Sensitivity of regional climate simulations of the summer 1998 extreme rainfall to convective parameterization schemes

In this paper, a comparison study of three cumulus parameterization schemes (CPSs), Kain-Fritsch2 (KF2), Grell (GR) and Anthes-Kuo (AK), is carried out using the Pennsylvania State University-National Center for Atmospheric Research mesoscale model (i.e., MM5). The performances of three CPSs are examined in simulations of the long-term heavy Meiyu-frontal rainfall events over the middle to lower reaches of the Yangtze River Basin (YRB-ML) during the summer of 1998. The initial and lateral boundary atmosphere conditions are taken from the National Centers for Environmental Prediction/Department of Energy Reanalysis-2 (R-2) data. The experiment with KF2 scheme (EX_KF2) reproduces reasonably well the major rainfall events, especially the heavy rainfall over YRB-ML during the later stage, and the middle and lower troposphere circulation patterns. In contrast, the experiments with both GR and AK schemes (EX_GR and EX_AK) only simulate the heavy rainfall during the first Meiyu rainy phase with weak intensity, and almost miss the rainfall along YRB-ML during the second phase. The analyses show that the location of 500?hPa western Pacific subtropical high during the first rainy phase, the northward advance during the transition period and the retreat during the second rainy phase, observed from the R-2 data, are successfully captured by EX_KF2, compared to the poor performance of EX_GR and EX_AK. A reasonable proportion of the subgrid-scale rainfall and smaller biases of temperature and moisture from lower to middle troposphere in EX_KF2 decide its good rainfall simulations, in contrast with the absolutely high proportions and the cold and dry biases caused by the decreased vertically convective transportation and the weak southwesterly wind in EX_GR and EX_AK. Overall, the three CPSs show substantial intersimulation differences in rainfall as well as in three-dimensional atmospheric structures, and KF2 shows superior performances. The results suggest that the realistic subgrid-scale CPS is still highly required for the high-resolution regional climate models to simulate the heavy rainfall events.     

The West African monsoon onset in 2006: sensitivity to surface albedo, orography, SST and synoptic scale dry-air intrusions using WRF

In order to test the sensitivity of the transitional phase of the 2006 West African monsoon (WAM) onset to different mechanisms, weather research and forecasting (WRF) model simulations have been carried out addressing the role of the Saharan heat low (SHL) and its sensitivity to the albedo field and to the northern Africa orography, and the role of the sea surface temperature (SST) in the eastern tropical Atlantic and Mediterranean. Lowering albedo over the desert region induces a northward location of the inter-tropical convergence zone (ITCZ), while removing mountains in North Africa reduces rainfall over West Africa. Shifting SST forward by 15?days leads to a northward location of the ITCZ before the WAM onset. However none of these factors modifies the timing of the WAM onset in 2006. The transitional phase of the 2006 WAM onset has been examined in more detail. The enhancement of SHL intensity, combined with the development of the oceanic cold tongue in the Guinea gulf, leads to low-level moisture flux divergence in the ITCZ reducing rainfall and increasing low-level humidity over the Sahel. However, weakening of convection can be clearly attributed to dry-air intrusions in mid-levels, originating from the subtropical westerly jet and associated with Rossby wave pattern over North Africa. Sensitivity tests on the synoptic scale forcing outside of the WRF model domain confirm the dominating role of large-scale dynamics to control the transitional phase of the WAM onset and its timing. However it is shown that the regional factors can modulate this larger scale forcing.     

How well are daily intense rainfall events captured by current climate models over Africa?

