在中尺度数值模式中,选用不同的参数化方案对降水的模拟和预测效果会有很大影响,合理选择参数化方案可以提高预测准确性。为此,本文使用中尺度预报模式WRF 3.8(weather research and forecasting model,WRF)版本,采用3 km和9 km两层嵌...在中尺度数值模式中,选用不同的参数化方案对降水的模拟和预测效果会有很大影响,合理选择参数化方案可以提高预测准确性。为此,本文使用中尺度预报模式WRF 3.8(weather research and forecasting model,WRF)版本,采用3 km和9 km两层嵌套网格,利用ECMWF(European Centre for Medium Range Weather Forecasts)再分析资料作为初始场和边界条件,对新疆地区4次暴雨过程进行模拟,采用TS(threat score)评分评估了Lin方案、WSM6方案、Thompson方案和WDM6方案4种云微物理参数化方案对新疆地区暴雨模拟的适用性。结果表明:Thompson方案在站点降雨量为小雨(0.1~5.0 mm)和中雨(5.1~10.0 mm)的预报模拟中具有优势,其他3种云微物理参数化方案均在不同程度上存在漏报情况,从相关系数上判断,Thompson方案模拟效果略优于其他方案,适用于多小雨、中雨的新疆地区,但4种云微物理参数化方案在大到暴雨降水等级的预报效果都不是很好,这也正是WRF模式在新疆地区需要改进的地方。展开更多
The monthly forecast of Indian monsoon rainfall during June to September is investigated by using the hindcast data sets of the National Centre for Environmental Prediction (NCEP)’s operational coupled model (known a...The monthly forecast of Indian monsoon rainfall during June to September is investigated by using the hindcast data sets of the National Centre for Environmental Prediction (NCEP)’s operational coupled model (known as the Climate Forecast System) for 25 years from 1981 to 2005 with 15 ensemble members each. The ensemble mean monthly rainfall over land region of India from CFS with one month lead forecast is underestimated during June to September. With respect to the inter-annual variability of monthly rainfall it is seen that the only significant correlation coefficients (CCs) are found to be for June forecast with May initial condition and September rainfall with August initial conditions. The CFS has got lowest skill for the month of August followed by that of July. Considering the lower skill of monthly forecast based on the ensemble mean, all 15 ensemble members are used separately for the preparation of probability forecast and different probability scores like Brier Score (BS), Brier Skill Score (BSS), Accuracy, Probability of Detection (POD), False Alarm Ratio (FAR), Threat Score (TS) and Heidke Skill Score (HSS) for all the three categories of forecasts (above normal, below normal and normal) have been calculated. In terms of the BS and BSS the skill of the monthly probability forecast in all the three categories are better than the climatology forecasts with positive BSS values except in case of normal forecast of June and July. The “TS”, “HSS” and other scores also provide useful probability forecast in case of CFS except the normal category of July forecast. Thus, it is seen that the monthly probability forecast based on NCEP CFS coupled model during the southwest monsoon season is very encouraging and is found to be very useful.展开更多
In recent years long-term precipitation trends on a regional scale have been given emphasis due to the impacts of global warming on regional hydrology. In this study, regional precipitation trends are simulated over t...In recent years long-term precipitation trends on a regional scale have been given emphasis due to the impacts of global warming on regional hydrology. In this study, regional precipitation trends are simulated over the Europe continent for a 60-year period in 1950-2010 using an advanced regional model, WRF, to study extreme precipitation events over Europe. The model runs continuously for each year during the period at a horizontal resolution of 25 km with initial/ boundary conditions derived from the National Center for Environmental Prediction (NCEP) 2.5 degree reanalysis data sets. The E-OBS 0.25 degree rainfall observation analysis is used for model validation. Results indicate that the model could reproduce the spatial annual rainfall pattern over Europe with low amounts (250 - 750 mm) in Iberian Peninsula, moderate to large amounts (750 - 1500 mm) in central, eastern and northeastern parts of Europe and extremely heavy falls (1500 - 2000 mm) in hilly areas of Alps with a slight overestimation in Alps and underestimation in other parts of Europe. The regional model integrations showed increasing errors (mean absolute errors) and decreasing correlations with increasing time scale (daily to seasonal). Rainfall is simulated relatively better in Iberian Peninsula, northwest and central parts of Europe. A large spatial variability with the highest number of wet days over eastern, central Europe and Alps (~200 days/year) and less number of wet days over Iberian Peninsula (≤150 days/year) is also found in agreement with observations. The model could simulate the spatial rainfall climate variability reasonably well with low rainfall days (1 - 10 mm/days) in almost all zones, heavy rainfall events in western, northern, southeastern hilly and coastal zones and extremely heavy rainfall events in northern coastal zones. An increasing trend of heavy rainfall in central, southern and southeastern parts, a decreasing trend in Iberian Peninsula and a steady trend in other zones are found. Overall, the simulated rainfall 展开更多
