Impacts of the spectral nudging technique on simulation of the East Asian summer monsoon

This study assesses the performance of spectral nudging methodology in dynamical regional climate downscaling for summer climate over East Asia. The regional climate model NCAR-MM5v3 was used to dynamically downscale the 2.5-degree NCEP/NCAR reanalysis (NNRP) data onto 50-km regional grids. The main focus is the model’s simulation of precipitation. The NCEP/CPC precipitation analysis data were used as the verification. Boreal summers (June, July, and August) in 1991, 1998, and 2003 and heavy floods that occurred in Eastern China were selected for the study. Compared to the control runs (CTLs) without spectral nudging (SN), experiments with SNs greatly reduced systematic errors in upper-level large-scale circulations and were in better agreement with the NNRP. At the same time, SNs outperformed CTLs in simulating model variables near the surface. In comparison with observational precipitation data, spectral nudging also improved the model’s simulation of precipitation in spatial and temporal distributions. SN-simulated precipitation field patterns, including the spatial distribution of monthly mean precipitation band, the seasonal march of major precipitation bands, and the daily variability of regional-averaged time series, show much more consistency with observations than those of the CTL runs.     

Ability of an ensemble of regional climate models to reproduce weather regimes over Europe-Atlantic during the period 1961–2000

One of the main concerns in regional climate modeling is to which extent limited-area regional climate models (RCM) reproduce the large-scale atmospheric conditions of their driving general circulation model (GCM). In this work we investigate the ability of a multi-model ensemble of regional climate simulations to reproduce the large-scale weather regimes of the driving conditions. The ensemble consists of a set of 13 RCMs on a European domain, driven at their lateral boundaries by the ERA40 reanalysis for the time period 1961–2000. Two sets of experiments have been completed with horizontal resolutions of 50 and 25 km, respectively. The spectral nudging technique has been applied to one of the models within the ensemble. The RCMs reproduce the weather regimes behavior in terms of composite pattern, mean frequency of occurrence and persistence reasonably well. The models also simulate well the long-term trends and the inter-annual variability of the frequency of occurrence. However, there is a non-negligible spread among the models which is stronger in summer than in winter. This spread is due to two reasons: (1) we are dealing with different models and (2) each RCM produces an internal variability. As far as the day-to-day weather regime history is concerned, the ensemble shows large discrepancies. At daily time scale, the model spread has also a seasonal dependence, being stronger in summer than in winter. Results also show that the spectral nudging technique improves the model performance in reproducing the large-scale of the driving field. In addition, the impact of increasing the number of grid points has been addressed by comparing the 25 and 50 km experiments. We show that the horizontal resolution does not affect significantly the model performance for large-scale circulation.     

Evaluation of Precipitation Indices over North America from Various Configurations of Regional Climate Models

This study presents the evaluation of simulations from two new Canadian regional climate models (RCMs), CanRCM4 and CRCM5, with a focus on the models’ skill in simulating daily precipitation indices and the Standardized Precipitation Index (SPI). The evaluation was carried out over the past two decades using several sets of gridded observations that partially cover North America. The new Canadian RCMs were also compared with four reanalysis products and six other RCMs. The different configurations of the Canadian RCM simulations also permit evaluation of the impact of different spatial resolutions, atmospheric drivers, and nudging conditions. The results from the new Canadian models show some improvement in precipitation characteristics over the previous Canadian RCM (CRCM4), but these differ with the seasons. For winter, CanRCM4 and CRCM5 have better skill than most other models over all of North America. For the summer, CRCM5 0.44° performs best over the United States, while CRCM4 has the best skill over Canada. Good skill is exhibited by CanRCM4 and CRCM4 in simulating the 6-month SPI over the Prairies and the western US Corn Belt. In general, differences are small between runs with or without large-scale spectral nudging; differences are small when different boundary conditions are used.     

