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.     

On the added value of regional climate modeling in climate change assessment

Regional climate models represent a promising tool to assess the regional dimension of future climate change and are widely used in climate impact research. While the added value of regional climate models has been highlighted with respect to a better representation of land-surface interactions and atmospheric processes, it is still unclear whether radiative heating implies predictability down to the typical scale of a regional climate model. As a quantitative assessment, we apply an optimal statistical filter to compare the coherence between observed and simulated patterns of Mediterranean climate change from a global and a regional climate model. It is found that the regional climate model has indeed an added value in the detection of regional climate change, contrary to former assumptions. The optimal filter may also serve as a weighting factor in multi-model averaging.     

The roles of bias-correction and resolution in regional climate simulations of summer extremes

Climate Dynamics - The suitability of dynamical downscaling in producing high-resolution climate scenarios for impact assessments is limited by the quality of the driving data and regional climate...     

Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is under-estimated (over-estimated) over wet (dry) regions of southern Africa.     

Tropical-temperate interactions over southern Africa simulated by a regional climate model

The Weather Research and Forecasting model (WRF) forced by ERA40 re-analyses, is used to examine, at regional scale, the role of key features of the local atmospheric circulation on the origin and development of Tropical Temperate Troughs (TTTs) representing a major contribution to South African rainfall during austral summer. A cluster analysis applied on 1971–2000 ERA40 and WRF simulated daily outgoing longwave radiation reveals for the November–February season three coherent regimes characteristic of TTTs over the region. Analyses of WRF simulated TTTs suggest that their occurrence is primarily linked with mid-latitude westerly waves and their phasing. Ensemble experiments designed for the case of austral summer 1996/1997 allow to examine the reproducibility of TTT events. The results obtained illustrate the importance of westerly waves phasing regarding the persistence of rain-producing continental TTT events. Moreover, oceanic surface conditions prevailing over the Agulhas current regions of the South West Indian Ocean (SWIO) are also found to influence TTT persistence for regional experiments with an oceanic mixed layer, warmer sea surface temperatures being associated with increased moisture advection from the SWIO where latent heat release is enhanced, favoring baroclinic instability and thus sustaining convection activity locally.     

Potential increase of flood hazards in Korea due to global warming from a high-resolution regional climate simulation

Because of the importance of the changes in the hydrologic cycle, accurate assessment of precipitation characteristics is essential to understand the impact of climate change due to global warming. This study investigates the changes in extreme precipitation with sub-daily and daily temporal scales. For a fine-scale climate change projection focusing on the Korean peninsula (20 km), we performed the dynamical downscaling of the global climate scenario covering the period 1971?C2100 (130-year) simulated by the Max-Planck-Institute global climate model, ECHAM5, using the latest version of the International Centre for Theoretical Physics (ICTP) regional climate model, RegCM3. While annual mean precipitation exhibits a pronounced interannual and interdecadal variability, with the increasing or decreasing trend repeated during a certain period, extreme precipitation with sub-daily and daily temporal scales estimated from the generalized extreme value distribution shows consistently increasing pattern. The return period of extreme precipitation is significantly reduced despite the decreased annual mean precipitation at the end of 21^st century. The decreased relatively weak precipitation is responsible for the decreased total precipitation, so that the decreased total precipitation does not necessarily mean less heavy precipitation. Climate change projection based on the ECHAM5-RegCM3 model chain clearly shows the effect of global warming in increasing the intensity and frequency of extreme precipitation, even without significantly increased total precipitation, which implies an increased risk for flood hazards.     

