COMET NWP Symposium

COMET NWP Symposium
December 1999

Ensemble Forecasting Lab

Goals of this Lab:

Facilitate the use of ensemble data in the forecast process
Introduce the forecasters to different ensemble displays
Examine and use ensemble probability forecasts
Give you ideas you can impart on your staff

Schedule

Before Lab – Ensemble forecasting techniques background
Introduction and scenarios briefing 10 minutes
Complete Part 1 – February Cold front 20 minutes
Complete Part II – November event 20 minutes
Answer and discussion questions 20 minutes

Case I Background

For this case, the forecaster will use available MRF and ensemble data to forecast the temperatures and frontal passage timing along the East Coast of the United States. Temperature forecasts, clouds, and the chance of precipitation. The forecast should be very generic following the NWS standard day 3-7 forecast formats. (I.e. HIGH IN THE 30s, 40s, 50s etc). The front may produce locally heavy rains and the timing of precipitation is critical. The key is timing the front and its impact on the weather.

The ensemble data is limited to spaghetti plot forecasts of 500-mb height, a mean 500-mb height forecast, and the probability of the exceedance of 5580 m over North America.

Lab Assignments:

Each team will do the same things.

Start with the data on 07 Feb 1999 (there is no data on 9 Feb)

End with the data from 11 Feb 1999

For each Day answer the following questions:

When will the cold front pass through the cities of the eastern United States?
Is there potential for any record temperatures over the eastern United States during this forecast period?
Where is the most likely location where it will rain over the eastern United States?
Create a standard NWS extended range forecast for: (use KMDT as the approximate location)
Thursday 11 Feb
Friday 12 Feb
Saturday 12 Feb

Case II Background

For this case, the forecaster will use available MRF and ensemble data to forecast the temperatures and sensible weather for the plain States

For this case, the ensemble data includes the standard 500-mb spaghetti plots, 850 MB and surface spaghetti plots and several probability charts. The probability charts include:

The probability of rain >= 0.01
The probability of rain >= 0.10
The probability of rain >= 0.25
The probability of rain >= 0.50
The probability T 850 =< 0C
The probability T 850 >=16C

Each spaghetti chart contains the following data:

Each ensemble member
The mean forecast of each isoline
The dispersion of the forecasts
A mean forecast in the lower panel comprised of all members equally weighted
The departure of this mean from the 30 year Climatology
This departure is divided by the 30 year standard deviation showing standardized anomalies

Lab Assignments:

Each team will do the same things.

Start with the data on 05 Nov 1999 through 07 November 1999

For each Day answer the following questions:

Create a standard NWS extended range forecast for your assigned location
08 Nov
09 Nov
10 Nov
What is the likelihood of rain in the plains?
Are you confident?
Why?
What is the likelihood it will be colder than normal in the plains?
Are you confident?
Why?
What charts provide confidence that:
It will likely be rain free?
What charts suggest no heavy rain is likely?
What charts suggest it may be warmer than normal?
Did the Temperature at 850 exceeding 16C add any information?

Discussion

What should be done at your office to improve the use of ensemble data into the forecast process at longer ranges?

What should be done at your office to improve the use of ensemble data into the forecast process at shorter ranges?

What value does the spaghetti and ensemble dispersion provide? Is it an improvement over the basic spaghetti plot?

What value does the probability forecasts provide? Can you think of other useful products?

What value does having the climatological data provide the forecaster? Should these kinds of data be in AWIPS?

With multiple models and multiple solutions, how specific or generic should our 3-7 day forecasts be?