# Satellite Climate Data Records: Development, Applications, and Societal Benefits
## 3 CDR Products and Applications
### CDRs and Scientific Applications
#### 3.1.1 NOAA Climate Data Record Program  
The mission of National Oceanic and Atmospheric Administration's (NOAA) Climate Data Record Program (CDRP) is to develop and implement a robust, sustainable, and scientifically defensible approach to producing and preserving climate records from satellite data [3]. The CDR Program provides FCDRs for numerous satellite records and TCDRs for atmospheric, oceanic and terrestrial variables, a few of which are summarized here. The full operational CDRs produced and sustained by NOAA CDRP along with their related documents and source codes can be freely accessed at the CDRP website [37]. * _MSUI/AMSUI brightness temperatures_: These are inter-calibrated brightness temperatures from microwave temperature sounding instruments: Microwave Sounding Unit (MSU)/Advanced Microwave Sounding Unit (AMSU), on-board NOAA and METOP (Meteorological Operational Satellite) operational polar orbiting satellites [38; 39]. These FCDRs are fundamental to climate monitoring because tropospheric and stratospheric temperature changes can be estimated from these datasets [40]. * _AVHRR Reflectance--PATMOS-x_: The PATMOS-x product [32] provides a reflectance CDR for the visible channels of AVHRR on the Polar Operational Satellites (POES) and METOP platforms. Due to its length, the AVHRR data record offers a unique resource for multi-decadal climate studies. PATMOS-x improved the quality of the dataset through work with re-calibrating and re-navigating the data. The resulting TCDRs, such as various cloud properties, provide confidence to climate variability studies over the last 30 years [41]. * _Geostationary Brightness Temperature--GridSat B1_: The Gridded Satellite (GridSat-B1) data [19] facilitates geostationary data usage for a wide range of users. The complete dataset provides data from 3 channels: the CDR-quality infrared window channel (near 11 \(\upmu\)m), the visible channel (near 0.6 \(\upmu\)m) and the infrared water vapor channel (near 6.7 \(\upmu\)m). The three-hourly International Satellite Cloud Climatology Project (ISCCP) B1 data are regridded to a 0.07 degree latitude equal-angle grid, resulting in a CDR that spans from 1980-present. The CDR merges satellites by selecting the nadir-most observations for each grid point. There are wide ranges of applicationsfor this dataset. For example, [PERSON] _et al._[PERSON] et al. (2016) used this data set to derive ITCZ climatology in the East Pacific. * _HIRS Channel 12 Brightness Temperature_: The high-resolution infrared radiation sounder (HIRS) channel 12 (\(\sim\)6.52 \(\upmu\)m) measures upper tropospheric humidity. HIRS level-1b data in conjunction with cloud-clearing, limb-correction, and inter-satellite calibration ([PERSON] et al., 2016) provide necessary inputs to produce the Brightness Temperature FCDR. This dataset is extensively used in climate studies due to the high importance of upper tropospheric humidity in our climate system ([PERSON] et al., 2016). It is worth noting that there is a European Union (EU) project named fidelity and uncertainty in climate data records from earth observations (FIDUCEO ([PERSON] et al., 2016)) which has embarked on creating an FCDR covering all channels of HIRS instrument. * _SSMI(S) Brightness Temperatures_: The FCDR of Special Sensor Microwave Imager/Sounder (SSMI(S)) brightness temperature (Tb) dataset comprises window-channel Tb from a series of 10 microwave radiometers flown on board the Defense Meteorological Satellite Program (DMSP) series of satellites ([PERSON] et al., 2016; [PERSON] et al., 2016; [PERSON] et al., 2016). Six SSM/I instruments first flown on DMSP F08 in July 1987 provide the inter-calibrated data along with the data from four currently operational SSMIS instruments. This FCDR dataset provides input into a number of TCDR products including precipitation, sea surface wind speed, sea ice extent, snow cover, cloud liquid water, and total precipitable water content. Numerous publications have used this dataset to look at climate applications ([PERSON] et al., 2016).