The ability of state-of-the-art climate models to capture the mean spatial and temporal characteristics of daily intense rainfall events over Africa is evaluated by analyzing regional climate model (RCM) simulations at 90- and 30-km along with output from four atmospheric general circulation models (AGCMs) and coupled atmosphere–ocean general circulation models (AOGCMs) of the Climate Model Intercomparison Project 5. Daily intense rainfall events are extracted at grid point scale using a 95th percentile threshold approach applied to all rainy days (i.e., daily rainfall ≥1 mm day^?1) over the 1998–2008 period for which two satellite-derived precipitation products are available. Both RCM simulations provide similar results. They accurately capture the spatial and temporal characteristics of intense events, while they tend to overestimate their number and underestimate their intensity. The skill of AGCMs and AOGCMs is generally similar over the African continent and similar to previous global climate model generations. The majority of the AGCMs and AOGCMs greatly overestimate the frequency of intense events, particularly in the tropics, generally fail at simulating the observed intensity, and systematically overestimate their spatial coverage. The RCM performs at least as well as the most accurate global climate model, demonstrating a clear added value to general circulation model simulations and the usefulness of regional modeling for investigating the physics leading to intense events and their change under global warming.     

Diagnosing GCM errors over West Africa using relaxation experiments. Part I: summer monsoon climatology and interannual variability

The CNRM atmospheric general circulation model Arpege-Climat is relaxed towards atmospheric reanalyses outside the 10°S?C32°N 30°W?C50°E domain in order to disentangle the regional versus large-scale sources of climatological biases and interannual variability of the West African monsoon (WAM). On the one hand, the main climatological features of the monsoon, including the spatial distribution of summer precipitation, are only weakly improved by the nudging, thereby suggesting the regional origin of the Arpege-Climat biases. On the other hand, the nudging technique is relatively efficient to control the interannual variability of the WAM dynamics, though the impact on rainfall variability is less clear. Additional sensitivity experiments focusing on the strong 1994 summer monsoon suggest that the weak sensitivity of the model biases is not an artifact of the nudging design, but the evidence that regional physical processes are the main limiting factors for a realistic simulation of monsoon circulation and precipitation in the Arpege-Climat model. Sensitivity experiments to soil moisture boundary conditions are also conducted and highlight the relevance of land?Catmosphere coupling for the amplification of precipitation biases. Nevertheless, the land surface hydrology is not the main explanation for the model errors that are rather due to deficiencies in the atmospheric physics. The intraseasonal timescale and the model internal variability are discussed in a companion paper.     

Impacts of Spectral Nudging on the Sensitivity of a Regional Climate Model to Convective Parameterizations in East Asia

The sensitivity of a regional climate model (RCM) to cumulus parameterization (CUPA) schemes in modeling summer precipitation over East Asia has been investigated by using the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (PSU-NCAR MM5). The feasibility of physical ensemble and the effect of interior (spectral) nudging are also assessed. The RCM simulations are evaluated against the NCEP/NCAR reanalysis data and NCEP/CPC precipitation data for three summers (JJA) in 1991, 1998, and 2003. The results show that the RCM is highly sensitive to CUPA schemes. Different CUPA schemes cause distinctive characteristics in the modeling of JJA precipitation and the intraseasonal (daily) variability of regional precipitation. The sensitivity of the RCM simulations to the CUPA schemes is reduced by adopting the spectral nudging technique, which enables the RCM to reproduce more realistic large-scale circulations at the upper levels of the atmosphere as well as near the surface, and better precipitation simulation in the selected experiments. The ensemble simulations using different CUPA schemes show higher skills than individual members for both control runs and spectral nudging runs. The physical ensemble adopting the spectral nudging technique shows the highest downscaling skill in capturing the general circulation patterns for all experiments and improved temporal distributions of precipitation in some regions.     

