served from dlibrary.snia.gub.uy
WORLDCLIM bio1: Annual Mean Temperature data
Annual Mean Temperature from WORLDCLIM: Current conditions (interpolations of observed data, representative of 1950-2000). Resolution: 30 arc-seconds (~1 km).Independent Variables (Grids)
- Longitud (longitude)
- grid: /X (degree_east) ordered (59.99583W) to (30.00417W) by 0.008333334 N= 3600 pts :grid
- Latitud (latitude)
- grid: /Y (degree_north) ordered (30.00417S) to (59.99583S) by 0.008333334 N= 3600 pts :grid
Other Info
- bufferwordsize
- 4
- CE
- 25
- colorscalename
- temp_colors
- CS
- 10
- datatype
- realarraytype
- maxncolor
- 254
- missing_value
- -3.39999995E38
- scale_factor
- 0.1
- scale_max
- 250.0
- scale_min
- 100.0
- units
- Celsius_scale
- standard units*
- degree_Kelvin above 273.15
- colorscale
Last updated: Thu, 04 Feb 2016 15:18:09 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| X | Y | |
 WORLDCLIM[bio5
prec
bio12
bio7
bio1
bio6
tmin
tmean
tmax
URUGUAY
alt
] | ||
| WORLDCLIM bio12[ X Y |] | M | M |
|---|---|---|
| WORLDCLIM bio12[ X Y |] | M | M |
| WORLDCLIM bio1[ X Y |] | M | M |
 WORLDCLIM bio1[ X Y |] | 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
- Differentiate along X Y
- Take differences along X Y
RMS (root mean square with mean *not* removed) over X Y | X Y |
RMSA (root mean square with mean removed) over X Y | X Y |
Maximum over X Y | X Y |
Minimum over X Y | X Y |
Detrend (best-fit-line) over X Y | X Y |
Note on units