Sensitivity to domain size of mid-latitude summer simulations with a regional climate model

The issue of Regional Climate Model (RCM) domain size is studied here by using a perfect-model approach, also known as the Big-Brother experiment. It is known that the control exerted by the lateral boundary conditions (LBC) on nested simulations increases when reducing the domain size. The large-scale component of the simulation that is forced by the LBC influences the small-scale features that develop along the large-scale flow. Small-scale transient eddies need space and time to develop sufficiently however, and small domains can impede their development. Our tests performed over eastern North America in summer reveal that the small-scale features are systematically underestimated over the entire domain, even for domain as large as 140 by 140 grid points. This result differs from that obtained in winter where the small scales were mainly underestimated on the west (inflow) side of the domain. This difference is due to the circulation regime over Eastern Canada, which is characterized by weak and variable flow in summer, but strong and westerly flow in winter. For both seasons, the small-scale transient-eddy amplitudes are systematically underestimated at higher levels, but this problem is less severe in summer. Overall the model is more skilful in regenerating the small scales in summer than in winter for comparable domain sizes, which can be related to the weaker summer flow and stronger physical processes occurring in this season.     

Simulation of Indian summer monsoon: experiments with SSTs

Summary Hindcasts for the Indian summer monsoons (ISMs) of 2002 and 2003 have been produced from an ensemble of numerical simulations performed with a global model by changing SST. Two sets of ensemble simulations have been produced without vegetation: (i) by prescribing the weekly observed SST from ECMWF (European Centre for Medium Range Weather Forecasting) analyses, and (ii) by adding weekly SST anomalies (SSTA) of April to the climatological SST during the simulation period from May to August. For each ensemble, 10 simulations have been realized with different initial conditions that are prepared from ECMWF data with five each from April and May analyses of both the years. The predicted June–July monsoon rainfall over the Indian region shows good agreement with the GPCP (observed) pentad rainfall distribution when 5 member ensemble is taken from May initial conditions. The All-India June–July simulated rainfall time series matches favourably with the observed time series in both the years for the five member ensemble from May initial condition but drifts away from observation with April initial conditions. This underscores the role of initial conditions in the seasonal forecasting. But the model has failed to capture the strong intra-seasonal oscillation in July 2002. Heating over equatorial Indian Ocean for June 2002 in a particular experiment using 29th May 12 GMT as initial conditions shows some intra-seasonal oscillation in July 2002 rainfall, as in observation. Further evaluation of the seasonal simulations from this model is done by calculating the empirical orthogonal functions (EOFs) of the GPCP rainfall over India. The first four EOFs explain more than 80% of the total variance of the observed rainfall. The time series of expansion coefficients (principal components), obtained by projecting on the observed EOFs, provide a better framework for inter-comparing model simulations and their evaluation with observed data. The main finding of this study is that the All-India rainfall from various experiments with prescribed SST is better predicted on seasonal scale as compares to prescribed SST anomalies. This is indicative of a possible useful seasonal forecasts from a GCM at least for the case when monsoon is going to be good. The model responses do not differ much for 2002 and 2003 since the evolution of SST during these years was very similar, hence July rainfall seems to be largely modulated by the other feedbacks on the overall circulation.     

Probabilistic prediction of Indian summer monsoon rainfall using global climate models

Probabilistic seasonal predictions of rainfall that incorporate proper uncertainties are essential for climate risk management. In this study, three different multi-model ensemble (MME) approaches are used to generate probabilistic seasonal hindcasts of the Indian summer monsoon rainfall based on a set of eight global climate models for the 1982–2009 period. The three MME approaches differ in their calculation of spread of the forecast distribution, treated as a Gaussian, while all three use the simple multi-model subdivision average to define the mean of the forecast distribution. The first two approaches use the within-ensemble spread and error residuals of ensemble mean hindcasts, respectively, to compute the variance of the forecast distribution. The third approach makes use of the correlation between the ensemble mean hindcasts and the observations to define the spread using a signal-to-noise ratio. Hindcasts are verified against high-resolution gridded rainfall data from India Meteorological Department in terms of meteorological subdivision spatial averages. The use of correlation for calculating the spread provides better skill than the other two methods in terms of rank probability skill score. In order to further improve the skill, an additional method has been used to generate multi-model probabilistic predictions based on simple averaging of tercile category probabilities from individual models. It is also noted that when such a method is used, skill of probabilistic forecasts is improved as compared with using the multi-model ensemble mean to define the mean of the forecast distribution and then probabilities are estimated. However, skill of the probabilistic predictions of the Indian monsoon rainfall is too low.     

Simulation of monsoon boundary-layer processes using a regional scale nested grid model

A nested grid regional model with a high vertical resolution in the atmospheric boundary layer is used to simulate various atmospheric processes during an active monsoon period. A turbulence kinetic energy closure scheme is used to predict the boundary-layer structure. Model predictions indicate different structures of the boundary layer over land and oceans, as observed. Significant diurnal variation in boundary-layer structure and associated processes is predicted over land and negligible variations over oceans. The Somali jet over the Arabian Sea is well predicted. Location of the predicted monsoon depression and the associated rainfall are in good agreement with the observations. Also, predicted rainfall and its spatial distribution along the west coast of India are in good agreement with the observations.     

