Multi-decadal scenario simulation over Korea using a one-way double-nested regional climate model system. Part 1: recent climate simulation (1971–2000)

We present an analysis of a high resolution multi-decadal simulation of recent climate (1971–2000) over the Korean Peninsula with a regional climate model (RegCM3) using a one-way double-nested system. Mean climate state as well as frequency and intensity of extreme climate events are investigated at various temporal and spatial scales, with focus on surface air temperature and precipitation. The mother intermediate resolution model domain encompasses the eastern regions of Asia at 60 km grid spacing while the high resolution nested domain covers the Korean Peninsula at 20 km grid spacing. The simulation spans the 30-year period of January 1971 through December 2000, and initial and lateral boundary conditions for the mother domain are provided from ECHO-G fields based on the IPCC SRES B2 scenario. The model shows a good performance in reproducing the climatological and regional characteristics of surface variables, although some persistent biases are present. Main results are as follows: (1) The RegCM3 successfully simulates the fine-scale structure of the temperature field due to topographic forcing but it shows a systematic cold bias mostly due to an underestimate of maximum temperature. (2) The frequency distribution of simulated daily mean temperature agrees well with the observed seasonal and spatial patterns. In the summer season, however, daily variability is underestimated. (3) The RegCM3 simulation adequately captures the seasonal evolution of precipitation associated to the East Asia monsoon. In particular, the simulated winter precipitation is remarkably good, clearly showing typical precipitation patterns that occur on the northwestern areas of Japan during the winter monsoon. Although summer precipitation is underestimated, area-averaged time series of precipitation over Korea show that the RegCM3 agrees better with observations than ECHO-G both in terms of seasonal evolution and precipitation amounts. (4) Heavy rainfall phenomena exceeding 300 mm/day are simulated only at the high resolution of the double nested domain. (5) The model shows a tendency to overestimate the number of precipitation days and to underestimate the precipitation intensities. (6) A CSEOF analysis reveals that the model captures the strength of the annual cycle and the surface warming trend throughout the simulated period.     

区域气候模式与陆面模式的耦合及其对东亚气候模拟的影响

将大气—植被相互作用模式AVIM（Atmosphere-Vegetation Interaction Model）与区域环境系统集成模式 RIEMS2.0（Regional Integrated Environment Modeling System Version 2.0）耦合,利用耦合后的AVIM-RIEMS2.0模式在东亚区域选定典型年份进行积分试验,通过模拟结果与观测资料对比分析,从整体上评估耦合模式对东亚区域的模拟能力。结果表明:模式能够较好地模拟850 hPa风场、500 hPa位势高度、气温、降水以及地表热通量空间分布型和季节变化。双向耦合具有动态植被过程的AVIM模式后,RIEMS2.0模拟能力有一定程度的提高。850 hPa风场在冬季的中国东北、华北地区以及夏季的中国东部地区,模拟偏差都减小;500 hPa高度场模拟在中国北方地区改进明显,而在中国南方地区的夏季并没表现出明显的改进趋势。耦合模式改进了RIEMS2.0模式冬季气温模拟偏低而夏季偏高的现象。从区域平均看,耦合模式改善了降水模拟偏多的现象,并使得潜热通量的模拟效果有明显的改进,对感热通量模拟在大部分地区也有改进。总的来看,AVIM-RIEMS2.0耦合模式对中国北方地区模拟改进较为明显,而对中国南方地区,特别是华南地区没有明显的改进。     

An inter-comparison of regional climate models for Europe: model performance in present-day climate

The analysis of possible regional climate changes over Europe as simulated by 10 regional climate models within the context of PRUDENCE requires a careful investigation of possible systematic biases in the models. The purpose of this paper is to identify how the main model systematic biases vary across the different models. Two fundamental aspects of model validation are addressed here: the ability to simulate (1) the long-term (30 or 40 years) mean climate and (2) the inter-annual variability. The analysis concentrates on near-surface air temperature and precipitation over land and focuses mainly on winter and summer. In general, there is a warm bias with respect to the CRU data set in these extreme seasons and a tendency to cold biases in the transition seasons. In winter the typical spread (standard deviation) between the models is 1 K. During summer there is generally a better agreement between observed and simulated values of inter-annual variability although there is a relatively clear signal that the modeled temperature variability is larger than suggested by observations, while precipitation variability is closer to observations. The areas with warm (cold) bias in winter generally exhibit wet (dry) biases, whereas the relationship is the reverse during summer (though much less clear, coupling warm (cold) biases with dry (wet) ones). When comparing the RCMs with their driving GCM, they generally reproduce the large-scale circulation of the GCM though in some cases there are substantial differences between regional biases in surface temperature and precipitation.     