Potential for added value in temperature simulated by high-resolution nested RCMs in present climate and in the climate change signal

Regional Climate Models (RCMs) have been developed in the last two decades in order to produce high-resolution climate information by downscaling Atmosphere-Ocean General Circulation Models (AOGCMs) simulations or analyses of observed data. A crucial evaluation of RCMs worth is given by the assessment of the value added compared to the driving data. This evaluation is usually very complex due to the manifold circumstances that can preclude a fair assessment. In order to circumvent these issues, here we limit ourselves to estimating the potential of RCMs to add value over coarse-resolution data. We do this by quantifying the importance of fine-scale RCM-resolved features in the near-surface temperature, but disregarding their skill. The Reynolds decomposition technique is used to separate the variance of the time-varying RCM-simulated temperature field according to the contribution of large and small spatial scales and of stationary and transient processes. The temperature variance is then approximated by the contribution of four terms, two of them associated with coarse-scales (e.g., corresponding to the scales that can be simulated by AOGCMs) and two of them describing the original contribution of RCM simulations. Results show that the potential added value (PAV) emerges almost exclusively in regions characterised by important surface forcings either due to the presence of fine-scale topography or land-water contrasts. Moreover, some of the processes leading to small-scale variability appear to be related with relatively simple mechanisms such as the distinct physical properties of the Earth surface and the general variation of temperature with altitude in the Earth atmosphere. Finally, the article includes some results of the application of the PAV framework to the future temperature change signal due to anthropogenic greenhouse gasses. Here, contrary to previous studies centred on precipitation, findings suggest for surface temperature a relatively low potential of RCMs to add value over coarser resolution models, with the greatest potential located in coastline regions due to the differential warming occurring in land and water surfaces.     

Internal variability in a regional climate model over West Africa

Sensitivity studies with regional climate models are often performed on the basis of a few simulations for which the difference is analysed and the statistical significance is often taken for granted. In this study we present some simple measures of the confidence limits for these types of experiments by analysing the internal variability of a regional climate model run over West Africa. Two 1-year long simulations, differing only in their initial conditions, are compared. The difference between the two runs gives a measure of the internal variability of the model and an indication of which timescales are reliable for analysis. The results are analysed for a range of timescales and spatial scales, and quantitative measures of the confidence limits for regional model simulations are diagnosed for a selection of study areas for rainfall, low level temperature and wind. As the averaging period or spatial scale is increased, the signal due to internal variability gets smaller and confidence in the simulations increases. This occurs more rapidly for variations in precipitation, which appear essentially random, than for dynamical variables, which show some organisation on larger scales.     

Characteristics of sub-daily precipitation extremes in observed data and regional climate model simulations

Theoretical and Applied Climatology - The study compares characteristics of observed sub-daily precipitation extremes in the Czech Republic with those simulated by Hadley Centre Regional Model...     

变网格模式LMDZ对东亚夏季气候平均态的模拟能力评估

将可变网格大气环流模式LMDZ的模拟中心移动至中国地理中心附近(37°N,112.5°E),在东亚地区进行加密,使用其对应全球模式同步输出资料进行环流强迫,以观测海表温度SST和海冰SIC资料对下边界强迫,对1979-2008年各年5-9月对500 hPa高度场,850 hPa温度场和地面要素等进行了模拟,并利用同期的NCEP/NCAR再分析资料和由中国气象台站资料生成的格点资料,评估该模式对东亚地区高空环流场、西太平洋副热带高压及地面温度、降水等的夏季气候平均态的模拟能力.结果表明:LMDZ可以较好的模拟平均环流场,其模拟结果能够反映实际的500 hPa高度场和850 hPa温度场的分布特征和趋势,但总体模拟值较观测值偏低;对副高强度的模拟能力偏弱、模拟的副高位置偏东,但准确的表现了副高随时间变化的移动特性;模式较好的再现了中国区域夏季地面气温和降水的空间分布特征;但从数值吻合度看,温度模拟主要呈区域性偏冷距平,在东南沿海地区偏低1～3℃,在西部青藏高原地区偏低3～4℃及以上,中部和东北大部基本无偏差;降水的模拟在中国西北地区与实际观测较为一致,其误差主要表现为在中国东南部沿海模拟的降水偏多;对7个子区域,模式对850 hPa温度场和地面日均气温的再现能力优于对500 hPa高度场的模拟,且子区域间模拟偏差结果相差大,其中华北区地面气温模拟偏差最小,西北区降水值模拟偏差最小.     

