Simulation of the summer circulation over South America by two regional climate models. Part I: Mean climatology

Summary This study investigates the capabilities of two regional models (the ICTP RegCM3 and the climate version of the CPTEC Eta model – EtaClim) in simulating the mean climatological features of the summer quasi-stationary circulations over South America. Comparing the results with the NCEP/DOE reanalysis II data it is seen that the RegCM3 simulates a weaker and southward shifted Bolivian high (BH). But, the Nordeste low (NL) is located close to its climatological position. In the EtaClim the position of the BH is reproduced well, but the NL is shifted towards the interior of the continent. To the east of Andes, the RegCM3 simulates a weaker low level jet and a weaker basic flow from the tropical Atlantic to Amazonia while they are stronger in the EtaClim. In general, the RegCM3 and EtaClim show, respectively a negative and positive bias in the surface temperature in almost all regions of South America. For both models, the correlation coefficients between the simulated precipitation and the GPCP data are high over most of South America. Although the RegCM3 and EtaClim overestimate the precipitation in the Andes region they show a negative bias in general over the entire South America. The simulations of upper and lower level circulations and precipitation fields in EtaClim were better than that of the RegCM3. In central Amazonia both models were unable to simulate the precipitation correctly. The results showed that although the RegCM3 and EtaClim are capable of simulating the main climatological features of the summer climate over South America, there are areas which need improvement. This indicates that the models must be more adequately tuned in order to give reliable predictions in the different regions of South America.     

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.     

QM和QDM方法对中国极端气候的高分辨率气候变化模拟的误差订正对比

采用分位数映射（Quantile Mapping, QM）和delta分位数映射（Quantile Delta Mapping, QDM）两种误差订正方法对区域气候模式RegCM4在中国区域内模拟的逐日气温和降水数据进行订正。模式数据是5种不同全球气候模式驱动下的区域模式气候变化模拟结果。计算订正前后的极端气候指数进行对比分析,包括日最高气温极大值（TXx）、日最低气温极小值（TNn）、连续干旱日数（CDD）和最大日降水量（RX1day）。结果表明,5组模拟结果和其集合平均（ensR）都显示气温指数的模拟效果高于降水指数,其中对TXx模拟最好,对CDD的模拟最差;经过订正后,针对不同模式的两种订正结果都能够有效地减小模式与观测的偏差并提高了空间相关系数,且两种方法的订正效果无明显差别。对RCP4.5情景下未来变化的分析中,QM在一定程度上改变了模式模拟的未来变化幅度和空间分布特征,QDM则能够有效地保留所有极端指数的气候变化信号。从全国平均来看,除CDD外,所有指数未来都呈现增加趋势,且QDM订正结果与订正前模式模拟的变化趋势更为接近。建议在气候变化模拟的误差订正中采用QDM方法。     

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）。     

区域气候模式对温室效应引起的中国地区气候变化的数值模拟

利用基于 ＲｅｇＣＭ２的区域气候模式并单向嵌套澳大利亚 ＣＳＩＲＯ Ｒ２１Ｌ９全球海－气耦合模式，进行了温室气体二氧化碳浓度倍增对中国气候变化影响的数值试验研究。控制试验结果表明：区域模式由于具有较高的分辨率，因而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；模式对 ２×ＣＯ２敏感性试验结果表明了在 ＣＯ２浓度倍增情况下，由于温室效应，中国区域的地面气温将有明显升高，降水也将呈增加趋势。     

Domain choice in an experimental nested modeling prediction system for South America

