Seasonnal Forecastingin Africa

J.P. Céron – Direction de la Climatologie

The Oceanic Forcing (ENSO) Planetary influence of El Niño (on left) and La Niña (on right)

The RCOFs Processes Main Objectives

To reduce the socio-economic vulnerabilty of countries to the impacts of Climate events,

To strengthen the capacity of NMHS and their users in the domain of Long Range Forecasts and their use,

To provide usefull and comprehensible products to the benefit of end-users (from making decision domain, National Authorities, Agriculture, hydrology, health domain, …).

Seasonnal Forecasting Process in Africa - RCOF (1)

Preforum (typically a few weeks) Presentation of key points for the next rainy season, Preparation of national statistical forecasts, Capacity building activity to the benefit of NMHS and users in

relationship with the general topics of Fora Sharing of experience in creating new products or improving exixting

material, Forum (typically a few days)

Presentation of the last informations on the climate system and its evolution,

Elaboration of consensual and regional products forecasting the quality of the next rainy season (+ hydrological caracteristics),

Presentation and discussion about specific topics (Agriculture, Climate forecasting, Hydrology, Climate and Health, Communication, …).

Discussion on expected, desirable and/or realistic developpments,

Seasonnal Forecasting Process in Africa - RCOF (1)

Dissemination Dissemination of products by the NMHS, and interpretation to the

benefit of users including national adaptation of regional products.

Update of the forecasts (Monthly base) : Continuous adaptation of the forecasts to the last available information

on the climate system and its evolutions (notably update of the SST).

Evaluation of Forecasts : Quality of rainfall forecasts (technical evaluation) and use of the

Forecasts (Users’ point of view evaluation – interest and value).

The RCOF processes (2) Process evaluation :

Pretoria meeting (16 – 20 October 2000) Sarcof (2000 – DMC Harare) Presao 5 (June 2002 - Niamey)

The RCOF processes (3) Targetted Zones :

West Africa

(5 PRESAO) Central Africa

(1 PRESAC) East Africa

(10 GHACOF) South Africa

(6 SARCOF) North Africa

(PRESANOR)

The forecasting method Oceanic key zones

Central/East Pacific (Niño 3 & 3.4 boxes), Atlantic (including the Atlantic dipole), Guinean Gulf Indian Ocean

Regions depending of the features of the rainy season in Africa. Use of information coming from SST

Countries divided by Zones, One model for each zone, Multiple Regression models and setpwise predictors selection, Transformation of quantitative forecast into qualitative forecast

(building 3 categories using the terciles of the anomalies’distribution), Evaluation of the quality of each model using cross validation and

contengency tables (Observed categories vs Forecasted categories)

Africa and ENSO in summer

Interannual variability

The Sahel and the Atlantic dipole

Climatic variability Warm=wet Sahel

Cool=dry Sahel

Cool=wet Sahel

warm=dry Sahel

The statistical models An exemple of National Forecast : The Congo Brazzaville

ZONING

11 12 13 14 15 16 17 18 19-5

-4

-3

-2

-1

0

1

2

3

4

BRAZZA

DJAMBALA

GAMBOMA

IMPFONDO

MAKOUA

MPOUYA

SIBITIMOUYONDZIDOLISIE

POINTE_NOIRE

SOUANKEOUESSO

Iso-correlation Factor1

11 12 13 14 15 16 17 18 19-5

-4

-3

-2

-1

0

1

2

3

4

BRAZZA

DJAMBALA

GAMBOMA

IMPFONDO

MAKOUA

MPOUYA

SIBITIMOUYONDZIDOLISIE

POINTE_NOIRE

SOUANKEOUESSO

Brazzaville

Djambala

Dolisie

Gamboma

Impfondo

Makoua

Mouyondzi

Makabana

Mpouya

Ouesso

Pointe_noire

Sibiti

Souanke

KelleZONE 4ZONE 3

ZONE 2ZONE 1Iso-correlation Factor3

3 models are calibratedfor the September – October – November

season

Statistical models

Zone 1(id) = – 0.053 + 0.011 PAC (Mai)

R = 0.628 R2 = 0.394 Performance of the model : SKILL(3) = 0.513

Zone 2(id) = 0.025 – 0.006 ALT (Mai)

R = 0.544 R2 = 0.296 Performance of the model : SKILL(3) = 0.647

R = 0.54 R2 = 0.292 Performance of the model : SKILL(3) = 0.44

Zone 3(id) = – 0.077 – 0.008 ALT – 0.129 EOF 07 (Août)

D

N

W

- 1.833

- 0.261

0.08

1.274

- 1.513

- 0.219

0.146

2.068

- 0.451

ZONE 1 ZONE 2 ZONE 3

- 0.997

-- 0.313

0.215

1.417

0.288

- 0.395

THE QUANTITATIVE / QUALITATIVE FORECAST

The Consensual Forecast To put together forecasts coming from each country, To take into account the complementary information

coming from Numerical Models (coupled and forced), To adapt the different forecasts to the expected evolution

of the climate system, to the Climate expertise of wellknown experts, ….

