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  • 11
    Publication Date: 2020-03-20
    Description: The Fundamental Climate Data Record (FCDR) of Microwave Imager Radiances from the Satellite Application Facility on Climate Monitoring (CM SAF) comprises inter-calibrated and homogenized brightness temperatures from the Scanning Multichannel Microwave Radiometer (SMMR), the Special Sensor Microwave/Imager (SSM/I), and the Special Sensor Microwave Imager/Sounder SSMIS radiometers. It covers the time period from October 1978 to December 2015 including all available data from the SMMR radiometer aboard Nimbus-7 and all SSM/I and SSMIS radiometers aboard the Defense Meteorological Satellite Program (DMSP) platforms. SMMR, SSM/I, and SSMIS data are used for a variety of applications, such as analyses of the hydrological cycle, remote sensing of sea ice, or as input into reanalysis projects. The improved homogenization and inter-calibration procedure ensures the long-term stability of the FCDR for climate-related applications. All available raw data records from different sources have been reprocessed to a common standard, starting with the calibration of the raw Earth counts, to ensure a completely homogenized data record. The data processing accounts for several known issues with the instruments and corrects calibration anomalies due to along-scan inhomogeneity, moonlight intrusions, sunlight intrusions, and emissive reflector. Corrections for SMMR are limited because the SMMR raw data records were not available. Furthermore, the inter-calibration model incorporates a scene dependent inter-satellite bias correction and a non-linearity correction in the instrument calibration. The data files contain all available original sensor data (SMMR: Pathfinder level 1b) and metadata to provide a completely traceable climate data record. Inter-calibration and Earth incidence angle normalization offsets are available as additional layers within the data files in order to keep this information transparent to the users. The data record is complemented with noise-equivalent temperatures (NeΔT), quality flags, surface types, and Earth incidence angles. The FCDR together with its full documentation, including evaluation results, is freely available at: https://doi.org/10.5676/EUM_SAF_CM/FCDR_MWI/V003 (Fennig et al., 2017).
    Print ISSN: 1866-3508
    Electronic ISSN: 1866-3516
    Topics: Geosciences
    Published by Copernicus
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  • 12
    Publication Date: 2002-03-05
    Print ISSN: 0941-2948
    Electronic ISSN: 1610-1227
    Topics: Geography , Physics
    Published by Schweizerbart
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  • 13
    Publication Date: 2017-07-31
    Description: Latent heat fluxes (LHF) are one of the main contributors to the global energy budget. As the density of LHF measurements over the global oceans is generally poor, the potential of remotely sensed LHF for meteorological applications is enormous. However, to date none of the available satellite products include estimates of systematic, random retrieval, and sampling uncertainties, all of which are essential for assessing their quality. Here, this challenge is taken on by applying regionally independent multi-dimensional bias analyses to LHF-related parameters (wind speed U, near-surface specific humidity qa, and sea surface saturation specific humidity qs) of the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite (HOAPS) climatology. In connection with multiple triple collocation analyses, it is demonstrated how both instantaneous (gridded) uncertainty measures may be assigned to each pixel (grid box). A high-quality in situ data archive including buoys and selected ships serves as the ground reference. Results show that systematic LHF uncertainties range between 15–50 W m-2 with a global mean of 25 W m-2. Local maxima are mainly found over the subtropical ocean basins as well as along the western boundary currents. Investigations indicate that contributions by qa (U) to the overall LHF uncertainty are in the order of 60 % (25 %). From an instantaneous point of view, random retrieval uncertainties are specifically large over the subtropics with a global average of 37 W m-2. In a climatological sense, their magnitudes become negligible, as do respective sampling uncertainties. Time series analyses show footprints of climate events, such as the strong El Niño during 1997/98. Regional and seasonal analyses suggest that largest total (i.e., systematic + instantaneous random) LHF uncertainties are seen over the Gulf Stream and the Indian monsoon region during boreal winter. In light of the uncertainty measures, the observed continuous global mean LHF increase up to 2009 needs to be treated with caution. First intercomparisons to other LHF climatologies (in situ, satellite) reveal overall resemblance with few, yet distinct exceptions.