Summary The purposes of this paper are to evaluate the new version of the regional model, RegCM3, over South America for two test seasons, and to select a domain for use in an experimental nested prediction system, which incorporates RegCM3 and the European Community-Hamburg (ECHAM) general circulation model (GCM). To evaluate RegCM3, control experiments were completed with RegCM3 driven by both the NCEP/NCAR Reanalysis (NNRP) and ECHAM, using a small control domain (D-CTRL) and integration periods of January–March 1983 (El Ni?o) and January–March 1985 (La Ni?a). The new version of the regional model captures the primary circulation and rainfall differences between the two years over tropical and subtropical South America. Both the NNRP-driven and ECHAM-driven RegCM3 improve the simulation of the Atlantic intertropical convergence zone (ITCZ) compared to the GCM. However, there are some simulation errors. Irrespective of the driving fields, weak northeasterlies associated with reduced precipitation are observed over the Amazon. The simulation of the South Atlantic convergence zone is poor due to errors in the boundary condition forcing which appear to be amplified by the regional model. To select a domain for use in an experimental prediction system, sensitivity tests were performed for three domains, each of which includes important regional features and processes of the climate system. The domain sensitivity experiments were designed to determine how domain size and the location of the GCM boundary forcing affect the regional circulation, moisture transport, and rainfall in two years with different large scale conditions. First, the control domain was extended southward to include the exit region of the Andes low level jet (D-LLJ), then eastward to include the South Atlantic subtropical high (D-ATL), and finally westward to include the subsidence region of the South Pacific subtropical high and to permit the regional model more freedom to respond to the increased resolution of the Andes Mountains (D-PAC). In order to quantify differences between the domain experiments, measures of bias, root mean square error, and the spatial correlation pattern were calculated between the model results and the observed data for the seasonal average fields. The results show the GCM driving fields have remarkable control over the RegCM3 simulations. Although no single domain clearly outperforms the others in both seasons, the control domain, D-CTRL, compares most favorably with observations. Over the ITCZ region, the simulations were improved by including a large portion of the South Atlantic subtropical high (D-ATL). The methodology presented here provides a quantitative basis for evaluating domain choice in future studies.     

Robust intensification of hydroclimatic intensity over East Asia from multi-model ensemble regional projections

This study assesses the hydroclimatic response to global warming over East Asia from multi-model ensemble regional projections. Four different regional climate models (RCMs), namely, WRF, HadGEM3-RA, RegCM4, and GRIMs, are used for dynamical downscaling of the Hadley Centre Global Environmental Model version 2–Atmosphere and Ocean (HadGEM2-AO) global projections forced by the representative concentration pathway (RCP4.5 and RCP8.5) scenarios. Annual mean precipitation, hydroclimatic intensity index (HY-INT), and wet and dry extreme indices are analyzed to identify the robust behavior of hydroclimatic change in response to enhanced emission scenarios using high-resolution (12.5 km) and long-term (1981–2100) daily precipitation. Ensemble projections exhibit increased hydroclimatic intensity across the entire domain and under both the RCP scenarios. However, a geographical pattern with predominantly intensified HY-INT does not fully emerge in the mean precipitation change because HY-INT is tied to the changes in the precipitation characteristics rather than to those in the precipitation amount. All projections show an enhancement of high intensity precipitation and a reduction of weak intensity precipitation, which lead to a possible shift in hydroclimatic regime prone to an increase of both wet and dry extremes. In general, projections forced by the RCP8.5 scenario tend to produce a much stronger response than do those by the RCP4.5 scenario. However, the temperature increase under the RCP4.5 scenario is sufficiently large to induce significant changes in hydroclimatic intensity, despite the relatively uncertain change in mean precipitation. Likewise, the forced responses of HY-INT and the two extreme indices are more robust than that of mean precipitation, in terms of the statistical significance and model agreement.

     

RegCM4对华北区域21世纪气候变化预估研究

利用国家气候中心完成的RegCM4区域气候模式在RCP4.5和RCP8.5两种排放路径下的气候变化动力降尺度试验结果,在检验模式对基准期(1986—2005年)气温和降水模拟能力基础上,进行华北区域21世纪气候变化预估分析。结果表明:RegCM4对华北区域基准期气温和降水的模拟能力较好。未来21世纪,两种情景下华北区域气温、降水、持续干期(consecutive dry days, CDD)和强降水量(R95p)变化逐渐增大,但变化幅度在高排放的RCP8.5情景下更为显著,其中近期(2021—2035年)、中期(2046—2065年)、远期(2080—2098年)RCP8.5情景下年平均气温分别升高1.77、3.44、5.82℃,年平均降水分别增加8.1%、14%、19.3%,CDD分别减少3、3、12 d, R95p分别增加30.8%、41.9%、69.8%。空间上,未来21世纪华北区域内年、冬季、夏季平均气温将一致升高,夏季升温幅度最大;年、冬季、夏季平均降水整体以增加为主,冬季降水增加幅度最大;CDD以减少为主,但近期和中期在山西和京津冀有所增加,而R95p以增加为主,表明21世纪华北区域干旱事件逐渐减少、极端降水事件不断增加。     