Comparison of the climate simulated by the CCM3 coupled to two different land-surface models

We present results from a coupled atmosphere-biosphere model CCM3/IBIS (the Community Climate Model coupled to the Integrated BIosphere Simulator), which is designed to study the dynamic interactions between climate and vegetation and the global carbon cycle. We analyze the climate simulated by CCM3/IBIS with fixed vegetation conditions and we compare it to the climate simulated by the standard CCM3, which includes the LSM (land surface model) land-surface package. Important differences between the two models include simple parametrizations of lakes, wetlands and crops in CCM3/LSM not taken into account in CCM3/IBIS. CCM3/IBIS and CCM3/LSM share common biases (compared to observations) in the temperature field in boreal winter and in the precipitation field annually, making the atmospheric model the most probable cause of those biases. The models differ in the temperature field and surface energy balance in the Sahara annually and in the mid-to high latitudes from spring through fall. CCM3/IBIS simulates global annual air temperatures that are on average 1.7 °C higher than CCM3/LSM and 0.5 °C higher than the observed climatology. Differences in albedo and/or snow parametrization explain most of the Sahara and high-latitude temperature disagreement. Our sensitivity study with CCM3/LSM shows that the presence of lakes and wetlands in CCM3/LSM can account for about half of the difference in temperature in summer over the lake and wetland regions of the mid-latitudes. A second sensitivity study shows that higher surface roughness length in CCM3/IBIS can also explain part of the difference in summer surface temperature in the mid-latitudes. Surface roughness length affects the surface temperature through a feedback mechanism linking surface wind speed, planetary boundary layer height, low level cloudiness and radiation     

Twenty-first century Arctic climate change in the CCSM3 IPCC scenario simulations

Arctic climate change in the Twenty-first century is simulated by the Community Climate System Model version 3.0 (CCSM3). The simulations from three emission scenarios (A2, A1B and B1) are analyzed using eight (A1B and B1) or five (A2) ensemble members. The model simulates a reasonable present-day climate and historical climate trend. The model projects a decline of sea-ice extent in the range of 1.4–3.9% per decade and 4.8–22.2% per decade in winter and summer, respectively, corresponding to the range of forcings that span the scenarios. At the end of the Twenty-first century, the winter and summer Arctic mean surface air temperature increases in a range of 4–14°C (B1 and A2) and 0.7–5°C (B1 and A2) relative to the end of the Twentieth century. The Arctic becomes ice-free during summer at the end of the Twenty-first century in the A2 scenario. Similar to the observations, the Arctic Oscillation (AO) is the dominant factor in explaining the variability of the atmosphere and sea ice in the 1870–1999 historical runs. The AO shifts to the positive phase in response to greenhouse gas forcings in the Twenty-first century. But the simulated trends in both Arctic mean sea-level pressure and the AO index are smaller than what has been observed. The Twenty-first century Arctic warming mainly results from the radiative forcing of greenhouse gases. The 1st empirical orthogonal function (explains 72.2–51.7% of the total variance) of the wintertime surface air temperature during 1870–2099 is characterized by a strong warming trend and a “polar amplification”-type of spatial pattern. The AO, which plays a secondary role, contributes to less than 10% of the total variance in both surface temperature and sea-ice concentration.     

