An Extended and Improved Special Sensor Microwave Imager (SSM/I) Period of Record

2010 ◽  
Vol 49 (3) ◽  
pp. 424-436 ◽  
Author(s):  
Hilawe Semunegus ◽  
Wesley Berg ◽  
John J. Bates ◽  
Kenneth R. Knapp ◽  
Christian Kummerow
Keyword(s):  
Passive Microwave ◽  
Sensor Data ◽  
Climatic Data ◽  
International Programs ◽  
Climate Data ◽  
National Climatic Data Center ◽  
Defense Meteorological Satellite Program ◽  
Data Record ◽  
Z Scores ◽  
Microwave Imager

Abstract The National Oceanic and Atmospheric Administration National Climatic Data Center has served as the archive of the Defense Meteorological Satellite Program Special Sensor Microwave Imager (SSM/I) data from the F-8, F-10, F-11, F-13, F-14, and F-15 platforms covering the period from July 1987 to the present. Passive microwave satellite measurements from SSM/I have been used to generate climate products in support of national and international programs. The SSM/I temperature data record (TDR) and sensor data record (SDR) datasets have been reprocessed and stored as network Common Data Form (netCDF) 3-hourly files. In addition to reformatting the data, a normalized anomaly (z score) for each footprint temperature value was calculated by subtracting each radiance value with the corresponding monthly 1° grid climatological mean and dividing it by the associated climatological standard deviation. Threshold checks were also used to detect radiance, temporal, and geolocation values that were outside the expected ranges. The application of z scores and threshold parameters in the form of embedded quality flags has improved the fidelity of the SSM/I TDR/SDR period of record for climatological applications. This effort has helped to preserve and increase the data maturity level of the longest satellite passive microwave period of record while completing a key first step before developing a homogenized and intercalibrated SSM/I climate data record in the near future.

scholarly journals Long-Term Aerosol Climate Data Record Derived from Operational AVHRR Satellite Observations

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
P. K. Chan ◽  
X.-P. Zhao ◽  
A. K. Heidinger
Keyword(s):  
Climate Forcing ◽  
Global Ocean ◽  
Climatic Data ◽  
Climate Data ◽  
Clear Sky ◽  
National Climatic Data Center ◽  
Data Record ◽  
Climate Data Record ◽  
Global Oceans

Aerosol optical thickness (AOT) was retrieved using the Advanced Very High Resolution Radiometer (AVHRR) PATMOS-x Level-2b gridded radiances and the two-channel algorithm of the National Climatic Data Center (NCDC). The primary retrieval product is AOT at 0.63 μm channel. AOT is also retrieved at 0.83 μm or 1.61 μm channel for consistent check. The retrieval was made during day time, under clear sky and snow-free conditions, and over the global oceans. The spatial resolution is 0.1×0.1 degree grid and the temporal resolution is both daily and monthly. The resultant AVHRR AOT climate data record (CDR) spans from August 1981 to December 2009 and provides the longest aerosol CDR currently available from operational satellites. This dataset is useful in studying aerosol climate forcing, monitoring long-term aerosol trends, and evaluating global air pollution and aerosol transport models over the global ocean.

scholarly journals A Fundamental climate data record of SMMR, SSM/I, and SSMIS brightness temperatures

2019 ◽  
Author(s):  
Karsten Fennig ◽  
Marc Schröder ◽  
Axel Andersson ◽  
Rainer Hollmann
Keyword(s):  
Hydrological Cycle ◽  
Sensor Data ◽  
Calibration Model ◽  
Climate Data ◽  
Raw Data ◽  
Brightness Temperatures ◽  
Data Record ◽  
Data Files ◽  
Microwave Imager ◽  
Climate Data Record