FGOALS-g2模式模拟和预估的全球季风区极端降水及其变化

利用LASG/IAP（中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室）全球耦合模式FGOALS-g2,评估了其对全球季风区极端气候指标的模拟能力,并讨论了RCP8.5排放情景下21世纪季风区极端气候指标的变化特征。总体而言,模式对季风区总降水和极端气候指标1997～2014年气候态和年际变率的空间分布均具有一定的模拟能力。偏差主要表现在模式低估了亚洲季风强降水中心,低估了中雨（10～20 mm d-1）和大雨（20～50 mm d-1）的频率而高估了暴雨（>50 mm d-1）频率。在RCP8.5排放情景下,由于可降水量的增加,模式预估的全球季风区极端降水、降水总量和降水强度将持续增加。到2076～2095年,极端降水和降水强度在北美季风区增加最显著（约22%和17%）,降水总量在澳大利亚增加最显著（约37%）。然而,FGOALS-g2对全球季风区平均的日降水量低于1 mm的连续最大天数（CDD）的预估变化不显著,这是由于预估的CDD在陆地季风区将增加,而在海洋季风区将减少。对各子季风区的分析显示,CDD在南美季风区变长最显著,达到30%,在澳洲季风区变短最显著,达到40%,这与两季风区日降水量低于1 mm的降水事件发生频率变化不同有关。     

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.     

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.     

Climate change impact on precipitation for the Amazon and La Plata basins

We analyze the local and remote impacts of climate change on the hydroclimate of the Amazon and La Plata basins of South America (SA) in an ensemble of four 21st century projections (1970–2100, RCP8.5 scenario) with the regional climate model RegCM4 driven by the HadGEM, GFDL and MPI global climate models (GCMs) over the SA CORDEX domain. Two RegCM4 configurations are used, one employing the CLM land surface and the Emanuel convective schemes, and one using the BATS land surface and Grell (over land) convection schemes. First, we find considerable sensitivity of the precipitation change signal to both the driving GCM and the RegCM4 physics schemes (with the latter even greater than the first), highlighting the pronounced uncertainty of regional projections over the region. However, some improvements in the simulation of the annual cycle of precipitation over the Amazon and La Plata basins is found when using RegCM4, and some consistent change signals across the experiments are found. One is a tendency towards an extension of the dry season over central SA deriving from a late onset and an early retreat of the SA monsoon. The second is a dipolar response consisting of reduced precipitation over the broad Amazon and Central Brazil region and increased precipitation over the La Plata basin and central Argentina. An analysis of the relative influence on the change signal of local soil-moisture feedbacks and remote effects of Sea Surface Temperature (SST) over the Niño 3.4 region indicates that the former is prevalent over the Amazon basin while the latter dominates over the La Plata Basin. Also, the soil moisture feedback has a larger role in RegCM4 than in the GCMs.     