Evaluation of regional climate simulations over the CORDEX-EA-II domain using the COSMO-CLM model

The COSMO-CLM (CCLM) model is applied to perform regional climate simulation over the second phase of CORDEX-East Asia (CORDEX-EA-II) domain in this study. Driven by the ERAInterim reanalysis data, the model was integrated from 1988 to 2010 with a high resolution of 0.22°. The model’s ability to reproduce mean climatology and climatic extremes is evaluated based on various aspects. The CCLM model is capable of capturing the basic features of the East Asia climate, including the seasonal mean patterns, interannual variations, annual cycles and climate extreme indices for both surface air temperature and precipitation. Some biases are evident in certain areas and seasons. Warm and wet biases appear in the arid and semi-arid areas over the northwestern and northern parts of the domain. The simulated climate over the Tibetan Plateau is colder and wetter than the observations, while South China, East China, and India are drier. The model biases may be caused by the simulated anticyclonic and cyclonic biases in low-level circulations, the simulated water vapor content biases, and the inadequate physical parameterizations in the CCLM model. A parallel 0.44° simulation is conducted and the comparison results show some added value introduced by the higher resolution 0.22° simulation. As a result, the CCLM model could be an adequate member for the next stage of the CORDEX-EA project, while further studies should be encouraged.     

A scenario of European climate change for the late twenty-first century: seasonal means and interannual variability

A scenario of European climate change for the late twenty-first century is described, using a high-resolution state-of-the-art model. A time-slice approach is used, whereby the atmospheric general circulation model, HadAM3P, was integrated for two periods, 1960–1990 and 2070–2100, using the SRES A2 scenario. For the first time an ensemble of such experiments was produced, along with appropriate statistical tests for assessing significance. The focus is on changes to the statistics of seasonal means, and includes analysis of both multi-year means and interannual variance. All four seasons are assessed, and anomalies are mapped for surface air temperature, precipitation and snow mass. Mechanisms are proposed where these are dominated by straightforward local processes. In winter, the largest warming occurs over eastern Europe, up to 7°C, mean snow mass is reduced by at least 80% except over Scandinavia, and precipitation increases over all but the southernmost parts of Europe. In summer, temperatures rise by 6–9°C south of about 50°N, and mean rainfall is substantially reduced over the same area. In spring and autumn, anomalies tend to be weaker, but often display patterns similar to the preceding season, reflecting the inertia of the land surface component of the climate system. Changes in interannual variance are substantial in the solsticial seasons for many regions (note that for precipitation, variance estimates are scaled by the square of the mean). In winter, interannual variability of near-surface air temperature is considerably reduced over much of Europe, and the relative variability of precipitation is reduced north of about 50°N. In summer, the (relative) interannual variance of both variables increases over much of the continent.     

Bayesian multi-model projection of climate: bias assumptions and interannual variability

Current climate change projections are based on comprehensive multi-model ensembles of global and regional climate simulations. Application of this information to impact studies requires a combined probabilistic estimate taking into account the different models and their performance under current climatic conditions. Here we present a Bayesian statistical model for the distribution of seasonal mean surface temperatures for control and scenario periods. The model combines observational data for the control period with the output of regional climate models (RCMs) driven by different global climate models (GCMs). The proposed Bayesian methodology addresses seasonal mean temperatures and considers both changes in mean temperature and interannual variability. In addition, unlike previous studies, our methodology explicitly considers model biases that are allowed to be time-dependent (i.e. change between control and scenario period). More specifically, the model considers additive and multiplicative model biases for each RCM and introduces two plausible assumptions (“constant bias” and “constant relationship”) about extrapolating the biases from the control to the scenario period. The resulting identifiability problem is resolved by using informative priors for the bias changes. A sensitivity analysis illustrates the role of the informative prior. As an example, we present results for Alpine winter and summer temperatures for control (1961–1990) and scenario periods (2071–2100) under the SRES A2 greenhouse gas scenario. For winter, both bias assumptions yield a comparable mean warming of 3.5–3.6°C. For summer, the two different assumptions have a strong influence on the probabilistic prediction of mean warming, which amounts to 5.4°C and 3.4°C for the “constant bias” and “constant relation” assumptions, respectively. Analysis shows that the underlying reason for this large uncertainty is due to the overestimation of summer interannual variability in all models considered. Our results show the necessity to consider potential bias changes when projecting climate under an emission scenario. Further work is needed to determine how bias information can be exploited for this task.     

