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Ed Maurer Partitioning precipitation Partitioning precipitation into rain and snow for into rain and snow for event-based hydrologic event-based hydrologic modeling in the Pacific modeling in the Pacific Northwest U.S. Northwest U.S. Edwin Maurer Civil Engineering Department Santa Clara University [email protected] H51G-04

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Page 1: Ed Maurer Partitioning precipitation into rain and snow for event-based hydrologic modeling in the Pacific Northwest U.S. Edwin Maurer Civil Engineering

Ed Maurer

Partitioning precipitation into rain Partitioning precipitation into rain and snow for event-based and snow for event-based

hydrologic modeling in the Pacific hydrologic modeling in the Pacific Northwest U.S. Northwest U.S.

Edwin Maurer

Civil Engineering DepartmentSanta Clara University [email protected]

H51G-04

Page 2: Ed Maurer Partitioning precipitation into rain and snow for event-based hydrologic modeling in the Pacific Northwest U.S. Edwin Maurer Civil Engineering

Ed Maurer

MotivationMotivation

Precipitation type can drive flood simulations

Determination of type in hydrology models is dubious

Unique data presents opportunities to improve precipitation type determination with radar

Potential for transferability

Page 3: Ed Maurer Partitioning precipitation into rain and snow for event-based hydrologic modeling in the Pacific Northwest U.S. Edwin Maurer Civil Engineering

Ed Maurer

Primary QuestionsPrimary Questions

• Do surface temperature-based methods work adequately for determining whether precipitation is falling as rain, snow, or a mixture?

• Can using a reflectivity from a vertically-pointing radar be used to improve this, and ultimately streamflow simulations?

• Can information on derived rain-snow partitioning be transferred to neighboring watersheds?

Page 4: Ed Maurer Partitioning precipitation into rain and snow for event-based hydrologic modeling in the Pacific Northwest U.S. Edwin Maurer Civil Engineering

Ed Maurer

Area of FocusArea of Focus

Improvement of Microphysical PaRameterization through Observational Verification Experiment (IMPROVE-2).

Intensive field observation campaign: 26 Nov- 22 Dec 2001

IMPROVE-2 domain overlaps with South Santiam River basin: total basin area of 1,440 km2.

Page 5: Ed Maurer Partitioning precipitation into rain and snow for event-based hydrologic modeling in the Pacific Northwest U.S. Edwin Maurer Civil Engineering

Ed Maurer

South Santiam River BasinSouth Santiam River Basin

High orographic influence

Winter storms include mix of rain and snow

Ground-based Meteorological Observations:

•Hourly P•Co-op Stations•SNOTEL•IMPROVE P•USGS•Radar

Page 6: Ed Maurer Partitioning precipitation into rain and snow for event-based hydrologic modeling in the Pacific Northwest U.S. Edwin Maurer Civil Engineering

Ed Maurer

Surface Air Temperature for Surface Air Temperature for Rain-Snow Determination Rain-Snow Determination

Accumulation

Melt

• T is not a good indicator of accumulation or melt

• Probably not good indicator of P type

JUMP OFF JOE LITTLE MEADOWS

Each 6-hourly observation where P>01. determine change in swe2. find P, Tavg3. Plot d(swe)/d(P) vs. T

11/25 12/01 12/07 12/13 12/1911/25 12/01 12/07 12/13 12/19

Page 7: Ed Maurer Partitioning precipitation into rain and snow for event-based hydrologic modeling in the Pacific Northwest U.S. Edwin Maurer Civil Engineering

Ed Maurer

Scenarios for Precipitation Type Scenarios for Precipitation Type DeterminationDetermination

Three scenarios:

1. Base Case – published T thresholds (0.0 °C and 0.7 °C)

2. Alternative 1 – 0°C level from Radar Data

3. Alternative 2 – Radar-derived T thresholds

Page 8: Ed Maurer Partitioning precipitation into rain and snow for event-based hydrologic modeling in the Pacific Northwest U.S. Edwin Maurer Civil Engineering

Ed Maurer

Vertically Pointing Radar Data – Vertically Pointing Radar Data – Reflectivity DataReflectivity Data

• NOAA/ETL S-band vertically pointing radar

• Sample from 2215 UTC 13 Dec- 0115 UTC 14 Dec 2001

• Bright band in red, the top is associated with 0°C temperatures.

• Approx. 300 meter thickness

11/25 12/01 12/07 12/13 12/19

Observed 0° Level Based on Bright Band Identification

Page 9: Ed Maurer Partitioning precipitation into rain and snow for event-based hydrologic modeling in the Pacific Northwest U.S. Edwin Maurer Civil Engineering

Ed Maurer

Alternative 1: Using Radar Detected Alternative 1: Using Radar Detected Melting Layer in Hydrologic ModelMelting Layer in Hydrologic Model

Radar-detected bright band

0°C level – Melting begins

Snow at land surface

Rain below bright band

Melt complete

Page 10: Ed Maurer Partitioning precipitation into rain and snow for event-based hydrologic modeling in the Pacific Northwest U.S. Edwin Maurer Civil Engineering

Ed Maurer

Alternative 2: Radar-derived surface Alternative 2: Radar-derived surface air temperature indexair temperature index