Multiyear hindcast simulations of summer monsoon over South Asia using a nested regional climate model��BCC_RegCM1.0

Multiyear (1983?C2006) hindcast simulation of summer monsoon over South Asia has been carried out using the regional climate model of the Beijing Climate Centre (BCC_RegCM1.0). The regional climate model (hereafter BCC RCM) is nested into the global climate model of the Beijing Climate Centre BCC_CGCM1.0 (here after CGCM). The regional climate model is initialized on 01 May and integrated up to the end of the September for 24?years. Compared to the driving CGCM the BCC RCM reproduces reasonably well the intensity and magnitude of the large-scale features associated with the South Asia summer monsoon such as the upper level anticyclone at 200?hPa, the mid-tropospheric warming over the Tibetan plateau, the surface heat low and the 850?hPa moisture transport from ocean to the land. Both models, i.e., BCC RCM and the driving CGCM overestimates (underestimates) the 850?hPa southwesterly flow over the northern (southern) Arabian Sea. Moreover, both models overestimate the seasonal mean precipitation over much of the South Asia region compared to the observations. However, the precipitation biases are significantly reduced in the BCC RCM simulations. Furthermore, both models simulate reasonably the interannual variability of the summer monsoon over India. The precipitation index simulated by BCC RCM shows significant correlation (0.62) with the observed one. The BCC RCM simulates reasonably well the spatial and temporal variation of the precipitation and surface air temperature compared to the driving CGCM. Further, the temperature biases are significantly reduced (1?C4°C) in the BCC RCM simulations. The simulated vertical structure of the atmosphere show biases above the four sub-regions, however, these biases are significantly reduced in the BCC RCM simulations compared to the driving CGCM. Compared to the driving CGCM, the evolution processes of the onset of summer monsoon, e.g., the meridional temperature gradient and the vertical wind shear are well simulated by the BCC RCM. The 24-year simulations also show that with a little exception the BCC RCM is capable to reproduce the monsoon active and break phases and the intraseasonal precipitation variation over the Indian subcontinent.     

WRF/ARPEGE-CLIMAT simulated climate trends over West Africa

The Weather Regional Forecast (WRF) model is used in this study to downscale low-resolution data over West Africa. First, the performance of the regional model is estimated through contemporary period experiments (1981?C1990) forced by ARPEGE-CLIMAT GCM output (ARPEGE) and ERA-40 re-analyses. Key features of the West African monsoon circulation are reasonably well represented. WRF atmospheric dynamics and summer rainfall compare better to observations than ARPEGE forcing data. WRF simulated moisture transport over West Africa is also consistent in both structure and variability with re-analyses, emphasizing the substantial role played by the West African Monsoon (WAM) and African Easterly Jet (AEJ) flows. The statistical significance of potential climate changes for the A2 scenario between 2032 and 2041 is enhanced in the downscaling from ARPEGE by the regional experiments, with substantial rainfall increases over the Guinea Gulf and eastern Sahel. Future scenario WRF simulations are characterized by higher temperatures over the eastern Tropical Atlantic suggesting more evaporation available locally. This leads to increased moisture advection towards eastern regions of the Guinea Gulf where rainfall is enhanced through a strengthened WAM flow, supporting surface moisture convergence over West Africa. Warmer conditions over both the Mediterranean region and northeastern Sahel could also participate in enhancing moisture transport within the AEJ. The strengthening of the thermal gradient between the Sahara and Guinean regions, particularly pronounced north of 10°N, would support an intensification of the AEJ northwards, given the dependance of the jet to the position/intensity of the meridional gradient. In turn, mid-tropospheric moisture divergence tends to be favored within the AEJ region supporting southwards deflection of moist air and contributing to deep moist convection over the Sahel where late summer rainfall regimes are sustained in the context of the A2 scenario regional projections. In conclusion, WRF proved to be a valuable and efficient tool to help downscaling GCM projections over West Africa, and thus assessing issues such as water resources vulnerability locally.     

