# Presentation: 228402

##  Part 2: Medium-Range Forecasting

- Ed O’Lenic
- Climate Prediction Center

**Notes:**
THESE MAPS WERE PRESENTED BY PRASHANT SARDESHMUKH IN AN EARLIER LECTURE.
Standard deviation maps for wintertime 500 hPa surface over 30 years.  Map (a) shows effects of daily weather.
Map (b) is very different from map (a) and shows the importance of the weekly time scale – it contains a large fraction of the total variability.  This is the time scale of 6-10 day and week 2 forecasts.

## f x P versus log f

**Notes:**
ANOTHER GRAPH FROM PRASHANT’S LECTURE.  Area under the curve integrates to 1.  Equal areas represent equal power.  The curve peaks in the 5-7 day region of time averages, the same averaging as is used for CPC extended range forecasts.  So, in terms of what’s happening in the atmosphere, these forecasts are where the action is.

## Outline

- Review
- Forecast process, tools, web page
- Tools for a recent forecast
- Official forecast
- Skill

## There is a lot of variability on the time scale of weekly mean
    daily data, some of it predictable.

Skill of daily 5-7+ forecasts is ~0. 

We can predict weekly average 500 hPa height, surface T, P probabilities with useable skill. 

CPC Week 2 forecasts are for probability of 7-day mean temperature and total precipitation at a lead of 7 days.

Three climatologically equally likely (terciles) categories.

-     daily data, some of it predictable.
- Skill of daily 5-7+ forecasts is ~0.
- We can predict weekly average 500 hPa height, surface T, P probabilities with useable skill.
- CPC Week 2 forecasts are for probability of 7-day mean temperature and total precipitation at a lead of 7 days.
- Three climatologically equally likely (terciles) categories.

- ~~~ Preliminaries ~~~

## Medium Range process schematic

- Weighted average of model 500 hPa height

- Downscale: get surface weather from 500 mb height via analogs, regression, neural network.

- R

- R

- Forecaster formulates maps of predicted T, P, PMD bulletin

- Disseminate via web, AWIPS, FOS 3-4 PM

- R

- = Forecaster reconciliation of tools required

**Notes:**
Generic 6-10 day/week 2 forecast flow of activities.

## Forecast tools

- DYNAMICAL MODELS
- Global Forecast System (GFS) Ensembles
- DAVA – _d_ivergent _a_nomaly _v_orticity _a_dvection barotropic model
- European Centre for Medium-range Weather Forecasts (ECMWF) ensembles
- Canadian ensembles
- STATISTICAL TOOLS
- Klein T
- GFS P, T
- Analog composites
- Tele-connections

## http://www.cpc.ncep.noaa.gov/products/predictions/short_range/tools/dp11.air.html

**Notes:**
This is how forecasters see the tools.

## GFS Ensemble-Mean Z500

## GFS Ensemble Mean Z500 Anomalies

## Recent Skill 

- Recent Skill

## GFS Ens Z500 Analog

## DAVA Z500 Heights

## DAVA Z500 Anomalies

## Recent Skill

## DAVA Z500 Analog

## Slide 16

## Bias-corrected GFS Z500

## Recent Skill of  Height Forecasts

## Ensemble Mean Klein T Tool

## Ensemble Mean Analog T Tool

## Bias-corrected T

## GFS Week 2 Precipitation forecast

## Ensemble Mean Analog P

## Bias-corrected GFS P

## Generic Week 2 Forecast Map

- B

- N

- N

- A

- 33

- 33

- 40

- 40

- 50

**Generic Week 2 Forecast Map**

- N=Near Normal Category
- Contours are labeled with the total probability for the indicated category.

## 6-10-Day T Outlook

## 6-10-Day P Outlook

## Z500 Official Forecast

## 6-10 day Monthly Average Skill Scores

- s=((c-e)/(t-e))*100c = # hitse = # chance hitst = # forecasts

## Heidke skill scoresofMedium-Range CPC-U.S. surface TemperatureForecasts in 2003

## Heidke skill scoresofMedium-Range CPC-U.S. surface PrecipitationForecasts in 2003

## The End