Information content of a far-Infrared radiometer and its complementarity to AIRS with a focus on polar regions
Abstract
Current observations used in numerical weather prediction systems come mostly from spaceborne thermal infrared sounders such as AIRS, IASI and CrIS. However, the thermal infrared only constitutes half of the Earth's emitted radiance, the other half being the far infrared (far-IR), ranging from 15 to 100 μm. In recent years, some theoretical studies have shown the added-value of far-IR observations for remote sensing of water vapor and clouds, especially in dry and cold regions. Satellite missions sounding in the far-IR, such as TICFIRE, FORUM and PREFIRE, are also emerging from various space agencies.
In this study, the objectives were to evaluate the potential of far-IR spaceborne measurements to provide information for temperature and humidity and to analyze the optimal trade-off between spectral and radiometric resolution. A radiometer was used since it allows to have bands with different spectral widths, which means that the bands can be selected where the Jacobians are strongest. A simple 1D framework was used to compare the impact of far-IR and mid-IR measurements through the reduction of the analysis error variance obtained by assimilating those. Information content (or Degrees of Freedom per Signal, DFS) was used as the metric to examine synthetic measurements for different number and widths of spectral bands, and measurement error. The results indicate that a few broader bands in the far-IR bring as much information as AIRS. Also, there is a complementarity in assimilating measurements in the far-IR and measurements in the mid-IR, since the DFS increases when far-IR measurements were assimilated on top of AIRS. It was shown that too many bands with a large noise do not give enough information on the atmosphere.- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2020
- Bibcode:
- 2020AGUFMA239...08C
- Keywords:
-
- 3305 Climate change and variability;
- ATMOSPHERIC PROCESSES;
- 3310 Clouds and cloud feedbacks;
- ATMOSPHERIC PROCESSES;
- 3359 Radiative processes;
- ATMOSPHERIC PROCESSES;
- 3360 Remote sensing;
- ATMOSPHERIC PROCESSES