Present climate simulation over Korea with a regional climate model using a one-way double-nested system

Summary This study investigates the capability of the regional climate model RegCM3 to simulate surface air temperature and precipitation over the Korean Peninsula. The model is run in one-way double nested mode, with a 60 km grid point spacing “mother” domain encompassing the eastern regions of Asia and a 20 km grid point spacing nested domain covering the Korean Peninsula. The simulation spans the three-year period of 1 October 2000 through 30 September 2003 and the boundary conditions needed to run the mother domain experiment are provided from the NCEP reanalysis of observations. The model results are compared with a high density station observation dataset to examine the fine scale structure of the surface climate signal. The model shows a good performance in capturing both the sign and magnitude of the seasonal and inter-annual variations of the surface variables both over East Asia as a whole and over the Korean Peninsula in the nested system. Some persistent biases are however present. Surface temperature is systematically underestimated, especially over mountainous regions in the warm season. This feature may be due to the relatively coarse representation of the Korean topography. The simulated precipitation over the mother domain successfully reproduces the broad spatial pattern of observed precipitation over East Asia along with its seasonal evolution. On the other hand, fine scale details from the nested results show a varying level of quality for the different individual years. Because of the better resolved topographic forcing, the increased resolution of the nested model improves the spatial agreement with the fine scale observation fields for temperature and cold season precipitation. For summer monsoon precipitation the simulation of individual monsoon convective events and tropical storms is however more important than the topographic forcing, and therefore the performance of the nested system is more case-dependent.     

Simulation and Analysis of China Climate Using Two-Way Interactive Atmosphere-Vegetation Model （RIEMS-AVIM）

In this paper, an Atmosphere-Vegetation Interaction Model （AVIM） is coupled to the Regional Integrated Environment Model System （RIEMS）, and a 10-year integration for China is performed using the RIEMS-AVIM. The analysis of the results of the 10-year integration shows that the characters of the spatial distributions of temperature and precipitation over China are well simulated. The patterns of simulated surface sensible and latent heat fluxes match well with the spatial climatological atlas： the values of winter surface sensible and latent heat fluxes are both lower than climatological values over the whole country. Summer surface sensible heat flux is higher than climatological values in western China and lower in eastern China, while summer surface latent heat flux is higher than climatological values in the eastern and lower in the western. Seasonal variations of simulated temperature and precipitation of RIMES-AVIM agree with those of the observed. Simulated temperature is lower than the observed in the Tibetan Plateau and Northwest China for the whole year, slightly lower in the remaining regions in winter, but consistent with the observed in summer. The simulated temperature of RIEMS-AVIM is higher in winter and lower in summer than that of RIEMS, which shows that the simulated temperature of RIEMS-AVIM is closer to the observed value. Simulated precipitation is excessive in the first half of the year, but consistent with the observed in the second half of the year. The simulated summer precipitation of RIEMS-AVIM has significant improvement compared to that of RIEMS, which is less and closer to the observed value. The interannual variations of temperature and precipitation are also fairly well simulated, with temperature simulation being superior to precipitation simulation. The interannual variation of simulated temperature is significantly correlated with the observed in Northeast China, the Transition Region, South China, and the Tibetan Plateau, but the correlation between precipitation simu     

A Regional Air--Sea Coupled Model and Its Application over East Asia in the Summer of 2000

A regional air-sea coupled model,comprising the Regional Integrated Environment Model System (RIEMS)and the Princeton Ocean Model(POM)was developed to simulate summer climate features over East Asia in 2000.The sensitivity of the model's behavior to the coupling time interval(CTI),the causes of the sea surface temperature(SST)biases,and the role of air-sea interaction in the simulation of precipitation over China are investigated.Results show that the coupled model can basically produce the spatial pattern of SST,precipitation,and surface air temperature(SAT)with five different CTIs respectively.Also,using a CTI of 3,6 or 12 hours tended to produce more successful simulations than if using 1 and 24 hours.Further analysis indicates that both a higher and lower coupling frequency result in larger model biases in air-sea heat flux exchanges,which might be responsible for the sensitivity of the coupled model's behavior to the CTI. Sensitivity experiments indicate that SST biases between the coupled and uncoupled POM occurring over the China coastal waters were due to the mismatch of the surface heat fluxes produced by the RIEMS with those required by the POM.In the coupled run,the air-sea feedbacks reduced the biases in surface heat fluxes,compared with the uncoupled RIEMS,consequently resulted in changes in thermal contrast over land and sea and led to a precipitation increase over South China and a decrease over North China.These results agree well observations in the summer of 2000.     

