data: min $integral dY$ [ NextGen CPT Estacional CHIRPS Guatemala NextGen1 Forecast Forecast ]

served from 45.183.221.150

min ∫dY [ NextGen CPT Estacional CHIRPS Guatemala NextGen1 Forecast Forecast ] : Pronóstico data

Forecast int_dY Pronóstico from NextGen CPT Estacional CHIRPS Guatemala NextGen1 Forecast: Forecast and Error.

Independent Variables (Grids)

Forecast Lead Time in Months: grid: /L (months) ordered [ (2.5)] :grid
S: grid: /S (months since 1960-01-01) unordered [ (0000 1 Dec 2020) (0000 1 Jan 2021) (0000 1 Feb 2021) ... (0000 1 May 2023)] N= 101 pts :grid
Latitude (latitude): grid: /Y (degree_north) ordered (5S) to (40N) by 0.1 N= 451 pts :grid

Other Info

bufferwordsize

CE

null

CS

null

datatype

doublearraytype

file_missing_value

-999.0

maxncolor

254

missing_value

NaN

units

1.74532925199433×10^-05 meter radian north

history

min $integral dY$ [ NextGen CPT Estacional CHIRPS Guatemala NextGen1 Forecast Forecast ]

S: 0000 1 Nov 2015 to 0000 1 May 2023 appended from NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Forecast
min over X[119.9W, 70W]

Last updated: Mon, 20 Mar 2023 20:23:28 GMT

Data Views

	L	S	Y
min $integral dY$ [ NextGen CPT Estacional CHIRPS Guatemala NextGen1 Forecast Forecast ] 2.5 months[ Y \| L S]	M	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 Y S
Differentiate along Y S
Take differences along Y S

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

Note on units