data: $integral dS$ $integral dS$ [ Hydromet Seasonal_Forecast Precipitation target

served from 181.199.253.14

∫dS ∫dS [ Hydromet Seasonal_Forecast Precipitation target_length ] : Length of forecast time data

Precipitation target_length int_dS int_dS Length of forecast time from Hydromet Seasonal_Forecast: Seasonal Forecast.

Independent Variables (Grids)

Forecast Lead Time in Months: grid: /L (months) ordered [ (2.5)] :grid
S (forecast_reference_time): grid: /S (days since 1960-01-01) ordered [ (1200 28 Feb 2019) (1200 31 Mar 2019) (0000 1 May 2019) (1200 31 May 2019) (0000 1 Jul 2019) (1200 31 Jul 2019) (1200 31 Aug 2019) (0000 1 Oct 2019) (1200 31 Oct 2019) (0000 1 Dec 2019) (1200 31 Dec 2019) (1200 31 Jan 2020) (1200 1 Mar 2020) (1200 31 Mar 2020) (0000 1 May 2020) (1200 31 May 2020) (0000 1 Jul 2020) (1200 31 Jul 2020) (1200 31 Aug 2020) (0000 1 Oct 2020) (1200 31 Oct 2020) (0000 1 Dec 2020) (1200 31 Dec 2020) (1200 31 Jan 2021) (0000 2 Mar 2021) (1200 31 Mar 2021) (0000 1 May 2021) (1200 31 May 2021) (0000 1 Jul 2021) (1200 31 Jul 2021) (1200 31 Aug 2021)] :grid

Other Info

bufferwordsize: 8
calendar: 360
CE: null
CS: null
datatype: doublearraytype
missing_value: NaN
pointwidth: 1.0
units: 622080000 second² year
history: Averaged in T with overlapping interval 3

Last updated: Fri, 12 Jan 2024 14:16:35 GMT

Data Views

	L	S
$integral dS$ $integral dS$ [ Hydromet Seasonal_Forecast Precipitation target_length ] 2.5 months[ S L \|]	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 S
Differentiate along S
Take differences along S