served from IRI/LDEO Climate Data Library
IRI Analyses ICPAC Models Montreal CMC1-CanCM3 HINDCAST sc8110 prec: Total Precipitation data
Analyses ICPAC Models Montreal CMC1-CanCM3 HINDCAST sc8110 Total Precipitation from IRI: International Research Institute for Climate and Society.Independent Variables (Grids)
- L (forecast_period)
- grid: /L (months) ordered (1.5 months) to (8.5 months) by 1.0 N= 8 pts :grid
- Forecast Start Time (forecast_reference_time)
- grid: /S (months since 01-Jan) periodic (0000 1 Jan) to (0000 1 Dec) by 1.0 N= 12 pts :grid
- Longitude (longitude)
- grid: /X (degree_east) periodic (0) to (1W) by 1.0 N= 360 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (90S) to (90N) by 1.0 N= 181 pts :grid
Other Info
- center
- Montreal (RSMC)
- datatype
- realarraytype
- file_missing_value
- 9.99900026E20
- grib_name
- PRATE
- gribcenter
- 54
- gribfield
- 1
- gribleveltype
- 1
- gribNumBits
- 16
- gribparam
- 59
- missing_value
- NaN
- PDS_TimeRange
- 10
- pointwidth
- 0
- standard_name
- lwe_precipitation_rate
- units
- mm /day
- standard units*
- 1.15740740740741×10-08 meter second-1
- history
- [(Averaged over M[0.5, 10.5] minimum 0.0% data present) (Averaged over S2[16 Dec 1980 - 15 Dec 1981, 16 Dec 2009 - 15 Dec 2010] minimum 0.0% data present) (Averaged in L with overlapping interval 3) (Boxes with less than 0.0% dropped)]
Last updated: Fri, 15 Dec 2017 15:57:24 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| L | S | X | Y | |
 IRI Analyses ICPAC Models Montreal CMC1-CanCM3 HINDCAST sc8110 prec[ X Y L | S] | M | 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 L S
- Differentiate along X Y L S
- Take differences along X Y L S
RMS (root mean square with mean *not* removed) over X Y L S | X Y X L X S Y L Y S L S | X Y L X Y S X L S Y L S | X Y L S |
RMSA (root mean square with mean removed) over X Y L S | X Y X L X S Y L Y S L S | X Y L X Y S X L S Y L S | X Y L S |
Maximum over X Y L S | X Y X L X S Y L Y S L S | X Y L X Y S X L S Y L S | X Y L S |
Minimum over X Y L S | X Y X L X S Y L Y S L S | X Y L X Y S X L S Y L S | X Y L S |
Detrend (best-fit-line) over X Y L S | X Y X L X S Y L Y S L S | X Y L X Y S X L S Y L S | X Y L S |
Note on units