Retrieval of atmospheric and surface parameters from AIRS/AMSU/HSB data in the presence of clouds

By J. Susskind, C. Barnet, J. Blaisdell. IEEE Transactions on Geoscience and Remote Sensing, 2003

793 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/29da1d710625459733b572290e14b45468f5beb6

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. Claire Parkinson
2. Lars Hoffmann
3. M. Alexander
4. Duane Waliser
5. Bin Wang
6. Z. Chen
7. C. Ahn
8. Omar Torres

In Global and Planetary Change

1. Claire Parkinson
2. M. Alexander
3. Lars Hoffmann
4. Duane Waliser
5. Bin Wang
6. Z. Chen
7. C. Ahn
8. Omar Torres

Citations in the corpus

• An overview of the AIRS radiative transfer model (2003, methodology): “Temperature retrievals, for example, use 24 vertical temperature derivatives of the radiance, corresponding to the 24 trapezoid functions discussed in [15].”
• Tropospheric water vapor, convection, and climate (2010, background): “Microwave sensors dedicated to humidity observations and observing at more absorptive wavelengths have been flown since the early 1990’s, starting with the SSMT/2 (Special Sensor Microwave Temperature) and continuing through to HSB (Humidity Sounder for Brazil) and AMSU (Advanced Microwave Sounding ”
• On the determination of atmospheric minor gases by the method of vanishing partial derivatives with application to CO2 (2005, background): “…algorithm employs information from a companion microwave sounder, the Advanced Microwave Sounding Unit (AMSU) to retrieve T(p), q(p), etc. in the presence of clouds on a horizontal scale of one AMSU field of view or 45 45 km at nadir, the equivalent of 3 3 AIRS footprints [Susskind et al., 2003].”
• AIRS/AMSU/HSB on the Aqua mission: design, science objectives, data products, and processing systems (2003, methodology): “Details of the cloud-clearing algorithm are described in [32].”
• Carbon monoxide distributions from the IASI/METOP mission: evaluation with other space-borne remote sensors (2009, methodology): “Tropospheric CO abundances are retrieved from AIRS cloudcleared radiances, utilizing a set of overlapping trapezoidal perturbation functions, similar to the retrieval of all AIRS products (Susskind et al., 2003).”
• Aqua: an Earth-Observing Satellite mission to examine water and other climate variables (2003, methodology): “…for obtaining temperature and moisture profiles from the microwave sounders alone [15], [16], initial temperature and moisture profiles incorporating the infrared data, to be used in operational weather prediction [11], and a full suite of research-quality AIRS/AMSU/HSB data products [4], [17].”
• Vertical Moist Thermodynamic Structure and Spatial-Temporal Evolution of the MJO in AIRS Observations (2006, background): “7 shows an interesting difference between the MJO vertical temperature and moisture structures The preconditioning temperature anomaly is generally found in the lower troposphere (Fig.”
• Atmospheric Radiation Measurement site atmospheric state best estimates for Atmospheric Infrared Sounder temperature and water vapor retrieval validation (2006, methodology): “[31] Validation of products from the new generation of advanced satellite sounders requires correlative data sets”
• Satellite-Based Atmospheric Infrared Sounder Development and Applications (2017, positive): “UTWV products from hyperspectral sounders have also been applied to the study of seasonal variance in monsoon regions (Gettelman et al. 2004), model assessment (Takahashi et al. 2016), and water vapor feedback mechanisms.”
• Global Estimates of CO Sources with High Resolution by Adjoint Inversion of Multiple Satellite Datasets (MOPITT, AIRS, SCIAMACHY, TES) (2009, positive): “However, unlike MOPITT and other instruments in this comparison, AIRS possesses a cloud clearing capability (Susskind et al., 2003, 2010) that enables it to retrieve partly cloudy scenes and thus achieve 70% effective daily coverage.”
• Retrieval of stratospheric temperatures from Atmospheric Infrared Sounder radiance measurements for gravity wave studies (2009, background): “Wave vertical wavelengths and temperature amplitudes of the waves can be determined from the AIRS retrieved temperatures, however the AIRS operational retrievals (Level 2 data) degrade the native resolution of the radiance measurements by factors of 3 3 (along-track cross-track) in order to perform ”
• Improvements to the OMI near-UV aerosol algorithm using A-train CALIOP and AIRS observations (2013, methodology): “The use of cloud-clearing (Chahine et al., 1974) allows the retrievals of global CO for conditions up to 80 % cloudy (Susskind et al., 2003).”
• Validation of Atmospheric Infrared Sounder temperature and water vapor retrievals with matched radiosonde measurements and forecasts (2006, methodology): “With the assumption that the AIRS FOVs differ only in the cloud amount, the cloudclearing procedure discards the data that violate the assumptions and produces cloud-cleared IR radiance product [Susskind et al., 2003].”
• Accuracy of geophysical parameters derived from Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit as a function of fractional cloud cover (2006, methodology): “Figure 7b includes analogous results found in simulation [Susskind et al., 2003].”
• AIRS: Improving Weather Forecasting and Providing New Data on Greenhouse Gases. (2006, methodology): “The physical retrieval algorithm (PRA) (Chahine et al. 2001) forms the basis for the cloud clearing of AIRS radiances within each AMSU footprint and for the retrieval of temperature and water vapor, as described by Susskind et al. (2003).”