Profile:

Sthapit holds a BS in Environmental Science and dual MS in Civil Engineering – Water Resources emphasis and Biological Sciences. Before joining NOAA CESSRST, she worked in the energy and environmental field for 10 years where she gained valuable industry experience.

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NERTO Research Project Title:

Understanding the snow representation in the Noah-MP Model through a single column experiment

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NERTO Project Details :

Snow plays an important role in the water balance since the input of melted snow during spring seasons contributes an important fraction of total runoff in snow-dominated watersheds. Water managers require accurate and precise estimates of snowpack to estimate runoff from snow dominant watersheds.

The objective was to analyze the representation of snow in the WRF-Hydro Model and one of its embedded land surface models (LSM), Noah-MP. The goals were to: 1) Test various forcing datasets for an idealized, single-column representation of Noah-MP. Datasets tested will likely include the NLDAS (used currently for retrospective NWM simulations), the AORC (developed by NOAA specifically for NWM forcing), and a ‘perfect’ forcing dataset from the CREST-Snow Analysis and Field Experiment. Comparison of the snow-specific performance of Noah-MP with these different forcing datasets will provide insight into physical reasons underlying model deficiencies. 2) Perform sensitivity analysis of snow parameters in the Noah-MP LSM. These sensitivity experiments will first be conducted for the idealized, single-column version of Noah-MP, and then, if time permits, for a cutout of the NWM-configured WRF-Hydro across the Aroostook River watershed in Caribou, Maine. For the latter, WRF-Hydro Model streamflow will be compared with the USGS streamflow for the selected watershed, and Noah-MP snow will be compared with selected satellite snow data products.

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NERTO Outcomes:

I learned how to run Noah-MP and WRF-Hydro model.

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Value of NERTO to the Line Office:

The work provided NOAA/ESRL with a better understanding of the differenced in the forcing datasets, snow parameters of NOAH-LSM and select satellite snow products. WRF-Hydro with the NOAH-MP LSM serves as the modeling framework of the National Water Model (NWM), therefore this work will help for future improvements to the NWM.

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NERTO Skills:

My programming skills in python has improved a great deal.