Open AccessAnalysis of Information Content of Infrared Sounding Radiances in Cloudy Conditions
Author(s) -
Tomoko Koyama,
Tomislava Vukićević,
Manajit Sengupta,
Thomas H. Vonder Haar,
Andrew S. Jones
Publication year - 2006
Publication title -
monthly weather review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.862
H-Index - 179
eISSN - 1520-0493
pISSN - 0027-0644
DOI - 10.1175/mwr3254.1
Subject(s) - depth sounding , environmental science , remote sensing , data assimilation , infrared , geostationary orbit , water vapor , radiative transfer , sky , geostationary operational environmental satellite , cloud fraction , satellite , brightness temperature , brightness , radiance , meteorology , cloud computing , cloud cover , physics , geology , optics , computer science , astronomy , oceanography , operating system
Information content analysis of the Geostationary Operational Environmental Satellite (GOES) sounder observations in the infrared was conducted for use in satellite data assimilation. Information content is defined as a first-order response of the top-of-atmosphere brightness temperature to perturbations of simulated temperature and humidity profiles, obtained from a cloud-resolving model, both in the presence and absence of clouds. Sensitivity to the perturbations was numerically evaluated using an observational operator for visible and infrared radiative transfer developed within a research satellite data assimilation system. The vertical distribution of the sensitivities was analyzed as a function of cloud optical thickness covering the range from a cloud-free scene to an optically thick cloud. The clear-sky sensitivities to temperature and humidity perturbations for each channel are representative of the corresponding channel weighting functions for a clear-sky case. For optically thin–moderate ice clouds, the vertical distributions of the sensitivities resemble clear-sky results, indicating that the use of infrared sounding observations in data assimilation can potentially improve temperature and humidity profiles below those clouds. This result is significant, as GOES infrared sounder data have until now only been used in cloud-cleared scenes. It is expected that the use of sounder data in data assimilation, even in the presence of optically thin to moderate high clouds, will help reduce errors in temperature and water vapor mixing ratio profiles below the clouds.