The Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmosphere (PATMOS) Climate Dataset: Initial Analyses and Evaluations

Stowe, Larry L.; Jacobowitz, H.; Ohring, George; Knapp, Kenneth R.; Nalli, Nicholas R.

doi:10.1175/1520-0442(2002)015<1243:tavhrr>2.0.co;2

Cited by 89 publications

(57 citation statements)

References 24 publications

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“…Validations of the individual aerosol satellite retrievals have been performed for several of the satellite products (e.g. Stowe et al, 2002;Torres et al, 2002;Remer et al, 2002;Holzer-Popp et al, 2002b;Kahn et al, 2005;Liu et al 2004). Comparison between the satellite retrievals and the AERONET as a function of time is shown in Fig.…”

Section: Comparison Of Aod Between Aerosol Satellite Retrievals and Amentioning

confidence: 99%

Intercomparison of satellite retrieved aerosol optical depth over ocean during the period September 1997 to December 2000

et al. 2005

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Abstract. Monthly mean aerosol optical depth (AOD) over ocean is compared from a total of 9 aerosol retrievals during a 40 months period. Comparisons of AOD have been made both for the entire period and sub periods. We identify regions where there is large disagreement and good agreement between the aerosol satellite retrievals. Significant differences in AOD have been identified in most of the oceanic regions. Several analyses are performed including spatial correlation between the retrievals as well as comparison with AERONET data. During the 40 months period studied there have been several major aerosol field campaigns as well as events of high aerosol content. It is studied how the aerosol retrievals compare during such circumstances. The differences found in this study are larger than found in a previous study where 5 aerosol retrievals over an 8 months period were compared. Part of the differences can be explained by limitations and deficiencies in some of the aerosol retrievals. In particular, results in coastal regions are promising especially for aerosol retrievals from satellite instruments particularly suited for aerosol research. In depth analyses explaining the differences between AOD obtained in different retrievals are clearly needed. We limit this study to identifying differences and similarities and indicating possible sources that affect the quality of the retrievals. This is a necessary first step towards understanding the differences and improving the retrievals.

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Section: Comparison Of Aod Between Aerosol Satellite Retrievals and Amentioning

confidence: 99%

Intercomparison of satellite retrieved aerosol optical depth over ocean during the period September 1997 to December 2000

et al. 2005

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“…As a result, the fractional cloud cover can differ greatly among various data sets depending upon the threshold values used. As shown by Stowe et al (2002), for example, the (absolute) difference in total cloud cover between ISCCP-D and NOAA/PATHFINDER (PATMOS) is quite large, reaching 15% in the tropics (with ISCCP giving on average 65% total cloud cover and PATMOS giving about 50%) and almost 35% at the poles (with ISCCP-D giving on average 60% total cloud cover and PATMOS 6 giving about 95%). We have therefore run a test to examine the sensitivity of the DLF to possible errors in the cloud data.…”

mentioning

confidence: 99%

Ten-year global distribution of downwelling longwave radiation

Pavlakis

Hatzidimitriou²,

Matsoukas³

et al. 2004

Atmos. Chem. Phys.