Abstract. The Fundamental Climate Data Record (FCDR) of Microwave Imager Radiances from the Satellite Application Facility on Climate Monitoring (CM SAF) comprises inter-calibrated and homogenised 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 Defence 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 homogenisation 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 homogenised 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 to the instrument calibration. The data files contain all available original sensor data (SMMR: Pathfinder Level 1b) and meta-data to provide a completely traceable climate data record. Inter-calibration and Earth incidence angle normalisation 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).

scholarly journals A Fundamental Climate Data Record of SMMR, SSM/I, and SSMIS brightness temperatures

2020 ◽  
Vol 12 (1) ◽  
pp. 647-681 ◽  
Author(s):  
Karsten Fennig ◽  
Marc Schröder ◽  
Axel Andersson ◽  
Rainer Hollmann
Keyword(s):  
Hydrological Cycle ◽  
Sensor Data ◽  
Calibration Model ◽  
Climate Data ◽  
Raw Data ◽  
Brightness Temperatures ◽  
Data Record ◽  
Data Files ◽  
Microwave Imager ◽  
Climate Data Record

Abstract. 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).

scholarly journals The Passive Microwave Neural Network Precipitation Retrieval Algorithm for Climate Applications (PNPR-CLIM): Design and Verification

2021 ◽  
Vol 13 (9) ◽  
pp. 1701
Author(s):  
Leonardo Bagaglini ◽  
Paolo Sanò ◽  
Daniele Casella ◽  
Elsa Cattani ◽  
Giulia Panegrossi
Keyword(s):  
Neural Network ◽  
Passive Microwave ◽  
Retrieval Algorithm ◽  
Climate Data ◽  
High Quality ◽  
Data Record ◽  
Global Precipitation ◽  
Climate Data Record

This paper describes the Passive microwave Neural network Precipitation Retrieval algorithm for climate applications (PNPR-CLIM), developed with funding from the Copernicus Climate Change Service (C3S), implemented by ECMWF on behalf of the European Union. The algorithm has been designed and developed to exploit the two cross-track scanning microwave radiometers, AMSU-B and MHS, towards the creation of a long-term (2000–2017) global precipitation climate data record (CDR) for the ECMWF Climate Data Store (CDS). The algorithm has been trained on an observational dataset built from one year of MHS and GPM-CO Dual-frequency Precipitation Radar (DPR) coincident observations. The dataset includes the Fundamental Climate Data Record (FCDR) of AMSU-B and MHS brightness temperatures, provided by the Fidelity and Uncertainty in Climate data records from Earth Observation (FIDUCEO) project, and the DPR-based surface precipitation rate estimates used as reference. The combined use of high quality, calibrated and harmonized long-term input data (provided by the FIDUCEO microwave brightness temperature Fundamental Climate Data Record) with the exploitation of the potential of neural networks (ability to learn and generalize) has made it possible to limit the use of ancillary model-derived environmental variables, thus reducing the model uncertainties’ influence on the PNPR-CLIM, which could compromise the accuracy of the estimates. The PNPR-CLIM estimated precipitation distribution is in good agreement with independent DPR-based estimates. A multiscale assessment of the algorithm’s performance is presented against high quality regional ground-based radar products and global precipitation datasets. The regional and global three-year (2015–2017) verification analysis shows that, despite the simplicity of the algorithm in terms of input variables and processing performance, the quality of PNPR-CLIM outperforms NASA GPROF in terms of rainfall detection, while in terms of rainfall quantification they are comparable. The global analysis evidences weaknesses at higher latitudes and in the winter at mid latitudes, mainly linked to the poorer quality of the precipitation retrieval in cold/dry conditions.

scholarly journals A multi-sensor data-driven methodology for all-sky passive microwave inundation retrieval

2017 ◽  
Vol 21 (6) ◽  
pp. 2685-2700 ◽  
Author(s):  
Zeinab Takbiri ◽  
Ardeshir M. Ebtehaj ◽  
Efi Foufoula-Georgiou
Keyword(s):  
Rank Correlation ◽  
Nearest Neighbor Search ◽  
Water Levels ◽  
Passive Microwave ◽  
Sensor Data ◽  
Convective Precipitation ◽  
Retrieval Algorithm ◽  
Inversion Method ◽  
Diurnal Variability ◽  
Microwave Imager