Regional climate simulations over South America: sensitivity to model physics and to the treatment of lateral boundary conditions using the MM5 model

In this study the capability of the MM5 model in simulating the main mode of intraseasonal variability during the warm season over South America is evaluated through a series of sensitivity experiments. Several 3-month simulations nested into ERA40 reanalysis were carried out using different cumulus schemes and planetary boundary layer schemes in an attempt to define the optimal combination of physical parameterizations for simulating alternating wet and dry conditions over La Plata Basin (LPB) and the South Atlantic Convergence Zone regions, respectively. The results were compared with different observational datasets and model evaluation was performed taking into account the spatial distribution of monthly precipitation and daily statistics of precipitation over the target regions. Though every experiment was able to capture the contrasting behavior of the precipitation during the simulated period, precipitation was largely underestimated particularly over the LPB region, mainly due to a misrepresentation in the moisture flux convergence. Experiments using grid nudging of the winds above the planetary boundary layer showed a better performance compared with those in which no constrains were imposed to the regional circulation within the model domain. Overall, no single experiment was found to perform the best over the entire domain and during the two contrasting months. The experiment that outperforms depends on the area of interest, being the simulation using the Grell (Kain–Fritsch) cumulus scheme in combination with the MRF planetary boundary layer scheme more adequate for subtropical (tropical) latitudes. The ensemble of the sensitivity experiments showed a better performance compared with any individual experiment.     

Impact of spectral nudging and domain size in studies of RCM response to parameter modification

The paper aims at finding an RCM configuration that facilitates studies devoted to quantifying RCM response to parameter modification. When using short integration times, the response of the time-averaged variables to RCM modification tend to be blurred by the noise originating in the lack of predictability of the instantaneous atmospheric states. Two ways of enhancing the signal-to-noise ratio are studied in this work: spectral nudging and reduction of the computational domain size. The approach followed consists in the analysis of the sensitivity of RCM-simulated seasonal averages to perturbations of two parameters controlling deep convection and stratiform condensation, perturbed one at a time. Sensitivity is analyzed within different simulation configurations obtained by varying domain size and using the spectral nudging option. For each combination of these factors multiple members of identical simulations that differ exclusively in initial conditions are also generated to provide robust estimates of the sensitivities (the signal) and sample the noise. Results show that the noise magnitude is decreased both by reduction of domain size and the spectral nudging. However, the reduction of domain size alters some sensitivity signals. When spectral nudging is used significant alterations of the signal are not found.     

Can ensembles of regional climate model simulations improve results from sensitivity studies?

Intrinsic variability (IV) in regional climate models (RCMs) is often assumed to be small because at climatological timescales, the model solutions tend to be dominated by the model??s lateral boundary conditions. Recent studies have indicated that this IV may actually be large in certain instances for some variables. Direct interpretation of anomalies from RCM sensitivity studies relies on the assumption that differences between model simulations are entirely due to a physical forcing. However, if IV is as large or larger than the physical signal, then this assumption is violated. Using a 20 member ensemble of RCM simulations, we verify that IV of precipitation within a RCM can be large enough to violate the sensitivity study assumption, and we show that generating ensembles of simulations can help reduce the level of IV. We also present two indicators that can rule out the influence of IV when it is ambiguous whether anomalies within a sensitivity study are due to the sensitivity perturbation or whether they are due to IV.     

不同区域海温异常对中国夏季旱涝影响的诊断研究和预测试验

利用季降水异常的典型集合相关预测模式, 研究了前期和同期不同季节全球海表温度距平场与中国夏季旱涝的遥相关分布特征以及这种相关型随季节的变化, 揭示了全球海温的异常变化在中国夏季旱涝中的信号特征.研究表明, 全球不同区域海温对我国夏季降水的影响存在着明显的季节差异.全球特定的海温分布可以作为中国夏季旱涝预报的信号因子.选取不同区域及不同时段的海温场作为因子场分别对1998、 1999年这两个典型年份的我国夏季降水进行了诊断研究和预测试验, 并通过不同区域海温的影响权重做集成预测.试验结果表明:不同区域海温的集成预测不仅可以有效地提高预测的准确性, 而且可以揭示不同时段不同区域海温的异常变化在夏季旱涝中的强信号现象.     

Evaluation of the regional climate model ALADIN to simulate the climate over North America in the CORDEX framework

In this study, an ensemble of four multi-year climate simulations is performed with the regional climate model ALADIN to evaluate its ability to simulate the climate over North America in the CORDEX framework. The simulations differ in their driving fields (ERA-40 or ERA-Interim) and the nudging technique (with or without large-scale nudging). The validation of the simulated 2-m temperature and precipitation with observationally-based gridded data sets shows that ALADIN performs similarly to other regional climate models that are commonly used over North America. Large-scale nudging improves the temporal correlation of the atmospheric circulation between ALADIN and its driving field, and also reduces the warm and dry summer biases in central North America. The differences between the simulations driven with different reanalyses are small and are likely related to the regional climate model’s induced internal variability. In general, the impact of different driving fields on ALADIN is smaller than that of large-scale nudging. The analysis of the multi-year simulations over the prairie and the east taiga indicates that the ALADIN 2-m temperature and precipitation interannual variability is similar or larger than that observed. Finally, a comparison of the simulations with observations for the summer 1993 shows that ALADIN underestimates the flood in central North America mainly due to its systematic dry bias in this region. Overall, the results indicate that ALADIN can produce a valuable contribution to CORDEX over North America.     

