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Title: Retrieving Temperature and Moisture Profiles from AERI Radiance Observations: AERIPROF Value-Added Product Technical Description Revision 1

Abstract

This document explains the procedure to retrieve temperature and moisture profiles from high-spectral resolution infrared radiance data measured by the U.S. Department Of Energy (DOE) Atmospheric Radiation (ARM) Program’s atmospheric emitted radiance interferometer (AERI) instrument. The technique has been named the AERIPROF thermodynamic retrieval algorithm. The software has been developed over the last decade at the University of Wisconsin-Madison and has matured into an ARM Value-Added Procedure. This document will describe the AERIPROF retrieval procedure, outline the algorithm routines, discuss the software heritage, and, finally, provide references with further documentation.

Authors:
; ; ; ; ; ; ; ; ;
Publication Date:
Research Org.:
DOE Office of Science Atmospheric Radiation Measurement (ARM) Program
Sponsoring Org.:
USDOE
OSTI Identifier:
948526
Report Number(s):
DOE/SC-ARM/TR-066.1
R&D Project: 15990; TRN: US200909%%263
DOE Contract Number:
DE-AC05-76RL01830
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 97 MATHEMATICS AND COMPUTING; ALGORITHMS; DOCUMENTATION; INTERFEROMETERS; MOISTURE; SOLAR RADIATION; RESOLUTION; TEMPERATURE DISTRIBUTION; DATA PROCESSING; COMPUTER CALCULATIONS

Citation Formats

WF Feltz, HB Howell, RO Knuteson, JM Comstock, R Mahon, DD Turner, WL Smith, HM Woolf, C Sivaraman, and TD Halter. Retrieving Temperature and Moisture Profiles from AERI Radiance Observations: AERIPROF Value-Added Product Technical Description Revision 1. United States: N. p., 2007. Web. doi:10.2172/948526.
WF Feltz, HB Howell, RO Knuteson, JM Comstock, R Mahon, DD Turner, WL Smith, HM Woolf, C Sivaraman, & TD Halter. Retrieving Temperature and Moisture Profiles from AERI Radiance Observations: AERIPROF Value-Added Product Technical Description Revision 1. United States. doi:10.2172/948526.
WF Feltz, HB Howell, RO Knuteson, JM Comstock, R Mahon, DD Turner, WL Smith, HM Woolf, C Sivaraman, and TD Halter. Mon . "Retrieving Temperature and Moisture Profiles from AERI Radiance Observations: AERIPROF Value-Added Product Technical Description Revision 1". United States. doi:10.2172/948526. https://www.osti.gov/servlets/purl/948526.
@article{osti_948526,
title = {Retrieving Temperature and Moisture Profiles from AERI Radiance Observations: AERIPROF Value-Added Product Technical Description Revision 1},
author = {WF Feltz and HB Howell and RO Knuteson and JM Comstock and R Mahon and DD Turner and WL Smith and HM Woolf and C Sivaraman and TD Halter},
abstractNote = {This document explains the procedure to retrieve temperature and moisture profiles from high-spectral resolution infrared radiance data measured by the U.S. Department Of Energy (DOE) Atmospheric Radiation (ARM) Program’s atmospheric emitted radiance interferometer (AERI) instrument. The technique has been named the AERIPROF thermodynamic retrieval algorithm. The software has been developed over the last decade at the University of Wisconsin-Madison and has matured into an ARM Value-Added Procedure. This document will describe the AERIPROF retrieval procedure, outline the algorithm routines, discuss the software heritage, and, finally, provide references with further documentation.},
doi = {10.2172/948526},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Apr 30 00:00:00 EDT 2007},
month = {Mon Apr 30 00:00:00 EDT 2007}
}

Technical Report:

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  • One of the goals of the Atmospheric Radiation Measurement (ARM) Program is to collect a long-term series of radiative and atmospheric state observations to improve the parameterization of these processes in global climate models. The ARM Program intended to move away from the traditional approach of directly measuring profiles of temperature and moisture using radiosondes, which is expensive in terms of expendables and manpower, and develop methods to retrieve these profiles with ground-based remote sensors. The atmospheric emitted radiance interferometer (AERI), whose radiance data contains information on the vertical distribution of water vapor and temperature, is an integral part ofmore » the ARM profiling plan.« less
  • This technical report provide a short description of the application of the principle component analysis techniques to remove uncorrelated random noise from ground-based high spectral resolution infrared radiance observations collected by the atmospheric emitted radiance interferometers (AERIs) deployed by the Atmospheric Radiation Measurement (ARM) Program. A general overview of the technique, the input, and output datastreams of the newly generated value-added product, and the data quality checks used are provided. A more complete discussion of the theory and results is given in Turner et al. (2006).
  • The purpose of this document is to describe the Raman Lidar Profiles–Temperature (RLPROFTEMP) value-added product (VAP) and the procedures used to derive atmospheric temperature profiles from the raw RL measurements. Sections 2 and 4 describe the input and output variables, respectively. Section 3 discusses the theory behind the measurement and the details of the algorithm, including calibration and overlap correction.
  • This report provides a short description of the Atmospheric Radiation Measurement (ARM) Climate Research Facility microwave radiometer (MWR) Retrieval (MWRRET) value-added product (VAP) algorithm. This algorithm utilizes a complementary physical retrieval method and applies brightness temperature offsets to reduce spurious liquid water path (LWP) bias in clear skies resulting in significantly improved precipitable water vapor (PWV) and LWP retrievals. We present a general overview of the technique, input parameters, output products, and describe data quality checks. A more complete discussion of the theory and results is given in Turner et al. (2007b).
  • The ARM Raman lidars are semi-autonomous ground-based systems that transmit at a wavelength of 355 nm with 300 mJ, {approx}5 ns pulses, and a pulse repetition frequency of 30Hz. Signals from the various detection channels are processed to produce time- and height-resolved estimates of several geophysical quantities, such as water vapor mixing ratio, relative humidity, aerosol scattering ratio, backscatter, optical depth, extinction, and depolarization ratio. Data processing is currently handled by a suite of six value-added product (VAP) processes. Collectively, these processes are known as the Raman Lidar Profiles VAP (RLPROF). The top-level best-estimate (BE) VAP process was introduced inmore » order to bring together the most relevant information from the intermediate-level VAPs. As such, the BE process represents the final stage in data processing for the Raman lidar. Its principal function is to extract the primary variables from each of the intermediate-level VAPs, perform additional quality control, and combine all of this information into a single output file for the end-user. The focus of this document is to describe the processing performed by the BE VAP process.« less