Temperature extremes and wildfires in Siberia in the 21st century: the MGO regional climate model simulation

Possible changes in temperature extremes and wildfires in the 21st century in the regions of Russia are analyzed using a regional climate model (RCM) with high space-time resolution. The IPCC A2 scenario of greenhouse gas and aerosol concentration increase in the atmosphere is used. It is shown that changes in extreme wildfires appear to be in the 21st century most pronounced relative to changes in moderate and high wildfires. In some areas, along with decreased moderate and high wildfires, a significant increase in extreme wildfires is expected. Further studies should be associated both with RCM development, aimed at improving simulation of the wildfire atmospheric condition, and with enlarging the parameter set for wildfire analysis. Not only seasonal mean, but also monthly mean wildfire conditions should be studied, along with the use of statistical methods of model data interpretation to analyze intraseasonal and interannual variability of wildfire characteristics.     

Changes in climate extremes on the territory of Siberia by the middle of the 21st century: An ensemble forecast based on the MGO regional climate model

The results are analyzed of the ensemble forecast of temperature and precipitation extremes on the territory of Siberia by the middle of the 21st century based on the regional climate model of the Main Geophysical Observatory (MGO) with the resolution of 25 km. The results of computation of oceanic components of CMIP3 coupled models are used as the boundary conditions on the sea surface. It is demonstrated that the high resolution of the regional model enables to simulate the observed climate variability in a more realistic way as compared to the low-resolution models. The analysis of the signal-to-noise ratio for future climate changes made it possible to determine to which degree its internal variability for various time scales (from interannual to interdecennial one) bounds the potential of the ensemble to compute the statistically significant anthropogenic changes of extremes. A comparative analysis of variations of extreme and average seasonal characteristics of the Siberian climate is carried out.     

Current trends of climate changes in southern arid regions of West Siberia

The regional climate changes in the arid regions in the south of West Siberia for the period of 1936–2010 are estimated by means of the statistical analysis of the series of climatic parameters and complex hydrothermal indices. Revealed is the close correlation between the above characteristics. The periodicity of variations of some climatic parameters and corresponding indices amounting to 8–12 years on average is revealed using the Welch’s method of spectral analysis.     

The radiation budget in a regional climate model

The long- and short-wave components of the radiation budget are among the most important quantities in climate modelling. In this study, we evaluated the radiation budget at the earth??s surface and at the top of atmosphere over Europe as simulated by the regional climate model CLM. This was done by comparisons with radiation budgets as computed by the GEWEX/SRB satellite-based product and as realised in the ECMWF re-analysis ERA40. Our comparisons show that CLM has a tendency to underestimate solar radiation at the surface and the energy loss by thermal emission. We found a clear statistical dependence of radiation budget imprecision on cloud cover and surface albedo uncertainties in the solar spectrum. In contrast to cloud fraction errors, surface temperature errors have a minor impact on radiation budget uncertainties in the long-wave spectrum. We also evaluated the impact of the number of atmospheric layers used in CLM simulations. CLM simulations with 32 layers perform better than do those with 20 layers in terms of the surface radiation budget components but not in terms of the outgoing long-wave radiation and of radiation divergence. Application of the evaluation approach to similar simulations with two additional regional climate models confirmed the results and showed the usefulness of the approach.     

气候模式分辨率对气溶胶气候效应模拟结果的影响

气候模式分辨率作为影响模式模拟结果的重要因素,其对气溶胶与云相互作用的影响尚未全面认识。利用公共大气模型CAM5.3在3种分辨率（2°、1°、0.5°）下,分别采用2000年和1850年气溶胶排放情景进行试验,检验提高分辨率是否能改进气候模式的模拟能力,分析不同分辨率下气溶胶气候效应的异同,探索模式分辨率对气溶胶气候效应数值模拟结果的影响。通过观测资料与模式结果对比发现,提高分辨率可以明显改进模式对总云量、云短波辐射强迫的模拟能力,0.5°分辨率下模拟结果与观测更接近,其他变量并无明显改善。在不同分辨率下,全球平均的气溶胶气候效应较为一致,总云量、云水路径均增加,云短波和长波辐射强迫均加强,而云顶的云滴有效半径和降水均减小,地面气温降低。不同分辨率下,气溶胶增加引起的气溶胶光学厚度、云水路径、地面温度、云短波和长波辐射强迫变化的纬向平均分布相似但大小存在差异;而降水和云量变化的纬向分布与大小均存在较大差异,在区域尺度上还存在较大的不确定性。全球平均而言, 0.5°分辨率下气溶胶的间接辐射强迫相比1°分辨率下的结果降低了2.5%,相比2°分辨率下的结果降低了6.4%。提高模式分辨率可以部分改进模式模拟能力,同时,气溶胶的间接效应随着模式分辨率的提高而减弱。但气溶胶引起的云量、降水的变化在不同分辨率下差异较大,存在较大的不确定性。      

