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NextGen CPT Estacional CHIRPS Guatemala NextGen1 Forecast Probabilities: Probabilidades data
Probabilities Probabilities Probabilidades 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 (forecast_reference_time)
- grid: /S (days since 1960-01-01) ordered [ (0000 1 Nov 2015) (0000 1 Dec 2015) (0000 1 Jan 2016) (0000 1 Feb 2016) (0000 1 Mar 2016) (0000 1 Apr 2016) (0000 1 May 2016) (0000 1 Jun 2016) (0000 1 Jul 2016) (0000 1 Aug 2016) (0000 1 Sep 2016) (0000 1 Oct 2016) (0000 1 Nov 2016) (0000 1 Dec 2016) (0000 1 Jan 2017) (0000 1 Feb 2017) (0000 1 Mar 2017) (0000 1 Apr 2017) (0000 1 May 2017) (0000 1 Jun 2017) (0000 1 Jul 2017) (0000 1 Aug 2017) (0000 1 Sep 2017) (0000 1 Oct 2017) (0000 1 Nov 2017) (0000 1 Dec 2017) (0000 1 Jan 2018) (0000 1 Feb 2018) (0000 1 Mar 2018) (0000 1 Apr 2018) (0000 1 May 2018) (0000 1 Jun 2018) (0000 1 Jul 2018) (0000 1 Aug 2018) (0000 1 Sep 2018) (0000 1 Oct 2018) (0000 1 Nov 2018) (0000 1 Dec 2018) (0000 1 Jan 2019) (0000 1 Feb 2019) (0000 1 Mar 2019) (0000 1 Apr 2019) (0000 1 May 2019) (0000 1 Jun 2019) (0000 1 Jul 2019) (0000 1 Aug 2019) (0000 1 Sep 2019) (0000 1 Oct 2019) (0000 1 Nov 2019) (0000 1 Dec 2019) (0000 1 Jan 2020) (0000 1 Feb 2020) (0000 1 Mar 2020) (0000 1 Apr 2020) (0000 1 May 2020) (0000 1 Jun 2020) (0000 1 Jul 2020) (0000 1 Aug 2020) (0000 1 Sep 2020) (0000 1 Oct 2020) (0000 1 Nov 2020) (0000 1 Dec 2020) (0000 1 Jan 2021) (0000 1 Feb 2021) (0000 1 Mar 2021) (0000 1 Apr 2021) (0000 1 May 2021) (0000 1 Jun 2021) (0000 1 Jul 2021) (0000 1 Aug 2021) (0000 1 Sep 2021) (0000 1 Oct 2021) (0000 1 Nov 2021) (0000 1 Dec 2021) (0000 1 Jan 2022) (0000 1 Feb 2022) (0000 1 Mar 2022) (0000 1 Apr 2022) (0000 1 May 2022) (0000 1 Jun 2022) (0000 1 Jul 2022) (0000 1 Aug 2022) (0000 1 Sep 2022) (0000 1 Oct 2022) (0000 1 Nov 2022) (0000 1 Dec 2022) (0000 1 Jan 2023) (0000 1 Feb 2023) (0000 1 Mar 2023) (0000 1 Apr 2023) (0000 1 May 2023)] :grid
- Longitud (longitude)
- grid: /X (degree_east) ordered (119.9W) to (70W) by 0.1 N= 500 pts :grid
- Latitude (latitude)
- grid: /Y (degree_north) ordered (39.9N) to (4.9S) by 0.1 N= 449 pts :grid
Other Info
- bufferwordsize
- 4
- CE
- 33
- colorscalename
- halfgreyscale
- CS
- 1
- datatype
- realarraytype
- file_missing_value
- 0
- fnname
- maskle
- maxncolor
- 254
- missing_value
- NaN
- units
- ids
- history
- [ dominant_class ( NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories Sobre ) + masklt ( { [ dominant_class ( NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories ) - 1. ] * 11. } , 22 ) ] + [ dominant_class ( NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories Normal ) + masknotrange ( { [ dominant_class ( NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories ) - 1. ] * 11. } , 10 , 12 ) ]
- dominant_class [ NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories Sobre ] + masklt [ ( { dominant_class [ NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories ] - 1. } * 11. ) , 22 ]
- dominant_class [ NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories Sobre ]
dominant_class over Probabilities-Categories[≤35, ≥80]
- masklt [ ( { dominant_class [ NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories ] - 1. } * 11. ) , 22 ]
dominant_class over C[Bajo, Sobre]
- dominant_class [ NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories Sobre ]
- dominant_class [ NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories Normal ] + masknotrange [ ( { dominant_class [ NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories ] - 1. } * 11. ) , 10 , 12 ]
- dominant_class [ NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories Normal ]
dominant_class over Probabilities-Categories[≤35, ≥80]
- masknotrange [ ( { dominant_class [ NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories ] - 1. } * 11. ) , 10 , 12 ]
dominant_class over C[Bajo, Sobre]
- dominant_class [ NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories Normal ]
- dominant_class [ NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories Sobre ] + masklt [ ( { dominant_class [ NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories ] - 1. } * 11. ) , 22 ]
- dominant_class [ NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories Bajo ] + maskgt [ ( { dominant_class [ NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories ] - 1. } * 11. ) , 0 ]
- dominant_class [ NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories Bajo ]
dominant_class over Probabilities-Categories[≤35, ≥80]
- maskgt [ ( { dominant_class [ NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories ] - 1. } * 11. ) , 0 ]
dominant_class over C[Bajo, Sobre]
- dominant_class [ NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories Bajo ]
- [ dominant_class ( NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories Sobre ) + masklt ( { [ dominant_class ( NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories ) - 1. ] * 11. } , 22 ) ] + [ dominant_class ( NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories Normal ) + masknotrange ( { [ dominant_class ( NextGen CPT Estacional CHIRPS Guatemala REALTIME1 NextGen1 Forecast Probabilities-Categories ) - 1. ] * 11. } , 10 , 12 ) ]
- colorscale
Last updated: Thu, 27 Jul 2023 16:42:19 GMT
Expires: Thu, 09 Feb 2023 00:00:00 GMT
Data Views
Views
data as colors
data as contours
colors with land
contours with land
colors with coasts| L | S | X | Y | |
 NextGen CPT Estacional CHIRPS Guatemala NextGen1 Forecast[target_length
Forecast
Var
Probabilities
target_date
PredErrorVars
Probabilities-Categories
] | ||||
 NextGen CPT Estacional CHIRPS Guatemala NextGen1 Forecast Probabilities 2.5 months[ X Y | L S] | M | M | 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 X Y S
- Differentiate along X Y S
- Take differences along X Y S
RMS (root mean square with mean *not* removed) over X Y S | X Y X S Y S | X Y S |
RMSA (root mean square with mean removed) over X Y S | X Y X S Y S | X Y S |
Maximum over X Y S | X Y X S Y S | X Y S |
Minimum over X Y S | X Y X S Y S | X Y S |
Detrend (best-fit-line) over X Y S | X Y X S Y S | X Y S |
Note on units