NOAA PSL and NOAA-CESSRST Brown Bag Seminar Series: Engela Sthapit

Posted on: November 23, 2020

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Date: Thursday, December 3, 2020

Time: 4:30 - 5:30 EST (2:30–3:30 pm MST)

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Understanding Snow Representation in the Noah-MP Model

This talk will examine uncertainties in atmospheric forcing variables to predict snowpack properties

such as snow water equivalent (SWE) and snow depth (SD). The project focused on understanding

snow representation in the Noah-MP land surface model, through a single column experiment.

Noah-MP simulated SWE and SD from two forcing datasets - North American Land Data Assimilation

System version 2 (NLDAS2), and in-situ station measured meteorological variables - were compared

with the SWE and SD observed at the in-situ station in Caribou, Maine (Station). The higher SWE and

SD simulated with NLDAS2 forcing compared to the ones with Station forcing, were consistent with

the lower near-surface temperature and outgoing longwave radiation in NLDAS2 compared to the

Station. Differences in total precipitation also influenced the snow variables in two model

simulations. But the relation with incoming shortwave radiation was not clear. The SWE and SD

observed at the site were significantly higher than those simulated by the models, possibly due to

wind blown redeposition of snow, a process not considered in Noah-MP. Such understanding about

the effect of forcing variables could benefit the NOAA's operational hydrologic model, the National

Water Model.

Speaker Bio

Engela Sthapit is a NOAA Educational Partnership Program graduate scholar at the Center for Earth

System Sciences and Remote Sensing Technologies, City College of New York. She is working on a

PhD in Civil Engineering, with focus on water prediction.