Jinxue Wang

Retrieval of CO from nadir remote-sensing measurements in the infrared by use of four different inversion algorithms

Four inversion schemes based on various retrieval approaches (digital gas correlation, nonlinear least squares, global fit adjustment, and neural networks) developed to retrieve CO from nadir radiances measured by such downward-looking satelliteborne instruments as the Measurement of Pollution in the Troposphere (MOPITT), the Tropospheric Emission Spectrometer (TES), and the Infrared Atmospheric Sounding Interferometer (IASI) instruments were compared both for simulated cases and for atmospheric spectra recorded by the Interferometric Monitor for Greenhouse Gases (IMG). The sensitivity of the retrieved CO total column amount to properties that may affect the inversion accuracy (noise, ancillary temperature profile, and water-vapor content) was investigated. The CO column amounts for the simulated radiance spectra agreed within 4%, whereas larger discrepancies were obtained when atmospheric spectra recorded by the IMG instrument were analyzed. The assumed vertical temperature profile is shown to be a critical parameter for accurate CO retrieval. The instruments line shape was also identified as a possible cause of disagreement among the result provided by the groups of scientist who are participating in this study.

Reviewing atmospheric radiative transfer modeling: new developments in high- and moderate-resolution FASCODE/FASE and MODTRAN

Spectrally uniform treatment of the atmospheric radiative transfer (RI) problem has been approached through two different techniques - very high resolution line-by-line (LBL) algorithms and lower resolution band models (BM). Each has its advantages and specific applications. However, if commonality and validation of a specific pair of RI approaches is to be mutually maintained, then these codes must be continually reevaluated against both measurements and other models.

Instrument Sensitivity and Error Analysis for the Remote Sensing of Tropospheric Carbon Monoxide by MOPITT

Abstract Measurement of Pollution in the Troposphere (MOPITT) is an eight-channel gas correlation radiometer selected for the Earth Observing System AM-1 platform to be launched in 1999. Its primary objectives are the measurement of tropospheric carbon monoxide (CO) and methane (CH4). In this paper, the sensitivities of instrument signals and CO retrieval errors to various instrument parameters, especially the gas cell pressure and temperature variations, instrument radiometric noise, and ancillary data errors (such as atmospheric temperature and water vapor profile errors), are presented and discussed. In the MOPITT pressure modulator cell pressure sensitivity study, the instrument calibration process is considered, which leads to the relaxation of previous stringent requirements on the accuracy of in-orbit cell pressure monitoring. The approach of MOPITT CO retrieval error analysis is described, and the error analysis results are compared with retrieval simulation statistics. The error analysis results ...

Retrieval of Tropospheric Carbon Monoxide Profiles from High-Resolution Interferometer Observations: A New Digital Gas Correlation (DGC)Method and Applications

Abstract Global tropospheric carbon monoxide (CO) distributions can be retrieved from observations by spaceborne gas correlation radiometers and high-resolution interferometers. The Measurement of Pollution in the Troposphere (MOPITT) is a gas correlation radiometer designed for tropospheric CO and CH4 remote sensing. It is being developed at the University of Toronto and the National Center for Atmospheric Research for launch on the EOS/AM-1 platform in 1999. Spaceborne high-resolution interferometers with troposphere CO remote sensing capability include the Interferometric Monitor for Greenhouse gases (IMG) instrument and the Troposphere Emission Spectrometer (TES). IMG was developed by the Ministry of International Trade and Industry (MITI) of Japan. It was on the ADEOS-1 spacecraft launched in October 1996. TES is being developed by the Jet Propulsion Laboratory for launch on the EOS/CHEM-1 platform in 2002. For the purpose of testing the MOPITT data processing algorithms before launch, a new digital ...

Retrieval of tropospheric carbon monxide profiles from MOPITT: algorithm description and retrieval simulation

The Measurement of Pollution in the troposphere (MOPITT) instrument is an eight-channel gas correlation radiometer to be launched on the Earth Observing System (EOS) Terra spacecraft in 1999. Its main measurement objectives are tropospheric carbon monoxide (CO) profiles and total column. This paper gives a detailed description of MOPITT CO retrieval algorithm, which derives total CO column and tropospheric CO mixing ratios at a number of atmospheric pressure levels from MOPITT radiance observations. Retrieval performance evaluation using simulated MOPITT data are discussed.

