data: $partialdiff sub Y$ $integral dT$ $partialdiff sub X$ $integral dY$ $integral dY$ [ NASA msu precipitation ]

served from IRI/LDEO Climate Data Library

∂_Y ∫dT ∂_X ∫dY ∫dY [ NASA msu precipitation ] : ∂_Y ∂_X precipitation data

precipitation int_dY int_dY partial_X int_dT ∂_Y ∂_X precipitation from NASA msu: Gridded oceanic rainfall data from the Microwave Sounding Unit.

Independent Variables (Grids)

Time (time): grid: /T (julian_day) ordered (0000 1 Jan 1979) to (0000 1 Jun 1994) by 1.0 N= 5631 pts :grid
Longitude (longitude): grid: /X (degree_east) periodic (180W) to (177.5E) by 2.5 N= 144 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (60N) to (60S) by 2.5 N= 49 pts :grid

Other Info

CE: null
CS: null
datatype: realarraytype
file_missing_value: -99.900002
missing_value: NaN
units: 86.3999999999999 meter second

References

Spencer, R.W. and J.R. Christy, 1990: Precise monitoring of global temperature trends from satellites. Science, 247, 1558-1562.

Spencer, R.W., J.R. Christy, and N.C. Grody, 1990: Global atmospheric temperature monitoring with satellite microwave measurements: Methods and results 1979-84. J. Climate, 3, 1111-1128.

Spencer, R.W. and J.R. Christy, 1993: Precision lower stratospheric temperature monitoring with the MSU: Technique, validation, and results 1979-91. J. Climate, 6, 1194-1204.

Last updated: Wed, 13 Feb 2019 20:27:28 GMT

Data Views

	T	X	Y
$partialdiff sub Y$ $integral dT$ $partialdiff sub X$ $integral dY$ $integral dY$ [ NASA msu precipitation ] [ X Y \| T]	M	M	M

Filters

Here are some filters that are useful for manipulating data. There are actually many more available, but they have to be entered manually. See Ingrid Function Documentation for more information.

Monthly Climatology calculates a monthly climatology by averaging over all years.
anomalies calculates the difference between the (above) monthly climatology and the original data.
Integrate along X Y T
Differentiate along X Y T
Take differences along X Y T