1. Climate Prediction Applications Science Workshop
Jim Noel
Senior Hydrologist
NOAA/ National Weather Service
Ohio River Forecast Center
March 4, 2008

2. Outline History of Flood Outlooks Why change now?
Ensemble Streamflow Prediction (ESP)
Climate Forecasts within ESP
Experimental Water Resources Outlooks
Expansion of Climate Products – Examples
Summary

3. History Subjective in nature Only produced in flood season
Based on series of text products
Subjective in nature
Only produced in flood
season
Not a continuous water
watch for high and low
flows
From Hydrologic Information Center – April 14, 2006

4. Why Change Now? Need for continuous water watch
Need to collaborate with our partners more
Technology advances allow us to provide more useful information
Innovate or dissipate

5. Ensemble Streamflow Prediction
River Forecast Centers capture soil moisture using
SAC-SMA (Sacramento) hydrologic soil moisture accounting model and capture snow using SNOW-17 model
Good estimations of soil moisture and snow pack water contents are critical to accurate hydrology (RFCs) and meteorology and climate (NCEP) forecasts.
To get good soil moisture estimations requires good precipitation inputs
Two main zones, an upper and lower

6. Ensemble Streamflow Prediction
Manual Calibration Program (MCP)
Operational Forecast System (OFS)
Ensemble Streamflow Prediction (ESP)
MCP
ESP
OFS

7. Ensemble Streamflow Prediction
Ensemble Streamflow Prediction (ESP) necessary component used to take short range deterministic SAC-SMA model into short term climate predictions of rivers
Similar in concept to the ensembling approach used for atmospheric modeling
RFC NWSRFS/ESP/Probabilistic
The continuous models feed short term deterministic and longer term probabilistic forecast to the Advanced Hydrologic Prediction Service.
Advanced Hydrologic Prediction Service

8. Ensemble Streamflow Prediction
Multiple streamflow scenarios with historic meteorological or forecast weather/climatic data
Possible scenarios
Flow
Scenario 2
Scenario 1
Scenario 3
Saved model states reflect current conditions
Time
So how does the ESP technique work? You begin by having the hydrologic model save the model states at a particular time. By comparing the model results to observed conditions, the model states can be adjusted to reflect the current conditions. Once saved, a model state acts as a starting point for future simulations. Since observed precipitation and temperature data haven’t happened yet, multiple scenarios using historic or forecast data can be used as input to the model. From each set of inputs, a possible streamflow hydrograph can be generated. Taken together, an ensemble of possible hydrographs are produced.
Once several scenario hydrographs are calculated, the results can be used to generate probabilistic streamflow values.
Results used in statistical analysis to produce
forecasts with probabilistic values
©The COMET Program

9. Ensemble Streamflow Prediction
Future
Now
Past
Low chance of this level flow or higher
Medium chance of this level flow or higher
Flow
High chance of this level flow or higher
In another example, past observations are use to adjust the hydrologic model. The current time is when model states are saved. The future will use forecast or historic data as input to the model to produce possible hydrographs. Here, a series of hydrograph traces are generated, each based on a particular set of input values. The resulting traces give an idea of the range of possible flows.
For this case, because all of the traces are above this point, the probability that this flow will occur is very high. For the this second case, there is a medium chance flows at this level will occur since some of the traces were above and below this point. For the third case, chances of this flow are low, since all of the trances are lower than this particular value.
Time
©The COMET Program

10. Climate Forecasts Within ESP
Pre Adjustment Technique
Weight/Modify on Input Side 71 72 73 74 75
Post Adjustment Technique
Weight On Output Side
We can use the pre-adjust technique by modifying the traces based on CPC outlooks before running each trace. The conditional trace versus historical trace.
We can also generate all the historical traces and then weight certain years based on things such as ENSO, the post adjust technique.

11. Climate Forecasts Within ESP
Historical
MAT and MAP
Adjustment
System
Adjusted Historical
MAP and MAT
Weather Forecasts
Climate Forecasts
This is the pre adjust technique where we generate each historical trace and then modify based on HPC 5 day QPF and CPC 30 and 90 day temperature and precipitation outlooks

12. Climate Forecasts Within ESP
Long range seasonal water supply
Spring snowmelt volume forecasts
Spring snowmelt peaks
Minimum flows for navigation, irrigation, environmental, recreation, etc
Water Resources Outlooks

13. Climate Forecasts within ESP
90-day probability of exceedance
Blue line is an historical simulation based on climatology
Black line is the conditional simulation with CPC inputs
Conditional simulation based on CPC inputs yield lower potential for flooding and high flows.
This is the result of ESP for AHPS that the NWS currently uses. This is the 90-day probability of exceedance. The historical simulation is in blue. I think of this as the current states plus normal conditions.
The black line is the conditional simulation with CPC outlooks. CPC outlooks made this 90-day outlook drier at the high end and wetter at the lower end.

14. Water Resources Outlooks
Uses NWSRFS SAC-SMA and ESP
Uses HPC/CPC Outlooks
Can generate a whole host of products
An experimental product of NOAA/NWS
Being develop for the 30 to 90 day period
A new continuous water watch product is in development. It is the WRO product for the Ohio Valley by OHRFC using ESP. SERFC is also working on WRO stuff.

15. Water Resources Outlooks
Partner with USGS/USACE
Utilize USGS streamflow percentiles
Verify product based on
USGS 28-day mean flows
Experimental has ended, waiting for operational approval
GOAL: Slowly expand nationwide

16. Water Resources Outlooks
Based on basins and point forecasts
159 of 266 OHRFC points have 30, 60 and 90 day expected streamflows
20 more USGS points could be used but incomplete data

17. Water Resources Outlooks
30-day Verification
August 2006 through January 2008
POD above normal flows = 0.78
FAR above normal flows = 0.30
POD below normal flows = 0.65
FAR below normal flows = 0.09
Percent of forecast basins in correct category = 78%

18. Water Resources Outlook
Other Approaches
Use analog years (year weighting technique in ESP (Post-Adjustment) based on atmospheric and oceanic response (ENSO/NAO etc)
Run ESP with CPC outlooks and analog years approach
Research on this is being done by OHRFC and hopefully Michigan Tech

19. Expansion of Climate Products - Examples
Probability of reaching flood stage
Uses NWSRFS SAC-SMA and ESP
Generated at NCRFC for minor, moderate and major flooding
An experimental product of NOAA/NWS
Being expanded at other RFCs
A new continuous water watch product is in development. It is the WRO product for the Ohio Valley by OHRFC using ESP. SERFC is also working on WRO stuff.

20. Expansion of Climate Products - Examples
Link WRO for each of our points to probability function images
Allow customers to drill down into the WRO further
Allow customers to modify risks based on ENSO as a starting point
This work is being driven by NWS Western Region
A new continuous water watch product is in development. It is the WRO product for the Ohio Valley by OHRFC using ESP. SERFC is also working on WRO stuff.

21. Summary
Technology (ESP) has advanced to allow subjective text based flood outlooks to be replaced by a more objective based water resources outlook
Climate forecasts are integrated into hydrologic forecasts mostly through adjustments to the inputs in the Ensemble Streamflow Prediction
Water Resources Outlooks would provide a continuous water watch for streamflows in the 1-90 day period for expected flows
Water Resources Outlooks would not only be for high flows but ALL flows

22. Summary Streamflow categories are based on USGS percentile categories
Verification is based on USGS data
Designed to promote NWS/USGS/COE and help us and other partners and customers in their missions!
The climate products can be used in providing necessary information on flood and drought potential during the coming months.