numerical modeling of climate-groundwater interactions, a groundwater component and new surface/subsurface runoff schemes were incorporated into the regional climate model RegCM3, renamed RegCM3_Hydro. 20－year simulations from both models were used to investigate the effects of groundwater dynamics and surface/subsurface runoff parameterizations on regional climate over seven river basins in China. A comparison of results shows that RegCM3_Hydro reduced the positive biases of annual and summer (June, July, August) precipitation over six river basins, while it slightly increased the bias over the Huaihe River Basin in eastern China. RegCM3_Hydro also reduced the cold bias of surface air temperature from RegCM3 across years, especially for the Haihe and the Huaihe river basins, with significant bias reductions of 0.80C and 0.88C, respectively. The spatial distribution and seasonal variations of water table depth were also well captured. With the new surface and subsurface runoff schemes, RegCM3_Hydro increased annual surface runoff by 0.11－0.62 mm d－1 over the seven basins. Though previous studies found that incorporating a groundwater component tends to increase soil moisture due to the consideration of upward groundwater recharge, our present work shows that the modified runoff schemes cause less infiltration, which outweigh the recharge from groundwater and result in drier soil, and consequently cause less latent heat and more sensible heat over most of the basins.     

2011—2050年长江流域气候变化预估问题的探讨

利用长江流域1961—2008年观测气象资料,对IPCC 第四次评估报告中12个全球气候模式及所有模式集合平均进行比较验证,结果表明：MIUB_ECHO_G模式对该地区降水模拟能力较强,NCAR_CCSM3模式对温度模拟效果较好。进一步利用MIUB_ECHO_G模式和NCAR_CCSM3模式结果在SRES-A2、-A1B、-B1 3种排放情景下的降水和温度数据,分析2011—2050年3种排放情景下长江流域降水和温度变化特征。结果表明,2011—2050年长江流域降水变化趋势不明显,温度呈增加趋势,增幅在2℃内。     

Detection of changes in streamflow and floods resulting from climate fluctuations and land use-drainage changes

Detection of effects of changing climate on the hydrologic responses of rivers can be further complicated by changes in land use, drainage, and water use. To discern effects of human-caused changes in a basin and those due to precipitation over time, a comparison was made of annual mean flows and peakflows in Midwestern basins that experienced increases in annual precipitation and heavy rain events during 1940–1990. Two pairs of basins, one pair in a rural area and one pair in an urbanized area, were selected for in-pair comparisons, with one basin in each pair experiencing more land use and drainage changes during 1940–1990 than the other basin. All basins experienced significant upward trends in annual precipitation and annual mean flows. Human-produced changes affecting runoff in both rural basins accounted for about two-thirds of the fluctuations in the mean flows, and precipitation changes accounted for the other third. However, much of the change in peakflows in the rural basin undergoing sizable changes in drainage was due to these changes (85%) versus 75% in the rural basin without comparable shifts in drainage. The mean and peak flows of the two urban basins showed considerably more response to precipitation shifts than those of the two rural basins. The urbanized area doubled within one urban basin during 1940–1990, and these land use changes explained much more of the increase in mean flows and peakflows there than in the urban basin with less change in land use. By 1990 precipitation accounted for 69% of the upward trend in mean flows since 1941 in the heavily developed urban basin, as compared to 37% of the trend in the less settled urban basin. For purposes of assessing climate change, the precipitation changes over fifty years in all basins produced marked uptrends in basin streamflow, but the magnitude of the precipitation effect was masked by the land use and drainage changes. The results illustrate the need for careful analysis of natural basin characteristics (soils and basin shape), land use and drainage changes, and of various precipitation conditions if the influence of shifting precipitation on hydrologic conditions is to be detected, accurately measured, and correctly interpreted. For such studies the paired basin comparison techniques appears to be a valuable approach.     