Radar-detected bright band

Surface air temperature at pixels set to Tmin(rain)

Surface air temperature at pixels set to Tmax(snow)

Page 11: Ed Maurer Partitioning precipitation into rain and snow for event-based hydrologic modeling in the Pacific Northwest U.S. Edwin Maurer Civil Engineering

Ed Maurer

Alternative 2: Using radar to set air Alternative 2: Using radar to set air temperature thresholdstemperature thresholds

Minimum Maximum Average

Tmin(Rain) -9.7 -0.6 -4.9

Tmax(Snow) -6.7 1.7 -2.4

Average over period

Basin average surface air temperatures for snow/rain inferred from radar 0°C level

Dynamic variability of radar-derived Tmax(snow) and

Tmin(rain)

Average over basin and time period shows values outside

published range

Page 12: Ed Maurer Partitioning precipitation into rain and snow for event-based hydrologic modeling in the Pacific Northwest U.S. Edwin Maurer Civil Engineering

Ed Maurer

Stream Flow SimulationStream Flow Simulation

Gauge 14185900elev. 320 m

Gauge 14185000elev. 230 m

Gauges selected based on:•observed data for period•no effects from dams

DHSVM implemented with:•150 m spatial resolution•3-hour time step•Gridded observed meteorology

Page 13: Ed Maurer Partitioning precipitation into rain and snow for event-based hydrologic modeling in the Pacific Northwest U.S. Edwin Maurer Civil Engineering

Ed Maurer

Improvement in simulated Improvement in simulated hydrographshydrographs

Gauge 14185000 Gauge 14185900

Base Case 38 46

Alternative 1 36 34

Alternative 2 37 35

• In all cases, improvement is seen over the base case, esp. peaks 3, 4, 5.

• 26% reduction in RMSE for gauge in higher elevation basin

• Temperature index derived from radar data achieves most of improvement seen in direct use of radar freezing level

Base Case

Alt. 1

Alt. 2

RMSE for flows over 50 m3/s

11/25 12/01 12/07 12/13 12/19

Page 14: Ed Maurer Partitioning precipitation into rain and snow for event-based hydrologic modeling in the Pacific Northwest U.S. Edwin Maurer Civil Engineering

Ed Maurer

Snow Simulations at SNOTEL siteSnow Simulations at SNOTEL site

•Simulated SWE at Little Meadows SNOTEL site, upstream of Gauges 14185900

•Alt. 1 shows dramatic improvement over base case

•Alt. 2, while better than Base Case later, substantially overestimates melt in intermediate period

Base Case

Alt. 1

Alt. 2

11/25 12/01 12/07 12/13 12/19

Page 15: Ed Maurer Partitioning precipitation into rain and snow for event-based hydrologic modeling in the Pacific Northwest U.S. Edwin Maurer Civil Engineering

Ed Maurer

Transferring methods to neighboring Transferring methods to neighboring watershedwatershed

Gauge 14185900

Gauge 14185000

Gauge 14182500elev. 200 m

Gauge 14178000elev. 485 m

Page 16: Ed Maurer Partitioning precipitation into rain and snow for event-based hydrologic modeling in the Pacific Northwest U.S. Edwin Maurer Civil Engineering

Ed Maurer

Changes at transferred sitesChanges at transferred sites

Gauge 14182500 Gauge 14178000

Base Case 44 64

Alternative 1 44 59

Alternative 2 47 75

• Higher elevation basin sees minor benefit using radar-detected 0o level

• Increasing from ~45 to ~80 km appears beyond the transfer range for “calibrated” temperature index for Tmax(snow) and Tmin(rain)

RMSE for flows over 50 m3/s (14182500) and 40 m3/s (14178000)

Base Case

Alt. 1

Alt. 2

11/25 12/01 12/07 12/13 12/19

Page 17: Ed Maurer Partitioning precipitation into rain and snow for event-based hydrologic modeling in the Pacific Northwest U.S. Edwin Maurer Civil Engineering

Ed Maurer

Radar as a calibration toolRadar as a calibration tool

•Apply to same period of previous year:

11/25/2000-12/19/2000shown as shaded region

Gauge 14185000 Gauge 14185900

Base Case 18 12

Alternative 2 16 9.5

Radar-derived Tmax(snow) and Tmin(rain) derived using December 2001.Decrease RMSE for same period in 2000 by 20% at higher elevation gauge

RMSE for flows over 10 m3/s

Alt. 2

Base Case

Page 18: Ed Maurer Partitioning precipitation into rain and snow for event-based hydrologic modeling in the Pacific Northwest U.S. Edwin Maurer Civil Engineering

Ed Maurer

ConclusionsConclusions

• Surface air temperature is not a good indicator of precipitation type

• Radar-detected freezing levels can improve P partitioning into rain/snow in hydrologic simulations

• Tmax(snow) and Tmin(rain) derived from radar-detected 0°C levels achieve much of the benefit of direct use of freezing levels for concurrent period

• Benefits are not realized when transferring to other basins

• Derived Tmax(snow) and Tmin(rain) show some promise in transferring to same period and basin in previous year