PSM.pdsi.pdsi

Creates a new PDSI PSM object

Syntax



obj = PSM.pdsi(season, years, lat, awcs, awcu, cafecYears, season)


obj = PSM.pdsi(…, useModified)


obj = PSM.pdsi(…, true|’m’|’modified’)


obj = PSM.pdsi(…, false|’s’|’standard’)

Description

Initializes a new PDSI PSM object. The first input indicates the season over which to estimate average PDSI. Currently, the DASH framework only implements PDSI seasons within a given calendar year. Seasons that cross multiple calendar years (such as DJF) are not yet supported. Note that the PDSI forward model itself does estimate values over multiple years, so you may want to run the model outside of DASH if estimating PDSI in seasons that span multiple years.

Please see the documentation of the “pdsi.m” function in the downloaded code for greater detail about the remaining inputs.

*Important* The PDSI model maintains significant memory between individual years. Thus, we strongly recommend using a time-ordered ensemble when running this forward model.



obj = PSM.pdsi(…, useModified)


obj = PSM.pdsi(…, true|’m’|’modified’)


obj = PSM.pdsi(…, false|’s’|’standard’)

Specify whether to estimate standard PDSI, or modified PDSI. Default is standard PDSI.

Input Arguments

season

logical vector | vector, linear indices
Indicates the season for which to estimate PDSI. A vector whose elements indicate months of the calendar year. The forward model will estimate the average PDSI value over these months.

If a logical vector, must have 12 elements. If linear indices, then the elements must be the (integer) numbers of months in the calendar year. For example, use 1:12 to estimate annual pdsi, 6:8 to estimate boreal-summer JJA pdsi, 6 to estimate June pdsi, etc.

Note Using a season like [12 1 2] will not implement a DJF season spanning two calendar years. Instead, this will calculate the average PDSI over Jan, Feb, and Dec from the same calendar year (i.e. The December 10 months after the February)

years

numeric vector [2]
The first and last year of the period in which monthly temperatures and precipitations will be input.

lat

numeric scalar
The latitude of the site in decimal degrees north

awcs

numeric scalar
The available water capacity of the surface layer in mm. A common default value is 25.4 mm.

awcu

numeric scalar
The available water capacity of the underlying layer in mm. A common default value is 127 mm.

cafecYears

numeric vector [2]
The first and last year of the calibration period used to compute CAFEC normalizations.

useModified

scalar, string|*logical*
Indicates whether to estimate standard PDSI or modified PDSI.

[true|”m”|”modified”]: The PSM will estimate modified PDSI

[false|”s”|”standard”]: (Default) The PSM will estimate standard PDSI

Output Arguments

obj

scalar PSM.*pdsi* object
The new PDSI PSM object