中国区域逐日融合降水数据集与国际降水产品的对比评估

中国国家气象信息中心基于2400多个国家级台站观测日降水量和CMORPH卫星反演降水产品,采用概率密度匹配和最优插值相结合的两步数据融合方法,研制了中国区域1998年以来的0.25°×0.25°分辨率的逐日融合降水产品(CMPA_Daily)。通过该数据集与广泛应用于中国天气气候领域的两种国际上降水融合产品TRMM 3B42(Tropical Rainfall Measuring Mission, 3B42)和GPCP(Global Precipitation Climatology Project, 1 degree daily)的对比评估,考察CMPA_Daily产品的质量,评价其能否合理体现中国降水的天气气候特征。首先利用2008—2010年5—9月独立检验数据定量对比了CMPA_Daily、TRMM 3B42和GPCP 三种降水产品的误差,结果表明,在误差的时间变化和空间分布上,CMPA_Daily均具有最高的相关系数和最小的平均偏差及均方根误差,TRMM 3B42其次,GPCP的误差相对较大。CMPA_Daily只低估了大暴雨,TRMM 3B42低估了大雨以上量级的降水,而GPCP低估了除小雨以外的所有降水。CMPA_Daily产品因融入了更多的站点观测信息,不论在中国东部沿海,还是中西部地形复杂区,其精度均优于TRMM 3B42和GPCP产品,即使在站点稀疏的青藏高原地区,CMPA_Daily降水量也更加接近站点观测,呈现明显的高相关。CMPA_Daily与独立检验数据的高相关在地形起伏时效果也较稳定,TRMM和GPCP的相关系数则随着地形变化幅度陡变而非常明显地降低。进一步通过对比分析各降水产品1998—2012年的气候平均降水特征表明,3种资料对中国区域气候平均降水量、降水强度、频率分布以及年际变化的总体描述基本一致,因有效融入了更多的中国站点观测信息,不论降水空间分布还是降水量,CMPA_Daily与地面观测均最为接近,在中国的中东部大部分地区对降水的估计精度明显更高,而在站点分布较稀疏的青藏高原地区,CMPA_Daily的降水分布型与TRMM、GPCP卫星融合资料类似,较地面站点插值产品更能体现出合理的降水分布。对中国强降水事件监测对比表明,CMPA_Daily产品可以更加准确地描述降水的强度变化,细致刻画降水空间分布,在把握降水小尺度特征上具有明显的优势,体现出高分辨率、高精度降水产品的特点。     

华东地区极端降水动力降尺度模拟及未来预估

利用CMIP5（Coupled Model Intercomparison Project Phase 5）数据集中的全球模式IPSL-CM5A-LR及其嵌套的区域气候模式WRF（Weather Research and Forecasting）,分别评估了模式对1981~2000中国华东区域极端降水指标的模拟能力,并讨论了RCP8.5排放情景下21世纪中期（2041~2060年）中国华东极端降水指标的变化特征。相比驱动场全球气候模式,WRF模式更好地再现了各个极端指数空间分布及各子区域降水年周期变化。在模拟区域气候特点方面,WRF模拟结果有所改进,并在弥补全球模式对小雨日过多模拟的缺陷起到了明显的作用。21世纪中期,华东区域的降水将呈现明显的极端化趋势。WRF模拟结果显示年总降雨量、年大雨日数、平均日降雨强度在华东大部分区域的增幅在20%以上;年极端降雨天数、连续5 d最大降水量的增幅在华东北部部分区域分别超过了50%和35%,同时最长续干旱日在华东区域全面增加;且变化显著的格点主要位于增加幅度较大的区域。未来华东区域会出现强降水事件和干旱事件同时增加的情况,降水呈现明显的极端化趋势,且华东北部极端化强于华东南部。     

The potential added value of Regional Climate Models in South America using a multiresolution approach

This paper aims to identify those regions within the South American continent where the Regional Climate Models (RCMs) have the potential to add value (PAV) compared to their coarser-resolution global forcing. For this, we used a spatial-scale filtering method based on the wavelet theory to distinguish the regional climatic signal present in atmospheric surface fields from observed data (CPC and TRMM) and 6 RCM simulations belonging to the CORDEX Project. The wavelet used for filtering was Haar wavelet, but a comparative analysis with Daubechies 4 wavelet indicated that meteorological fields or regional indices were not very sensitive to the wavelet selected. Once the longer wavelengths were filtered, we focused on analyzing the spatial variability of extreme rainfall and the spatiotemporal variability of maximum and minimum surface air temperature on a daily basis. The results obtained suggest essential differences in the spatial distribution of the small-scale signal of extreme precipitation between TRMM and regional models, together with a large dispersion between models. While TRMM and CPC register a large signal throughout the continent, the RCMs place it over the Andes Cordillera and some over tropical South America. PAV signal for surface air temperature was found over the Andes Cordillera and the Brazilian Highlands, which are regions characterized by complex topography, and also on the coasts of the continent. The signal came specially from the small-scale stationary component. The transient part is much smaller than the stationary one, except over la Plata Basin where they are of the same order of magnitude. Also, the RCMs and CPC showed a large spread between them in representing this transient variability. The results confirm that RCMs have the potential to add value in the representation of extreme precipitation and the mean surface temperature in South America. However, this condition is not applicable throughout the whole continent but is particularly relevant in those terrestrial regions where the surface forcing is strong, such as the Andes Cordillera or the coasts of the continent.     