Uncertainties in simulating regional climate of Southern Africa: sensitivity to physical parameterizations using WRF

This study aims at quantifying seasonal biases of regional climate model outputs during southern African summer, against a dense in situ measurement network (daily rain-gauge and surface air temperature records, and 12?h UTC radiosondes), and uncertainties associated with some physical parameterizations. Using the non-hydrostatic Advanced Research Weather Forecast (WRF) laterally forced by ERA40 reanalysis, twenty-seven experiments configured with three schemes of cumulus (CU), planetary boundary layer (PBL) and microphysics (MP), are performed at 35?km horizontal resolution during the core of a summer rainy season (December 1993 to February 1994 season) representative of the South African rainfall climatology. WRF simulates accurately seasonal large-scale rainfall patterns, as well as seasonal gradients of South African rainfall and 2-m temperature, and seasonal vertical profiles of the air temperature and humidity. However seasonal biases fluctuate strongly from an experiment to another, denoting considerable uncertainties generated by the physical package. Rainfall amounts are the most sensitive parameter to the tested schemes. Their geography, intensity, and intraseasonal characteristics are predominantly sensitive to CU schemes, and much less to PBL and MP schemes. Some CU-PBL combinations produce additive effects, which can dramatically either reduce or increase biases. Satisfactory configurations are found for South African climate, which would not have been possible without testing numerous physical parameterizations.     

Estimation methods for monthly humidity from dynamical downscaling data for quantitative assessments of climate change impacts

Methods are proposed to estimate the monthly relative humidity and wet bulb temperature based on observations from a dynamical downscaling coupled general circulation model with a regional climate model (RCM) for a quantitative assessment of climate change impacts. The water vapor pressure estimation model developed was a regression model with a monthly saturated water vapor pressure that used minimum air temperature as a variable. The monthly minimum air temperature correction model for RCM bias was developed by stepwise multiple regression analysis using the difference in monthly minimum air temperatures between observations and RCM output as a dependent variable and geographic factors as independent variables. The wet bulb temperature was estimated using the estimated water vapor pressure, air temperature, and atmospheric pressure at ground level both corrected for RCM bias. Root mean square errors of the data decreased considerably in August.     

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

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

Simulations of precipitation using NRCM and comparisons with satellite observations and CAM: annual cycle

The accurate representation of rainfall in models of global climate has been a challenging task for climate modelers owing to its small space and time scales. Quantifying this variability is important for comparing simulations of atmospheric behavior with real time observations. In this regard, this paper compares both the statistical and dynamically forced aspects of precipitation variability simulated by the high-resolution (36?km) Nested Regional Climate Model (NRCM), with satellite observations from the Tropical Rainfall Measuring Mission (TRMM) 3B42 dataset and simulations from the Community Atmosphere Model (CAM) at T85 spatial resolution. Six years of rainfall rate data (2000?C2005) from within the Tropics (30°S?C30°N) have been used in the analysis and results are presented in terms of long-term mean rain rates, amplitude and phase of the annual cycle and seasonal mean maps of precipitation. Our primary focus is on characterizing the annual cycle of rainfall over four land regions of the Tropics namely, the Indian Monsoon, the Amazon, Tropical Africa and the North American monsoon. The lower tropospheric circulation patterns are analyzed in both the observations and the models to identify possible causes for biases in the simulated precipitation. The 6-year mean precipitation simulated by both models show substantial biases throughout the global Tropics with NRCM/CAM systematically underestimating/overestimating rainfall almost everywhere. The seasonal march of rainfall across the equator, following the motion of the sun, is clearly seen in the harmonic vector maps. The timing of peak rainfall (phase) produced by NRCM is in closer agreement with the observations compared to CAM. However like the long-time mean, the magnitude of seasonal mean rainfall is greatly underestimated by NRCM throughout the Tropical land mass. Some of these regional biases can be attributed to erroneous circulation and moisture surpluses/deficits in the lower troposphere in both models. Overall, the results seem to indicate that employing a higher spatial resolution (36?km) does not significantly improve simulation of precipitation. We speculate that a combination of several physics parameterizations and lack of model tuning gives rise to the observed differences between NRCM and the observations.     

