Neural networks approach to high vertical resolution atmospheric temperature profile retrieval from spaceborne high spectral resolution infrared sounder measurements

2006 ◽  
Author(s):  
Deming Jiang ◽  
Chaohua Dong ◽  
Weisong Lu
Author(s):  
Pei Wang ◽  
Zhenglong Li ◽  
Jun Li ◽  
Timothy J. Schmit

AbstractHigh spectral resolution (or hyperspectral) infrared (IR) sounders onboard low earth orbiting satellites provide high vertical resolution atmospheric information for numerical weather prediction (NWP) models. In contrast, imagers on geostationary (GEO) satellites provide high temporal and spatial resolution which are important for monitoring the moisture associated with severe weather systems, such as rapidly developing local severe storms (LSS). A hyperspectral IR sounder onboard a geostationary satellite would provide four-dimensional atmospheric temperature, moisture, and wind profiles that have both high vertical resolution and high temporal/spatial resolutions. In this work, the added-value from a GEO-hyperspectral IR sounder is studied and discussed using a hybrid Observing System Simulation Experiment (OSSE) method. A hybrid OSSE is distinctively different from the traditional OSSE in that, (a) only future sensors are simulated from the nature run and (b) the forecasts can be evaluated using real observations. This avoids simulating the complicated observation characteristics of the current systems (but not the new proposed system) and allows the impact to be assessed against real observations. The Cross-track Infrared Sounder (CrIS) full spectral resolution (FSR) is assumed to be onboard a GEO for the impact studies, and the GEO CrIS radiances are simulated from the ECMWF Reanalysis v5 (ERA5) with the hyperspectral IR all-sky radiative transfer model (HIRTM). The simulated GEO CrIS radiances are validated and the hybrid OSSE system is verified before the impact assessment. Two LSS cases from 2018 and 2019 are selected to evaluate the value-added impacts from the GEO CrIS-FSR data. The impact studies show improved atmospheric temperature, moisture, and precipitation forecasts, along with some improvements in the wind forecasts. An added-value, consisting of an overall 5% Root Mean Square Error (RMSE) reduction, was found when a GEO CrIS-FSR is used in replacement of LEO ones indicating the potential for applications of data from a GEO hyperspectral IR sounder to improve local severe storm forecasts.


2018 ◽  
Vol 176 ◽  
pp. 01023
Author(s):  
Ilya I. Razenkov ◽  
Edwin W. Eloranta

This paper reports the atmospheric temperature profile measurements using a University of Wisconsin-Madison High Spectral Resolution Lidar (HSRL) and describes improvements in the instrument performance. HSRL discriminates between Mie and Rayleigh backscattering [1]. Thermal motion of molecules broadens the spectrum of the transmitted laser light due to Doppler effect. The HSRL exploits this property to allow the absolute calibration of the lidar and measurements of the aerosol volume backscatter coefficient. Two iodine absorption filters with different line widths are used to resolve temperature sensitive changes in Rayleigh backscattering for atmospheric temperature profile measurements.


2018 ◽  
Vol 176 ◽  
pp. 01024
Author(s):  
Ilya I. Razenkov ◽  
Edwin W. Eloranta

This paper describes the modifications done on the University of Wisconsin-Madison High Spectral Resolution Lidar (HSRL) that improved the instrument’s performance. The University of Wisconsin HSRL lidars designed by our group at the Space Science and Engineering Center were deployed in numerous field campaigns in various locations around the world. Over the years the instruments have undergone multiple modifications that improved the performance and added new measurement capabilities such as atmospheric temperature profile and extinction cross-section measurements.


2010 ◽  
Vol 22 (7) ◽  
pp. 1449-1452
Author(s):  
卜令兵 Bu Lingbing ◽  
郭劲秋 Guo Jinqiu ◽  
田力 Tian Li ◽  
黄兴友 Huang Xingyou ◽  
刘博 Liu Bo ◽  
...  

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