served from IRI/LDEO Climate Data Library
IRI Analyses SPI SPI-UEA_9-Month: SPI-UEA_9-month data
SPI-UEA_9-month from IRI Analyses SPI: Standardized Precipitation Index analyses of multiple global precipitation datasets.Independent Variables (Grids)
- Time (time)
- grid: /T (months since 1960-01-01) ordered (Jan-Sep 1901) to (Apr-Dec 1998) by 1.0 N= 1168 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) periodic (179.75W) to (179.75E) by 0.5 N= 720 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (89.75S) to (89.75N) by 0.5 N= 360 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- 3.0999999
- CS
- -3.0999999
- datatype
- doublearraytype
- file_missing_value
- -9.9899998
- maxncolor
- 254
- missing_value
- NaN
- scale_max
- 3.0999999
- scale_min
- -3.0999999
- units
- unitless
- colorscale
References
Guttman, N. B., 1999: Accepting the Standandardized Precipitation Index: a calculation algorithm. J. Amer. Water Resour. Assoc., 35(2), 311-322McKee, T.B., N. J. Doesken, and J. Kliest, 1993: The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference of Applied Climatology, 17-22 January, Anaheim, CA. American Meterological Society, Boston, MA. 179-184.
McKee, T.B., N.J. Doesken, and J. Kliest, 1995: Drought monitoring with multiple time scales. In Proceedings of the 9th Conference of Applied Climatology, 15-20 January, Dallas TX. American Meteorological Society, Boston, MA. 233-236
Last updated: Thu, 03 Oct 2024 14:15:55 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| T | X | Y | |
 IRI Analyses SPI SPI-UEA_9-Month[ T | X Y] | M | M | M |
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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 T X Y
- Differentiate along T X Y
- Take differences along T X Y
RMS (root mean square with mean *not* removed) over T X Y | T X T Y X Y | T X Y |
RMSA (root mean square with mean removed) over T X Y | T X T Y X Y | T X Y |
Maximum over T X Y | T X T Y X Y | T X Y |
Minimum over T X Y | T X T Y X Y | T X Y |
Detrend (best-fit-line) over T X Y | T X T Y X Y | T X Y |
Note on units