served from IRI/LDEO Climate Data Library
root mean sq ∂T detrended-bfl detrended-bfl detrended-bfl [ NOAA NCEP CPC CAMS anomaly temp ] : ∂T temperature anomaly data
anomaly temp adif adif adif adif partial_T ∂T temperature anomaly from NOAA NCEP CPC CAMS: Climate Anomaly Monitoring System monthly gridded and station precipitation and temperature data.Independent Variables (Grids)
- Time (time)
- grid: /T (months since 1960-01-01) ordered (Feb 1950) to (Oct 2019) by 1.0 N= 837 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (89S) to (89N) by 2.0 N= 90 pts :grid
Other Info
- bufferwordsize
- 8
- CE
- null
- CS
- null
- datatype
- doublearraytype
- file_missing_value
- -9999.0
- missing_value
- NaN
- units
- 12 degree_Kelvin year-1
- history
- Averaged over X[0, 0] minimum 0.0% data present
References
Ropelewski, C.F., J.E. Janowiak, and M.S. Halpert, 1985: The analysis and display of real time surface climate data. Mon. Wea. Rev., 113, 1101-1106.
Last updated: Tue, 03 Dec 2019 20:25:17 GMT
Expires: Wed, 01 Jan 2020 07:00:00 GMT
Data Views
Views
data as colors
data as contours| T | Y | |
 root mean sq $partialdiff sub T$ detrended-bfl detrended-bfl detrended-bfl [ NOAA NCEP CPC CAMS anomaly temp ] [ Y | T] | 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 Y T
- Differentiate along Y T
- Take differences along Y T
RMS (root mean square with mean *not* removed) over Y T | Y T |
RMSA (root mean square with mean removed) over Y T | Y T |
Maximum over Y T | Y T |
Minimum over Y T | Y T |
Detrend (best-fit-line) over Y T | Y T |
Note on units