Nudging方法对中国西北强降水过程的模拟试验研究

通过在WRF(Weather Research and Forecasting)模式中运用松弛逼近方法(Nudging)同化NCEP-FNL资料,对中国西北地区夏季3次对流降水过程进行了模拟试验,检验了模式运用谱逼近(Spectral Nudging,SN)和格点逼近(Grid Nudging,GN)方案后对研究区域内降水过程的模拟性能。结果表明:SN和GN试验相对于控制试验,模拟的降水结果更接近于站点观测。在降水落区和量级的模拟效果上都有显著提高,且SN试验所得结果优于GN试验。通过分析两个同化试验在降水时段的基本要素场(湿度、温度和风速)变化,在近地面层,GN试验模拟的风速和温度较SN试验更接近观测;但700 hPa上,SN试验中风速、风向、温度、湿度的增量场变化及分布同降水的模拟结果存在较好的对应关系。最后,从物理诊断量—水汽通量散度的空间垂直变化来看,SN试验中600 hPa和700 hPa的水汽通量散度的正负分布有效调节降水的空间分布,更逼近观测。因此700 hPa的物理量场变量增量是降水模拟效果改善的主要原因之一。     

A multi-physics ensemble of present-day climate regional simulations over the Iberian Peninsula

This work assesses the influence of the model physics in present-day regional climate simulations. It is based on a multi-phyiscs ensemble of 30-year long MM5 hindcasted simulations performed over a complex and climatically heterogeneous domain as the Iberian Peninsula. The ensemble consists of eight members that results from combining different parametrization schemes for modeling the Planetary Boundary Layer, the cumulus and the microphysics processes. The analysis is made at the seasonal time scale and focuses on mean values and interannual variability of temperature and precipitation. The objectives are (1) to evaluate and characterize differences among the simulations attributable to changes in the physical options of the regional model, and (2) to identify the most suitable parametrization schemes and understand the underlying mechanisms causing that some schemes perform better than others. The results confirm the paramount importance of the model physics, showing that the spread among the various simulations is of comparable magnitude to the spread obtained in similar multi-model ensembles. This suggests that most of the spread obtained in multi-model ensembles could be attributable to the different physical configurations employed in the various models. Second, we obtain that no single ensemble member outperforms the others in every situation. Nevertheless, some particular schemes display a better performance. On the one hand, the non-local MRF PBL scheme reduces the cold bias of the simulations throughout the year compared to the local Eta model. The reason is that the former simulates deeper mixing layers. On the other hand, the Grell parametrization scheme for cumulus produces smaller amount of precipitation in the summer season compared to the more complex Kain-Fritsch scheme by reducing the overestimation in the simulated frequency of the convective precipitation events. Consequently, the interannual variability of precipitation (temperature) diminishes (increases), which implies a better agreement with the observations in both cases. Although these features improve in general the accuracy of the simulations, controversial nuances are also highlighted.     

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).     

Atmospheric and terrestrial water budgets: sensitivity and performance of configurations and global driving data for long term continental scale WRF simulations

Driving data and physical parametrizations can significantly impact the performance of regional dynamical atmospheric models in reproducing hydrometeorologically relevant variables. Our study addresses the water budget sensitivity of the Weather Research and Forecasting Model System WRF (WRF-ARW) with respect to two cumulus parametrizations (Kain–Fritsch, Betts–Miller–Janji?), two global driving reanalyses (ECMWF ERA-INTERIM and NCAR/NCEP NNRP), time variant and invariant sea surface temperature and optional gridded nudging. The skill of global and downscaled models is evaluated against different gridded observations for precipitation, 2 m-temperature, evapotranspiration, and against measured discharge time-series on a monthly basis. Multi-year spatial deviation patterns and basin aggregated time series are examined for four globally distributed regions with different climatic characteristics: Siberia, Northern and Western Africa, the Central Australian Plane, and the Amazonian tropics. The simulations cover the period from 2003 to 2006 with a horizontal mesh of 30 km. The results suggest a high sensitivity of the physical parametrizations and the driving data on the water budgets of the regional atmospheric simulations. While the global reanalyses tend to underestimate 2 m-temperature by 0.2–2 K, the regional simulations are typically 0.5–3 K warmer than observed. Many configurations show difficulties in reproducing the water budget terms, e.g. with long-term mean precipitation biases of 150 mm month^?1 and higher. Nevertheless, with the water budget analysis viable setups can be deduced for all four study regions.     