Abstract. We present a multi-sensor Bayesian passive microwave retrieval algorithm for flood inundation mapping at high spatial and temporal resolutions. The algorithm takes advantage of observations from multiple sensors in optical, short-infrared, and microwave bands, thereby allowing for detection and mapping of the sub-pixel fraction of inundated areas under almost all-sky conditions. The method relies on a nearest-neighbor search and a modern sparsity-promoting inversion method that make use of an a priori dataset in the form of two joint dictionaries. These dictionaries contain almost overlapping observations by the Special Sensor Microwave Imager and Sounder (SSMIS) on board the Defense Meteorological Satellite Program (DMSP) F17 satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Aqua and Terra satellites. Evaluation of the retrieval algorithm over the Mekong Delta shows that it is capable of capturing to a good degree the inundation diurnal variability due to localized convective precipitation. At longer timescales, the results demonstrate consistency with the ground-based water level observations, denoting that the method is properly capturing inundation seasonal patterns in response to regional monsoonal rain. The calculated Euclidean distance, rank-correlation, and also copula quantile analysis demonstrate a good agreement between the outputs of the algorithm and the observed water levels at monthly and daily timescales. The current inundation products are at a resolution of 12.5 km and taken twice per day, but a higher resolution (order of 5 km and every 3 h) can be achieved using the same algorithm with the dictionary populated by the Global Precipitation Mission (GPM) Microwave Imager (GMI) products.

scholarly journals Fundamental Climate Data Records of Microwave Brightness Temperatures

2018 ◽  
Vol 10 (8) ◽  
pp. 1306 ◽  
Author(s):  
Wesley Berg ◽  
Rachael Kroodsma ◽  
Christian Kummerow ◽  
Darren McKague
Keyword(s):  
Land Surface ◽  
Surface Wind ◽  
Precipitable Water ◽  
Original Data ◽  
Climate Data ◽  
Sea Ice Extent ◽  
Brightness Temperatures ◽  
Precipitation Total ◽  
Data Record ◽  
Microwave Imager

An intercalibrated Fundamental Climate Data Record (FCDR) of brightness temperatures (Tb) has been developed using data from a total of 14 research and operational conical-scanning microwave imagers. This dataset provides a consistent 30+ year data record of global observations that is well suited for retrieving estimates of precipitation, total precipitable water, cloud liquid water, ocean surface wind speed, sea ice extent and concentration, snow cover, soil moisture, and land surface emissivity. An initial FCDR was developed for a series of ten Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) instruments on board the Defense Meteorological Satellite Program spacecraft. An updated version of this dataset, including additional NASA and Japanese sensors, has been developed as part of the Global Precipitation Measurement (GPM) mission. The FCDR development efforts involved quality control of the original data, geolocation corrections, calibration corrections to account for cross-track and time-dependent calibration errors, and intercalibration to ensure consistency with the calibration reference. Both the initial SSMI(S) and subsequent GPM Level 1C FCDR datasets are documented, updated in near real-time, and publicly distributed.

scholarly journals The AMSU-Based Hydrological Bundle Climate Data Record—Description and Comparison with Other Data Sets

2018 ◽  
Vol 10 (10) ◽  
pp. 1640 ◽  
Author(s):  
Ralph Ferraro ◽  
Brian Nelson ◽  
Tom Smith ◽  
Olivier Prat
Keyword(s):  
Land Surface ◽  
Snow Water Equivalent ◽  
Precipitable Water ◽  
Climate Data ◽  
Sea Ice Concentration ◽  
Data Set ◽  
Data Record ◽  
Microwave Imager ◽  
Global Precipitation ◽  
Climate Data Record