Analysis of the present and future winter Pacific-North American teleconnection in the ECHAM5 global and RegCM3 regional climate models

We use the NCEP/NCAR Reanalysis (NCEP) and the MPI/ECHAM5 general circulation model to drive the RegCM3 regional climate model to assess the ability of the models to reproduce the spatiotemporal aspects of the Pacific-North American teleconnection (PNA) pattern. Composite anomalies of the NCEP-driven RegCM3 simulations for 1982–2000 indicate that the regional model is capable of accurately simulating the key features (500-hPa heights, surface temperature, and precipitation) of the positive and negative phases of the PNA with little loss of information in the downscaling process. The basic structure of the PNA is captured in both the ECHAM5 global and ECHAM5-driven RegCM3 simulations. The 1950–2000 ECHAM5 simulation displays similar temporal and spatial variability in the PNA index as that of NCEP; however, the magnitudes of the positive and negative phases are weaker than those of NCEP. The RegCM3 simulations clearly differentiate the climatology and associated anomalies of snow water equivalent and soil moisture of the positive and negative PNA phases. In the RegCM3 simulations of the future (2050–2100), changes in the location and extent of the Aleutian low and the continental high over North America alter the dominant flow patterns associated with positive and negative PNA modes. The future projections display a shift in the patterns of the relationship between the PNA and surface climate variables, which suggest the potential for changes in the PNA-related surface hydrology of North America.     

Assessment of CMIP5 global model simulations over the subset of CORDEX domains used in the Phase I CREMA

We present an assessment of the CMIP5 global model simulations over a subset of CORDEX domains used in the Phase I CREMA (CORDEX RegCM hyper-MAtrix) experiment (Africa, HYMEX-MED (Mediterranean), South America, Central America and West Asia). Three variants of the transformed Mielke measure are used to assess (1) the model skill in simulating surface temperature and precipitation historical climatology, (2) the degree of surface temperature and precipitation change occurring under greenhouse gas forcing, and (3) the consistency of a model’s projected change with that of the Multi Model Ensemble (MME) mean. The majority of models exhibit varying degrees of skill depending on the region and season; however, a few models are identified as performing well globally. We find that resolution improves the model skill in most regional and seasonal cases, especially for temperature. Models with the highest and lowest climate sensitivity, as well as those whose change most resembles the ensemble mean are also discussed. Although the higher resolution models perform better, we find that resolution does not have a statistically significant impact on the models’ response to GHG forcing, indicating that model biases do not play a primary role in affecting the model response to GHG forcing. We also assess the three selected models for the CREMA Phase I experiment (HADGEM2ES, MPI-ESMMR and GFDL-ESM2M) and find that they are characterized by a relatively good level of performance, a range of high to low climate sensitivities and a good consistency with the MME changes, thereby providing a reasonably representative sample of the CMIP5 ensemble.     

CLIMATE CHANGE DUE TO GREENHOUSE EFFECTS IN CHINA AS SIMULATED BY A REGIONAL CLIMATE MODEL-PART I:EVALUATION OF THE MODEL SIMULATIONS*

