CPC Forecasts: Current and Future Methods and Requirements Ed O’Lenic NOAA-NWS-Climate Prediction Center Camp Springs, Maryland [email protected] 301-763-8000,

CPC Forecasts: Current and FutureMethods and Requirements

Ed O’Lenic

NOAA-NWS-Climate Prediction Center

Camp Springs, Maryland

[email protected]

301-763-8000, ext 7528 

Summary• CPC long-lead seasonal outlooks are produced using, in order of

perceived reliability:

- ENSO composites, trend, soil moisture and dynamical models (DMs) and statistical models.

• Frequent model changes hamper perceived reliability of DMs.

• Lack of convincing information about model biases reduces reliability of DM forecasts.

• Weather/climate impacts of AO, MJO, PDO are known.

• Prediction of AO, MJO, PDO is not yet possible.

• DMs cannot yet predict subtle differences among ENSOs.

• Stratospheric annular mode (SAM) is a link to AO prediction.

• DMs ability to predict SAM is unknown/doubtful.

• Relationship of Indian Ocean to predictable signals is unclear.

• Relationship of QBO, Southern Hemisphere mid-latitude circulations to predictable signals is unclear.

WEATHER vs. CLIMATE

Weather/climate links

- ENSO- Teleconnections- Extreme events- Tropical storms- Drought/Floods- Climate/Weather Monitoring

Applied Research, Diagnostics and Forecast ToolsCollaborators: EMC, CDC, GFDL, IRI

Dynamical/statistical models

- Tools Evaluation- Real-Time Diagnostics- Model Simulations- Ensembles- Verification

Decadal Variability

- PDO- AO/NAO- Global Warming

Intra-seasonal Variability

- Tropical MJO- Blocking- AO/NAO/NPO/PNA

Seasonal Extended RangeClimate Prediction Center Forecast System Schematic

HighFrequency:Interannual

Low-Frequency:

Trend

U.S.Threats Assessment

6-10 Day

Week Two

Monthly

International Threats

Forecast Process Schematic

Dynamical Model Forecasts

Recent observationsHistorical

observations

Verifications/Statistical tools

Downscaling, Analogs, Composites

Web pages, automated databases

Forecaster-created or automated products

Dissemination to public

TOOLS VS

SIGNALS

ENSO

STRONG

ENSO MODER-ATE

ENSO

WEAK-

NEUTRAL

PDO AO MJO STRAT

ANNLR

MODE

QBO

COMPOSITES

o o o ? o o ? ?

TREND o o o ? ? ? ? ?

COUPLED AGCM

o o o ? ? ? ? ?

STATISTICAL TOOLS-

CCA, REGRESSION o o o ? ? ? ? ?

SOIL MOISTURE –

SUMMER o o o? ? ? ? ?

TOOLS VS SIGNALS

TOOL RELIABILITY: o ~ 70-100% o ~ 30-70% o ~ < 30%

Forecast tools page

Forecast tools web page

CMP T Forecasts

CMP NDJ 2000-01 T Verification

CCA 0.5 Mo lead NDJ T Outlook

OCN 0.5 Mo lead NDJ T Outlook

CMP 0.5 Mo lead NDJ T Outlook

OFFICIAL NDJ 2001-02 T Outlook

CMP P Forecasts

CMP NDJ 2000-01 P Verification

CCA 0.5 Mo lead NDJ P Outlook

OCN 0.5 Mo lead NDJ P Outlook

Official NDJ 2001-02 P Outlook

Operations Concept for Ocean/Atmosphere Model

• NCEP currently uses dynamical coupled ocean-atmosphere models in combination with statistical models to produce seasonal outlooks with ½ to 5 ½ month leads and, to a lesser extent, monthly outlooks with ½ month lead. Enhanced model operations which include increased numbers of ensemble members, more frequent model runs and enhanced capability to include the influence of within-season variations in SST and OLR will be used to:

- Produce more highly resolved distributions of predicted variables,

- Produce forecasts which increasingly and more appropriately reflect the influence of intra-seasonal variability on middle latitude climate,

- Produce improved week 2 and monthly outlooks and develop and implement new outlook products for the week 3-4

period.- Develop and implement new products to predict seasonal variations in frequency of extreme events, primarily during ENSO.

Detailed operations concept for ocean-atmosphere model

Currently, coupled dynamical model forecasts are one of several tools used in

preparing long-range outlooks. NCEP’s model is run to produce one set of

ensemble forecasts per month during the first week of the month. This is done in a

two-tiered system, in which first, an ensemble of 16 ocean forecasts are created

using a coupled GCM. The average of these is used as the official SST forecast.

This SST forecast is then used as the lower boundary for an AGCM to create a set

of 20 atmosphere ensemble members. The forecasts are run out to 9 months. A

20-year run of the AGCM is created each month. The seasonal means from this

run are used as the climatology to create anomaly maps from each of the

ensemble members. The means of these anomaly maps are used as the forecast

tools which are presented to the forecasters.

The forecasters use the NCEP model tools, together with other model tools to

subjectively create outlook maps of the probability of monthly and seasonal mean

temperature and total precipitation category.

1. Crop/Stock Dam age 2. Energy Savings 3. Famine 4. Fires 5. Fisheries Disruption 6. Health Risks 7. Hum an Fatalities

8. Pests Increased 9. Property Damage10. Tourism Decreased11. Transportation Problems12. Social Disruptions13. Wildlife Fatalities14. Water Rationing

Impac ts from 1997/98 E l N ino

1

1 8

1011

136

4

14

610

11

14

3

4

7

11

12

1

5 1 144

1

11

1434

6

8

9

9 9

101213

5

1

14

69

9

11

789

91

4

78

91113

52

~

El Nino Global Impacts

Summary• CPC long-lead seasonal outlooks are produced using, in order of

perceived reliability:

- ENSO composites, trend, soil moisture and dynamical models (DMs) and statistical models.

• Frequent model changes hamper perceived reliability of DMs.

• Lack of convincing information about model biases reduces perceived reliability of DM forecasts.

• Weather/climate impacts of AO, MJO, PDO are known.

• Prediction of AO, MJO, PDO is not yet possible.

• DMs cannot yet predict subtle differences among ENSOs.

• Stratospheric annular mode (SAM) is a link to AO prediction.

• DMs ability to predict SAM is unknown/doubtful.

• Relationship of Indian Ocean to predictable signals is unclear.

• Relationship of QBO, Southern Hemisphere mid-latitude circulations to predictable signals is unclear.