27 August 2008 Validation of the IASI temperature and water vapor profile retrievals by correlative radiosondes
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Proceedings Volume 7081, Earth Observing Systems XIII; 70810J (2008); doi: 10.1117/12.795382
Event: Optical Engineering + Applications, 2008, San Diego, California, United States
Abstract
The METOP-A satellite Infrared Atmospheric Sounding Interferometer (IASI) Level 2 products comprise retrievals of vertical profiles of temperature and water vapor. The L2 data were validated through assessment of their error covariances and biases using radiosonde data for the reference. The radiosonde data set includes dedicated launches as well as the ones performed at regular synoptic times at Lindenberg station (Germany). For optimal error estimate the linear statistical Validation Assessment Model (VAM) was used. The model establishes relation between the compared satellite and reference measurements based on their relations to the true atmospheric state. The VAM utilizes IASI averaging kernels and statistical characteristics of the ensembles of the reference data to allow for finite vertical resolution of the retrievals and spatial and temporal non-coincidence. For temperature retrievals expected and assessed errors are in good agreement; error variances/rms of a single FOV retrieval are 1K between 800 - 300 mb with an increase to ~1K in tropopause and ~2K at the surface, possibly due to wrong surface parameters and undetected clouds/haze. Bias against radiosondes oscillates within ±0 5K . between 950 - 100 mb. As for water vapor, its highly variable complex spatial structure does not allow assessment of retrieval errors with the same degree of accuracy as for temperature. Error variances/rms of a single FOV relative humidity retrieval are between 10 - 13% RH in the 800 - 300 mb range.
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Nikita Pougatchev, Thomas August, Xavier Calbet, Tim Hultberg, Osoji Oduleye, Peter Schlüssel, Bernd Stiller, Karen St. Germain, Gail Bingham, "Validation of the IASI temperature and water vapor profile retrievals by correlative radiosondes", Proc. SPIE 7081, Earth Observing Systems XIII, 70810J (27 August 2008); doi: 10.1117/12.795382; https://doi.org/10.1117/12.795382
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KEYWORDS
Error analysis

Satellites

Humidity

Statistical analysis

Systems modeling

Atmospheric sensing

Data modeling

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