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Bootes Field GMRT 153-MHz Source Catalog
The authors obtained deep, high-resolution radio interferometric observations at 153 MHz to complement the extensively studied NOAO Bootes field. In their paper, they provide a description of the observations, data reduction and source catalog construction. From their single-pointing GMRT observation of ~12 hours, they obtained a high-resolution (26" x 22") image of ~11.3 square degrees, fully covering the Bootes field region and beyond. The image has a central noise level of ~1.0 mJy beam<sup>-1</sup>, which rises to 2.0 - 2.5 mJy beam<sup>-1</sup> at the field edge, placing it amongst the deepest ~150 MHz surveys to date. The catalog of 598 extracted sources is estimated to be ~92% complete for > 10 mJy sources, while the estimated contamination by false detections is < 1%. The low rms positional uncertainty of 1.24" facilitates accurate matching against catalogs at optical, infrared and other wavelengths. Differential source counts were determined down to < ~10 mJy. The authors find no evidence for flattening of the counts towards lower flux densities as observed in deep radio surveys at higher frequencies, suggesting that their catalog is dominated by the classical radio-loud AGN population that explains the counts at higher flux densities. Combination with available deep 1.4 GHz observations yields an accurate determination of spectral indices for 417 sources down to the lowest 153 MHz flux densities, of which 16 have ultra-steep spectra with spectral indices below -1.3. The authors confirm that flattening of the median spectral index towards low flux densities also occurs at this frequency. The detection fraction of the radio sources in the NIR K<sub>s</sub>-band is found to drop with radio spectral index, which is in agreement with the known correlation between spectral index and redshift for brighter radio sources. This table contains the list of 598 153-MHz sources detected in the GMRT observation and their properties at this frequency. There are a number of other tables of objects in the Bootes field made at other frequencies: <pre> HEASARC Table | Title | Reference BOOTESDF | 1.4GHz imaging of the Bootes field | de Vries+ 2002,AJ,123,1784 LALABOOCXO | LALA Bootes field X-ray source catalog | Wang+ 2004,AJ,127,213 --- | Faint radio sources in NOAO Bootes field | Wrobel+ 2005,AJ,130,923 --- | 16um sources in the NOAO Bootes field | Kasliwal+ 2005,ApJ,634,L1 XBOOTES | X-ray survey of the NDWFS Bootes field | Kenter+ 2005,ApJS,161,9 XBOOTESOID | Optical counterparts in the NDWFS Bootes | Brand+ 2006,ApJ,64,140 | field | </pre> This table was created by the HEASARC in December 2011 based on <a href="https://cdsarc.cds.unistra.fr/ftp/cats/J/A+A/535/A38">CDS Catalog J/A+A/535/A38</a> file table3.dat. This is a service provided by NASA HEASARC .
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GPM MHS on NOAA-19 (GPROF) Radiometer Precipitation Profiling L2A 1.5 hours 17 km V07 (GPM 2AGPROFNOAA19MHS) at GES DISC
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Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07.The 2AGPROF (also known as, GPM GPROF (Level 2)) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors: GMI, SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18) AMSR2 (GCOM-W1), TMI MHS (NOAA 18&19, METOP A&B), ATMS (NPP), SAPHIR (MT1) This provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are near-realtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided. The GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an a-priori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.
GPM AMSU-B on NOAA17 (GPROF) Climate-based Radiometer Precipitation Profiling L2 1.5 hours 16 km V07 (GPM 2AGPROFNOAA17AMSUB) at GES DISC
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Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07.The 'CLIM' products differ from their 'regular' counterparts (without the 'CLIM' in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series. Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the 'CLIM' output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals.The 2AGPROF (Goddard Profiling) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors:+ TMI (TRMM)+ GMI, (GPM)+ SSMI (DMSP F11, F13, F14, F15); SSMIS (DMSP F16, F17, F18, F19)+ AMSR2 (GCOM-W1)+ MHS (NOAA 18,19)+ MHS (METOP A,B)+ ATMS (NPP)+ SAPHIR (MT1)This provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are nearrealtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided.The GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an apriori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty
GPM ATMS on NOAA-20 (GPROF) Radiometer Precipitation Profiling L2A 1.5 hours 17 km V07 (GPM 2AGPROFNOAA20ATMS) at GES DISC
공공데이터포털
Version 07 is the current version of the data set. The 2AGPROF (also known as, GPM GPROF (Level 2)) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors: GMI, SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18) AMSR2 (GCOM-W1), TMI MHS (NOAA 18&19, METOP A&B), ATMS (SNPP and NOAA-20). This provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are near-realtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided. The GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an a-priori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty.