wmoioc 1 dbcp capacity building workshop for the western indian ocean, cape town, 19-23 april 2010...

DBCP Capacity Building workshop for the Western Indian Ocean, Cape town, 19-23 April 2010

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Regional Applications of the NCEP Coupled Forecast System (CFS)

Dr. Wassila M. Thiaw

Team Lead African and International Desks

Climate Prediction CenterNational Centers for Environmental Predictions

National Oceanic and Atmospheric Administration

http://www.wmo.int/

http://ioc.unesco.org/

http://www.jcommops.org/dbcp


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Acknowledgments

• Vadlamani Kumar and Nick Novella, CPC International Team

• EMC Ocean Modeling Team, Dave Behringer, Lead

• CPC Ocean Monitoring Team, Yan Xue, Lead

• NCEP CFS Team, Suranjana Saha and Hua Lu Pan

http://www.wmo.int/




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Climate Prediction Center Mission

• National temperature and precipitation National temperature and precipitation outlooks, but not monthly / seasonal outlooks, but not monthly / seasonal rankingsrankings

• Focus: weeks, months, seasons, years Focus: weeks, months, seasons, years (i.e. (i.e. short term climateshort term climate))

• Forecasts in collaboration with other Forecasts in collaboration with other NCEP Centers, NOAA line offices, other NCEP Centers, NOAA line offices, other agencies and labs agencies and labs

• Integral to NWS Seamless Suite of Integral to NWS Seamless Suite of ProductsProducts

We deliver climate prediction, monitoring, and assessment

products for timescales from weeks to years to the Nation and the global community for the protection of life and property and

the enhancement of the economy.

Temperature Outlook

http://www.wmo.int/




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Training Coverage

Climate Prediction Center

International DesksAfrican Desk, International Projects

Week1 PrecipitationProbability of exceedance

• Support capacity building in weather and climate in developing countries: Africa, central America, and Asia

• Provide access to NCEP global data and products to domestic and international agencies and to the public

Global TC monitoring

New Website

Africa Hazards

http://www.wmo.int/




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CPC International Desks

• Deliver climate information and services

• Transfer technology to National Meteorological and Hydrological Services and regional institutions

• Build network of well-trained international scientists

• Provide data to support NCEP’s mission

http://www.wmo.int/




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Outline

• NCEP Climate Forecast System (CFS)

• CPC Prediction and Monitoring Tools

• CFS Reanalysis and Reforecast Project

• Climate Dynamics of southern and eastern Africa

http://www.wmo.int/




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The NCEP CFS ComponentsCFS Operational Implementation : 24 Aug 2004

• T62/64-layer version of the 2003 operational NCEP atmospheric GFS (Global Forecast System) model

• GFDL MOM-3 (Modular Ocean Model, version 3)– 40 levels– 1 degree resolution, 1/3 degree on equator

• Reference: Saha et al. (2006), Journal of Climate, 19, 3483-3517.

http://www.wmo.int/




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Data Assimilation Systems

• Atmosphere (Global Data Assimilation System – GDAS)

• Ocean (Global Ocean Data Assimilation System – GODAS).

• Models incorporate observations in a dynamically consistent fashion to produce analyses of initial conditions, which provide starting point for making predictions of future conditions.

http://www.wmo.int/




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Skill in SST Anomaly Predictions

Predictions archived since 1997. The CFS shows a substantial increase in skill over the previous NCEP operational forecast model (CMP14) and comparable skill to operational statistical forecast models (CCA, CA, CONS, and MARKOV).

http://www.wmo.int/




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SST Biases for DJF and JAS

DJF Climatology JAS Climatology

Lead0 - Obs

Lead3 - Obs

Lead6 - Obs

http://www.wmo.int/




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SST Biases for DJF and JAS

DJF JAS

Lead0 - Obs

Lead3 - Obs

Lead6 - Obs

http://www.wmo.int/




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Skill for Raw and Bias-corrected Niño 3.4 SST Predictions

Bias correction improves the skill for all prediction methods (compare bottom panels with top panels).

http://www.wmo.int/




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Precipitation Biases for DJF and JAS

