A statistically optimal analysis of systematic differences between Aeolus horizontal line-of-sight winds and NOAA's Global Forecast System

H. Liu; H. Liu; K. Garrett; K. Ide; R. N. Hoffman; R. N. Hoffman; K. E. Lukens; K. E. Lukens

doi:10.5194/amt-15-3925-2022

Atmospheric Measurement Techniques (Jul 2022)

A statistically optimal analysis of systematic differences between Aeolus horizontal line-of-sight winds and NOAA's Global Forecast System

H. Liu,
H. Liu,
K. Garrett,
K. Ide,
R. N. Hoffman,
R. N. Hoffman,
K. E. Lukens,
K. E. Lukens

Affiliations

H. Liu: NOAA/NESDIS/Center for Satellite Applications and Research (STAR), College Park, MD 20740, USA
H. Liu: Cooperative Institute for Satellite Earth System Studies (CISESS), University of Maryland, College Park, MD 20740, USA
K. Garrett: NOAA/NESDIS/Center for Satellite Applications and Research (STAR), College Park, MD 20740, USA
K. Ide: Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD 20740, USA
R. N. Hoffman: NOAA/NESDIS/Center for Satellite Applications and Research (STAR), College Park, MD 20740, USA
R. N. Hoffman: Cooperative Institute for Satellite Earth System Studies (CISESS), University of Maryland, College Park, MD 20740, USA
K. E. Lukens: NOAA/NESDIS/Center for Satellite Applications and Research (STAR), College Park, MD 20740, USA
K. E. Lukens: Cooperative Institute for Satellite Earth System Studies (CISESS), University of Maryland, College Park, MD 20740, USA

DOI: https://doi.org/10.5194/amt-15-3925-2022
Journal volume & issue: Vol. 15
pp. 3925 – 3940

Abstract

Read online

The European Space Agency Aeolus mission launched a first-of-its-kind spaceborne Doppler wind lidar in August 2018. To optimize the assimilation of the Aeolus Level-2B (B10) horizontal line-of-sight (HLOS) winds, significant systematic differences between the observations and numerical weather prediction (NWP) background winds should be removed. Total least squares (TLS) regression is used to estimate speed-dependent systematic differences between the Aeolus HLOS winds and the National Oceanic and Atmospheric Administration (NOAA) Finite-Volume Cubed-Sphere Global Forecast System (FV3GFS) 6 h forecast winds. Unlike ordinary least squares regression, TLS regression optimally accounts for random errors in both predictors and predictands. Large, well-defined, speed-dependent systematic differences are found in the lower stratosphere and troposphere in the tropics and Southern Hemisphere. Correction of these systematic differences improves the forecast impact of Aeolus data assimilated into the NOAA global NWP system.

Published in Atmospheric Measurement Techniques

ISSN: 1867-1381 (Print); 1867-8548 (Online)
Publisher: Copernicus Publications
Country of publisher: Germany
LCC subjects: Technology: Engineering (General). Civil engineering (General): Environmental engineering; Technology: Engineering (General). Civil engineering (General): Earthwork. Foundations
Website: http://www.atmospheric-measurement-techniques.net/home.html

About the journal