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3 edition of Methodology for interpretation of SST retrievals using the AVHRR split window algorithm found in the catalog.

Methodology for interpretation of SST retrievals using the AVHRR split window algorithm

Methodology for interpretation of SST retrievals using the AVHRR split window algorithm

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Published by National Aeronautics and Space Administration, Goddard Space Flight Center in Greenbelt, Md .
Written in English

    Subjects:
  • Algorithms.,
  • Ocean temperature.

  • Edition Notes

    StatementR.W. Barbieri, C.N. McClain and D.L. Endres.
    SeriesNASA technical memorandum -- 85100.
    ContributionsEndres, D. L., McClain, C. R., Goddard Space Flight Center.
    The Physical Object
    FormatMicroform
    Pagination1 v.
    ID Numbers
    Open LibraryOL17658505M

    Generalized Split- Window Algorithm for Retrieving LST (Wan, ) Wan proposes a generalized split-window method for retrieving land-surface temperature (LST) from AVHRR and MODIS data. Accurate radiative transfer simulations show that the coefficients of this LST algorithm depends on viewing angle, if we are to achieve a LST. A methodology to obtain the sea surface temperature (SST) in the Canary-Azores-Gibraltar area has been developed. The final accuracy of the AVHRR-based SST retrievals depends both on the accuracy of the measured radiance and the accuracy of the SST retrieval algorithm that converts the measured radiance into sea surface temperature.

    The Advanced Very High Resolution Radiometer (AVHRR) of the National Oceanic and Atmospheric Administration (NOAA)’s satellite was the first sensor successfully used to compute SST following the development and validation of the atmospheric correction algorithm known as “split-window”. 15) with total average of scenes per day. Multichannel sea surface temperature (MCSST) “split window” algorithm [McClain et al., ] was used to estimate the SST values for both daytime and nighttime scenes: TS = a0 + a1T4 + a2(T4 – T5) + a3(T4 – T5)(secθ - 1) where TS is the SST in °C, T4 and T5 are the AVHRR channels 4 and 5.

    This article taking coastal waters of Lianyungang as the research area, and by using MODIS images during 15 April and 1 May, as source data, and the results of sea surface temperature were extracted by band operation, and by using changes in the different time of SST, spatial variation and comparative analysis to verify the accuracy of the two algorithms. or K using broadband split-window data provided that the a priori surface emissivity spectrum has a bias less than %. As for LST retrieval, simple extension to LST using the algorithm originally developed for SST would lead to unacceptable errors. Wan and Dozier6 analyzed the major difficulties in.


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Methodology for interpretation of SST retrievals using the AVHRR split window algorithm Download PDF EPUB FB2

Methodology for interpretation of SST retrievals using the AVHRR split window algorithm [microform] / R.W. Barbieri, C.N. McClain and D.L. Endres National Aeronautics and Space Administration, Goddard Space Flight Center Greenbelt, Md.

Methodology for interpretation of SST retrievals using the AVHRR split window algorithm products derived from the operational NOAA-7 AVHRR-II algorithm and in situ observations are made. The data sets consist of ship survey data during the winter from the Mid-Atlantic Bight (MAB), ship and buoy measurements during April and September.

The RMSE of the derived results is within K. The accuracy of the algorithm is good in theory. However, the RMSE of the algorithm with wvc is K, which is smaller than the RMSE of the algorithm without wvc. It shows that the method proposed in the paper is effective.

This paper has improved the method of split-window algorithm to Author: Jiaoqi Fu, Chao Chen, Biyun Guo, Yanli Chu, Hong Zheng. (), by using the split-window algorithm, determine SST in midlatitudes from NOAA-AVHRR data. The accuracy achieved for SST is °K, which is the limit accuracy that can be obtained from AVHRR measurements over midlatitudes.

In this section we briefly describe a theoretical split-window model for LST retrieval from AVHRR data. Later, a method- ology is proposed and justified for deriving the split-window coefficients of the model by using SST matchups.

Theoretical Model The split-window model used in this paper has been given already by Collet al. The results of preliminary tests of a two-window method using AVHRR measurements from NOAA-6 were verified against buoy and XBT temperatures and yielded root mean square differences of about K.

2. Split Window Algorithm (SWA) The SWA was first proposed by McMillin [] who suggested using the differences in the atmospheric absorbance of two adjacent LWIR bands in order to accurately retrieve the sea surface temperature (SST).In order to make the transition from SST to LST retrieval, one has to assume the land surface emissivity (LSE) in both bands a priori [].