    Electronic ISSN: 1867-8610
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 14
    Publication Date: 2016-06-14
    Description: Global ocean precipitation is an important part of the water cycle in the climate system. A number of efforts have been undertaken to acquire reliable estimates of precipitation over the oceans based on remote sensing and reanalysis modelling. However, validation of these data is still a challenging task, mainly due to a lack of suitable in situ measurements of precipitation over the oceans. In this study, validation of the satellite-based Hamburg Ocean Atmosphere Parameters and fluxes from Satellite data (HOAPS) climatology was conducted with in situ measurements by ship rain gauges over the Baltic Sea from 1995 to 1997. The ship rain gauge data are point-to-area collocated against the HOAPS data. By choosing suitable collocation parameters, a detection rate of up to about 70% is achieved. Investigation of the influence of the synoptic situation on the detectability shows that HOAPS performs better for stratiform than for convective precipitation. The number of collocated data is not sufficient to validate precipitation rates. Thus, precipitation rates were analysed by applying an interpolation scheme based on the Kriging method to both data sets. It was found that HOAPS underestimates precipitation by about 10%, taking into account that precipitation rates below 0.3 mm h−1 cannot be detected from satellite information.
    Type: Article , PeerReviewed
    Format: text
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  • 15
    Publication Date: 2019-02-01
    Description: Latent heat fluxes (LHF) play an essential role in the global energy budget and are thus important for understanding the climate system. Satellite-based remote sensing permits a large-scale determination of LHF, which, amongst others, are based on near-surface specific humidity qa. However, the qa random retrieval error (Etot) remains unknown. Here, a novel approach is presented to quantify the error contributions to pixel-level qa of the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite (HOAPS, version 3.2) dataset. The methodology makes use of multiple triple collocation (MTC) analysis between 1995-2008 over the global ice-free oceans. Apart from satellite records, these datasets include selected ship records extracted from the Seewetteramt Hamburg (SWA) archive and the International Comprehensive Ocean-Atmosphere Data Set (ICOADS), serving as the in-situ ground reference. The MTC approach permits the derivation of Etot as the sum of model uncertainty EM and sensor noise EN, while random uncertainties due to in-situ measurement errors (Eins) and collocation (EC) are isolated concurrently. Results show an Etot average of 1.1 ± 0.3 g kg-1, whereas the mean EC (Eins) is in the order of 0.5 ± 0.1 g kg-1 (0.5 ± 0.3 g kg-1). Regional analyses indicate a maximum of Etot exceeding 1.5 g kg-1 within humidity regimes of 12-17 g kg-1, associated with the single-parameter, multilinear qa retrieval applied in HOAPS. Multi-dimensional bias analysis reveals that global maxima are located off the Arabian Peninsula.
    Type: Article , PeerReviewed
    Format: text
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  • 16
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    In:  [Poster] In: EGU General Assembly 2014, 27.04.-02.05.2014, Vienna, Austria .
    Publication Date: 2014-08-11
    Type: Conference or Workshop Item , NonPeerReviewed
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  • 17
    Publication Date: 2022-01-31
    Description: The satellite-derived HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data) precipitation estimates have been validated against in-situ precipitation measurements from optical disdrometers, available from OceanRAIN (Ocean Rainfall And Ice-phase precipitation measurement Network) over the open-ocean by applying a statistical analysis for binary estimates. In addition to using directly collocated pairs of data, collocated data were merged within a certain temporal and spatial threshold into single events, according to the observation times. Although binary statistics do not show perfect agreement, simulations of areal estimates from the observations themselves indicate a reasonable performance of HOAPS to detect rain. However, there are deficits at low and mid-latitudes. Weaknesses also occur when analyzing the mean precipitation rates; HOAPS underperforms in the area of the intertropical convergence zone, where OceanRAIN observations show the highest mean precipitation rates. Histograms indicate that this is due to an underestimation of the frequency of moderate to high precipitation rates by HOAPS, which cannot be explained by areal averaging.