Impacts of greenhouse effects(2×CO₂) on climate change over China as simulated by a regional climate model have been investigated.The model was based on RegCM2 and is nested in one-way mode within a global coupled atmosphere-ocean model(CSIRO R₂₁L₉ AOGCM).Two multi-year simulations,the control run with normal CO₂ concentration and the sensitivity run with doubled CO₂ concentration are conducted. As Part I of the publications,results of control run of the CSIRO,i.e.its simulation of present climate in China,are analyzed briefly.It shows that the model can basically reproduce the surface air temperature and precipitation pattern over China.Therefore,its outputs can be used to drive the regional model. Analysis of control run of RegCM shows that with a high resolution,the model improves the simulations of surface air temperature and precipitation in China as compared to the CSIRO model, especially for the precipitation.The spatial correlation coefficient between simulated and observed annual temperature increased from 0.83 in the CSIRO to 0.92 in the RegCM and for annual precipitation from 0.48 in the CSIRO to 0.65 in the RegCM.A similar improvement in the RegCM compared to the CSIRO was found in all simulated months.The main improvement for surface temperature is that RegCM can simulate the fine scale structure of temperature caused by topography.RegCM greatly improved the spatial distribution of precipitation by eliminating the virtual precipitation center in central China,which was simulated by many other GCMs.The precipitation simulated by RegCM in North and Northwest China is smaller than that by CSIRO, which makes it closer to the observation.     

6.25 km高分辨率降尺度数据对雄安新区及整个京津冀地区未来极端气候事件的预估

基于RCP4.5情景下6.25 km高分辨率统计降尺度数据,使用国际上通用的极端气候事件指数,分析雄安新区及整个京津冀地区未来极端气候事件的可能变化。首先对当代模拟结果进行评估,结果表明,集合平均模拟可以较好地再现大部分极端气候事件指数的分布,且对与气温有关的极端气候事件指数模拟效果较好。但也存在一定偏差,特别是对连续干旱日数(CDD)的模拟效果相对较差。集合平均的预估结果表明,未来在全球变暖背景下,雄安新区及整个京津冀地区均表现为极端暖事件增多,极端冷事件减少,连续干旱日数减少,极端强降水事件增多。具体来看,到21世纪末期,日最高气温最高值(TXx)和日最低气温最低值(TNn)在整个区域上都是增加的,大部分地区增加值分别超过2.4℃和3.2℃;夏季日数(SU)和热带夜数(TR)也都表现为增加,但两者的变化分布基本相反,其中SU在山区增加幅度较大,平原地区增加幅度较小,而TR在平原地区的增加值较山区更显著,两个指数未来增加值分别为20~40 d和5~40 d;霜冻日数(FD)和冰冻日数(ID)都表现为减少,减少值分别超过10 d和5 d;与降水有关的极端气候事件指数,CDD、降雨日数(R_1mm)和中雨日数(R_10mm)的变化均以减少为主,但数值较小,一般都在?10%~0之间;最大5 d降水量(R_X5day)、降水强度(SDII)和大雨日数(R_20mm)主要表现为增加,增加值一般在0~25%之间。从区域平均的变化来看,与气温有关的极端气候事件指数的变化趋势较为显著,与降水有关的极端气候事件指数变化趋势较小。两个区域对比来看,雄安新区模式间的不确定性更大,反映出模式对较小区域模拟的不足。     

Change in Extreme Climate Events over China Based on CMIP5

The changes in a selection of extreme climate indices(maximum of daily maximum temperature(TXx),minimum of daily minimum temperature(TNn),annual total precipitation when the daily precipitation exceeds the 95th percentile of wet-day precipitation(very wet days,R95p),and the maximum number of consecutive days with less than 1 mm of precipitation(consecutive dry days,CDD))were projected using multi-model results from phase 5 of the Coupled Model Intercomparison Project in the early,middle,and latter parts of the 21st century under different Representative Concentration Pathway(RCP)emissions scenarios.The results suggest that TXx and TNn will increase in the future and,moreover,the increases of TNn under all RCPs are larger than those of TXx.R95p is projected to increase and CDD to decrease significantly.The changes in TXx,TNn,R95p,and CDD in eight sub-regions of China are different in the three periods of the 21st century,and the ranges of change for the four indices under the higher emissions scenario are projected to be larger than those under the lower emissions scenario.The multi-model simulations show remarkable consistency in their projection of the extreme temperature indices,but poor consistency with respect to the extreme precipitation indices.More substantial inconsistency is found in those regions where high and low temperatures are likely to happen for TXx and TNn,respectively.For extreme precipitation events(R95p),greater uncertainty appears in most of the southern regions,while for drought events(CDD)it appears in the basins of Xinjiang.The uncertainty in the future changes of the extreme climate indices increases with the increasing severity of the emissions scenario.