Customization of regional climate model (RegCM4) over Indian region

The regional climate model (RegCM4) is customized for 10-year climate simulation over Indian region through sensitivity studies on cumulus convection and land surface parameterization schemes. The model is configured over 30° E–120° E and 15° S–45° N at 30-km horizontal resolution with 23 vertical levels. Six 10-year (1991–2000) simulations are conducted with the combinations of two land surface schemes (BATS, CLM3.5) and three cumulus convection schemes (Kuo, Grell, MIT). The simulated annual and seasonal climatology of surface temperature and precipitation are compared with CRU observations. The interannual variability of these two parameters is also analyzed. The results indicate that the model simulated climatology is sensitive to the convection as well as land surface parameterization. The analysis of surface temperature (precipitation) climatology indicates that the model with CLM produces warmer (dryer) climatology, particularly over India. The warmer (dryer) climatology is due to the higher sensible heat flux (lower evapotranspiration) in CLM. The model with MIT convection scheme simulated wetter and warmer climatology (higher precipitation and temperature) with smaller Bowen ratio over southern India compared to that with the Grell and Kuo schemes. This indicates that a land surface scheme produces warmer but drier climatology with sensible heating contributing to warming where as a convection scheme warmer but wetter climatology with latent heat contributing to warming. The climatology of surface temperature over India is better simulated by the model with BATS land surface model in combination with MIT convection scheme while the precipitation climatology is better simulated with BATS land surface model in combination with Grell convection scheme. Overall, the modeling system with the combination of Grell convection and BATS land surface scheme provides better climate simulation over the Indian region.     

百分位统计降尺度方法及在GCMs日降水订正中的应用

在格点观测的逐日降水量数据基础上,采用百分位统计降尺度方法对全球气候模式(GCM)输出的日降水量进行了订正处理。5种订正方案的比较结果表明,取12个百分位数进行日降水量订正是合理的。观测资料与3个GCMs订正前后全国平均年、季降水量空间分布以及主要流域平均年、月和日降水序列多年平均、变化趋势及概率密度的对比分析表明:(1)统计降尺度处理可在一定程度上降低GCMs模拟的降水量偏差,特别是中国中部、长江以南和东北部分地区,对德国马普研究所的海气耦合模式(MPI/ECHAM5)模拟的降水量订正效果最显著;(2)GCMs统计降尺度处理的降水量季节分布特征与观测更为接近,所有流域MPI/ECHAM5订正的降水量优于或接近直接输出结果;(3)与GCM直接输出的降水相比,部分流域经统计降尺度处理后降水量变化趋势与观测的一致性有所增加,但不明显;(4)当日降水量<30mm时,订正的降水量与观测的偏差明显减小;当日降水量>30mm时,部分流域由负偏差转为正偏差。由于GCMs结构和降尺度方法的局限性,在用于具体流域未来气候变化预估及气候变化影响评估时,应选择尽可能多的、模拟能力强的GCMs数据,以包含尽可能多的模拟气候情景。     

温室效应引起的中国区域气候变化的数值模拟Ⅰ:模式对中国气候模拟能力的检验

使用RegCM2区域气候模式单向嵌套澳大利亚CSIRO R21L9全球海-气耦合模式,进行了CO2加倍对中国区域气候变化影响的数值试验研究,分析了控制试验(1×CO2)即模式对中国当代气候的模拟情况.首先给出了全球模式控制试验在中国地区的结果,分析表明它对中国区域的地面气温和降水具有一定的模拟能力,其结果可以用来制作驱动区域气候模式的初始场和侧边界.对RegCM2 5 a时间长度控制试验积分结果的分析与检验表明,区域气候模式由于具有较高的分辨率和较完善的物理过程,它对中国区域地面气温和降水的模拟效果较全球模式有了较大提高,如它模拟的各月气温与实况的相关系数全年12个月的平均由全球模式的0.83提高到0.92,降水由0.48提高到0.65.     

CSIRO Mk3.6.0模式及其驱动下RegCM4.4模式对中国气候变化的预估

使用区域气候模式RegCM4.4,对全球模式CSIRO-Mk3.6.0在RCP4.5情景下的气候变化试验结果（1950-2100年）在东亚地区进行25 km动力降尺度试验,比较了CSIRO-Mk3.6.0和RegCM4.4预估中国地区的21世纪气候变化。结果表明,两个模式预估未来中国地区气温持续升高,升温幅度具有区域性特征,RegCM4.4预估区域平均升温幅度低于CSIRO-Mk3.6.0,但二者年际波动基本一致。两个模式预估未来降水在中国西部以持续增加为主,东部则表现出较大的不一致性,预估区域平均年降水量变化不大,呈现冬季明显增加,夏季微弱减少的特点。此外,为了解区域气候模式对中国降水预估的不确定性,对本研究和以往RegCM3使用相同分辨率模拟得到的未来降水预估进行了对比,两个区域模式预估中国西部大部分地区未来降水一致性增加,东部存在明显不一致（冬季中、高纬除外）。     

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.