DJFClimo

JASClimo

Lead0 - Obs

Lead3 - Obs

Lead6 - Obs

http://www.wmo.int/




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OBS DJF Clim. 1981-2004 CFS DJF Clim. 1981-2004

http://www.wmo.int/




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CFS Wind Clim. 1981-2004 CDAS Wind Clim. 1981-2004

Atmospheric Circulation

http://www.wmo.int/




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CFS_2-tier DJF Precipitation Climatology1981-2004

OBS

CFS

http://www.wmo.int/




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Precipitation Time Series

0

1

2

3

4

5

6

7

8

1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003

CFS

CFS 2-Tier

OBS

DJF Precipitation Anomalies

-3

-2

-1

0

1

2

1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

CFS

CFS 2-tier

OBS

http://www.wmo.int/




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Precipitation Interannual Variability

RFE Oct 1 2005 – May 31 2006 RFE Oct 1 2006 – May 31 2007

http://www.wmo.int/




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Time – Latitude 5-day RFE 30-40E

2005-06 2006-07

http://www.wmo.int/




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Time – Latitude 5-day CFS 30-40E

2005-06 2006-07

http://www.wmo.int/




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3

Time – Latitude 5-day P Difference 30-40E

RFE 2006-07 minus 2005-06 RFE 2006-07 minus 2005-06

http://www.wmo.int/




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Central Africa Seasonal Rainfall Predictability

http://www.wmo.int/




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CFS PREDICTED SST for OND over DRC (cor 31%)

0.0

50.0

100.0

150.0

200.0

250.0

1983 1988 1993 1998 2003 2008

years

rain

fall

(m

m)

Forecast

Obs

CFS PREDICTED SST FOR JFM Over DRC (Cor:60%)

0.0

50.0

100.0

150.0

200.0

1983 1988 1993 1998 2003 2008

Years

Rai

nfa

ll (

mm

)

Forecast

Obs

http://www.wmo.int/




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Summary of CFS Version 2004

• CFS skill in predicting Niño 3.4 SST anomalies is greater than the previous NCEP operational 2-tier model (CMP14), and comparable to NCEP operational statistical models.

• For southern Africa, precipitation biases appear to be related to errors in low level wind fields and atmospheric convection. Nonetheless, there is some predictability in the system for the austral summer.

• Seasonal rainfall predictability can be significantly enhanced in the areas where the ENSO signal is strong such as portions of central Africa and eastern Africa by downscaling CFS forecasts.

http://www.wmo.int/




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CFS SST ForecastsMarch 2010 initial conditions

The CFS ensemble mean (heavy blue line) predicts neutral conditions to return by late spring-early summer followed by a development of La Nina that is expected to last through fall 2010.

http://www.wmo.int/




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IRI Forecasts for Niño 3.4 (March 2010)

Most models suggest a gradual return to ENSO-neutral conditions by May-July 2010, which persist into the fall.

Some models suggest the potential of continued El Niño conditions or the development of La Niña conditions during the late summer or fall.

http://www.wmo.int/




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Prediction, Assessment, and Monitoring of the climate system at CPC

• Global and Regional Climate Analysis (R1, R2, NARR, CFSR)

• Real-time Global Climate Predictions and Monitoring

• Forecast Tool Development/ Improvement• Verifications and Expert Assessments• Climate Diagnostics and Attribution• Applied Research• Outreach and Service• International Activities

http://www.wmo.int/




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Predictions and Monitoring of the Global Ocean

• Weekly and monthly briefings

– State of Global Oceans

– Variations in tropical eastern Pacific--El Niño & La Niña

– Global Climate Impacts of Sea Surface Temperatures

http://www.wmo.int/




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Global SST Anomaly (0C) and Anomaly Tendency

- El Nino condition (NINO 3.4 > 0.5oC) weakened slightly in the tropical Pacific;

- PDO was in positive phase (slide 19);

- SST was above-normal in the tropical Indian Ocean and tropical North and South Atlantic;

- Large SST anomalies in the subtropical South Pacific, and North Atlantic

- SST decreased slightly in the eastern tropical Pacific;

- SST tendency was large in the Southern Ocean

- SST increased in tropical North and South Atlantic.