具有热力-动力耦合的二维能量平衡气候模式

本文设计了一个热力—动力耦合的理论模式,所得到温度场和运动场的平均气候状态基本上与实况接近.分析表明,温度场和速度场是相互制约的,温度分布在纬向上的不均匀形成了垂直经圈环流,此种流场又把赤道的热量往极地输送,其结果与没有运动场耦合的情况相比,可使赤道温度降低而极地温度升高. 研究模式气候对太阳常数变化的敏感性后指出,要使冰界线从现在的72°N南移到冰河期的50°N,太阳常数要减小15％左右.这在考虑或不考虑流场耦合的模式中都是差不多的.     

The Last Glacial Maximum climate over Europe and western Siberia: a PMIP comparison between models and data

 Under the framework of the Palaeoclimate Modelling Intercomparison Project (PMIP), 17 climate models, 16 of which are atmospheric general circulation models, have been run to simulate the climate of the Last Glacial Maximum (21 000 years ago) using the same set of boundary conditions. Parallel to these numerical experiments, new, consistent, data bases have been developed on a continental scale. The present work compares the range of the model responses to the large perturbation corresponding to the conditions of the Last Glacial Maximum with consistently derived climate reconstructions from pollen records over Europe and western Siberia. It accounts for the differences in the model results due to the models themselves and directly compares this “error bar” due to the models to the uncertainties in the climate reconstructions from the pollen records. Overall the Last Glacial Maximum climate simulated by the models over western Europe is warmer, especially in winter, and wetter than the one depicted by the reconstructions. This is the region where the reconstructed increase in temperature, precipitation and moisture index from the Last Glacial Maximum to the present conditions is largest. The same disagreement, but of smaller amplitude, is found over Central Europe and the eastern Mediterranean Basin, while models and data are in broad agreement over western Siberia. The numerous modelling results allow a study of the link between the changes in atmospheric circulation and those in temperature, and an interpretation of the discrepancies in precipitation in terms of those in temperature. Received: 1 February 2000 / Accepted: 9 May 2000     

Developing a climate model for Iran using GIS

Summary In order to develop a climate model for Iran, monthly mean climatic variables from 117 synoptic stations were obtained from the Iranian Meteorological Organisation. These variables were reduced to six orthogonal factors using factor analysis. The stations were then divided into six groups using cluster analysis. Within each climatic group, the lowest and highest thresholds for each factor were identified. The factor scores of the stations within each factor were interpolated across the country applying Inverse Squared Distance Weight in the ArcGIS environment. Based on the factor scores, six conditional functions were defined to allocate each pixel to a region. In order to simplify the models, one index variable was substituted for each factor. Then, through Discriminant Analysis, the constants and coefficients of the models were determined. The final models were evaluated against some examples, one of which, Yazd, was demonstrated fully. Authors’ address: Bohloul Alijani, Manijeh Ghohroudi, Nahid Arabi, Department of Geography, Teacher Training University, Mofetteh Avenue, Tehran, Iran.     

Role of climate in removing dissolved organic matter from cryolithozone watersheds in central Siberia

With reference to 2001–2005, the fluxes of dissolved organic matter (DOM) are analyzed in a water stream of the northern taiga subzone of continuous permafrost. Dynamics of hydroclimatic parameters is shown during a frost-free period. It is found that, in spite of a potential decrease in the DOM concentrations with the increased thickness of a seasonally thawed layer, one observes their direct dependence on the precipitation amount and part that enters the water stream. Seasonal variations in the DOM qualitative composition are determined. The basic DOM part exported from the watershed is observed during the regimes of a maximum water content (spring flooding and floods).     