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Abstract. Downwelling longwave fluxes, DLFs, have been derived for each month over a ten year period (1984)(1985)(1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993), on a global scale with a spatial resolution of 2.5×2.5 degrees and a monthly temporal resolution. The fluxes were computed using a deterministic model for atmospheric radiation transfer, along with satellite and reanalysis data for the key atmospheric input parameters, i.e. cloud properties, and specific humidity and temperature profiles. The cloud climatologies were taken from the latest released and improved International Satellite Climatology Project D2 series. Specific humidity and temperature vertical profiles were taken from three different reanalysis datasets; NCEP/NCAR, GEOS, and ECMWF (acronyms explained in main text). DLFs were computed for each reanalysis dataset, with differences reaching values as high as 30 Wm −2 in specific regions, particularly over high altitude areas and deserts. However, globally, the agreement is good, with the rms of the difference between the DLFs derived from the different reanalysis datasets ranging from 5 to 7 Wm −2 . The results are presented as geographical distributions and as time series of hemispheric and global averages. The DLF time series based on the different reanalysis datasets show similar seasonal and inter-annual variations, and similar anomalies related to the 86/87 El Niño and 89/90 La Niña events. The global ten-year average of the DLF was found to be between 342.2 Wm −2 and 344.3 Wm −2 , depending on the dataset. We also conducted a detailed sensitivity analysis of the calculated DLFs to the key input data. Plots are given that can be used to obtain a quick assessment of the sensitivity of the DLF to each of the three key climatic quantities, for specific climatic conditions corresponding to different regions of the globe. Our model downwelling fluxes are validated against available data from ground-based stations distributed over the globe, as given by the Baseline Surface Radiation Network.Correspondence to: I. Vardavas (vardavas@iesl.forth.gr) There is a negative bias of the model fluxes when compared against BSRN fluxes, ranging from −7 to −9 Wm −2 , mostly caused by low cloud amount differences between the station and satellite measurements, particularly in cold climates. Finally, we compare our model results with those of other deterministic models and general circulation models.

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“…This measurement system is key (along with the more traditional 11 and 12 µm split-window method) to producing the high precision SST measurements that are the primary aim of the instruments. The dual-view system has also been widely used to separate atmospheric and surface contributions to the top of atmosphere (TOA) signal when using ATSR-2 and AATSR to retrieve aerosol and surface properties (Veefkind et al, 1998;Grey et al, 2006;Thomas et al, 2009a).…”

Section: Atsr-2mentioning

confidence: 99%

“…Therefore the GRAPE aerosol product is derived from the nadir view only. Subsequent development of the ORAC algorithm has included a dual-view aerosol and surface reflectance retrieval (Thomas et al, 2009a) utilising a BRDF description of the surface reflectance, which has been applied to ATSR-2 and part of the GlobAEROSOL project (Portela et al, 2010).…”

Section: Classmentioning

confidence: 99%

“…The time period covered by the GRAPE dataset is almost identical to that covered by the NOAA-14 AVHRR instrument in the GACP dataset. GACP is one of two important aerosol retrievals developed for AVHRR, the second being the Pathfinder Atmosphere (PATMOS) algorithm (Stowe et al, 2002). Several variants of the PATMOS product have been developed and, although they are not included in this study, have been comprehensively compared with the GACP dataset (Zhao et al, 2008).…”

Section: Intercomparison With Gacpmentioning

confidence: 99%

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Validation of the GRAPE single view aerosol retrieval for ATSR-2 and insights into the long term global AOD trend over the ocean

et al. 2010

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Abstract. The Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) project has produced a global dataset of cloud and aerosol properties from the Along Track Scanning Radiometer-2 (ATSR-2) instrument, covering the time period 1995-2001. This paper presents the validation of aerosol optical depths (AODs) over the ocean from this product against AERONET sun-photometer measurements, as well as a comparison to the Advanced Very High Resolution Radiometer (AVHRR) optical depth product produced by the Global Aerosol Climatology Project (GACP).The GRAPE AOD over ocean is found to be in good agreement with AERONET measurements, with a Pearson's correlation coefficient of 0.79 and a best-fit slope of 1.0±0.1, but with a positive bias of 0.08±0.04. Although the GRAPE and GACP datasets show reasonable agreement, there are significant differences. These discrepancies are explored, and suggest that the downward trend in AOD reported by GACP may arise from changes in sampling due to the orbital drift of the AVHRR instruments.

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The Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmosphere (PATMOS) Climate Dataset: Initial Analyses and Evaluations

Cited by 89 publications

References 24 publications

Intercomparison of satellite retrieved aerosol optical depth over ocean during the period September 1997 to December 2000

Intercomparison of satellite retrieved aerosol optical depth over ocean during the period September 1997 to December 2000

Ten-year global distribution of downwelling longwave radiation

Validation of the GRAPE single view aerosol retrieval for ATSR-2 and insights into the long term global AOD trend over the ocean

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