The Result : Regional forecast (AO, AC, GH, SA) expressed as a probabilistic forecast for the 3 categories previously presented (Dry, Normal and Wet)

Concensual ForecastRainfall

-15 -10 -5 0 5 10 15 20 25

5

10

15

20

25

3 5

4 0

2 52 5

4 0

3 5

5 0

3 0

2 0

3 5

4 0

2 5

2 5

4 0

3 5

P REVISION SAISONNIERE DES P LUIES EN AFRIQUE DE L 'OUEST, LE TCHAD ET LE CAM EROUN

JUILLET- AOUT- SEP TEM B RE 2 0 0 1

ZO NE I ZO NE II

ZO NE IIIZO NE IV

Consensual ForecastHydrology

Seasonnal Forecast

MAM 2002 GH

Seasonnal Forecast 2002 AO

Seasonnal Forecast

SOND 2002

AC

- 5 0 5 1 0 1 5 2 0 2 5 3 0

-15

-10

-5

0

5

10

15

20

Saison Oct-Nov-Dec 2002

Saison Sept-Oct-Nov 2002

2 5

4 5

3 0

3 5

4 5

2 0

2 0

3 5

4 5

2 0

4 5

3 5

3 5

5 0

1 5

PREVI SI O N SAI SO NNI ERE DES PRECI P I T AT I O NS EN AFRI Q UE CENT RALE

ET LES PAY S DU GO LFE DE GU I NEE

SAISO N SEC H E

SAISO N SEC H E

Seasonnal Forecast

SOND 2002 GH

Seasonnal Forecast

OND 2002 SA

Seasonnal Forecast

JFM 2003 SA

Forecast Verification A National exemple : The Niger

2 4 6 8 10 12 14

12

14

16

18

20

22

Zone Ouest

Zone Est

Zone Sud

5 02 52 5

3 54 52 0

4 53 52 0

Au-dessus de la Normale

Au-dessus de la Normale

Normale

M IS E A J O U R D E L A P R E V IS IO N S A IS O N N IE R E D E S P L U IE S (J u ille t-A o u t-S ep tem b re 2 0 0 1 )

2 4 6 8 10 12 14

12

14

16

18

20

22

< à la Norm ale (10.7% ) Proche à la Norm ale (35.7% ) > à la Norm ale (53.6% )

Situation Pluviom étrique Observée durant les m ois de juillet - août - septem bre 2001 au Niger

1 2 3 4 5 6 7 8 9 10 11 12 13 14

12

13

14

15

16

Pluviom étrie Observée Pour juillet - août - septem bre 2001 en Point de grille de1degré Latitude X 1 degré Longitude

Supérieur à la Normale

Proche à la Normale

Inférieure à la Normale

1 2 3 4 5 6 7 8 9 10 11 12 13 14

12

13

14

15

16

Pluviom étrie Prévue Pour juillet - août - septem bre 2001 en Point de grille de1degré Latitude X 1 degré Longitude

Inférieure à la Normale

Proche à la Normale

Supérieur à la Normale

1 2 3 4 5 6 7 8 9 10 11 12 13 14

12

13

14

15

16

Différence entre Catégorie de Pluie Observée et Prévue en Point de grille de1degré Latitude X 1 degré Longitude

Hit (Observé = Prévu)

1/2 Hit (Prévu Normal à Humide, Observé soit Normal soit Humide

Erreur d'une catégorie(Prévu Humide, Obs Normale)

Erreur de deux catégories(Ex. Prévu humide, obs Sec)

Forecast Verification A Regional exemple : South Africa

Forecast Verification A Regional exemple : South Africa

Conclusions on RCOFs A quite common way for seasonnal forecasting in

Tropical regions (WMO/Clips), Processes presently evaluated and recognized as a

very usefull Processes, Expected improvments for the future :

Evaluation of use and value of the forecasts, Elaboration of new products users’oriented and

adapted (notably but not only in term of downscaling), Consolidation and improvment of existing material

(like statistical models, new predictors, mixing of informations coming from different models, … ),

Strengthenning the communication toward users. …..

The Evaluation of RCOFs’ Processes What is well adressed

Strengthenning of capacity building of NMHs Trainning of Climate forecasters, Forecast of the quality of the next rainy season and the

discharge of the main rivers (not everywhere).

