province
ENACTS version0 WASP queriesENACTS provincequery[str1_year exp1_year status disp_area the_geom coarse_geom shape_area shape_leng gid adm1_code adm0_name adm0_code adm1_name ]
ENACTS version0 WASP queriesENACTS provincequery adm1_name[ | province]	M
$integral dprovince$ [ ENACTS version0 WASP queriesENACTS provincequery adm1_name ][ | province]	D
ENACTS version0 WASP queriesENACTS provincequery exp1_year[ | province]	M
ENACTS version0 WASP queriesENACTS provincequery adm0_name[ | province]	M
ENACTS version0 WASP queriesENACTS provincequery shape_leng[ | province]	M
ENACTS version0 WASP queriesENACTS provincequery coarse_geom[ | province]	M
ENACTS version0 WASP queriesENACTS provincequery shape_area[ | province]	M
ENACTS version0 WASP queriesENACTS provincequery shape_area[ | province]	M
ENACTS version0 WASP queriesENACTS provincequery gid[ | province]	M

SOURCES .ENACTS .version0 .WASP .queriesENACTS .provincequery adm1_name 1 index .adm1_name province integral 2 index .exp1_year 3 index .adm0_name 4 index .shape_leng 5 index .coarse_geom 6 index .shape_area shape_area 8 index .gid

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 province
• Differentiate along province
• Take differences along province

Average over province |
RMS (root mean square with mean *not* removed) over province |
RMSA (root mean square with mean removed) over province |
Maximum over province |
Minimum over province |
Detrend (best-fit-line) over province |

Convert units from unitless to

Note on units