Observations of mid-troposhheric circulation from water vapour radiances of polar orbiting satellites

Water vapour tracers can provide useful information on winds at ≈ 500mb by observing the 6·7μ radiances. This fills the data gap in the cloud motion winds provided by conventional meteorological geostationary satellites. There is no geostationary satellite at present over the Indian Ocean with 6·7μ imaging capability to provide mid-tropospheric winds. The potentials of 6·7μ radiances, available from polar orbiting satellites, for mid-tropospheric circulation features have been examined in this study. Tiros-N satellite data of May 1979 and ECMWF level-IIIb wind data were analysed to relate the radiances with the streamlines. We find that the radiances of 6·7μ from orbiting satellites agree well with the wind field.     

A novel wide-field hard x-ray telescope

We discuss a hard x-ray telescope for the range 25–70 keV based on a one-dimensional lobster-eye telescope and x-ray supermirror coatings. This approach enables wide field-of-view imaging. A telescope suitable for a large balloon payload, with a 50×100 cm frontal area, could have an effective area of 50–100 cm² and a 10⁰×10⁰ field of view, and thereby detect AGN that are 0.5 milliCrab in the soft x-rays in a 10⁴ second exposure. 29% of the sky could be surveyed to this limit in a 2-week balloon flight, reaching 6 times fainter than the HEAO A-4 all-sky survey.     

喀斯特地区地表温度空间降尺度方法初探

喀斯特地区地形起伏大,常规的降尺度方法及所选择的因子对其不适用。该文根据喀斯特地区的特点,选取反射率、遥感指数及高程因子为尺度因子,通过随机森林模型建立MODIS第31、32波段辐射亮度数据和尺度因子之间的非线性关系,构建适合喀斯特地区的随机森林(Karst Random Forest,KRF)模型,成功将空间分辨率为1 km的热红外辐射亮度降至100 m,最后利用劈窗算法反演得到空间分辨率为100 m的地表温度。将KRF方法与仅考虑常规因子的多因子随机森林回归模型(MTVRF)和热锐化算法(TsHARP)对比,结果表明:1)在不同高差的喀斯特地区,KRF方法可较大程度提高地表温度降尺度精度,均方根误差(RMSE)在遵义市西北部和贵阳市以南地区分别为2.46 K和1.45 K,较MTVRF模型分别降低了0.1419 K和0.2928 K,较TsHARP算法分别降低了0.6204 K和0.6953 K,且在地形起伏度较低的喀斯特山区城市(贵阳市以南)表现更好;2)在喀斯特地区不同地类上,KRF方法效果也较好,其中植被区域最优,RMSE为1.41 K,破碎的裸土区域RMSE为1.84 K。研究显示,考虑特殊尺度因子的KRF方法可提高喀斯特地区地表温度的降尺度精度,为该地区以地表温度为基础的研究提供更精细可靠的地表温度产品。     

云的移动轨迹成像模拟及云量变化分析

以全天空数字成像仪的等角投影成像原理为基础，将云型简化为正方体及圆柱体云体。模拟了相同云体在不同空间位置的移动轨迹情况，对其所占面积变化（云量）进行了计算，并对云在移动过程中云体侧面成像情况做了分析研究。结果表明，云量随空间位置变化情况与云的宽高比相关，当宽高比大于某一值时云量随天项角（云所处位置）的增大先增大而后减小，反之则随着天顶角的增大而减小。     

全天空数字相机观测云量的初步研究

采用带有鱼眼镜头的数字相机拍摄全天空图像,对图像进行处理并分析,实现根据图像获取云量的目的。介绍了工作的基本原理和方法并给出初步实验结果。结果表明,用目前分析图像所获取的算法计算云量（与观测员记录相比）,平均误差在15％以内,结果的准确度受地面能见度影响较大,对能见度达15km以上的图像分析效果最好。     