    Type: Article , PeerReviewed
    Format: text
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  • 18
    Publication Date: 2022-05-26
    Description: Author Posting. © American Meteorological Society, 2020. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 33(19), (2020): 8415-8437, doi:10.1175/JCLI-D-19-0954.1.
    Description: Four state-of-the-art satellite-based estimates of ocean surface latent heat fluxes (LHFs) extending over three decades are analyzed, focusing on the interannual variability and trends of near-global averages and regional patterns. Detailed intercomparisons are made with other datasets including 1) reduced observation reanalyses (RedObs) whose exclusion of satellite data renders them an important independent diagnostic tool; 2) a moisture budget residual LHF estimate using reanalysis moisture transport, atmospheric storage, and satellite precipitation; 3) the ECMWF Reanalysis 5 (ERA5); 4) Remote Sensing Systems (RSS) single-sensor passive microwave and scatterometer wind speed retrievals; and 5) several sea surface temperature (SST) datasets. Large disparities remain in near-global satellite LHF trends and their regional expression over the 1990–2010 period, during which time the interdecadal Pacific oscillation changed sign. The budget residual diagnostics support the smaller RedObs LHF trends. The satellites, ERA5, and RedObs are reasonably consistent in identifying contributions by the 10-m wind speed variations to the LHF trend patterns. However, contributions by the near-surface vertical humidity gradient from satellites and ERA5 trend upward in time with respect to the RedObs ensemble and show less agreement in trend patterns. Problems with wind speed retrievals from Special Sensor Microwave Imager/Sounder satellite sensors, excessive upward trends in trends in Optimal Interpolation Sea Surface Temperature (OISST AVHRR-Only) data used in most satellite LHF estimates, and uncertainties associated with poor satellite coverage before the mid-1990s are noted. Possibly erroneous trends are also identified in ERA5 LHF associated with the onset of scatterometer wind data assimilation in the early 1990s.
    Description: FRR, JBR, and MGB acknowledge support for this investigation through the NASA Energy and Water Cycle Study (NEWS), Dr. Jared Entin, Program Manager. MS acknowledges the financial support by the EUMETSAT member states through CM SAF. The NOAA-CIRES-DOE Twentieth Century Reanalysis Project version 3 used resources of the National Energy Research Scientific Computing Center managed by Lawrence Berkeley National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract DE-AC02-05CH11231 and used resources of NOAA’s remotely deployed high-performance computing systems. Support for the Twentieth Century Reanalysis Project version 3 dataset is provided by the U.S. DOE, Office of Science Biological and Environmental Research (BER), by the NOAA Climate Program Office, and by the NOAA Physical Sciences Laboratory. RSS products are supported by funding from the NASA Earth Science Division. H. Tomita acknowledges support from JSPS Grants JP18H03726, JP18H03737, and JP19H05696 and JAXA Announcement EO-2. We gratefully acknowledge provision and institutional support for the following SST datasets: ESA CCI (http://data.ceda.ac.uk/neodc/esacci/sst/data/CDR_v2/); NOAA Optimum Interpolation 1/4 Degree Daily Sea Surface Temperature (OISST) Analysis, version 2, (https:/doi.org/10.7289/V5SQ8XB5); NOAA ERSST v5 (https:/doi.org/10.7289/V5T72FNM) and access to COBE-SST2 provided by the NOAA/OAR/ESRL PSD (boyin.huang@noaa.gov); 20CRv3 data are available at the NERSC Science Tape Gateway via portal.nersc.gov.
    Description: 2021-03-01
    Keywords: Atmosphere-ocean interaction ; Hydrologic cycle ; Microwave observations ; Satellite observations ; Reanalysis data ; Decadal variability
    Repository Name: Woods Hole Open Access Server
    Type: Article
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