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Improvements In GOES/GOES-R Water Vapor Calibration and Validation


The calibration and validation (Cal/Val) of GOES-R moisture products will be challenging primarily for two reasons. The first is that temperature and humidity retrievals using the limited number of infrared channels on the Advanced Baseline Imager (ABI) will require the use of a numerical weather prediction model to provide the first guess for profile estimation. The second is that the relative absence of independent observations with known or verifiable accuracy and precision limits our ability to validate the observations or products derived from them. Of course, these problems are not unique to GOES-R, and so improvements in our ability to calibrate, validate, and verify satellite and other upperatmospheric observations are important in numerous areas, especially climate monitoring, but also in weather forecasting and research. Over the last several years, NOAA’s Earth System Research Laboratory (ESRL) has investigated the error characteristics of current GOES and GOES-R Proxy total precipitable water (TPW) products by comparing them with TPW retrieved from Global Positioning System observations. In the process, we have compiled evidence of systematic errors in GOES TPW products as well as in the operational numerical weather prediction (NWP) models providing the first guess for these retrievals. This has raised some concern, especially in the climate community which is increasingly dependent on satellite observations to monitor climate change and verify climate model predictions. The reader is referred to Paper 5A.4 by Birkenheuer and Gutman presented to the 18th Conference on Applied Climatology at the 90th Annual Meeting of the AMS. This paper summarizes our major findings and makes specific recommendations to improve both existing GOES water vapor products and those derived from next generation of U.S. environmental satellite sensors in geostationary and polar Earth orbits.

Article / Publication Data
Available Metadata
Accepted On
October 16, 2009
Fiscal Year
Published On
January 01, 2010
Submitted On
March 15, 2021

This publication was presented at the following:

14th Symposium on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land
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