南海夏季风爆发的数值模拟

利用高分辨率的区域气候模式 (RegCM_NCC) 对南海夏季风爆发进行模拟研究。研究表明:该模式对积云对流参数化方案的选择十分敏感, 其中以Kuo积云参数化方案为最好, 可以比较成功地模拟出南海夏季风的爆发时间、爆发前后高、低层风场的剧烈变化以及季风与季风雨带的向北推进。然而该方案对于雨量和副热带高压位置的模拟, 与观测相比尚存在一定的偏差, 主要表现为副热带高压位置模拟偏北、偏东; 南海地区的降水量模拟偏少、降水范围偏小。此外, 采用4种参数化方案 (Kuo, Grell, MFS, Betts-Miller) 集成的结果在某种程度上要优于单个方案的结果, 这种改善主要体现在对南海地区季风爆发后降水的模拟上。     

Regional climate modelling of the 2006 West African monsoon: sensitivity to convection and planetary boundary layer parameterisation using WRF

Regional climate model (RCM) is a valuable scientific tool to address the mechanisms of regional atmospheric systems such as the West African monsoon (WAM). This study aims to improve our understanding of the impact of some physical schemes of RCM on the WAM representation. The weather research and forecasting model has been used by performing six simulations of the 2006 summer WAM season. These simulations use all combinations of three convective parameterization schemes (CPSs) and two planetary boundary layer schemes (PBLSs). By comparing the simulations to a large set of observations and analysis products, we have evaluated the ability of these RCM parameterizations to reproduce different aspects of the regional atmospheric circulation of the WAM. This study focuses in particular on the WAM onset and the rainfall variability simulated over this domain. According to the different parameterizations tested, the PBLSs seem to have the strongest effect on temperature, humidity vertical distribution and rainfall amount. On the other hand, dynamics and precipitation variability are strongly influenced by CPSs. In particular, the Mellor?CYamada?CJanjic PBLS attributes more realistic values of humidity and temperature. Combined with the Kain?CFritsch CPS, the WAM onset is well represented. The different schemes combination tested also reveal the role of different regional climate features on WAM dynamics, namely the low level circulation, the land?Catmosphere interactions and the meridional temperature gradient between the Guinean coast and the Sahel.     

EVALUATION OF THE PARAMETERIZATION SCHEMES AND NUDGING TECHNIQUES IN GRAPES FOR WARM SECTOR TORRENTIAL RAINS USING SURFACE OBSERVATIONS

Sensitivities of parameterization schemes were conducted based on the Global/Regional Assimilation and Prediction System (GRAPES) model. Surface observations were used to evaluate the simulations and to improve the model’s ability to simulate the extreme precipitation over southern China on 20 July 2016. The results showed that GRAPES captured the large-scale precipitation over southern China but failed to predict the extreme precipitation over Xinyi. The model showed a systematic cold biases by adopting different parameterization schemes. In particular, the ECMWF analyses data showed a strong cold bias over Guangdong province and Guangxi Region. Observational nudging results showed that the surface temperature could largely help to alleviate the cold bias. The alleviation in the warm sector accounted for main improvement by the nudging scheme, and the RMSE was reduced by 1.56 degree from 3.25 degree to 1.69 degree by 1-h simulation and with 1.3 degree alleviation by 2-h simulation. Sensitivities using different parameterizations and the nudging scheme showed that the model’s underestimation of the precipitation was still present despite improvements in the predictions of surface temperature.     

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.     