Passive microwave measurements have been available on satellites back to the 1970s, first flown on research satellites developed by the National Aeronautics and Space Administration (NASA). Since then, several other sensors have been flown to retrieve hydrological products for both operational weather applications (e.g., the Special Sensor Microwave/Imager—SSM/I; the Advanced Microwave Sounding Unit—AMSU) and climate applications (e.g., the Advanced Microwave Scanning Radiometer—AMSR; the Tropical Rainfall Measurement Mission Microwave Imager—TMI; the Global Precipitation Mission Microwave Imager—GMI). Here, the focus is on measurements from the AMSU-A, AMSU-B, and Microwave Humidity Sounder (MHS). These sensors have been in operation since 1998, with the launch of NOAA-15, and are also on board NOAA-16, -17, -18, -19, and the MetOp-A and -B satellites. A data set called the “Hydrological Bundle” is a climate data record (CDR) that utilizes brightness temperatures from fundamental CDRs (FCDRs) to generate thematic CDRs (TCDRs). The TCDRs include total precipitable water (TPW), cloud liquid water (CLW), sea-ice concentration (SIC), land surface temperature (LST), land surface emissivity (LSE) for 23, 31, 50 GHz, rain rate (RR), snow cover (SC), ice water path (IWP), and snow water equivalent (SWE). The TCDRs are shown to be in general good agreement with similar products from other sources, such as the Global Precipitation Climatology Project (GPCP) and the Modern-Era Retrospective Analysis for Research and Applications (MERRA-2). Due to the careful intercalibration of the FCDRs, little bias is found among the different TCDRs produced from individual NOAA and MetOp satellites, except for normal diurnal cycle differences.

scholarly journals A long-term and reproducible passive microwave sea ice concentration data record for climate studies and monitoring

2013 ◽  
Vol 6 (1) ◽  
pp. 95-117
Author(s):  
G. Peng ◽  
W. N. Meier ◽  
D. J. Scott ◽  
M. H. Savoie
Keyword(s):  
Sea Ice ◽  
Passive Microwave ◽  
Climate Data ◽  
Concentration Data ◽  
Sea Ice Concentration ◽  
Ice Concentration ◽  
Data Record ◽  
Climate Data Record ◽  
Climate Studies

Abstract. A long-term, consistent, and reproducible satellite-based passive microwave sea ice concentration climate data record (CDR) is available for climate studies, monitoring, and model validation with an initial operation capability (IOC). The daily and monthly sea ice concentration data are on the National Snow and Ice Data Center (NSIDC) polar stereographic grid with nominal 25 × 25 km grid cells in both the Southern and Northern Hemisphere Polar Regions from 9 July 1987 to 31 December 2007 with an update through 2011 underway. The data files are available in the NetCDF data format at http://nsidc.org/data/g02202.html and archived by the National Oceanic and Atmospheric Administration (NOAA)'s National Climatic Data Center (NCDC) under the satellite climate data record program (http://www.ncdc.noaa.gov/cdr/operationalcdrs.html). The description and basic characteristics of the NOAA/NSIDC passive microwave sea ice concentration CDR are presented here. The CDR provides similar spatial and temporal variability as the heritage products to the user communities with the additional documentation, traceability, and reproducibility that meet current standards and guidelines for climate data records. The dataset along with detailed data processing steps and error source information can be found at: doi:10.7265/N5B56GN3.

Construction of a climate data record of sea surface temperature from passive microwave measurements

2020 ◽  
Vol 236 ◽  
pp. 111485 ◽  
Author(s):  
Emy Alerskans ◽  
Jacob L. Høyer ◽  
Chelle L. Gentemann ◽  
Leif Toudal Pedersen ◽  
Pia Nielsen-Englyst ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Passive Microwave ◽  
Sea Surface ◽  
Microwave Measurements ◽  
Climate Data ◽  
Data Record ◽  
Climate Data Record
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