Performance Comparison of an Energy-Performance Comparison of an Energy-Budget and the Temperature Index-Based Budget and the Temperature Index-Based

(Snow-17) Snow Models at SNOTEL Stations(Snow-17) Snow Models at SNOTEL Stations

Fan LeiFan Lei1, Victor Koren, Victor Koren22, Fekadu Moreda, Fekadu Moreda33, and , and Michael SmithMichael Smith22

11Riverside Technology, incRiverside Technology, inc22Hydrology Laboratory, Office of Hydrologic Hydrology Laboratory, Office of Hydrologic

Development, NWS/NOAADevelopment, NWS/NOAA 33MHW, IncMHW, Inc

MotivationMotivation

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

BackgroundBackground

Simple degree-day, conceptual lumped model is currently used to Simple degree-day, conceptual lumped model is currently used to model snow accumulation and melt for NOAA/NWS operational river model snow accumulation and melt for NOAA/NWS operational river forecasting. forecasting.

Energy-budget snowmelt models are physically more consistent and Energy-budget snowmelt models are physically more consistent and they require no (or much less) calibration.they require no (or much less) calibration.

Without reliable driving fields of meteorological data, the application Without reliable driving fields of meteorological data, the application of energy-budget snowmelt models is limited so far. of energy-budget snowmelt models is limited so far. 

Emerging meteorological data may lead to better performance Emerging meteorological data may lead to better performance of energy-budget snowmelt models.of energy-budget snowmelt models.

NWS Office of Hydrologic Development (OHD) is conducting NWS Office of Hydrologic Development (OHD) is conducting research on transitioning from conceptual to energy-budget research on transitioning from conceptual to energy-budget snowmelt modeling to improve current operational river forecasts.snowmelt modeling to improve current operational river forecasts.

Model Description (1)Model Description (1)

SNOW-17SNOW-17

• A current operational snowmelt component in A current operational snowmelt component in the NWS River Forecast System (NWSRFS),the NWS River Forecast System (NWSRFS),

Developed by Anderson (1973,1976);Developed by Anderson (1973,1976);• Uses air temperature as index of major snow Uses air temperature as index of major snow

processes;processes;• Model performs well after calibration;Model performs well after calibration;• Being tested in distributed mode (HL-RDHM, Being tested in distributed mode (HL-RDHM,

Moreda et al., 2005)Moreda et al., 2005)

Model Description (2)Model Description (2)

Energy-Budget Snowmelt Model (EBSM)Energy-Budget Snowmelt Model (EBSM)

• One layer model linked to multilayer soil/vegetation One layer model linked to multilayer soil/vegetation scheme (a version of Eta-LSS, Koren et al [1999]);scheme (a version of Eta-LSS, Koren et al [1999]);

• Energy forcings are described by meteorological Energy forcings are described by meteorological fields, including: surface air temperature, surface fields, including: surface air temperature, surface downward short wave flux, surface downward long downward short wave flux, surface downward long wave flux, surface wind and surface humidity;wave flux, surface wind and surface humidity;

• Model does not include conceptual type Model does not include conceptual type parameters, no (or very little) calibration is needed.parameters, no (or very little) calibration is needed.

Test BasinTest Basin Considering Considering

snow data snow data availability, availability, Carson Carson River Basin River Basin is selected is selected as the test as the test basinbasin. .

Carson River Basin elevation (units: m)Carson River Basin elevation (units: m)

Nevada

California

CarsonRiver Basin

PacificOcean

Data (1)Data (1)

SNOpack TELemetry (SNOTEL)SNOpack TELemetry (SNOTEL) ground measurements ground measurements• Hourly temperature, precipitation since 1997; Hourly temperature, precipitation since 1997; • Daily snow water equivalent.Daily snow water equivalent.