A simple soil moisture scheme for regional climate simulations in the tropics

Summary A regional climate model (RCM) is described which incorporates an improved scheme for soil moisture availability (SMA) compared to an earlier version. The improvement introduces a sensitivity of SMA to soil type, vegetation cover and ground albedo, making the model more adaptable to divers regions. In addition, the interactive SMA depends on past precipitation, ground temperature and terrain relief. Six RCM simulations of the monthly mean climate over southern Africa are performed at 0.5° grid spacing. Improvements in the RCM climate simulations compared to control runs are attributed to the newer SMA scheme. Only a slight improvement in skill results from driving the RCM with observational analyses as opposed to GCM “predicted” lateral boundary conditions. The high spatial resolution of the RCM provides a distinct advantage in the simulated spatial distribution of precipitation compared with a global model run at an effective grid spacing of 2.8°. The mesoscale precipitation signal in the RCM simulations is more dominant during the rather dry December 1982 than during December 1988. The improved SMA scheme contributed to a realistic partition between latent and sensible heat fluxes at the ground-atmosphere boundary and consequently a realistic diurnal cycle of ground temperature. Simulated differences in the spatial distribution of rainfall between December 1982 and December 1988 are more realistic with the improved scheme. Received June 28, 2001 Revised August 27, 2001     

A study on large-scale nudging effects in regional climate model simulation

The large-scale nudging effects on the East Asian summer monsoon (EASM) are examined using the National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM). The NCEP/DOE reanalysis data is used to provide large-scale forcings for RSM simulations, configured with an approximately 50-km grid over East Asia, centered on the Korean peninsula. The RSM with a variant of spectral nudging, that is, the scale selective bias correction (SSBC), is forced by perfect boundary conditions during the summers (June–July–August) from 1979 to 2004. The two summers of 2000 and 2004 are investigated to demonstrate the impact of SSBC on precipitation in detail. It is found that the effect of SSBC on the simulated seasonal precipitation is in general neutral without a discernible advantage. Although errors in large-scale circulation for both 2000 and 2004 are reduced by using the SSBC method, the impact on simulated precipitation is found to be negative in 2000 and positive in 2004 summers. One possible reason for a different effect is that precipitation in the summer of 2004 is characterized by a strong baroclinicity, while precipitation in 2000 is caused by thermodynamic instability. The reduction of convective rainfall over the oceans by the application of the SSBC method seems to play an important role in modeled atmosphere.     

区域和全球模式的嵌套技术 及其长期积分试验

将区域模式嵌入澳大利亚CSIRO (Commonwealth Scientific and Industrial Research Organization）的全球模式中,并将其应用于区域模式的长期气候积分试验。模拟结果表明,当区域与全球模式嵌套时,边界吸收问题十分重要,由区域模式得到的高分辨率大尺度环流形式在边界上必须与全球模式提供的强迫一致,同时区域模式必须给出基于模式内部物理过程产生的高分辨信息。因此,在嵌套过程中,必须仔细考虑缓冲区的设置,使大尺度强迫与中尺度特征充分混合,既保持区域模式内外的一致性,又使区域内部中尺度强迫物理过程得到充分发展。将区域模式与澳大利亚CSIRO的9层21波三角形截断谱模式嵌套后,完成了连续3年的区域气候模式积分。模拟结果表明,由于区域模式较好地刻划了区域尺度的地形、下垫面和海岸线分布等的细节特征,模拟的区域气候特征比全球模式有较大的改进,尤其是对季风降水的模拟,区域模式明显改进了全球模式的模拟结果。     

Assessment of CORDEX-SA experiments in representing precipitation climatology of summer monsoon over India

The present work assesses the performance of 11 regional climate simulations in representing the precipitation patterns of summer monsoon over India for the period 1970–2005. These simulations have been carried out under Coordinated Regional Climate Downscaling Experiment–South Asia (CORDEX-SA) project. The regional climate models (RCMs) have been inter-compared as well as evaluated against the observation to identify the common weaknesses and differences between them. For this, a number of statistical analysis has been carried out to compare the model precipitation field with the corresponding observation. Model uncertainty has been also evaluated through bias studies and analysis of the spread in the ensemble mean (hereafter, ensemble). The models which perform better than the rest are identified and studied to look for any improvement in the ensemble performance. These better performing experiments (best RCM experiments) are further assessed over the monsoon core region (MCR) of India. This has been done to understand how well the models perform in a spatially homogeneous zone of precipitation which is considered to be a representative region of Indian summer monsoon characteristics. Finally, an additional analysis has been done to quantify the skill of models based on two different metrics—performance and convergence including a combination of the two. The experiment with regional model RegCM4 forced with the global model GFDL-ESM2M shows the highest combined mean skill in capturing the seasonal mean precipitation. In general, a significant dry bias is found over a larger part of India in all the experiments which seems most pronounced over the central Indian region. Ensemble on an average tends to outperform many of the individual experiments with bias of smaller magnitude and an improved spatial correlation compared with the observation. Experiments which perform better over India improve the results but only slightly in terms of agreement among experiments and bias.