基于MODIS数据中国天山积雪面积时空变化特征分析

基于2011-2015年MOD10A2积雪产品和气象数据,通过几何校正、去云预处理,应用归一化差分积雪指数算法等获取中国境内天山山区积雪覆盖面积数据,分析了积雪面积的时空变化特征及与气温降水的关系。结果表明：（1）年内积雪面积呈单峰变化,9月开始积累,次年1月达峰值,3月气温回暖消融加速,至7月最小。春秋季波动较大但没有明显的增减趋势,夏季积雪面积最小,冬季最大且呈减小趋势。（2）2001-2015年积雪覆盖面积整体上呈减少趋势,积雪覆盖率最大值的波动比最小值的波动更加剧烈。（3）积雪覆盖率随着海拔升高而增大,海拔<1 500 m区域积雪覆盖率低于10%,海拔>4 500 m以上区域平均可达70%,为常年稳定积雪区。积雪覆盖率在西北坡最高,南坡最低。（4）年均气温升高是积雪覆盖面积减小的主因,年积雪覆盖面积变化与年降水量变化保持一致的下降趋势。     

高分辨率青藏高原历史月降水数据重建

青藏高原对全球气候研究具有重要意义,而降水数据对水文、气象和生态等领域的研究也至关重要,且随着研究内容和尺度的变化,对高时空分辨率的历史降水数据的需求越发迫切。本文基于TRMM 3B43降水数据,采用随机森林算法,引入归一化植被指数(AVHRR NDVI)、高程(SRTM DEM)、坡度、坡向、经度、纬度6个地理因子,建立历史降水重建模型,获得1982-1997年分辨率为0.0833°的青藏高原年降水数据,然后根据比例系数法计算出月降水数据。为提高精度,利用站点数据对月降水数据进行校正。结果表明,该方法能简单有效地获得高时空分辨率的历史降水数据,决定系数R²大部分在0.4~0.9之间,平均值为0.6767,其中夏季效果最好,冬季效果最差;均方根误差RMSE和平均绝对误差MAE均在50 mm以下,RMSE均值为22.66 mm,MAE均值为15.97 mm;偏差Bias较小,基本在0.0~0.1之间。     

Assimilation of Feng-Yun-3B Satellite Microwave Humidity Sounder Data over Land

The ECMWF has been assimilating Feng-Yun-3B(FY-3B) satellite microwave humidity sounder(MWHS) data over ocean in an operational forecasting system since 24 September 2014. It is more difficult, however, to assimilate microwave observations over land and sea ice than over the open ocean due to higher uncertainties in land surface temperature, surface emissivity and less effective cloud screening. We compare approaches in which the emissivity is retrieved dynamically from MWHS channel 1 [150 GHz(vertical polarization)] with the use of an evolving emissivity atlas from 89 GHz observations from the MWHS onboard NOAA and EUMETSAT satellites. The assimilation of the additional data over land improves the fit of short-range forecasts to other observations, notably ATMS(Advanced Technology Microwave Sounder) humidity channels, and the forecast impacts are mainly neutral to slightly positive over the first five days. The forecast impacts are better in boreal summer and the Southern Hemisphere. These results suggest that the techniques tested allow for effective assimilation of MWHS/FY-3B data over land.