# Presentation: 769965

## A Proposal for  NAEFS 8-14-day Forecasts

- <date/time>

- A Proposal for  NAEFS 8-14-day Forecasts

- Edward O’Lenic
- NOAA-NWS-Climate Prediction Center
- Camp Springs, Maryland
- _[ed.olenic@noaa.gov](http://www.cpc.ncep.noaa.gov/products/predictions/schedule.html)_
- 301-763-8000, ext 7528

## Summary of NCEP Proposal

- NCEP proposes to collaborate with CMC to develop and implement an automated version of its 8-14-day outlook, to be issued daily.
- The new product would cover Mexico, Canada, Alaska and the Continental United States.
-  Probability of tercile categories of surface temperature and precipitation, and ensemble mean 500-hPa height and anomalies and spread would be predicted.
- CMC and NCEP models would provide the primary model input.
- Model output would be bias-corrected every 6 hours or so.
- Model forecasts would be adjusted for systematic differences between the operational analysis and the reanalysis.
- Adjusted model forecasts would all be compared with the reanalysis climate pdf.
- Automated techniques will be jointly developed to combine the bias-corrected, adjusted forecasts from CMC and NCEP.
- Forecasts from this technique will be carefully monitored, including verification.
- A joint decision to implement these forecasts will be made.

## Modified Extended-Range Forecast Process

- Multi-model ensembles from NCEP, CMC, Others?

- Historical observations, Reanalysis, R

**Fully-automated** weighted average 500-hPa 8-14-day mean height and anomaly forecast with **spread**

**Automated** Dissemination

- Bias correction of 6-hourly model output with respect to operational analysis.

- Quantify systematic differences
- between the Operational Analysis
- and the Reanalysis, d*=R-O

- Adjust all forecasts
- by d*

- Operational Analysis, O

- Compare forecasts to the Reanalysis-based
- climate PDF

**Fully-automated** downscale to T, P tercile probabilities

- Daily real-time observations

**Notes:**
Generic forecast process.  Basic elements of ANY forecast system.

## Forecast Map Probabilities

- N

- B

- A

- Example 2.
- Pr(A)=1-0.30=0.70

- Example 1.
- Pr(B)=0.70

- Making a forecast amounts to shifting and enhancing the likelihood of the mean of the distribution (left).  The probability plotted on the map gives the likelihood that a variable will be less than the below threshold or greater than the above threshold.  The cumulative distribution function gives this probability (right).  Two examples of a 70% probability forecast, one each for below and above, are shown.

- BELOW
-  threshold

- ABOVE
-  threshold

- BELOW
-  threshold

- ABOVE
-  threshold

- Probability of a particular value of x

- Probability of x being less than a threshold

## Possible combinations of A, N, B for probability lines on CPC forecast maps.  Combinations 8, 9, 10 are rarely used.

- Possible combinations of A, N, B for probability lines on CPC forecast maps.  Combinations 8, 9, 10 are rarely used.

- Map labeled **BELOW**

- Map labeled **ABOVE**

- EC

- EC

## North American 8-14-day Forecast T

- 40% chance A,
- 33.3% chance N,
- 26.7% chance B

- 26.7 % chance A,
- 33.3% chance N,
- 40 % chance B

- 33.3 to 30.05% chance A,
- 33.4 to 39.9% chance N,
- 33.3 to 30.05% chance B

## North American 8-14-day Forecast P

## 8-14-day 500-hPa height and anomalies forecast – a weighted average of CFS, Canadian, ECMWF models

## Schematic example of forecast tools consolidation

- Temperature (F)

## Using consolidation to improve seasonal temperature outlooks by an average of 26%