A multi-model ensemble of downscaled spatial climate change scenarios for the Dommel catchment, Western Europe

Regional or local scale hydrological impact studies require high resolution climate change scenarios which should incorporate some assessment of uncertainties in future climate projections. This paper describes a method used to produce a multi-model ensemble of multivariate weather simulations including spatial–temporal rainfall scenarios and single-site temperature and potential evapotranspiration scenarios for hydrological impact assessment in the Dommel catchment (1,350 km²) in The Netherlands and Belgium. A multi-site stochastic rainfall model combined with a rainfall conditioned weather generator have been used for the first time with the change factor approach to downscale projections of change derived from eight Regional Climate Model (RCM) experiments for the SRES A2 emission scenario for the period 2071–2100. For winter, all downscaled scenarios show an increase in mean daily precipitation (catchment average change of +9% to +40%) and typically an increase in the proportion of wet days, while for summer a decrease in mean daily precipitation (−16% to −57%) and proportion of wet days is projected. The range of projected mean temperature is 7.7°C to 9.1°C for winter and 19.9°C to 23.3°C for summer, relative to means for the control period (1961–1990) of 3.8°C and 16.8°C, respectively. Mean annual potential evapotranspiration is projected to increase by between +17% and +36%. The magnitude and seasonal distribution of changes in the downscaled climate change projections are strongly influenced by the General Circulation Model (GCM) providing boundary conditions for the RCM experiments. Therefore, a multi-model ensemble of climate change scenarios based on different RCMs and GCMs provides more robust estimates of precipitation, temperature and evapotranspiration for hydrological impact assessments, at both regional and local scale.     

不同分辨率CCSM4对东亚和中国气候模拟能力分析

本文利用通用气候系统模式CCSM4在三种水平分辨率下的工业化革命前期气候模拟试验,结合观测和再分析资料,比较了各分辨率下模式对中国温度和降水、东亚海平面气压和850 hPa风场的模拟能力,综合评价了模式分辨率对东亚和中国气候模拟的影响.结果表明,三种分辨率对中国温度均具有很好的模拟能力,除春季外,低分辨率(T31,约3.75°×3.75°)对全年温度的模拟能力均要稍好于中(f19,约1.9°×2.5°)、高(f09,约0.9°×1.25°)分辨率;各分辨率对中国降水的模拟能力远不如温度,除冬季外全年都出现的中部地区虚假降水并未因为模式分辨率提高而得到本质改善;对于东亚海平面气压场,低分辨率在冬季模拟能力相对最好,中等分辨率在夏季相对较好,而高分辨率的模拟能力均表现最差;低分辨率对850 hPa东亚冬季风和夏季风的模拟能力均要好于中、高分辨率,而两种较高分辨率的模拟能力则比较接近.总的来说,低分辨率CCSM4在东亚和中国气候模拟中表现出了较大优势,加之其计算代价小,适合进行需要较长时间积分的气候模拟研究.     

利用区域气候模式对我国南方百年气温和降水的动力降尺度模拟

本文采用NCAR的WRF3.5.1模式,以NOAA的20世纪再分析资料作为区域气候模式的初始场和侧边界场,对东亚地区进行了百年以上(1900~2010年)尺度、水平分辨率为50 km的动力降尺度数值模拟试验。通过与观测气候资料的对比,分析了驱动场(20世纪再分析资料)和区域气候模式对我国南方地区近50年(1961~2010年)气温和降水的气候平均态的模拟能力。结果表明:经过动力降尺度的区域气候模式试验结果能更好地模拟我国南方地区气温气候平均态和季节循环。WRF模式模拟的气温与观测的气温的空间相关系数均在0.97以上。年平均和夏季,WRF模式模拟的气温与观测的气温的偏差大多介于-1°C到+1°C之间。对于降水,WRF模式显著提高了我国南方降水的模拟能力。和驱动场相比,WRF模式模拟的降水与观测的偏差明显减小。夏季,WRF模式模拟的降水空间相关系数在0.5以上。由此延伸至对近百年我国南方地区三个子区域(华南地区、江淮地区和西南地区)四个时段(1914~1942年、1943~1971年、1972~2000年和2001~2010年)的分析,结果表明区域气候模式动力降尺度的结果在区域平均的气温和降水的模拟数值上与观测比较接近,夏季模拟能力有明显的提高,冬季存在气温模拟偏低的误差。对气温趋势分析表明,在20世纪40年代以后的两个时间段,区域气候模式明显提高了气温变化线性趋势的模拟性能。     