Anthropogenic climate change over the Mediterranean region simulated by a global variable resolution model

Two 30-year simulations corresponding to 1960-1989 and 2070-2099 have been performed with a variable resolution atmospheric model. The model has a maximum horizontal resolution of 0.5° over the Mediterranean Sea. Simulations are driven by IPCC-B2 scenario radiative forcing. Sea surface temperatures (SSTs) are prescribed from monthly observations for the present climate simulation, and from a blend of observations and coupled simulations for the scenario. Another pair of forced atmospheric simulations has been run under these forcings with the same uniform low resolution as the coupled model. Comparisons with observations show that the variable resolution model realistically reproduces the main climate characteristics of the Mediterranean region. At a global scale, changes in latitudinal temperature profiles are similar for the forced and coupled models, justifying the time-slice approach. The 2 m temperature and precipitation responses predict a warming and drying of the Mediterranean region. A comparison with the coupled simulation and forced low-resolution simulation shows that this pattern is robust. The decrease in mean precipitation is associated with a significant decrease in soil wetness, and could involve considerable impact on water resources around the Mediterranean basin.     

Error characteristics of high resolution regional climate models over the Alpine area

This study describes typical error ranges of high resolution regional climate models operated over complex orography and investigates the scale-dependence of these error ranges. The results are valid primarily for the European Alpine region, but to some extent they can also be transferred to other orographically complex regions of the world. We investigate the model errors by evaluating a set of 62 one-year hindcast experiments for the year 1999 with four different regional climate models. The analysis is conducted for the parameters mean sea level pressure, air temperature (mean, minimum and maximum) and precipitation (mean, frequency and intensity), both as an area average over the whole modeled domain (the “Greater Alpine Region”, GAR) and in six subregions. The subregional seasonal error ranges, defined as the interval between the 2.5th percentile and the 97.5th percentile, lie between ?3.2 and +2.0 K for temperature and between ?2.0 and +3.1 mm/day (?45.7 and +94.7%) for precipitation, respectively. While the temperature error ranges are hardly broadened at smaller scales, the precipitation error ranges increase by 28%. These results demonstrate that high resolution RCMs are applicable in relatively small scale climate impact studies with a comparable quality as on well investigated larger scales as far as temperature is concerned. For precipitation, which is a much more demanding parameter, the quality is moderately degraded on smaller scales.     

Assessment of future climate change over East Asia due to the RCP scenarios downscaled by GRIMs-RMP

This study assesses future climate change over East Asia using the Global/Regional Integrated Model system—Regional Model Program (RMP). The RMP is forced by two types of future climate scenarios produced by the Hadley Center Global Environmental Model version 2 (HG2); the representative concentration pathways (RCP) 4.5 and 8.5 scenarios for the intergovernmental panel on climate change fifth assessment report (AR5). Analyses for the current (1980–2005) climate are performed to evaluate the RMP’s ability to reproduce precipitation and temperature. Two different future (2006–2050) simulations are compared with the current climatology to investigate the climatic change over East Asia centered in Korea. The RMP satisfactorily reproduces the observed seasonal mean and variation of precipitation and temperature. The spatial distribution of the simulated large-scale features and precipitation by the RMP is generally less reflective of current climatic conditions than that is given by the HG2, but their inter-annual variations in East Asia are better captured by the RMP. Furthermore, the RMP shows higher reproducibility of climate extremes including excessive heat wave and precipitation events over South Korea. In the future, strong warming is distinctly coupled with intensified monsoonal precipitation over East Asia. In particular, extreme weather conditions are increased and intensified over South Korea as follows: (1) The frequency of heat wave events with temperature greater than 30 °C is projected to increase by 131 and 111 % in the RCP 8.5 and 4.5 downscaling, relative to the current climate. (2) The RCP 8.5 downscaling shows the frequency and variability of heavy rainfall to increase by 24 and 31.5 %, respectively, while the statistics given by the RCP 4.5 downscaling are similar to those of the current climate.