The aerosol module in the INM RAS climate model

The aerosol module is included into the INM RAS climate model. The module computes the evolution of main aerosols: sea salt, mineral dust, sulfate aerosol, and black and organic carbon. Aerosol surface fluxes, advection, gravitational sedimentation, surface absorption, and scavenging by precipitation are taken into account to compute aerosol concentration variations. Model aerosol distribution is used to compute radiation fluxes. The ten-year run of the climate model is performed. The climatology of model aerosol is considered. The aerosol mass, integral source values, optical thickness, and radiative forcing are presented. The results are compared with the data of other models and observations.     

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.     

BCC_CSM气候系统模式移植优化及其气候模拟验证

为了提高BCC_CSM气候系统模式运行效率,保障业务科研工作的顺利开展,进行BCC_CSM气候系统模式在IBM高性能计算系统的移植工作;通过性能优化使BCC_CSM模式运行效率显著提高,通过气候要素形势场分布和相对误差量化指标对BCC_CSM气候系统模式模拟性能进行验证。结果表明：移植优化后,BCC_CSM气候系统模式计算效率提高为原来的1.4倍;基于CMIP5 piControl试验,完成531-540年10 a的气候模拟,年平均地表气温形势场分布合理,相对误差小于0.5%,BCC_CSM气候系统模式计算和模拟性能均能满足应用需求。     

Regional climate model projections for the State of Washington

Global climate models do not have sufficient spatial resolution to represent the atmospheric and land surface processes that determine the unique regional climate of the State of Washington. Regional climate models explicitly simulate the interactions between the large-scale weather patterns simulated by a global model and the local terrain. We have performed two 100-year regional climate simulations using the Weather Research and Forecasting (WRF) model developed at the National Center for Atmospheric Research (NCAR). One simulation is forced by the NCAR Community Climate System Model version 3 (CCSM3) and the second is forced by a simulation of the Max Plank Institute, Hamburg, global model (ECHAM5). The mesoscale simulations produce regional changes in snow cover, cloudiness, and circulation patterns associated with interactions between the large-scale climate change and the regional topography and land-water contrasts. These changes substantially alter the temperature and precipitation trends over the region relative to the global model result or statistical downscaling. To illustrate this effect, we analyze the changes from the current climate (1970–1999) to the mid twenty-first century (2030–2059). Changes in seasonal-mean temperature, precipitation, and snowpack are presented. Several climatological indices of extreme daily weather are also presented: precipitation intensity, fraction of precipitation occurring in extreme daily events, heat wave frequency, growing season length, and frequency of warm nights. Despite somewhat different changes in seasonal precipitation and temperature from the two regional simulations, consistent results for changes in snowpack and extreme precipitation are found in both simulations.     

A flexible climate model for use in integrated assessments

 Because of significant uncertainty in the behavior of the climate system, evaluations of the possible impact of an increase in greenhouse gas concentrations in the atmosphere require a large number of long-term climate simulations. Studies of this kind are impossible to carry out with coupled atmosphere ocean general circulation models (AOGCMs) because of their tremendous computer resource requirements. Here we describe a two dimensional (zonally averaged) atmospheric model coupled with a diffusive ocean model developed for use in the integrated framework of the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change. The 2-D model has been developed from the Goddard Institute for Space Studies (GISS) GCM and includes parametrizations of all the main physical processes. This allows it to reproduce many of the nonlinear interactions occurring in simulations with GCMs. Comparisons of the results of present-day climate simulations with observations show that the model reasonably reproduces the main features of the zonally averaged atmospheric structure and circulation. The model’s sensitivity can be varied by changing the magnitude of an inserted additional cloud feedback. Equilibrium responses of different versions of the 2-D model to an instantaneous doubling of atmospheric CO₂ are compared with results of similar simulations with different AGCMs. It is shown that the additional cloud feedback does not lead to any physically inconsistent results. On the contrary, changes in climate variables such as precipitation and evaporation, and their dependencies on surface warming produced by different versions of the MIT 2-D model are similar to those shown by GCMs. By choosing appropriate values of the deep ocean diffusion coefficients, the transient behavior of different AOGCMs can be matched in simulations with the 2-D model, with a unique choice of diffusion coefficients allowing one to match the performance of a given AOGCM for a variety of transient forcing scenarios. Both surface warming and sea level rise due to thermal expansion of the deep ocean in response to a gradually increasing forcing are reasonably reproduced on time scales of 100–150 y. However a wide range of diffusion coefficients is needed to match the behavior of different AOGCMs. We use results of simulations with the 2-D model to show that the impact on climate change of the implied uncertainty in the rate of heat penetration into the deep ocean is comparable with that of other significant uncertainties. Received: 10 March 1997 / Accepted: 20 October 1997     

