application of numerical models in the forecast process - from national centers to the local wfo...

APPLICATION OF NUMERICAL MODELS IN APPLICATION OF NUMERICAL MODELS IN THE FORECAST PROCESS -THE FORECAST PROCESS -

FROM NATIONAL CENTERS TO THE LOCAL FROM NATIONAL CENTERS TO THE LOCAL WFOWFO

David W. Reynolds David W. Reynolds

National Weather ServiceNational Weather Service WFO San Francisco Bay Area WFO San Francisco Bay Area

Monterey, CAMonterey, CA 5050thth Anniversary of Operational Numerical Weather Prediction Anniversary of Operational Numerical Weather Prediction

June 17, 2004June 17, 2004

NOAA’s National Weather ServiceNOAA’s National Weather Service

NOAA’s National Weather Service

5050thth Anniversary of Numerical Modeling Anniversary of Numerical Modeling

Models and ForecastersModels and Forecasters

• Focus talk on T+12 hrs and beyond Focus talk on T+12 hrs and beyond • For these valid times the forecaster is heavily dependent on For these valid times the forecaster is heavily dependent on

numerical model guidance. numerical model guidance.

• Major paradigm shift is taking place in how forecasts Major paradigm shift is taking place in how forecasts are being prepared at local WFOs.are being prepared at local WFOs.• Have transitioned from forecaster spending several hours Have transitioned from forecaster spending several hours

reviewing model output then manually preparing text forecasts to reviewing model output then manually preparing text forecasts to nudging an existing digital forecast database toward a new nudging an existing digital forecast database toward a new collaborated model solution, “drawing the forecast.” collaborated model solution, “drawing the forecast.”

• National Centers made significant paradigm shift National Centers made significant paradigm shift several years ago when transitioning from acetate and several years ago when transitioning from acetate and grease pencils to digital product creation.grease pencils to digital product creation.• NCEP service centers very often initiate guidance forecast from NCEP service centers very often initiate guidance forecast from

new model guidance – the forecast challenge is picking the new model guidance – the forecast challenge is picking the “right” model and value adding by knowing how to adjust for “right” model and value adding by knowing how to adjust for model biases. model biases.



• Where do Where do forecasters add value? forecasters add value? • A difficult question and A difficult question and

hard to find good hard to find good objective quantifiable objective quantifiable data, especially related data, especially related to sensible weather to sensible weather parameters. parameters.

• Long standing QPF data Long standing QPF data shows forecasters can shows forecasters can add value. Equivalent to add value. Equivalent to 10-15 years of model 10-15 years of model development.development.



• Current QPF Current QPF process in NWS process in NWS shows value added shows value added in each step of the in each step of the forecast process.forecast process.

• However However uncertainty still uncertainty still large. Migrate from large. Migrate from deterministic to deterministic to probabilistic. probabilistic.

• USWRP USWRP supportedsupported


• For other manual For other manual forecast parameters forecast parameters such as medium range such as medium range surface pressure it surface pressure it becomes more becomes more problematic to problematic to determine forecaster determine forecaster contributions. contributions. • Relates to forecast Relates to forecast

uncertainty. uncertainty.

• Begs the question of the Begs the question of the role of the forecaster role of the forecaster when uncertainty is high. when uncertainty is high.

• Deterministic versus Deterministic versus probabilistic forecasts. probabilistic forecasts.




• UKMET office does UKMET office does show some skill in show some skill in days 3 and 4 utilizing days 3 and 4 utilizing special software special software package called On-package called On-Screen Field Screen Field Modification that Modification that allows a four allows a four dimensional dimensional adjustment of model adjustment of model output through output through manipulation of manipulation of surface pressure surface pressure features. features.


Models and Forecasters – Models and Forecasters – The FutureThe Future

• Interactive Forecast Interactive Forecast Preparation System – the new Preparation System – the new paradigm. Paper by Ruth to paradigm. Paper by Ruth to follow.follow.

• 2.5 or 5 km gridded 2.5 or 5 km gridded forecasts at 1, 3, 6, or 12 forecasts at 1, 3, 6, or 12 hour temporal frequency hour temporal frequency of sensible weather, wave of sensible weather, wave heights out through day 7. heights out through day 7.