North American Regional Reanalysis (NARR)North American Regional Reanalysis (NARR)• Based on National Centers for Environmental Prediction Based on National Centers for Environmental Prediction

(NCEP)'s mesoscale Eta forecast model and Eta Data (NCEP)'s mesoscale Eta forecast model and Eta Data Assimilation System (EDAS);Assimilation System (EDAS);

• 3-hourly 2m air temp., 2m relative humidity, surface 3-hourly 2m air temp., 2m relative humidity, surface downward long wave radiation, 10m surface wind, downward long wave radiation, 10m surface wind, precipitation; precipitation;

• 0.375 degree (about 32km) resolution. 0.375 degree (about 32km) resolution.

Data (2)Data (2)

GEWEX [Global Energy and Water Cycle Experiment] GEWEX [Global Energy and Water Cycle Experiment] Continental Scale International Project (GCIP) and GEWEX Continental Scale International Project (GCIP) and GEWEX America Prediction Project (GAPP) Surface Radiation America Prediction Project (GAPP) Surface Radiation Budget (SRB) Data Budget (SRB) Data Re-processedRe-processed hourly averaged surface downward short hourly averaged surface downward short

wave flux;wave flux; 1/8 degree (about 16 km) resolution.1/8 degree (about 16 km) resolution.

North American Land Data Assimilation System (NLDAS)North American Land Data Assimilation System (NLDAS) Surface albedo, Leaf Area Index (LAI), (Greeness Surface albedo, Leaf Area Index (LAI), (Greeness

FRACtion) GFRAC, Soil type, vegetation type, etc;FRACtion) GFRAC, Soil type, vegetation type, etc; 1/8 degree (about 16 km) resolution across North America;1/8 degree (about 16 km) resolution across North America; Some of the parameters are adjusted in energy-budget Some of the parameters are adjusted in energy-budget

snow melt model.snow melt model.

Experiment DesignExperiment Design 1999 water year was selected for experiments, based on 1999 water year was selected for experiments, based on

data availability and quality;data availability and quality; Snow Water Equivalent (SWE) was selected as main Snow Water Equivalent (SWE) was selected as main

snow property;snow property; Extracted NLDAS data are used as EBSM model Extracted NLDAS data are used as EBSM model

parameters.parameters.• LAI and GFRAC are manually adjusted to match the sites land LAI and GFRAC are manually adjusted to match the sites land

cover. cover. Extracted NARR data, SNOTEL ground measured Extracted NARR data, SNOTEL ground measured

Temp. & Precip. were applied as model inputs;Temp. & Precip. were applied as model inputs;• NARR Temp. are adjusted for elevation. NARR Temp. are adjusted for elevation.

Both models are run to generate:Both models are run to generate: Point SWE simulations, Point SWE simulations, Basin SWE simulations (on going), Basin SWE simulations (on going), Basin outlet hydrographs (in plan).Basin outlet hydrographs (in plan).

AccumulatedAccumulated Precipitation from NARR and SNOTELPrecipitation from NARR and SNOTELExperiment Experiment Design (2)Design (2)

Precip-NARRPrecip-SNOTEL

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

SN17-T2m-NARREBSM-T2m-NARR

SN17-TSnotelEBSM-TSnotelSWE-Measured

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

SN17-TSnotelEBSM-TSnotel

SN17-T2m-NARREBSM-T2m-NARRSWE-Measured

DiscussionDiscussion

The two models show reasonable agreement with each other and The two models show reasonable agreement with each other and with the ground measurements, given reasonable temperature and with the ground measurements, given reasonable temperature and precipitation data. precipitation data.

Both models are very sensitive to temperature especially during Both models are very sensitive to temperature especially during accumulation periods.accumulation periods.

The experiments indicate that with the elevationThe experiments indicate that with the elevation adjustment, the adjustment, the temperature data interpolated from NARR may be used to drive the temperature data interpolated from NARR may be used to drive the EBSM, although some model fitting may be needed. EBSM, although some model fitting may be needed.

Given the highly spatially-variable nature of precipitation in Given the highly spatially-variable nature of precipitation in mountainous areas, special treatment is necessary or other more mountainous areas, special treatment is necessary or other more reliable data sources need to be explored. reliable data sources need to be explored.