NWSRFS Ensemble Streamflow Prediction - … · Ensemble Streamflow Prediction NWSRFS models and...
Transcript of NWSRFS Ensemble Streamflow Prediction - … · Ensemble Streamflow Prediction NWSRFS models and...
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NWSRFSEnsemble Streamflow Prediction
Manual Calibration Program (MCP) Operational Forecast System (OFS)Ensemble Streamflow Prediction (ESP)
MCP
OFS ESP
NWS Workshop on Hydrologic ForecastingPrague Campus
Czech University of AgricultureJune 20-24, 2005
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Ensemble Streamflow Prediction
NWSRFS models and current states.Historical MAPs and MATs from calibration.Flexible analysis window.Many forecast variables.Better performance under extreme conditions.Use of weather and climate forecasts.
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ESP Uses
Long range seasonal water supply.Spring snowmelt volume forecasts.Spring snowmelt peaks.Minimum flows for navigation, irrigation, environmental, recreation, etc.Experimental Short Term EnsemblesHours to days
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ESP Flexibility
Time WindowDays, Weeks, Months, Seasons
VariablesVolumeMean DischargePeak FlowLow FlowDays to Peak, Low, or Specified Rate
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Key Model StatesInitial Conditions Are Important
Snow ModelLiquid and frozen water equivalentHeat contentAreal extent
Soils ModelUpper zone moisture content (tension/free)Lower zone moisture content (tension/free)Frozen ground
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Accurate Snowpack States
Real time network consistent with calibration network.Quality control temperature and precipitation observations.Update snow water equivalent with snow course observations.
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ESP Process
Trace GenerationStatistical Analysis
NWSRFSModel States
AnalysisWindow
ProbablisticForecast
NWSRFSModel
Parameters
(Pre-adjusted)Historical
Temp/Precip
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Ensemble Streamflow Prediction
ClimateForecast
Adjustments
Daily RFCForecasting•Data Ingest•Data QC•Model Updating
Current Conditions•Soil•Reservoir Levels•Streamflow
HistoricalTime Series
All Years ofRecord
ForecastTime
Series
Mean ArealTime Series
PrecipitationTemperature
NWSRFSHydrologic
Models
Time St
ream
flow
April-July
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Making an Ensemble Forecast Using ESP
-> Future Time
Past StagesSoil/SnowStates
19711972197319741975
Blend QPF/QTF
7172737475
Historical Precip/Temps for Past YearsCreates a Flow for Each Year
Flow Traces
Past <-Past Future Time - >
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Defining Your Time For the Forecast
Past Future Time - >
Flow
Window
Make a frequency distribution using each ensemble value in the window…and then fit a probability function.
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Frequency Diagram (PDF)
Cumulative Frequency Diagram (CDF)
100 90 80 70 60 50 40 30 20 10 0Exceedance Probability
Flood Stage 18000
6%
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Raw Data(Ensemble Members)
Window
Elementary Probability Concept
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Climate Variability In ESP
Pre -Adjustment Technique Weight/Modify on Input Side
7172737475
Post -Adjustment TechniqueWeight On Output Side
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ESP Use of Weather and ClimateForecasts
HistoricalMAT and MAP
AdjustmentSystem
Adjusted HistoricalMAP and MAT
Weather Forecasts Climate Forecasts
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ESP Product Generation
Generate conditional traces with ESPSelect product attributes and generate tables and graphics with ESP Analysis and Display Program (ESPADP).
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ESPADP - ESP Analysis and Display Program
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ESPADP Options
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ESP Trace Ensembles
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Mean Daily Flows
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Mean Weekly Flows
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ESPADP Web Interface“Allows Customers to Build Their Own Products”
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Suggestions for Using ESP
Data quality control is a high priority.Be aware of biases or limitations in the model calibration.Avoid large changes to model states that cannot be explained by input data errors.Remember that ESP does not use runtime MODs.
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Future use of ESP
Better use of weather/climate forecasts.Implementation of error models.Development of short-term techniques.Development of regulated forecasts.
Reservoir and diversion impacts.Interactive use by customers/partners.
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Seamless Suite of MAT EnsemblesFrom Three Sources/Models After 'Shuffling'
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6-hour MATs
MA
T (C
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ENS 1ENS 2ENS 3ENS 4ENS 5ENS 6ENS 7ENS 8ENS 9
Unconnected MAT EnsemblesFrom Three Sources/Models Before Connecting
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6-hour MATs
ENS 1ENS 2ENS 3ENS 4ENS 5ENS 6ENS 7ENS 8ENS 9
SHORT TERM DAY 1-3 HAS
MEDIUM RANGE DAY 4-14GFS(MRF)
LONG RANGE DAY 15 – 365CPC PRE-ADJUSTMENT/ OTHER
Example of Creating a Seamless Suite of MATs
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Short Term5-day Precipitation Ensembles
QPF = 1.5 inches in two successive 6-hr periods, otherwise zero
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Short Term 5-day Streamflow Ensembles
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Short Term5-day Streamflow Forecast Distribution
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Medium Range Forecasts
MRF is colder than normal in this case.
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Input into ESP
Hourly instantaneous flow ensembles are created by ESP and saved. MRF shows higher flows than historical when it is warmer (during the first week). These may be converted into probabilistic forecasts…
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An example of the skill in producingstreamflow runoff from using temperaturand precipitation downscaled fromthe MRF vs historicalprecipitation and temperature (ESP).
It shows by using temperatures from thedownscaled MRF in lieu of historical information that streamflow forecastscan be improved.
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The End
Ensemble Streamflow Prediction Component
(ESP)