Consistent seasonal snow cover depth and duration variability over the Western Himalayas (WH)

Precipitation in solid form, i.e., snow, during winter season over the Western Himalayas (WH) leads to the build-up of seasonal snow cover. Seasonal snow cover build-up (snow cover depth and duration) largely depends on atmospheric variables such as temperature, precipitation, radiation, wind, etc. Integrated (combined) influence of atmospheric variables on seasonal snow cover gets reflected in terms of spatial and temporal variability in seasonal snow cover build-up pattern. Hence spatial and temporal variability of seasonal snow cover build-up can serve as a good indicator of climate change in high altitude mountainous regions like the WH. Consistent seasonal snow cover depth and duration, delay days and early melt days of consistent seasonal snow cover at 11 stations spread across different mountain ranges over the WH were analyzed. Mean, maximum and percentiles (25th, 50th, 75th, 90th and 95th) of consistent seasonal snow cover depth and duration show decline over the WH in the recent past 2–3 decades. Consistent seasonal snow cover is found to melt early and snow cover build-up pattern is found to show changes over the WH. Decline in consistent seasonal snow cover depth, duration and changing snow cover build-up pattern over the WH in recent decades indicate that WH has undergone considerable climate change and winter weather patterns are changing in the WH.     

Verification and Correction of Cloud Base and Top Height Retrievals from Ka–band Cloud Radar in Boseong,Korea

In this study,cloud base height(CBH) and cloud top height(CTH) observed by the Ka-band(33.44 GHz) cloud radar at the Boseong National Center for Intensive Observation of Severe Weather during fall 2013(September-November) were verified and corrected.For comparative verification,CBH and CTH were obtained using a ceilometer(CL51) and the Communication,Ocean and Meteorological Satellite(COMS).During rainfall,the CBH and CTH observed by the cloud radar were lower than observed by the ceilometer and COMS because of signal attenuation due to raindrops,and this difference increased with rainfall intensity.During dry periods,however,the CBH and CTH observed by the cloud radar,ceilometer,and COMS were similar.Thin and low-density clouds were observed more effectively by the cloud radar compared with the ceilometer and COMS.In cases of rainfall or missing cloud radar data,the ceilometer and COMS data were proven effective in correcting or compensating the cloud radar data.These corrected cloud data were used to classify cloud types,which revealed that low clouds occurred most frequently.     

西南地区夏季大气水汽含量及其与南亚高压关系

利用欧洲中期天气预报中心 (ECMWF) 提供的ERA-interim高分辨率资料,借助经验正交函数 (EOF) 分解、距平合成和相关分析等方法,讨论1979—2014年我国西南地区夏季大气水汽含量的时空变化特征及其与南亚高压的关系。研究结果表明:我国西南地区夏季大气水汽含量空间分布形态主要有全区一致型、南北振荡型和东西振荡型。全区一致型 (EOF1) 能够反映西南地区夏季水汽含量的主要特征,西南地区夏季大气水汽含量具有明显的年际变化特征;西南地区夏季大气水汽含量与南亚高压强度指数、面积指数及东伸指数均存在非常显著的正相关关系;南亚高压的异常偏强,有利于南海地区水汽向西南地区输送,且在西南地区气流由低层向高层的上升运动显著增强,引起西南地区大气水汽含量的异常偏多。     

Comparison of prediction performance using statistical postprocessing methods

As the 2018 Winter Olympics are to be held in Pyeongchang, both general weather information on Pyeongchang and specific weather information on this region, which can affect game operation and athletic performance, are required. An ensemble prediction system has been applied to provide more accurate weather information, but it has bias and dispersion due to the limitations and uncertainty of its model. In this study, homogeneous and nonhomogeneous regression models as well as Bayesian model averaging (BMA) were used to reduce the bias and dispersion existing in ensemble prediction and to provide probabilistic forecast. Prior to applying the prediction methods, reliability of the ensemble forecasts was tested by using a rank histogram and a residualquantile-quantile plot to identify the ensemble forecasts and the corresponding verifications. The ensemble forecasts had a consistent positive bias, indicating over-forecasting, and were under-dispersed. To correct such biases, statistical post-processing methods were applied using fixed and sliding windows. The prediction skills of methods were compared by using the mean absolute error, root mean square error, continuous ranked probability score, and continuous ranked probability skill score. Under the fixed window, BMA exhibited better prediction skill than the other methods in most observation station. Under the sliding window, on the other hand, homogeneous and non-homogeneous regression models with positive regression coefficients exhibited better prediction skill than BMA. In particular, the homogeneous regression model with positive regression coefficients exhibited the best prediction skill.     

基于 Flex 的市级国土资源综合监管平台设计与实现

采用Flex技术,基于NewMap Server进行WebGIS系统的开发,设计并实现呼伦贝尔市级国土资源"一张图"信息监管平台。系统克服数据来源多样、数据格式异构、数据基准不一致等问题,实现土地利用、矿产、地籍等多种数据的复合显示、查询、分析、输出、国土综合应用等功能,为国土管理部门提供管理、决策服务。