CaltechAUTHORS
  A Caltech Library Service

Estimating sampling biases and measurement uncertainties of AIRS/AMSU-A temperature and water vapor observations using MERRA reanalysis

Hearty, Thomas J. and Savtchenko, Andrew and Tian, Baijun and Fetzer, Eric and Yung, Yuk L. and Theobald, Michael and Vollmer, Bruce and Fishbein, Evan and Won, Young-In (2014) Estimating sampling biases and measurement uncertainties of AIRS/AMSU-A temperature and water vapor observations using MERRA reanalysis. Journal of Geophysical Research. Atmospheres, 119 (6). pp. 2725-2741. ISSN 2169-897X. http://resolver.caltech.edu/CaltechAUTHORS:20140825-081520508

[img]
Preview
PDF - Published Version
See Usage Policy.

10Mb
[img] MS Word - Supplemental Material
See Usage Policy.

15Kb
[img]
Preview
Image (JPEG) (Figure S1) - Supplemental Material
See Usage Policy.

2160Kb
[img]
Preview
Image (JPEG) (Figure S2) - Supplemental Material
See Usage Policy.

2873Kb
[img]
Preview
Image (JPEG) (Figure S3) - Supplemental Material
See Usage Policy.

2834Kb
[img]
Preview
Image (JPEG) (Figure S4) - Supplemental Material
See Usage Policy.

3097Kb
[img]
Preview
Image (JPEG) (Figure S5) - Supplemental Material
See Usage Policy.

3051Kb

Use this Persistent URL to link to this item: http://resolver.caltech.edu/CaltechAUTHORS:20140825-081520508

Abstract

We use MERRA (Modern Era Retrospective-Analysis for Research Applications) temperature and water vapor data to estimate the sampling biases of climatologies derived from the AIRS/AMSU-A (Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A) suite of instruments. We separate the total sampling bias into temporal and instrumental components. The temporal component is caused by the AIRS/AMSU-A orbit and swath that are not able to sample all of time and space. The instrumental component is caused by scenes that prevent successful retrievals. The temporal sampling biases are generally smaller than the instrumental sampling biases except in regions with large diurnal variations, such as the boundary layer, where the temporal sampling biases of temperature can be ± 2 K and water vapor can be 10% wet. The instrumental sampling biases are the main contributor to the total sampling biases and are mainly caused by clouds. They are up to 2 K cold and > 30% dry over midlatitude storm tracks and tropical deep convective cloudy regions and up to 20% wet over stratus regions. However, other factors such as surface emissivity and temperature can also influence the instrumental sampling bias over deserts where the biases can be up to 1 K cold and 10% wet. Some instrumental sampling biases can vary seasonally and/or diurnally. We also estimate the combined measurement uncertainties of temperature and water vapor from AIRS/AMSU-A and MERRA by comparing similarly sampled climatologies from both data sets. The measurement differences are often larger than the sampling biases and have longitudinal variations.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://onlinelibrary.wiley.com/doi/10.1002/2013JD021205/abstractPublisherArticle
http://dx.doi.org/10.1002/2013JD021205DOIArticle
http://onlinelibrary.wiley.com/doi/10.1002/2013JD021205/suppinfoRelated ItemSupporting Information
Additional Information:© 2014 American Geophysical Union. Received 14 Nov 2013. Accepted 11 Feb 2014. Accepted article online 14 Feb 2014. Published online 18 Mar 2014. T.H. wishes to acknowledge conversations with Gregory Leptoukh as an early impetus for this work. Also, Ron Gelaro, Mike Bosilovich, Peter Smith, and Dana Ostrenga provided insights into the MERRA data. Glynn Hulley, Suhung Shen, and Zhanqing Li helped us to understand some of the atmospheric and surface phenomena discussed in this paper. John Blaisdel and Joel Susskind helped us to understand aspects of the AIRS/AMSU-A retrieval algorithm relevant to this study. We also acknowledge three anonymous referees who helped us to improve this paper and suggested ideas for future studies. Part of this research was performed at the Jet Propulsion Laboratory (JPL), California Institute of Technology (Caltech), under a contract with the National Aeronautics and Space Administration (NASA). The AIRS/AMSU-A and MERRA data presented in this paper are available from Goddard Earth Sciences Data and Information Services Center (GES DISC; disc.gsfc.nasa.gov).
Funders:
Funding AgencyGrant Number
NASA/JPL/CaltechUNSPECIFIED
Subject Keywords: AIRS/AMSU-A; climatology; sampling; MERRA; temperature; water vapor
Record Number:CaltechAUTHORS:20140825-081520508
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20140825-081520508
Official Citation:Hearty, T. J., A. Savtchenko, B. Tian, E. Fetzer, Y. L. Yung, M. Theobald, B. Vollmer, E. Fishbein, and Y.-I. Won (2014), Estimating sampling biases and measurement uncertainties of AIRS/AMSU-A temperature and water vapor observations using MERRA reanalysis, J. Geophys. Res. Atmos., 119, 2725–2741, doi:10.1002/2013JD021205.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:48829
Collection:CaltechAUTHORS
Deposited By: Ruth Sustaita
Deposited On:25 Aug 2014 15:52
Last Modified:15 Jan 2015 23:58

Repository Staff Only: item control page