Search Results

You are looking at 1 - 2 of 2 items for :

  • Author or Editor: Jennifer Wei x
  • Journal of Atmospheric and Oceanic Technology x
  • Refine by Access: Content accessible to me x
Clear All Modify Search
Feng Ding
,
Andrey Savtchenko
,
Thomas Hearty
,
Jennifer Wei
,
Michael Theobald
,
Bruce Vollmer
,
Baijun Tian
, and
Eric Fetzer

Abstract

The Atmospheric Infrared Sounder (AIRS) on board NASA’s Aqua satellite provides more than 16 years of data. Its monthly gridded (Level 3) product has been widely used for climate research and applications. Since counts of successful soundings in a grid cell are used to derive monthly averages, this averaged by observations (ABO) approach effectively gives equal importance to all participating soundings within a month. It is conceivable then that days with more observations due to day-to-day orbit shift and regimes with better retrieval skills will contribute disproportionately to the monthly average within a cell. Alternatively, the AIRS Level 3 monthly product can be produced through an averaged by days (ABD) approach, where the monthly mean in a grid cell is a simple average of the daily means. The effects of these averaging methods on the AIRS version 6 monthly product are assessed quantitatively using temperature and water vapor at the surface and 500 hPa. The ABO method results in a warmer (slightly colder) global mean temperature at the surface (500 hPa) and a drier global mean water vapor than ABD method. The AIRS multiyear monthly mean temperature and water vapor from both methods are also compared with the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) product and evaluated with a simulation experiment, indicating the ABD method has lower error and is more closely correlated with MERRA-2. In summary, the ABD method is recommended for future versions of the AIRS Level 3 monthly product and more data services supporting Level 3 aggregation are needed.

Free access
Jennifer C. Wei
,
Laura L. Pan
,
Eric Maddy
,
Jasna V. Pittman
,
Murty Divarkarla
,
Xiaozhen Xiong
, and
Chris Barnet

Abstract

Motivated by a significant potential for retrieving atmospheric ozone profile information from advanced satellite infrared sounders, this study investigates various methods to optimize ozone retrievals. A set of retrieval experiments has been performed to assess the impact of different background states (or the a priori states) and retrieval algorithms on the retrieved ozone profiles in the upper troposphere and lower stratosphere (UTLS) using Atmospheric Infrared Sounder (AIRS) measurements. A new tropopause-based ozone climatology, using publicly available global ozonesonde data to construct the a priori state, is described. Comparisons are made with the AIRS version 5 (v5) ozone climatology. The authors also present the result of a newly implemented optimal estimation (OE) algorithm and compare it to the current AIRS science team (AST) algorithm used in version 5. The ozone climatology using tropopause-referenced coordinates better preserves the shape and the magnitude of the ozone gradient across the tropopause, especially in the extratropical region. The results of the retrieval experiments indicate that the tropopause-referenced climatology not only helps to optimize the use of instrument sensitivity in the UTLS region, but it also provides better constraints to the OE algorithm.

Full access