Seasonal evolution of subtropical anticyclones in the climate system model FGOALS-s2

The simulation characteristics of the seasonal evolution of subtropical anticyclones in the Northern Hemisphere are documented for the Flexible Global Ocean-Atmosphere-Land Systemmodel, Spectral Version 2 (FGOALS-s2), developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, the Institute of Atmospheric Physics. An understanding of the seasonal evolution of the subtropical anticyclones is also addressed. Compared with the global analysis established by the European Centre for Medium-Range Forecasts, the ERA-40 global reanalysis data, the general features of subtropical anticyclones and their evolution are simulated well in both winter and summer, while in spring a pronounced bias in the generation of the South Asia Anticyclone(SAA) exists. Its main deviation in geopotential height from the reanalysis is consistent with the bias of temperature in the troposphere. It is found that condensation heating (CO) plays a dominant role in the seasonal development of the SAA and the subtropical anticyclone over the western Pacific (SAWP) in the middle troposphere. The CO biases in the model account for the biases in the establishment of the SAA in spring and the weaker strength of the SAA and the SAWP from spring to summer. CO is persistently overestimated in the central-east tropical Pacific from winter to summer, while it is underestimated over the area from the South China Sea to the western Pacific from spring to summer. Such biases generate an illusive anticyclonic gyre in the upper troposphere above the middle Pacific and delay the generation of the SAA over South Asia in April. In midsummer, the simulated SAA is located farther north than in the ERA-40 data owing to excessively strong surface sensible heating (SE) to the north of the Tibetan Plateau. Whereas, the two surface subtropical anticyclones in the eastern oceans during spring to summer are controlled mainly by the surface SE over the two continents in the Northern Hemisphere, which are simulated reasonably well, albeit with their centers shifted westwards owing to the weaker longwave radiation cooling in the simulation associated with much weaker local stratiform cloud. Further improvements in the related parameterization of physical processes are therefore identified.     

Regional climate change experiments over southern South America. I: present climate

We present an analysis of a regional simulation of present-day climate (1981–1990) over southern South America. The regional model MM5 was nested within time-slice global atmospheric model experiments conducted by the HadAM3H model. We evaluate the capability of the model in simulating the observed climate with emphasis on low-level circulation patterns and surface variables, such as precipitation and surface air mean, maximum and minimum temperatures. The regional model performance was evaluated in terms of seasonal means, seasonal cycles, interannual variability and extreme events. Overall, the regional model is able to capture the main features of the observed mean surface climate over South America, its seasonal evolution and the regional detail due to topographic forcing. The observed regional patterns of surface air temperatures (mean, maxima and minima) are well reproduced. Biases are mostly within 3°C, temperature being overestimated over central Argentina and underestimated in mountainous regions during all seasons. Biases in northeastern Argentina and southeastern Brazil are positive during austral spring season and negative in other seasons. In general, maximum temperatures are better represented than minimum temperatures. Warm bias is larger during austral summer for maximum temperature and during austral winter for minimum temperature, mainly over central Argentina. The broad spatial pattern of precipitation and its seasonal evolution are well captured; however, the regional model overestimates the precipitation over the Andes region in all seasons and in southern Brazil during summer. Precipitation amounts are underestimated over the La Plata basin from fall to spring. Extremes of precipitation are better reproduced by the regional model compared with the driving model. Interannual variability is well reproduced too, but strongly regulated by boundary conditions, particularly during summer months. Overall, taking into account the quality of the simulation, we can conclude that the regional model is capable in reproducing the main regional patterns and seasonal cycle of surface variables. The present reference simulation constitutes the basis to examine the climate change simulations resulting from the A2 and B2 forcing scenarios which are being reported in a separate study.     