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

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

Skill, reproducibility and potential predictability of the West African monsoon in coupled GCMs

In the framework of the ENSEMBLES FP6 project, an ensemble prediction system based on five different state-of-the-art European coupled models has been developed. This study evaluates the performance of these models for forecasting the West African monsoon (WAM) at the monthly time scale. From simulations started the 1 May of each year and covering the period 1991–2001, the reproducibility and potential predictability (PP) of key parameters of the WAM—rainfall, zonal and meridional wind at four levels from the surface to 200 hPa, and specific humidity, from July to September—are assessed. The Sahelian rainfall mode of variability is not accurately reproduced contrary to the Guinean rainfall one: the correlation between observations (from CMAP) and the multi-model ensemble mean is 0.17 and 0.55, respectively. For the Sahelian mode, the correlation is consistent with a low PP of about ~6%. The PP of the Guinean mode is higher, ~44% suggesting a stronger forcing of the sea surface temperature on rainfall variability over this region. Parameters relative to the atmospheric dynamics are on average much more skillful and reproducible than rainfall. Among them, the first mode of variability of the zonal wind at 200 hPa that depicts the Tropical Easterly Jet, is correlated at 0.79 with its “observed” counterpart (from the NCEP/DOE2 reanalyses) and has a PP of 39%. Moreover, models reproduce the correlations between all the atmospheric dynamics parameters and the Sahelian rainfall in a satisfactory way. In that context, a statistical adaptation of the atmospheric dynamic forecasts, using a linear regression model with the leading principal components of the atmospheric dynamical parameters studied, leads to moderate receiver operating characteristic area under the curve and correlation skill scores for the Sahelian rainfall. These scores are however much higher than those obtained using the modelled rainfall.     

Simulating the impact of the large-scale circulation on the 2-m temperature and precipitation climatology

The impact of the simulated large-scale atmospheric circulation on the regional climate is examined using the Weather Research and Forecasting (WRF) model as a regional climate model. The purpose is to understand the potential need for interior grid nudging for dynamical downscaling of global climate model (GCM) output for air quality applications under a changing climate. In this study we downscale the NCEP-Department of Energy Atmospheric Model Intercomparison Project (AMIP-II) Reanalysis using three continuous 20-year WRF simulations: one simulation without interior grid nudging and two using different interior grid nudging methods. The biases in 2-m temperature and precipitation for the simulation without interior grid nudging are unreasonably large with respect to the North American Regional Reanalysis (NARR) over the eastern half of the contiguous United States (CONUS) during the summer when air quality concerns are most relevant. This study examines how these differences arise from errors in predicting the large-scale atmospheric circulation. It is demonstrated that the Bermuda high, which strongly influences the regional climate for much of the eastern half of the CONUS during the summer, is poorly simulated without interior grid nudging. In particular, two summers when the Bermuda high was west (1993) and east (2003) of its climatological position are chosen to illustrate problems in the large-scale atmospheric circulation anomalies. For both summers, WRF without interior grid nudging fails to simulate the placement of the upper-level anticyclonic (1993) and cyclonic (2003) circulation anomalies. The displacement of the large-scale circulation impacts the lower atmosphere moisture transport and precipitable water, affecting the convective environment and precipitation. Using interior grid nudging improves the large-scale circulation aloft and moisture transport/precipitable water anomalies, thereby improving the simulated 2-m temperature and precipitation. The results demonstrate that constraining the RCM to the large-scale features in the driving fields improves the overall accuracy of the simulated regional climate, and suggest that in the absence of such a constraint, the RCM will likely misrepresent important large-scale shifts in the atmospheric circulation under a future climate.     