-SST tendency was small in the Indian Ocean

Fig. G1. Sea surface temperature anomalies (top) and anomaly tendency (bottom). Data are derived from the NCEP OI SST analysis, and anomalies are departures from the 1971-2000 base period means.

http://www.wmo.int/




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Evolution of Indian Ocean SST Indices

Fig. I1a. Indian Ocean Dipole region indices, calculated as the area-averaged monthly mean sea surface temperature anomalies (OC) for the SETIO [90ºE-110ºE, 10ºS-0] and WTIO [50ºE-70ºE, 10ºS-10ºN] regions, and Dipole Mode Index, defined as differences between WTIO and SETIO. Data are derived from the NCEP OI SST analysis, and anomalies are departures from the 1971-2000 base period means.

- Positive eastern (SETIO) pole SSTA persisted in Mar 2010.

- Both eastern (SETIO) and western (WTIO) pole SST have been persistently above-normal since April 09.

- DMI became above-normal in Mar 2010.

http://www.wmo.int/




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- SSTA exceeding +1C presented in the tropical Indian Ocean.

- Net surface heat flux anomalies contributed to the positive (negative) SSTA tendency in the North (South) Indian Ocean.

- Convection was suppressed over the Maritime Continent, and intensified in southeastern Indian Ocean

- Consistent with the suppressed convection was low-level divergence (up-level convergence) wind anomalies in the Maritime Continent

Tropical Indian: SST Anom., SST Anom.

Tend., OLR, Sfc Rad, Sfc Flx, 925-mb &

200-mb Wind Anom.

Fig. I2. Sea surface temperature (SST) anomalies (top-left), anomaly tendency (top-right), Outgoing Long-wave Radiation (OLR) anomalies (middle-left), sum of net surface short- and long-wave radiation, latent and sensible heat flux anomalies (middle-right), 925-mb wind anomaly vector and its amplitude (bottom-left), 200-mb wind anomaly vector and its amplitude (bottom-right). SST are derived from the NCEP OI SST analysis, OLR from the NOAA 18 AVHRR IR window channel measurements by NESDIS, winds and surface radiation and heat fluxes from the NCEP CDAS. Anomalies are departures from the 1979-1995 base period means except SST anomalies are computed with respect to the 1971-2000 base period means.

http://www.wmo.int/




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CFS DMI SST Predictions from Different Initial Months

- Latest forecasts called for weak positive Indian Ocean Dipole (IOD) in fall 2010.

DMI = WTIO- SETIO

SETIO = SST anomaly in [90oE-110oE, 10oS-0]

WTIO = SST anomaly in [50oE-70oE, 10oS-10oN]

Fig. M2. CFS Dipole Model Index (DMI) SST predictions from the latest 9 initial months. Displayed are 40 forecast members (brown) made four times per day initialized from the last 10 days of the initial month (labelled as IC=MonthYear) as well as ensemble mean (blue) and observations (black). The hindcast climatology for 1981-2006 was removed, and replaced by corresponding observation climatology for the same period. Anomalies were computed with respect to the 1971-2000 base period means.

http://www.wmo.int/




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http://www.wmo.int/




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IESA – Integrated Earth System Analysis

http://www.wmo.int/




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http://www.wmo.int/




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http://www.wmo.int/




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http://www.wmo.int/




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Climate Forecast System V1 vs. V2

CFSv1 CFSv2

Atmosphere GFS 2003 (T62/L64) GFS2009 (T126/L64)

Land OSU 2-L NOAH 4-L

Ocean MOM3 MOM4

Sea ice Climatology Predicted

CO2 Fixed at 1988 level Evolving with time

Initial conditions R2/GODAS CFSR

Hindcasts 15/month CFSrR

http://www.wmo.int/




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New Global Ocean Data Assimilation

System

Ocean Model MOMv4 (GFDL)

1/2o x 1/2o

z-coord, 40 levels

Data Assimilation3DVariationalCost Function:

J = ½ (x-xb)TB-1(x-xb) + ½ (y-H(x))TR-1(y-H(x))

Model Data

First Guess Analysis

Forcing: Wind StressHeat Flux

Data:T(z)&S(z)SSTSSH

http://www.wmo.int/




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NEW GODAS

• Based on MOMv4, the new GODAS has a resolution of 1/2o x 1/2o (1/4o in the tropics). It uses a z-coordinate in the vertical and has 40 levels. The domain is global and includes an ice model.

