Meteorological variable derivation with backward accumulation

Knowledge graph centered on Meteorological variable derivation with backward accumulation with 15 nodes and 29 connections. Top connected: Crested Butte, Modeling Spatial Distribution of Snow Water Equiva, Multiscale Model to Model Cloud Compare method, Random Forest, Gunnison-East River.

Method synopsis

Processing of PRISM daily precipitation and temperature data to derive snow-relevant variables through backward time accumulation from observation dates, including snowfall estimation and degree-day calculations.

Synthesized from method descriptions across 1 paper using this protocol.

Procedure as described in the canonical source

Steps below were extracted from the paper that introduces this protocol — Modeling Spatial Distribution of Snow Water Equivalent by Combining Meteorological and Satellite Data with Lidar Maps (2022), Artificial Intelligence for the Earth Systems. Implementations in other papers (listed below) may differ.

1. Collect meteorological data
   Obtained daily precipitation and temperature from Parameter-Elevation Regressions on Independent Slopes Model (PRISM) at 800-m spatial resolution. Calculated accumulated snowfall using 0°C temperature threshold, PDD sum (positive degree-days), accumulated precipitation, and mean seasonal temperature (Tmean) through backward time accumulation from ASO snapshot dates.
   Quantities: Daily data processed for entire snow seasons, backward accumulation from 15 March to snapshot date for each mapDuration: Seasonal accumulation periods, typically October 1 to snapshot dateConditions: Temperature threshold of 0°C for snow/rain partitioning
   Equipment: PRISM Climate Group dataset

Typical Equipment

• PRISM Climate Group dataset

Output Measurements

• accumulated snowfall
• PDD sum
• accumulated precipitation
• mean seasonal temperature

Papers Using This Protocol (1)

Places Where Used