MM5 simulations of interannual change and the diurnal cycle of southern African regional climate

Summary Two cumulus convection and two planetary boundary layer schemes are used to investigate the climate of southern Africa using the MM5 regional climate model. Both a wet (1988/89) and a dry (1991/92) summer (December–February, DJF) rainfall season are simulated and the results compared with three different observational sources: Climate Research Unit seasonal data (precipitation, 2 m surface temperature, number of rain days), satellite-derived diurnal precipitation and the Surface Radiation Budget diurnal short-wave fluxes and optical depth. Using the ETA model boundary layer in MM5 simulates too much incident short-wave radiation at the surface at 12 UTC, whereas the medium range forecast model boundary layer yields a diurnal cycle of short-wave radiation closer to the observed. The Betts-Miller convection scheme in MM5 simulates peak rainfall later in the day and less rain days than observed, whereas when using the Kain-Fritsch convection scheme a peak rainfall earlier in the day and more rain days than observed are simulated. The intensity of the hydrological cycle is therefore dependent on the choice of convection scheme, which in turn is further modified by the boundary layer scheme. Precipitation during the wet 1988/89 season is reasonably captured by most simulations, though using the Betts-Miller scheme more accurately simulates rainfall during the dry 1991/92 season. Mean DJF biases in the surface temperature and diurnal temperature range are consistent with biases in the number of rain days and the diurnal cycles of surface moisture and energy.     

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.     

The Siberian High and climate change over middle to high latitude Asia

Summary The Siberian High is the most important atmospheric centre of action in Eurasia during the winter months. Here its variability and relationship with temperature and precipitation is investigated for the period 1922 to 2000. The pronounced weakening of the Siberian High during the last ∼ 20 years is its most remarkable feature. Mean temperature, averaged over middle to high latitude Asia (30° E–140° E, 30° N–70° N), is correlated with the Siberian High central intensity (SHCI) with correlation coefficient of − 0.58 (1922–1999), and for precipitation, the correlation coefficient is − 0.44 (1922–1998). Taking the Arctic Oscillation (AO), the SHCI, the Eurasian teleconnection pattern (EU), and the Southern Oscillation (SO) index into account, 72 percent of the variance in temperature can be explained for the period 1949–1997 (for precipitation the variance is 26 percent), with the AO alone explaining 30 percent of the variance, and the Siberian High contributing 24 percent. The precipitation variance explained by the Siberian High is only 9.8 percent of the total. Received January 2, 2001 Revised November 24, 2001     

Tropical cyclone genesis frequency over the western North Pacific simulated in medium-resolution coupled general circulation models

This study examines the tropical cyclone (TC) genesis frequency over the western North Pacific simulated in atmosphere–ocean coupled general circulation models from the World Climate Research Programme’s Coupled Model Intercomparison Project phase 3. We first evaluate performances of eight models with atmospheric horizontal resolution of T63 or T106 by analyzing their daily-mean atmospheric outputs of twentieth-century climate simulations available from the Program for Climate Model Diagnosis and Intercomparison database. The genesis frequency is validated against the best-track data issued by the Japan Meteorological Agency. Five of the eight models reproduce realistic horizontal distribution of the TC genesis with a large fraction over the 10°–20°N, 120°–150°E area. These five high-performance models also realistically simulate the summer–winter contrast of the frequency. However, detailed seasonal march is slightly unrealistic; four of the models overestimate the frequency in the early season (May–June) while all of them underestimate the frequency in the mature season (July–September). Reasons for these biases in the seasonal march for the five high-performance models are discussed using the TC genesis potential (GP) index proposed by Emanuel and Nolan (in Am Meteor Soc, pp 240–241, 2004). The simulated GP has seasonal biases consistent with those of the TC genesis frequency. For all five models, the seasonal biases in GP are consistent with those in environmental lower-tropospheric vorticity, vertical wind shear, and relative humidity, which can be attributed to the simulated behavior of monsoon trough. The observed trough migrates northward from the equatorial region to reach the 10°–20°N latitudinal band during the mature season and contributes to the TC frequency maximum, whereas the simulated trough migrates northward too rapidly and reaches this latitude band in the early season, leading to the overestimation of the TC genesis frequency. In the mature season, the simulated trough reaches as far as 15°–25°N, accompanied by a strong vertical shear south of the trough, providing an unfavorable condition for TC genesis. It is concluded that an adequate simulation of the monsoon trough behavior is essential for a better reproduction of the TC frequency seasonal march.