• Formatters used to Formatters used to generate text forecasts generate text forecasts from the grids. from the grids.



• More dependence now on statistically post More dependence now on statistically post processed model output then before (MOS).processed model output then before (MOS).• Model biases in 2m temperatures, dewpoints, and Model biases in 2m temperatures, dewpoints, and

inability to obtain raw model output consistent with grid inability to obtain raw model output consistent with grid resolution (2.5-5 km). resolution (2.5-5 km).

• Shear workload of populating the large number Shear workload of populating the large number of grids required questions how relevant the of grids required questions how relevant the forecaster will be in the gridded forecast process. forecaster will be in the gridded forecast process. • Forecasters coping with workload but no reliable Forecasters coping with workload but no reliable

measure of forecast quality. Lack of “analysis of measure of forecast quality. Lack of “analysis of record” at 2.5 or 5 km. record” at 2.5 or 5 km.

• Grids deterministic implying accuracy. No uncertainty Grids deterministic implying accuracy. No uncertainty provided to the customer. provided to the customer.



• No gridded No gridded verification to date. verification to date.

• Utilization of point Utilization of point verification would verification would indicate little value indicate little value being added by being added by forecasters over MOS forecasters over MOS for most if not all for most if not all parameters.parameters.

• Must have a measure Must have a measure of uncertainty. of uncertainty.



• How should we proceed?How should we proceed?• Rapid expansion into short and medium range Rapid expansion into short and medium range

ensemble forecasting provides new opportunities.ensemble forecasting provides new opportunities.

• Multi-model ensembles available from the WRF Multi-model ensembles available from the WRF architecture and multi-model medium range architecture and multi-model medium range ensembles (GFS and CMC) will provide the catalyst ensembles (GFS and CMC) will provide the catalyst to move in a new direction. to move in a new direction.

• Statistically post processed ensemble means and Statistically post processed ensemble means and calibration of ensemble probabilities could provide calibration of ensemble probabilities could provide the basis for populating the grids. the basis for populating the grids.

• Ensemble means and downscaling methods could Ensemble means and downscaling methods could provide the expected value forecasts. (Jun Du) provide the expected value forecasts. (Jun Du)

• Calibrated probabilities provide a reliable measure of Calibrated probabilities provide a reliable measure of uncertainty (probability density function). uncertainty (probability density function).



• So how does the forecaster fit into this new picture both So how does the forecaster fit into this new picture both nationally and locally?nationally and locally?• EMC and MDL prototype use of calibrated ensemble based EMC and MDL prototype use of calibrated ensemble based

forecasts and downscaling techniques to populate sensible weather forecasts and downscaling techniques to populate sensible weather grids (Test Bed). Parallel with the deterministic approach. Provides grids (Test Bed). Parallel with the deterministic approach. Provides objective measure of uncertainty we can’t get from forecasters.objective measure of uncertainty we can’t get from forecasters.– Hand off this methodology to WFOs who will QC grids locally.Hand off this methodology to WFOs who will QC grids locally.

– WFOs primary function will be the interface with local partners and customers to WFOs primary function will be the interface with local partners and customers to educate on interpretation and application of output. educate on interpretation and application of output.

• EMC and HPC begin testing methods to improve model forecasts of EMC and HPC begin testing methods to improve model forecasts of significant events via manual “intervention” in the assimilation significant events via manual “intervention” in the assimilation cycle. cycle. – THORPEX provides an opportunity to test this concept. THORPEX provides an opportunity to test this concept.



• InterventionIntervention• Forecaster intervenes with Forecaster intervenes with

data assimilation cycle during data assimilation cycle during significant expected weather significant expected weather events in order to maintain events in order to maintain critical observations in the critical observations in the forecast cycle.forecast cycle.– Methodology has proven useful in Methodology has proven useful in

MET office for major extratropical MET office for major extratropical cyclones.cyclones.

– Applications for both west and east Applications for both west and east coast rapid cyclogenises. coast rapid cyclogenises.

– Forecaster now adds value at the Forecaster now adds value at the front end, not the back end, of the front end, not the back end, of the process.process.

application of numerical models in the forecast process - from national centers to the local wfo...

Documents

numerical model guidance

guidance forecast

forecast process

new model guidance

model output

right model

model biases

forecast challenge