• GODAS has a 3D variational assimilation scheme.

• Assimilation data are temperature profiles (XBT, Argo, TAO, TRITON, PIRATA, RAMA), salinity profiles (Argo, synthetic profiles derived from a seasonal T-S relation), TOPEX/Jason-1 Altimetry and SST (Reynolds’ daily 1/4o SST).

• GODAS can be forced by surface flux products (wind stress, heat flux components) in “stand alone” mode or be coupled to an atmospheric model.

http://www.wmo.int/




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New CFS at NCEP

GODAS3DVAR

Ocean ModelMOMv4

fully global1/2ox1/2o (1/4o in tropics)

40 levels

Atmospheric ModelGFS (2007)

T382 64 levels

Land Model Ice Mdl SISLDAS

GDASGSI

6hr

24hr

6hr

Ice Ext6hr

Climate Forecast System

http://www.wmo.int/




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GODAS compared with independent surface drifter velocities

MOMv4 based GODAS 1/2o resolutionGlobal

MOMv3 based GODAS 1o resolutionQuasi-global

AOML surface drifter based climatology IndependentLumpkin et al.

GODAS has eastward flow on equator in Indian Ocean

Drifters show stronger flow in westernBoundary and Southern Ocean

The agreement is very good given that GODAS does not directly assimilate velocity observations and the drifter velocities are derived from the lagrangian motion of the drifters.

http://www.wmo.int/




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MOMv4 based GODAS 1/2o resolution Global

MOMv3 based GODAS 1o resolution Quasi-global

AOML surface drifter based SST climatology Independent data(Lumpkin et al.)

GODAS compared with surface drifter velocities

http://www.wmo.int/




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CFSR

GODAS

CFSR - GODAS

CFSR SSH has a higher correlation with Altimetry SSH than GODAS SSH in the tropical Indian Ocean and extratropical Oceans, but CFSR has a lower correlation in the tropical Atlantic, which is probably associated with drifts in subsurface temperature and salinity and erroneous overturning circulation cells in the tropics (see next slide).

http://www.wmo.int/




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Climate Dynamics of Eastern and Southern Africa

• Present the basic atmospheric features of southern and eastern Africa climate

• Place the climate dynamics of the region in a global context as seen from NCEP reanalysis-1

• See if the NCEP CFS Reanalysis (CFSR) is able to capture the atmospheric features

http://www.wmo.int/




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Northern and southern hemisphere seasons

DJF, austral summer

JAS, boreal summer

Emphasis on the large-scale flow and precipitation fields

Climate Dynamics of Eastern and Southern Africa

http://www.wmo.int/




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Low level, 850 hPa geopotential heights, DJF 1979-2008

Atmospheric Circulation Atlantic-Indian Ocean Basin

Subtropicalhighs

http://www.wmo.int/




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Low level, 850 hPa geopotential heights, DJF 1979-2008

Thermallows

Atmospheric Circulation Atlantic-Indian Ocean Basin

http://www.wmo.int/




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Low level, 850 hPa geop. heights & winds, DJF 1979-2008

http://www.wmo.int/




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Low level, 850 hPa geop. heights & winds, DJF 1979-2008

CFSRRA-1

http://www.wmo.int/




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Reanalysis-1Low level, 850 hPa geopotential heights & winds

Southern Hemisphere Summer DJF 1979-2008

Northern Hemisphere Summer JAS 1979-2008

http://www.wmo.int/




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CFSRLow level, 850 hPa geopotential heights & winds

Southern Hemisphere Summer DJF 1979-2008

Northern Hemisphere Summer JAS 1979-2008

http://www.wmo.int/




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What is the relationship between the large-scale circulation and the precipitation climatology?

http://www.wmo.int/




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IntertropicalConvergence Zone (ITCZ)

South Indian Convergence Zone (SICZ)

Austral Summer DJF Precipitation

http://www.wmo.int/




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Austral Summer DJF Precipitation

http://www.wmo.int/




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Austral Summer Precipitation Characteristics

• Synoptic systems form along the SICZ, an area favorable for tropical-temperate troughs (TTTs) to develop. These systems produce much of the rainfall over southern Africa in the summer.