嵌套域大小对区域气候模式模拟效果的影响

This paper presents a numerical study on the 1998 summer rainfall over the Yangtze River valley in central and eastern China, addressing effect of a nested area size on simulations in terms of the technique of nesting a regional climate model (RCM) upon a general circulation model (GCM). Evidence suggests that the size exerts greater impacts upon regional climate of the country, revealing that a larger nested size is su perior to a small one for simulation in mitigating errors of GCM-provided lateral boundary forcing. Also,simulations show that the RCM should incorporate regions of climate systems of great importance into study and a low-resolution GCM yields more pronounced errors as a rule when used in the research of the Tibetan Plateau, and, in contrast, our PσRCM can do a good job in describing the plateau′s role in a more realistic and accurate way. It is for this reason that the tableland should be included in the nested area when the RCM is employed to investigate the regional climate. Our PσRCM nesting upon a GCM reaches morerealistic results compared to a single GCM used.     

Assessing the effect of domain size over the Caribbean region using the PRECIS regional climate model

This study investigates the sensitivity of the one-way nested PRECIS regional climate model (RCM) to domain size for the Caribbean region. Simulated regional rainfall patterns from experiments using three domains with horizontal resolution of 50 km are compared with ERA reanalysis and observed datasets to determine if there is an optimal RCM configuration with respect to domain size and the ability to reproduce important observed climate features in the Caribbean. Results are presented for the early wet season (May–July) and late wet season (August–October). There is a relative insensitivity to domain size for simulating some important features of the regional circulation and key rainfall characteristics e.g. the Caribbean low level jet and the mid summer drought (MSD). The downscaled precipitation has a systematically negative precipitation bias, even when the domain was extended to the African coast to better represent circulation associated with easterly waves and tropical cyclones. The implications for optimizing modelling efforts within resource-limited regions like the Caribbean are discussed especially in the context of the region’s participation in global initiatives such as CORDEX.     

New regression model for Indian summer monsoon rainfall

Summary Based on the study of 45 years (1948–1992) data, the average lowest MSL pressure of heat low over central Pakistan and adjoining northwest India of the month of May is found to have potential as a parameter for predicting all India Summer monsoon seasonal rainfall. This new parameter is seen to have stable and significant correlation with monsoon rainfall. Its correlation coefficients for different periods are found significant at 0.1% to 1% level of significance. The stability of the correlation coefficients was tested using 10, 20 and 30 year sliding windows. This test revealed that it is the most dependable parameter in comparison with 7 of the well known parameters analysed in this study. Regression models have been developed considering this new parameter along with other circulation parameters. The regression models developed are seen to perform very well for the independent data. The Root Mean Square Error (RMSE) values of some of these models, for independent data, are smaller than those of similar regression models reported in literature.With 8 Figures     

Uncertainties in the regional climate models simulations of South-Asian summer monsoon and climate change

The uncertainties in the regional climate models (RCMs) are evaluated by analyzing the driving global data of ERA40 reanalysis and ECHAM5 general circulation models, and the downscaled data of two RCMs (RegCM4 and PRECIS) over South-Asia for the present day simulation (1971–2000) of South-Asian summer monsoon. The differences between the observational datasets over South-Asia are also analyzed. The spatial and the quantitative analysis over the selected climatic regions of South-Asia for the mean climate and the inter-annual variability of temperature, precipitation and circulation show that the RCMs have systematic biases which are independent from different driving datasets and seems to come from the physics parameterization of the RCMs. The spatial gradients and topographically-induced structure of climate are generally captured and simulated values are within a few degrees of the observed values. The biases in the RCMs are not consistent with the biases in the driving fields and the models show similar spatial patterns after downscaling different global datasets. The annual cycle of temperature and rainfall is well simulated by the RCMs, however the RCMs are not able to capture the inter-annual variability. ECHAM5 is also downscaled for the future (2071–2100) climate under A1B emission scenario. The climate change signal is consistent between ECHAM5 and RCMs. There is warming over all the regions of South-Asia associated with increasing greenhouse gas concentrations and the increase in summer mean surface air temperature by the end of the century ranges from 2.5 to 5 °C, with maximum warming over north western parts of the domain and 30 % increase in rainfall over north eastern India, Bangladesh and Myanmar.     

Simulation of Indian summer monsoon intraseasonal oscillations in a superparameterized coupled climate model: need to improve the embedded cloud resolving model

The characteristic features of Indian summer monsoon (ISM) and monsoon intraseasonal oscillations (MISO) are analyzed in the 25 year simulation by the superparameterized Community Climate System Model (SP-CCSM). The observations indicate the low frequency oscillation with a period of 30–60 day to have the highest power with a dominant northward propagation, while the faster mode of MISO with a period of 10–20 day shows a stationary pattern with no northward propagation. SP-CCSM simulates two dominant quasi-periodic oscillations with periods 15–30 day and 40–70 day indicating a systematic low frequency bias in simulating the observed modes. Further, contrary to the observation, the SP-CCSM 15–30 day mode has a significant northward propagation; while the 40–70 day mode does not show prominent northward propagation. The inability of the SP-CCSM to reproduce the observed modes correctly is shown to be linked with inability of the cloud resolving model (CRM) to reproduce the characteristic heating associated with the barotropic and baroclinic vertical structures of the high-frequency and the low-frequency modes. It appears that the superparameterization in the General Circulation Model (GCM) certainly improves seasonal mean model bias significantly. There is a need to improve the CRM through which the barotropic and baroclinic modes are simulated with proper space and time distribution.     

