served from IRI/LDEO Climate Data Library
∂Y [ IRI Analyses Fire Amazon FirePrediction Apr18Lead1 Apr18FCST_MJJ_SST ]: ∂Y data
Amazon FirePrediction Apr18Lead1 Apr18FCST_MJJ_SST ∂Y from IRI Analyses Fire: Fire maproom analyses.Independent Variables (Grids)
- Time
- grid: /T (Year) ordered (2000.0 Year) to (2018.0 Year) by 1.0 N= 19 pts :grid
- Longitude
- grid: /X (degree_east) ordered (80W) to (62W) by 0.25 N= 73 pts :grid
- Latitude
- grid: /Y (degree_north) ordered (17.875S) to (3.875N) by 0.25 N= 88 pts :grid
Other Info
- datatype
- realarraytype
- file_missing_value
- -999.0
- missing_value
- NaN
- units
- Standard Deviation /degree_north
Last updated: Wed, 15 Aug 2018 14:35:50 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| T | X | Y | |
 $partialdiff sub Y$ [ IRI Analyses Fire Amazon FirePrediction Apr18Lead1 Apr18FCST_MJJ_SST ][ X Y | T] | 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 X Y T
- Differentiate along X Y T
- Take differences along X Y T
RMS (root mean square with mean *not* removed) over X Y T | X Y X T Y T | X Y T |
RMSA (root mean square with mean removed) over X Y T | X Y X T Y T | X Y T |
Maximum over X Y T | X Y X T Y T | X Y T |
Minimum over X Y T | X Y X T Y T | X Y T |
Detrend (best-fit-line) over X Y T | X Y X T Y T | X Y T |
Note on units