• TTTs account for much of the precipitation variability on the synoptic time scale with northwest to southeast oriented cloud band that span southern Africa and the southwest Indian Ocean

http://www.wmo.int/




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Boreal summer: July-August-September

http://www.wmo.int/




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Monsoon Trough

Indian Monsoon

West African Monsoon

Somali Jet

Reanalysis 1

Low level, 925 hPa geop. heights & winds, JAS 1979-2008

http://www.wmo.int/




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CFSRRA-1

Low level, 925 hPa geop. heights & winds, JAS 1979-2008

http://www.wmo.int/




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Somali Jet Characteristics

• Also called the East African Jet (EAJ)

• Likely the strongest and most sustained low-level wind patterns in the world (mean maximum wind speeds of 25 m/s – observed up to 50 m/s)

• Low-level wind speed maximum at 1.5 km msl

• Accounts for 65% of global cross equatorial mass flux

• Links African and Asian rainfall systems

http://www.wmo.int/




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Indian monsoonupper-level high

TropicalEasterly Jet

Upper level heights and winds 200 hPa JAS

Reanalysis 1

http://www.wmo.int/




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RA-1 CFSR

Upper level heights and winds 200 hPa JAS

http://www.wmo.int/




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Northern Summer JAS Precipitation

http://www.wmo.int/




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Summary Preliminary Assessment of CFSR over Africa

• For both austral and boreal summers, the subtropical ridges appear to be shallower in CFSR than in RA1, while the monsoon troughs are stronger

• The upper level jet streak in the Indian monsoon is placed farther north in the CFSR, while the upper level equatorial low is deeper.

• The precipitation positive biases in the Gulf of Guinea region during the boreal summer and in southern Africa during the austral summer appear to be related to the strong thermal lows and winds. CFSR did not seem to improve the negative precipitation biases in the Sahel north of the Gulf of Guinea region.

http://www.wmo.int/




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CPC Resources

• http://www.cpc.noaa.gov/

• http://www.cpc.noaa.gov/products/african_desk/

• http://www.cpc.noaa.gov/products/analysis_monitoring/enso_advisory/index.shtml

• http://www.cpc.ncep.noaa.gov/products/GODAS/ocean_briefing_gif/global_ocean_monitoring_current.ppt

http://www.wmo.int/




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NCEP Data Access

Daily RA2 and monthly CFSR

http://nomad1.ncep.noaa.gov/ncep_data/

Daily CFSR

www.ncdc.noaa.gov

http://www.wmo.int/




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African Desk Training Program

• Sponsored by the US National Weather Service as part of the contribution to the WMO Voluntary Cooperation Program (VCP)

• African Desk established in 1994 and hands-on-raining began in 1995. Since then the African Desk has hosted more than 90 residents from over 30 countries in Africa

• Objective: Build human resource capacity in weather and climate at NMHSs in Africa

• Professional meteorologists with at least 4-year university degree and 3 years professional experience are eligible to apply. Candidates must be nominated by the WMO PR of the country of origin

• African Desk offers 12 slots per year: six in each weather and climate desks. Trainees arrive at staggered intervals of 2 months. The duration of the training is 4 months

http://www.wmo.int/




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African Desk Training Curriculum

• Climate Desk– Modes of variability: ENSO and MJO– Seasonal rainfall predictions– Week1&2 outlooks– Climate diagnostics– Climate monitoring and hazard assessments– Satellite rainfall estimates

• Weather Desk– Use of ensembles in operational weather forecasting– Model performance evaluation and forecast verifications– Case studies– Regional modeling: NWS Weather Research Forecast (WRF)

http://www.wmo.int/




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Future Plan

• Expand CPC International Desks– International Monsoon Desk – Begin with China

and expand to include SE Asia later– Off-site 1-2 week trainings in all ocean basins:

Indian Ocean, Vietnam, June 2009; Mediterranean, Turkey, July 2010; Atlantic, summer 2011; Pacific, summer 2012

• Challenges– National resources– Implementation plan

http://www.wmo.int/




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Thank you!

[email protected]

http://www.wmo.int/



wmoioc 1 dbcp capacity building workshop for the western indian ocean, cape town, 19-23 april 2010...

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