GOES-16 ABI观测和ERA5全天空模拟亮温揭示的热带对流水平特征尺度对比分析

本研究通过将GOES-16 ABI观测亮温和ERA5再分析资料的全天空模拟亮温进行对比分析,发现观测亮温和模拟亮温对流低值区位置大体接近,也能够定性反映出对流从发展到减弱的日变化过程,但亮温低值区域的强度存在较大差异。即使把高分辨率ABI通道13观测亮温平均到ERA5分辨率(0.25°×0.25°),在热带对流区的低亮温强度仍然高于ERA5全天空模拟亮温。因此利用主成分分析(Principal Component Analysis,PCA)和离散傅里叶变换(Discrete Fourier Transform,DFT)对任意选择的两对流区域内的观测和模拟亮温进行了尺度分析和对比。在其中对流较强的区域内,当ABI观测亮温的主成分分量从1增加到9时,水平特征尺度从700 km逐渐减小到150 km。ERA5全天空模拟亮温从主成分1增加到4时,水平特征尺度从950 km减小到270 km空间尺度,但当主成分4增加到9时,特征尺度几乎不变。在对流较弱的另一区域也能够发现ERA5模拟亮温对对流水平特征尺度有明显高估。ERA5模拟亮温各主成分的相位和观测亮温存在2 h以内的误差。由于ERA5全天空...     

Evaluation of the assimilation of conventional and satellite-based observations in simulating heavy rainfall event using WRFDA over the North-West Himalayan region

Present work elucidates the impact of 3DVAR data assimilation technique for the simulation of one of the heavy rainfall events reported over Kotdwara region in the North-West Himalayan (NWH) region on 4th August 2017. We have examined the impact of conventional and satellite-based radiance datasets on the simulated results with and without assimilating the observations into the Weather Research and Forecasting (WRF) model. Three experiments have been designed with 3 nested domains of variable resolutions, one without assimilation (referred as control experiment) and other two experiments after assimilating conventional and satellite radiances observations (refer as DA-OBS and DA-SAT respectively). In the present study, assimilation of surface, upper air and the satellite-based radiance observations has been carried out for the outermost domain with horizontal resolution of 9 km. Statistical analysis suggests that the correlation coefficient is high (0.55) and root mean square error (RMSE) is low (17.12) for DA-SAT experiment as compared to other two experiments. Substantial improvement in the location, pattern and intensity of extreme rainfall event is noted after assimilation of both conventional and satellite observations with respect to the observed rainfall data. However, it is noted that the assimilation of satellite radiances has greater impact in simulating better intensity of the heavy rainfall event as compared to the assimilation of conventional observations. Plausible reason behind this could be the non-availability of the conventional observations close to the extreme rainfall event affected region.     

Assimilating All-sky Infrared Radiances from Himawari-8 Using the 3DVar Method for the Prediction of a Severe Storm over North China

Although radar observations capture storm structures with high spatiotemporal resolutions, they are limited within the storm region after the precipitation formed. Geostationary satellites data cover the gaps in the radar network prior to the formation of the precipitation for the storms and their environment. The study explores the effects of assimilating the water vapor channel radiances from Himawari-8 data with Weather Research and Forecasting model data assimilation system(WRFDA) for a severe storm case over north China. A fast cloud detection scheme for Advanced Himawari imager(AHI)radiance is enhanced in the framework of the WRFDA system initially in this study. The bias corrections, the cloud detection for the clear-sky AHI radiance, and the observation error modeling for cloudy radiance are conducted before the data assimilation. All AHI radiance observations are fully applied without any quality control for all-sky AHI radiance data assimilation. Results show that the simulated all-sky AHI radiance fits the observations better by using the cloud dependent observation error model, further improving the cloud heights. The all-sky AHI radiance assimilation adjusts all types of hydrometeor variables, especially cloud water and precipitation snow. It is proven that assimilating all-sky AHI data improves hydrometeor specifications when verified against the radar reflectivity. Consequently, the assimilation of AHI observations under the all-sky condition has an overall improved impact on both the precipitation locations and intensity compared to the experiment with only conventional and AHI clear-sky radiance data.     

Evaluation of All-Sky Assimilation of FY-3C/MWHS-2 on Mei-yuPrecipitation Forecasts over the Yangtze-Huaihe River Basin

正1School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610025, China2International Center for Climate and Environment Sciences, Institute of Atmospheric Physics,Chinese Academy of Sciences, Beijing 100029, China3University of Chinese Academy of Sciences, Beijing 100049, China     

Satellite All-sky Infrared Radiance Assimilation: Recent Progress and Future Perspectives

Satellite infrared(IR)sounder and imager measurements have become one of the main sources of data used by data assimilation systems to generate initial conditions for numerical weather prediction(NWP)models and atmospheric analysis/reanalysis.This paper reviews the development of satellite IR data assimilation in NWP in recent years,especially the assimilation of all-sky satellite IR observations.The major challenges and future directions are outlined and discussed.