谱逼近方法在东亚夏季降水区域模式模拟中的适用性研究:区域大小和位置的影响

利用区域气候模式 MM5V3 对1991、1998和2003年的东亚夏季降水进行了模拟.首先通过6个嵌套区域大小、位置的敏感性试验,研究了区域气候模式在东亚地区的模拟对嵌套区域的敏感性.在此基础上研究了谱逼近方案对降低此敏感性的作用.结果表明:(1)区域气候模式MM5V3能够基本模拟出东亚夏季极端降水的分布特征和强度变...     

Impact of domain size on the simulation of Indian summer monsoon in RegCM4 using mixed convection scheme and driven by HadGEM2

In this study, a smaller domain over India alone and a larger South Asia (SA) domain have been used in the Regional Climate Model version 4.2 (RegCM4.2) to examine the effect of the domain size on the Indian summer monsoon simulations. These simulations were carried out over a period of 36 years at 50 km horizontal resolution with the lateral boundary forcings of the UK Met Office Hadley Centre Global Circulation Model Version 2.0. Results show that the Indian summer monsoon rainfall is significantly reduced when the domain size for the model integration is reduced from SA to the Indian domain. In case of SA domain simulation, the Equitable Threat Scores have higher values in case of very light, light and moderate rainfall events than those in case of the Indian domain simulation. It is also found that the domain size of model integration has dominant impact on the simulated convective precipitation. The cross-equatorial flow and the Somali Jet are better represented in the SA simulation than those in the Indian domain simulation. The vertically integrated moisture flux over the Arabian Sea in the SA domain simulation is close to that in the NCEP/NCAR reanalysis while it is underestimated in the Indian domain simulation. It is important to note that when RegCM4.2 is integrated over the smaller Indian domain, the effects of the Himalayas and the moisture advection from the Indian seas are not properly represented in the model simulation and hence the monsoon circulation and associated rainfall are underestimated over India.     

RSM模式对中国东部夏季降水模拟能力的检验

本文利用美国国家环境预报中心NCEP(National Centers for Environmental Prediction)区域谱模式RSM(Regional Spectral Model)对中国东部地区夏季降水进行了为期20 a(1984—2003年)、水平分辨率为30 km的高精度模拟,并对模拟所得降水的气候态、年际变率、逐日变化以及极端事件进行了检验,和对造成降水偏差的大气环流特征进行了分析。结果表明RSM模拟所得夏季降水的空间分布、时间变率,以及降水量值都与实况相近,也基本可以再现夏季降水的年际变率分布情况,但是模拟所得的雨带存在偏南且偏弱的特点。对于逐日降水特征,RSM模拟所得季节内逐日降水变化与实况的走势基本一致,再现了夏季降水主要集中于东部和南部的特点,模拟出了江淮地区6月日降水区随时间北抬的特点。对于极端事件,模拟和实测的夏季不同雨强的天数分布对比表明模拟与实况基本接近,但是模拟的降水日大值中心较实况偏北;极端降水指数的计算结果也表明RSM模拟的极端降水情况与实况基本一致。综上,RSM模式对中国东部地区降水有着较好的模拟能力,可以用于中国东部地区的夏季降水气候特征研究。     

A study on the role of land-atmosphere coupling on the south Asian monsoon climate variability using a regional climate model

The spatial and temporal trends of 11 (7) temperature (precipitation) extreme indices are examined for the Loess Plateau Region (LPR) and its southeast and northwest sub-regions based on daily observations at 214 meteorological stations. Results show widespread significant warming trends for all the temperature extremes except for the diurnal temperature range (DTR) and the lowest daily maximum temperature in each year (TXn) during 1961–2010. When regionally averaged, a significant warming trend is detected for all the indices except for DTR and TXn in the past 50 years. Compared with the entire LPR, a significant warming trend is detected for all the indices except for DTR and TXn over the southeast sub-region of LPR; while it is observed for all the indices over the northwest. The trends for these indices are generally stronger in the northwest than in the southeast in the past 50 years. In contrast, for precipitation indices, only a small percentage of areas show significant drying or wetting trends and, when regionally averaged, none of them displays significant trends during the past 50 years. On the sub-regional scale, however, a larger percentage of areas show significant drying trends for precipitation indices generally over the southeast relative to the entire LPR, and noticeably, the sub-regional average heavy precipitation (R10mm) and wet day precipitation (PRCPTOT) display significant decreasing trends during the past 50 years; whereas only a slightly larger percentage of areas show significant wetting trends for these indices over the northwest compared with the entire LPR, and when sub-regionally averaged, none of the indices have significant trends during the past 50 years.