An urban canopy-layer climate model

Summary This paper outlines a computer simulation model designed to assess the thermal characteristics of the urban canopy layer (UCL). In contrast to other UCL models, the layer simulated here includes both closed volumes (buildings) and open volumes (canyons). The purpose of the model is to allow the comparison of the climate impacts of different building group configurations. Traditional boundary-layer theory is applied to the surface urban boundary layer (UBL) which lies above the UCL and the derived relations are used to parameterize exchanges of momentum and heat across the UBL/UCL interface. The exterior energy budgets of the roof, walls and floor of the canopy are solved using an equilibrium surface temperature method. The open canopy and interior building air temperatures are found which are in agreement with the surface exchanges. Using measured data for Los Angeles in June, the output of the model is examined. The results show some agreement with measurement studies and suggest that the density of structures can have a substantial impact on UCL/UBL interaction.With 6 Figures     

A stochastic model of SST for climate simulation experiments

 This study describes the implementation of a statistical method to simulate a multi-century sequence of global sea surface temperature (SST) fields. A multi-variable auto-regressive (AR) model is trained on the observed time series of SST from the data set compiled at the Hadley Centre (GISST 2.0). To reduce the dimensionality of the model, the stochastic process is in practice fitted to empirical orthogonal function (EOF) time coefficients of the SST series, retaining the first 14 EOFs. Selected lag cross-covariances among the EOF time series are retained, based on the structure of the cross-correlation matrix and lags up to 64 months are included. Though the resulting system is quite large (a 14-dimensional AR process, with 400 parameters to be determined) the calculation is possible and a stable process is obtained. The process can then be used to investigate some statistical properties of the SST data set and to generate synthetic SST data that could be used in very long numerical experiments with atmospheric or ocean models in which only the main features of the observed statistics of the SST must be retained. Results indicate that the synthetic SST data set seems to be of usable quality as boundary condition for the atmosphere or the ocean in climate experiments. Analysis of extreme events and extreme decades in the synthetic SST data confirms the exceptional character of the 1980s, but also provides circumstantial evidence that the 1980s were indeed within the limits of the statistics of the previously observed record. Received: 6 August 1996 / Accepted: 29 September 1997     

A regional climate model for the western United States

A numerical approach to modeling climate on a regional scale is developed whereby large-scale weather systems are simulated with a global climate model (GCM) and the GCM output is used to provide the boundary conditions needed for high-resolution mesoscale model simulations over the region of interest. In our example, we use the National Center for Atmospheric Research (NCAR) community climate model (CCM1) and the Pennsylvania State University (PSU)/NCAR Mesoscale Model version 4 (MM4) to apply this approach over the western United States (U.S.). The topography, as resolved by the 500-km mesh of the CCM1, is necessarily highly distorted, but with the 60-km mesh of the MM4 the major mountain ranges are distinguished. To obtain adequate and consistent representations of surface climate, we use the same radiation and land surface treatments in both models, the latter being the recently developed Biosphere-Atmosphere Transfer Scheme (BATS). Our analysis emphasizes the simulation at four CCM1 points surrounding Yucca Mountain, NV, because of the need to determine its climatology prior to certification as a high-level nuclear waste repository.We simulate global climate for three years with CCM1/BATS and describe the resulting January surface climatology over the western U.S. The details of the precipitation patterns are unrealistic because of the smooth topography. Selecting five January CCM1 storms that occur over the western U.S. with a total duration of 20 days for simulation with the MM4, we demonstrate that the mesoscale model provides much improved wintertime precipitation patterns. The storms in MM4 are individually much more realistic than those in CCM1. A simple averaging procedure that infers a mean January rainfall climatology calculated from the 20 days of MM4 simulation is much closer to the observed than is the CCM1 climatology. The soil moisture and subsurface drainage simulated over 3–5 day integration periods of MM4, however, remain strongly dependent on the initial CCM1 soil moisture and thus are less realistic than the rainfall. Adequate simulation of surface soil water may require integrations of the mesoscale model over time periods.The National Center for Atmospheric Research is sponsored by the National Science Foundation. of up to several months or longer.