Radiometric consistency assessment of hyperspectral infrared sounders

Lossless Data Compression for Infrared Hyperspectral Sounders - An Overview

Hyperspectral sounding data requires accuracy for useful retrieval of atmospheric temperature, moisture, trace gases, clouds, aerosols and surface properties. Therefore, compression of hyperspectral sounding data is better to be lossless or near lossless. Given the large volume of three-dimensional hyperspectral data that will be generated by the hyperspectral sounders such as AIRS, CrIS, IASI,...

Hyperspectral Imaging FT-Spectroradiometers Radiometric Accuracy for Infrared Signature Measurements

Integrating High Spatial Resolution Imager Observations to improve Cloud-cleared Radiances from Hyperspectral Infrared Sounders

Today, most Numerical Weather Prediction (NWP) centers are assimilating cloud-free radiances. Radiances from the Atmospheric Infrared Sounder have been directly assimilated in NWP models with modest positive impacts. However, since only 5% percentage of AIRS fields of view (fovs) are cloud-free, only very small amounts of the data in the lower troposphere are assimilated. (Note that channels in...

Radiometric Performance Requirements for Optimal Atmospheric Processing of Hyperspectral Imagery

The radiometric performance of an hyperspectral sensor is limited due to physical constraints such as quantization, noise levels, spectral resolutions, and calibration accuracy. During the definition phase of a hyperspectral instrument, these numbers have to be defined based on scientific requirements for atmospheric correction methods to be applied and with respect to a variety of hyperspectra...

Assessment and Correction of on-Orbit Radiometric Calibration for FY-3 VIRR Thermal Infrared Channels

FengYun-3 (FY-3) Visible Infrared Radiometer (VIRR), along with its predecessor, Multispectral Visible Infrared Scanning Radiometer (MVISR), onboard FY-1C&D have had continuous global observation more than 14 years. This data record is valuable for weather prediction, climate monitoring, and environment research. Data quality is vital for satellite data assimilations in Numerical Weather Predic...