A form of the split-window algorithm was applied to generate the most often used long time series AVHRR SST product from the Pathfinder project (Kilpatrick et al., ; Casey et al., ).

AVHRR SST is a global 4 km daily. Since the late s, SST retrievals in cloud-free areas can be combined into weekly, monthly, and yearly SST fields. The same regression analysis method.

from PGS of FY-3C are used to estima te FY-3C/VIRR SST. The split window MCSST algorithm is used to using advanced very high resolution radiometer. Cold-biased NLSST (MODIS, AVHRR, and VIIRS) and triple-window (AVHRR and VIIRS only) SST retrievals are modeled based on operational algorithms using radiative transfer model simulations conducted with a hypothetical km-thick OTC cloud placed incrementally from to km above mean sea level for cloud optical depths between and Get this from a library.

Methodology for interpretation of SST retrievals using the AVHRR split window algorithm. [R W Barbieri; D L Endres; C R McClain; Goddard Space Flight Center.]. [1] Volcanic ash in volcanic clouds can be mapped in two dimensions using two‐band thermal infrared data available from meteorological satellites.

Wen and Rose developed an algorithm that allows retrieval of the effective particle size, the optical depth of the volcanic cloud, and the mass of fine ash in the cloud. Both the mapping and the retrieval scheme are less accurate in the humid.

In the next section, we propose a split-window equation with a single functional form, which includes an emissivity term and can be used with both SEVIRI and AVHRR scenes. Using only the empirical satellite brightness temperatures, we have devised a method to obtain angle.

Operational sea surface temperature (SST) retrieval algorithms are stratified into nighttime and daytime. The nighttime algorithm uses two split-window Visible Infrared Imaging Radiometer Suite (VIIRS) bands—M15 and M16, centered at ~11 and ~12 m, respectively—and a shortwave infrared band—M12, centered at ~ m.

The M12 is most transparent and critical for accurate SST retrievals. our method for SST retrievals are described in section 3.

split) and triple-window algorithm, and of the water vapor algorithms. The first is the nonlinear sea surface temperature NOAA/NASA advanced very high resolution radiometer Pathfinder algorithm for sea surface temperature and associated matchup database, J. Geophys. Res., Here, it is extended to estimate the accuracy of the split-window sea surface temperature and atmospheric water vapor retrievals from NOAA-9 over the tropical and North Atlantic in July The authors confirm the previously drawn conclusion that in a general case no angle-independent coefficients in a linear SST retrieval algorithm can.

Single-channel algorithms for satellite thermal-infrared- (TIR-) derived land and sea surface skin temperature (LST and SST) are advantageous in that they can be easily applied to a variety of satellite sensors.

They can also accommodate decade-spanning instrument series, particularly for periods when split-window capabilities are not available. However, the benefit of one unified retrieval. Meanwhile, the LST retrieval technology from remote sensing data made a great progress, and various methods have been proposed, such as single channel method [6, 7], split-window (SW) method [8–12], temperature emissivity separation (TES) method, and multichannel method.

LST, methods for its estimation from space have continuously been developed [12]. For example, sensors, such as the Advanced Very High Resolution Radiometer (AVHRR) [13] and the Moderate-resolution Imaging Spectroradiometer (MODIS) [14], have provided public domain global thermal data twice daily, using two longwave.

SST data: AVHRR Pathfinder v, NOAA NODC "The AVHRR Pathfinder Version (PFV52) data set was computed using an entirely modernized system, based on SeaDAS and incorporating several key changes over the older Pathfinder V and V datasets. PFV52 is viewed as a significant step forward in preparation for the future Version 6 (PFV6) data set.

ature. Sea and land surface temperature (SST and LST) temperatures used in the retrieval of snow-covered ice retrieval algorithms have been developed by using the surface temperature from the split-window thermal thermal infrared window portion of the spectrum, with the channels of the advanced very high resolution radiometer.Kerr, Y.H., J.P.

Lagouarde and J. Imbernon (): Accurate Land Surface Temperature Retrieval from AVHRR Data with Use of an Improved Split Window Algorithm. Remote Sensing of Environment, 41, – CrossRef Google Scholar.Atmospheric effects on estimated LST are described and atmospheric-correction using a radiative transfer model (RTM) is explained.

The methods discussed are the single channel method, the split window techniques (SWTs), and the multi-angle method.