# Presentation: 276683

## Performance Comparison of an Energy-Budget and the Temperature Index-Based (Snow-17) Snow Models at SNOTEL Stations

**Fan Lei****1****, Victor Koren****2****, Fekadu Moreda****3****, and Michael Smith****2****1****Riverside Technology, inc****2****Hydrology Laboratory, Office of Hydrologic Development, NWS/NOAA**
** ****3****MHW, Inc**

## Motivation

- Improve National Weather Service (NWS) water resources forecasts by using energy budget models of snow accumulation and melt.

## Background

- Simple degree-day, conceptual lumped model is currently used to model snow accumulation and melt for NOAA/NWS operational river forecasting.
- Energy-budget snowmelt models are physically more consistent and they require no (or much less) calibration.
- Without reliable driving fields of meteorological data, the application of energy-budget snowmelt models is limited so far.
- Emerging meteorological data may lead to better performance of energy-budget snowmelt models.
- NWS Office of Hydrologic Development (OHD) is conducting research on transitioning from conceptual to energy-budget snowmelt modeling to improve current operational river forecasts.

## Model Description (1)

- SNOW-17
- A current operational snowmelt component in the NWS River Forecast System (NWSRFS),
-      Developed by Anderson (1973,1976);
- Uses air temperature as index of major snow processes;
- Model performs well after calibration;
- Being tested in distributed mode (HL-RDHM, Moreda et al., 2005)

## Model Description (2)

- Energy-Budget Snowmelt Model (EBSM)
- One layer model linked to multilayer soil/vegetation scheme (a version of Eta-LSS, Koren et al [1999]);
- Energy forcings are described by meteorological fields, including: surface air temperature, surface downward short wave flux, surface downward long wave flux, surface wind and surface humidity;
- Model does not include conceptual type parameters, no (or very little) calibration is needed.

## Test Basin  

- Considering snow data availability, Carson River Basin is selected as the test basin.

- Carson River Basin elevation (units: m)

- Nevada

- California

- Carson
- River Basin

- Pacific
- Ocean

## Data (1)

**SNOpack TELemetry (SNOTEL)** ground measurements
- Hourly temperature, precipitation since 1997;
- Daily snow water equivalent.
**North American Regional Reanalysis (NARR)**
- Based on National Centers for Environmental Prediction (NCEP)'s mesoscale Eta forecast model and Eta Data Assimilation System (EDAS);
- 3-hourly 2m air temp., 2m relative humidity, surface      downward long wave radiation, 10m surface wind, precipitation;
- 0.375 degree (about 32km) resolution.

## Data (2)

**GEWEX [Global Energy and Water Cycle Experiment] Continental Scale International Project (GCIP) and GEWEX America Prediction Project (GAPP) Surface Radiation Budget (SRB) Data **
- Re-processed hourly averaged surface downward short wave flux;
- 1/8 degree (about 16 km) resolution.** **
**North American Land Data Assimilation System (NLDAS)**
- Surface albedo, Leaf Area Index (LAI), (Greeness FRACtion) GFRAC, Soil type, vegetation type, etc;
- 1/8 degree (about 16 km) resolution across North America;
- Some of the parameters are adjusted in energy-budget snow melt model.

## Experiment Design

- 1999 water year was selected for experiments, based on data availability and quality;
- Snow Water Equivalent (SWE) was selected as main snow property;
- Extracted NLDAS data are used as EBSM model parameters.
- LAI and GFRAC are manually adjusted to match the sites land              cover.
- Extracted NARR data, SNOTEL ground measured Temp. & Precip. were applied as model inputs;
- NARR Temp. are adjusted for elevation.
- Both models are run to generate:
- Point SWE simulations,
- Basin SWE simulations (on going),
- Basin outlet hydrographs (in plan).

## Accumulated Precipitation from NARR and SNOTEL

- Experiment
- Design (2)

- Precip-NARR

- Precip-SNOTEL

## Results: Observed and simulated SWE using Snotel precip.

- SN17-T2m-NARR

- EBSM-T2m-NARR

## Results: Observed and simulated SWE using NARR precip.

- EBSM

- SN17-TSnotel

- EBSM-TSnotel

- SN17-T2m-NARR

- EBSM-T2m-NARR

- SWE-Measured

## Discussion

- The two models show reasonable agreement with each other and with the ground measurements, given reasonable temperature and precipitation data.
- Both models are very sensitive to temperature especially during accumulation periods.
- The experiments indicate that with the elevation adjustment, the temperature data interpolated from NARR may be used to drive the EBSM, although some model fitting may be needed.
- Given the highly spatially-variable nature of precipitation in mountainous areas, special treatment is necessary or other more reliable data sources need to be explored.

## Future Plans

- Lengthen analysis period to confirm initial results.
- Investigate sensitivity of EBSM to meteorological forcings.
- Conduct error propagation tests of EBSM.
- Expand experiments to distributed version at basin scales.
- Develop recommendations on potential use of available and emerging meteorological data for operational EBSM application.

- This work is supported under NWS AHPS Contract DG133W-03-CQ-0021 with Riverside Technology, inc.