文摘在中尺度数值模式中,选用不同的参数化方案对降水的模拟和预测效果会有很大影响,合理选择参数化方案可以提高预测准确性。为此,本文使用中尺度预报模式WRF 3.8(weather research and forecasting model,WRF)版本,采用3 km和9 km两层嵌套网格,利用ECMWF(European Centre for Medium Range Weather Forecasts)再分析资料作为初始场和边界条件,对新疆地区4次暴雨过程进行模拟,采用TS(threat score)评分评估了Lin方案、WSM6方案、Thompson方案和WDM6方案4种云微物理参数化方案对新疆地区暴雨模拟的适用性。结果表明:Thompson方案在站点降雨量为小雨(0.1~5.0 mm)和中雨(5.1~10.0 mm)的预报模拟中具有优势,其他3种云微物理参数化方案均在不同程度上存在漏报情况,从相关系数上判断,Thompson方案模拟效果略优于其他方案,适用于多小雨、中雨的新疆地区,但4种云微物理参数化方案在大到暴雨降水等级的预报效果都不是很好,这也正是WRF模式在新疆地区需要改进的地方。
文摘The monthly forecast of Indian monsoon rainfall during June to September is investigated by using the hindcast data sets of the National Centre for Environmental Prediction (NCEP)’s operational coupled model (known as the Climate Forecast System) for 25 years from 1981 to 2005 with 15 ensemble members each. The ensemble mean monthly rainfall over land region of India from CFS with one month lead forecast is underestimated during June to September. With respect to the inter-annual variability of monthly rainfall it is seen that the only significant correlation coefficients (CCs) are found to be for June forecast with May initial condition and September rainfall with August initial conditions. The CFS has got lowest skill for the month of August followed by that of July. Considering the lower skill of monthly forecast based on the ensemble mean, all 15 ensemble members are used separately for the preparation of probability forecast and different probability scores like Brier Score (BS), Brier Skill Score (BSS), Accuracy, Probability of Detection (POD), False Alarm Ratio (FAR), Threat Score (TS) and Heidke Skill Score (HSS) for all the three categories of forecasts (above normal, below normal and normal) have been calculated. In terms of the BS and BSS the skill of the monthly probability forecast in all the three categories are better than the climatology forecasts with positive BSS values except in case of normal forecast of June and July. The “TS”, “HSS” and other scores also provide useful probability forecast in case of CFS except the normal category of July forecast. Thus, it is seen that the monthly probability forecast based on NCEP CFS coupled model during the southwest monsoon season is very encouraging and is found to be very useful.
文摘In recent years long-term precipitation trends on a regional scale have been given emphasis due to the impacts of global warming on regional hydrology. In this study, regional precipitation trends are simulated over the Europe continent for a 60-year period in 1950-2010 using an advanced regional model, WRF, to study extreme precipitation events over Europe. The model runs continuously for each year during the period at a horizontal resolution of 25 km with initial/ boundary conditions derived from the National Center for Environmental Prediction (NCEP) 2.5 degree reanalysis data sets. The E-OBS 0.25 degree rainfall observation analysis is used for model validation. Results indicate that the model could reproduce the spatial annual rainfall pattern over Europe with low amounts (250 - 750 mm) in Iberian Peninsula, moderate to large amounts (750 - 1500 mm) in central, eastern and northeastern parts of Europe and extremely heavy falls (1500 - 2000 mm) in hilly areas of Alps with a slight overestimation in Alps and underestimation in other parts of Europe. The regional model integrations showed increasing errors (mean absolute errors) and decreasing correlations with increasing time scale (daily to seasonal). Rainfall is simulated relatively better in Iberian Peninsula, northwest and central parts of Europe. A large spatial variability with the highest number of wet days over eastern, central Europe and Alps (~200 days/year) and less number of wet days over Iberian Peninsula (≤150 days/year) is also found in agreement with observations. The model could simulate the spatial rainfall climate variability reasonably well with low rainfall days (1 - 10 mm/days) in almost all zones, heavy rainfall events in western, northern, southeastern hilly and coastal zones and extremely heavy rainfall events in northern coastal zones. An increasing trend of heavy rainfall in central, southern and southeastern parts, a decreasing trend in Iberian Peninsula and a steady trend in other zones are found. Overall, the simulated rainfall