High-resolution simulations of West African climate using regional climate model (RegCM3) with different lateral boundary conditions

To downscale climate change scenarios, long-term regional climatologies employing global model forcing are needed for West Africa. As a first step, this work examines present-day integrations (1981–2000) with a regional climate model (RCM) over West Africa nested in both reanalysis data and output from a coupled atmospheric–ocean general circulation model (AOGCM). Precipitation and temperature from both simulations are compared to the Climate Research Unit observations. Their spatial distributions are shown to be realistic. Annual cycles are considerably correlated. Simulations are also evaluated with respect to the driving large-scale fields. RCM offers some improvements compared to the AOGCM driving field. Evaluation of seasonal precipitation biases reveals that RCM dry biases are highest on June–August around mountains. They are associated to cold biases in temperature which, in turn, are connected to wet biases in precipitation outside orographic zones. Biases brought through AOGCM forcing are relatively low. Despite these errors, the simulations produce encouraging results and show the ability of the AOGCM to drive the RCM for future projections.     

Validating a regional climate model’s downscaling ability for East Asian summer monsoonal interannual variability

Performance of a regional climate model (RCM), WRF, for downscaling East Asian summer season climate is investigated based on 11-summer integrations associated with different climate conditions with reanalysis data as the lateral boundary conditions. It is found that while the RCM is essentially unable to improve large-scale circulation patterns in the upper troposphere for most years, it is able to simulate better lower-level meridional moisture transport in the East Asian summer monsoon. For precipitation downscaling, the RCM produces more realistic magnitude of the interannual variation in most areas of East Asia than that in the reanalysis. Furthermore, the RCM significantly improves the spatial pattern of summer rainfall over dry inland areas and mountainous areas, such as Mongolia and the Tibetan Plateau. Meanwhile, it reduces the wet bias over southeast China. Over Mongolia, however, the performance of precipitation downscaling strongly depends on the year: the WRF is skillful for normal and wet years, but not for dry years, which suggests that land surface processes play an important role in downscaling ability. Over the dry area of North China, the WRF shows the worst performance. Additional sensitivity experiments testing land effects in downscaling suggest the initial soil moisture condition and representation of land surface processes with different schemes are sources of uncertainty for precipitation downscaling. Correction of initial soil moisture using the climatology dataset from GSWP-2 is a useful approach to robustly reducing wet bias in inland areas as well as to improve spatial distribution of precipitation. Despite the improvement on RCM downscaling, regional analyses reveal that accurate simulation of precipitation over East China, where the precipitation pattern is strongly influenced by the activity of the Meiyu/Baiu rainfall band, is difficult. Since the location of the rainfall band is closely associated with both lower-level meridional moisture transport and upper-level circulation structures, it is necessary to have realistic upper-air circulation patterns in the RCM as well as lower-level moisture transport in order to improve the circulation-associated convective rainfall band in East Asia.     

Future Precipitation Extremes in China under Climate Change and Their Physical Quantification Based on a Regional Climate Model and CMIP5 Model Simulations

The atmospheric water holding capacity will increase with temperature according to Clausius-Clapeyron scaling and affects precipitation.The rates of change in future precipitation extremes are quantified with changes in surface air temperature.Precipitation extremes in China are determined for the 21st century in six simulations using a regional climate model,RegCM4,and 17 global climate models that participated in CMIP5.First,we assess the performance of the CMIP5 models and RCM runs in their simulation of extreme precipitation for the current period(RF:1982-2001).The CMIP5 models and RCM results can capture the spatial variations of precipitation extremes,as well as those based on observations:OBS and XPP.Precipitation extremes over four subregions in China are predicted to increase in the mid-future(MF:2039-58)and far-future(FF:2079-98)relative to those for the RF period based on both the CMIP5 ensemble mean and RCM ensemble mean.The secular trends in the extremes of the CMIP5 models are predicted to increase from 2008 to 2058,and the RCM results show higher interannual variability relative to that of the CMIP5 models.Then,we quantify the increasing rates of change in precipitation extremes in the MF and FF periods in the subregions of China with the changes in surface air temperature.Finally,based on the water vapor equation,changes in precipitation extremes in China for the MF and FF periods are found to correlate positively with changes in the atmospheric vertical wind multiplied by changes in surface specific humidity(significant at the p<0.1 level).     

