In situ data: ICOADS2.5 before 2007 and NCEP in situ data from 2008 to present. Ice data: HadISST ice before 2010 and NCEP ice after 2010.

The NOAA Global Surface Temperature Dataset (NOAAGlobalTemp) is a merged land&ocean surface temperature analysis (formerly known as
MLOST) It is a spatially gridded (5° - 5°) global surface temperature dataset, with monthly resolution from January 1880
to present. We combine a global sea surface (water) temperature (SST) dataset with a global land surface air temperature dataset into this merged
dataset of both the Earth's and land's and ocean surface temperatures. The SST dataset is the Extended Reconstructed Sea Surface Temperature

Subjectively identified areas of large-scale organized convection over the global tropics (25N-25S) have been gridded daily for a 15-year period from 1971 to 1988.

Data is interpolated in time and space from NOAA twice-daily OLR values and averaged to once daily

The optimum interpolation (OI) sea surface temperature (SST) analysis is produced weekly on a one-degree grid. The analysis uses in situ and
satellite SST's plus SST's simulated by sea-ice cover. Before the analysis is computed, the satellite data is adjusted for biases using the
method of Reynolds (1988) and Reynolds and Marsico (1993). Monthly data is calculated by interpolating weekly data to daily and then producing
monthly values.

The ocean atlas contains annual, seasonal, and monthly long term means for temperature and salinity at multiple depths.

The ocean atlas contains annual, seasonal, and monthly long term means for temperature and salinity at multiple depths.

Monthly North American snow sover extent derived from weekly values

The product contains the 1-degree by 1-degree daily mean outgoing longwave radiation flux at the top of the atmosphere derived from HIRS radiance observations onboard NOAA TIROS-N series and MetOp satellites. The OLR retrieval uses multispectral regression models (Ellingson et al., 1989, Lee, 2014). The CDR processing includes HIRS radiance calibration, inter-satellite HIRS OLR calibration, normalization of geostationary-based OLR retrieval to HIRS, and grid-based 7-day boxcar temporal integration assisted with Imager-based OLR derived from Gridsat CDR data (Lee, 2014).

PDSI from the Dai dataset. The Palmer Drought Severity Index (PDSI) is devised by Palmer (1965) to represent the severity of dry and wet spells over
the U.S. based on monthly temperature and precipitation data as well as the soil-water holding capacity at that location. These data consist of the
monthly PDSI over global land areas from 1850 to 2010. Different precipitation/temperature datasets are used in the different files. Update and more
information are available at CGD (Climate and Global Dynamics Division).