Validation Study of the MOPITT Retrieval Algorithm: Carbon Monoxide Retrieval from IMG Observations during WINCE

Abstract The Measurement of Pollution in the Troposphere (MOPITT) instrument is an eight-channel gas correlation radiometer selected for the Earth Observing System (EOS) Terra spacecraft launched in December 1999. Algorithms for the retrieval of tropospheric carbon monoxide (CO) profiles from MOPITT measurements have been developed. In this paper, validation studies of the MOPITT CO retrieval algorithm using observations by the Interferometric Monitor for greenhouse Gases (IMG) during the Winter Clouds Experiment (WINCE) conducted from 23 January to 13 February 1997 are described. Synthetic radiance spectra calculated by a line-by-line radiative transfer model, FASCOD3, using the retrieved CO profile agrees well with IMG-measured radiance spectra. Observations by the Moderate Resolution Imaging Spectrometer (MODIS) Airborne Simulator (MAS) from the NASA ER-2 platform during WINCE were successfully used to assist in the identification of clear and cloudy IMG observations.

Analysis and characterization of the retrieval algorithm for measuring tropospheric CO using the MOPITT instrument

We have developed a retrieval algorithm for deriving the tropospheric CO profile and column amount from the radiances measured by the Measurements of Pollution in the troposphere instrument. The main components of the algorithm are a fast radiative transfer model, based on the GENLN2 line-by-line model, and a maximum likelihood inversion method. The retrieval a priori information is derived from the results of several aircraft in situ measurements and a 3D chemical- transport model. This paper discusses the CO retrieval algorithm with an emphasis on the analysis and characterization of the algorithm. Forward model and retrieval sensitivities, along with the a priori information used in the retrieval are discussed in terms of their orthogonal components. Examples of ensemble retrieval experiments are also included.

Retrieval of tropospheric methane from MOPITT measurements: algorithm description and simulations

Tropospheric concentrations of methane have been increasing at a rate of approximately 1%/year, though recent measurements suggest some slowing in this trend. Increased concentrations of methane, a greenhouse gas, will have significant consequences for tropospheric chemistry and climate on a global scale. Characterization of the spatial and temporal variability of methane is one goal of the MOPITT (Measurement of Pollution In The Troposphere) instrument included on the EOS Terra satellite. This instrument includes spectral channels designed to measure methane total column with approximately 1% precision with a spatial resolution of approximately 22 X 22 km. Retrieval of the methane total column will be accomplished by the MOPITT instrument from measurements of solar radiation reflected at the earths surface. Gas correlation radiometry will be used to separate the spectral signature of methane in the upwelling radiance from features produced by other trace gases. The retrieval algorithm is based on maximum likelihood and uses an initial guess profile and methane total column variance estimates provided by aircraft in-situ measurements. In this talk, we will describe features of the retrieval algorithm in detail and present results of retrieval simulations conducted to test the sensitivity of the retrieval algorithm to various sources of error.

EOS MOPITT experiment: extracting the information from the measurements

This paper will serve as an overview of the challenges to the recovery of information on atmospheric CO and CH4 from the measurements made by the MOPITT instrument that has been described by Drummond et al. It will also provide a context and introduction to several of the following papers that go into greater detail on particular topics, and outline plans for the data processing. Here we briefly outline the principles of correlation radiometry as used by MOPITT, and introduce the principles behind the retrievals. After noting plans for data processing, we discuss our approach to data validation, and the ability to see global distributions of CO in the MOPITT data.

Remote sensing of tropospheric carbon monoxide amd methane from space by MOPITT: validation plan and prelaunch activities

The measurement of pollution in the troposphere (MOPITT) is an eight-channel gas correlation radiometer to be launched on EOS/AM1 spacecraft in 1999. The goal of the experiment is to support studies of the oxidizing capacity of the lower atmosphere on large scales by measuring the global distributions of carbon monoxide (CO) and methane and thus, will represent a significant advancement in the application of space based remote sensing to global tropospheric chemistry research. Validation of data processing algorithms and products is an essential component of the MOPITT project. Strategies and techniques to verify MOPITT measurement precision, accuracy, and resolutions will be described. Correlative measurements for MOPITT algorithm and data validation include measurements will be described. Correlative measurements for MOPITT algorithm and data validation include measurements by airborne remote sensing and in-situ techniques and ground-based spectroscopic techniques. The MOPITT data processing algorithms are being tested and validated using existing airborne and satellite observations before launch. Pre-launch validation campaigns have been conducted to intercompare different correlative measurement techniques and associated data processing algorithms.