MM5模式中不同对流参数化方案的比较试验

应用MM5中尺度模式, 在60、20和10 km模式分辨率下, 分别选用4种不同对流参数化方案 (KUO方案、GRELL方案、KAIN-FRITSCH方案和BETTS-MILLER方案, 以下简称KU、GR、KF和BM方案) 对1996年8月3~4日石家庄暴雨过程进行数值模拟试验.模拟结果的对比分析及其与观测的比较表明:主要雨带位置对参数化方案并不是十分敏感, 但随分辨率提高, 雨带分布特征的模拟更接近实况; 当分辨率提高到10 km时, 虚假的降水中心也明显增加; 模拟的暴雨中心强度随分辨率的提高而增强并随参数化方案的不同有所变化, 但均比实况偏弱.分析还发现, MM5模式的GR、KF及BM方案的次网格降水对总降水的贡献率随分辨率的提高而减小, 而KU方案的情况则呈现出不合理的缓慢增加态势.虽然4种方案下模拟的水平环流特征有较好的一致性, 但模拟的云物理特征和垂直运动特征还是存在一定差别的, 这种差别对定点、定量降水和天空状况、地面气温、湿度等要素的准确预报都会产生影响.因此, 在预报和模拟中应考虑预报和研究对象的特点来选择对流参数化方案.     

Internal variability of RCM simulations over an annual cycle

Three one-year simulations generated with the Canadian RCM (CRCM) are compared to each other in order to study internal variability in nested regional climate models and to evaluate the influence exerted by the lateral boundaries information supplied by the nesting procedure. All simulations are generated over a large domain and cover an annual cycle. The simulations use different combinations of surface and atmospheric initial conditions but all of them share the same set of time-dependent lateral boundary conditions taken from a simulation by the Canadian GCM. A first simulation is used as control, the second simulation is launched with different atmospheric and surface initial conditions (IC) and the third simulation is launched taking its surface IC from the control simulation. Comparison of the root-mean-square differences (RMSD) between each pair of simulations shows two distinct seasonal behaviours in the time series of the RMSD. In winter all simulations are almost identical to each other resulting in very low RMSD values while in summer large discrepancies develop between pairs of simulations. For water vapour related fields such as precipitation or specific humidity, these discrepancies are sometimes as large as the monthly averaged variability. However, analysis of the climate statistics shows that, although the evolution of the various summer weather systems is different, the climates of each simulation are similar.     

Projected changes in vertical temperature profiles for Australasia

The vertical temperature profile in the atmosphere reflects a balance between radiative and convective processes and interactions with the oceanic and land surfaces. Changes in vertical temperature profiles can affect atmospheric stability, which in turn can impact various aspects of weather systems. In this study, we analyzed recent-past trends of temperature over the Australian region using a homogenized monthly upper-air temperature dataset and four reanalysis datasets (NCEP, ERA-Interim, JRA-55 and MERRA). We also used outputs of 12 historical and future regional climate model (RCM) simulations from the NSW/ACT (New South Wales/Australian Capital Territory) Regional Climate Modelling (NARCliM) project and 6 RCM simulations from the CORDEX (Coordinated Regional Downscaling Experiment) Australasian project to investigate projected changes in vertical temperature profiles. The results show that the currently observed positive trend in the troposphere and negative trend in the lower stratosphere will continue in the future with significant warming over the whole troposphere and largest over the middle to upper troposphere. The increasing temperatures are found to be latitude-dependent with clear seasonal variations, and a strong diurnal variation for the near surface layers and upper levels in tropical regions. Changes in the diurnal variability indicate that near surface layers will be less stable in the afternoon leading to conditions favoring convective systems and more stable in the early morning which is favorable for temperature inversions. The largest differences of future changes in temperature between the simulations are associated with the driving GCMs, suggesting that large-scale circulation plays a dominant role in regional atmospheric temperature change.