What is less adressed : The use of the forecasted products (notably the

improvement of products and the demonstration of the real value of the SIF),

Involvement of all the partners (including national levels and financial supports),

Some Scheduling problems (dates, welfare problems, …)

The Preforum Major problems :

Some organisation problems, Use of the experience of participants (new vs experienced

people), Lack of expertise for users categories,

Positive points : Satistical software quite well appreciated (despite some

problems for graphical aspects), Satistical methods seen as good starting base (despite the

SSTs limitations),

The Forum Major Problems :

Organisation problems (not everywhere), Lack of confidence of users and Authorities in Forum’s

products,

Positive Points : To be preserve and improve

The dissemination Major problems :

Comprehension for, usefulness of and confidence in disseminated products (partly related to the probabilistic formulation),

A few technical problems to get efficient tools for dissemination,

Dissemination (sometime) only toward the National Authorities,

Update of the Forecasts Major problems :

A few difficulties with internet capabilities, A very few feedbacks to the update from users ,

The Evaluation Major Problems :

Scheduling of evaluations (depending of the products : e.g. rain vs river discharges),

A few feedbacks from users (organisation?), No evaluation on the reason why the forecast is right or

wrong, Lack of feedbacks toward all the participants (e.g. Global

Numerical Products Centres). No evaluation of the use and the value of Seasonal to

Interannual products.

Conclusions and Suggestions Suggestions (for Presao) :

Fix the process in a sustainable way particularly in term of resources (human, material and finances),

Get, in a contractual form, the commitment of the different participants,

Create a committee in charge of the follow-up of the organisation (including Planification and organisation of PRESAO sufficiently early - at least 6 month in advance), its progress report and the reporting of decided actions in the frame of Presao,

Reorganize the different component of the process (notably in term of calendar and delocalisation),

Install pilot studies at the national level that use seasonal forecasting, particularly but not only, in order to establish the value and the usefulness of the products,

Conclusions and Suggestions Suggestions (for Presao) :

To organise the sharing of experiences at the regional or sub-regional level,

To strengthen the users’ linkage (particularly to take into account present and future needs) and to insist on training of the dissemination chain of information,

To write a PRESAO guide where should be explained, in a step by step way, the methods and described inputs and outputs, (without forgetting the update of the guide!),

To organise an inventory at the country level devoted to the evaluation of all encountered problems in each country.

Some other available products (1) Numerical products from big numerical

seasonnal forecasting centres (ECMWF, IRI, NCEP, MF, UKMO, JMA, …)

Specific statistical products built out off Africa (UKMO, African Desk, …)

Other Products Beginning and end of the rainy season (AO -

Omotosho) Intraseasonnal evolution

Some other available products (2) Numerical products from big seasonnal numerical

forecast centres (ECMWF, IRI, NCEP, MF, UKMO, JMA, …)

Elaboration of numerical products Direct Methods (deterministic and probabilistic products)

formulation as Indices or Anomalies

m/s,...mm/D, C,

FFAO

F

%

Model forecats compared to its own climatology

Adaptation to « local » observation properties

Numerical products

Numerical products

Numerical products

Last Forecasts JFM

Butterfly effect (JFM Forecast)

Statistical products

Statistical products

Other Products Beginning of the rainy season

Omotosho method using the wind shear int the lower and middle troposphere,

Low-frequency evolution of rainfall, Numerical Products (Céron & Guérémy) Statistical adaptation of GCM (Mainguy,

Guérémy & Céron for Kenya)

Some complementary products Forecasts at smaller time scales (Monthly/10

days monitoring and forecasts) Exemple of DMC (East Africa) Exemple of ACMAD (Experimental product -

Kamga – West Africa)

Some complementary products Monthly bulletins (DMC)

Drought Severity – October 2002 Rainfall anomaly – ASO

Some complementary products 10 days follow-up and forecasts (DMC)

Drought Severity – Decade 31 Forecast – Decade 33

Some complementary products 10 days bulletins and associated forecasts

(ACMAD)

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Tel. : (227) 73 49 92 or 72 31 60 Fax : (227) 72 36 27 or 72 28 94 E-mail :

acmadem@acmad.ne Internet : http//www.acmad.ne

November 26, 2002

REPORT FOR THE PERIOD OCTOBER – NOVEMBER 2002

Andre KAMGA FOAMOUHOUE

ACMAD - NIAMEY-NIGER

ABSTRACT

The objective of this report is to discuss some climate events of 2002, the predictions issued by ACMAD and the potentials related to increase in support for development of applications based on international centers products. A follow up activity to evaluate the effective and efficient use of weather and climate information may be suggested. Some future activities will be presented.

Seasonnal Forecastingin Africa (additionnal)

J.P. Céron – Direction de la Climatologie

East Africa and the SST signal

Southern Africa and the Indian Ocean signal

Summary: For the Indian Ocean, Negative correlations (up to –0.6) exist between area-averaged rainfall in southern Africa and central equatorial Indian Ocean SSTs (Makarau, Rocha, Jury, Pathack, Mason, Zhakata, Landman).

The window comprising the equator-10°S and 60-70 ° E offers useful forecast guidance at 3-6 months prior to austral summer.

At –9 months, rainfall is positively correlated with SSTs in the South Indian Ocean (r=+0.42 near 35 ° S, 65 ° E)

Southern Africa and the Atlantic signal

Summary: The Atlantic Ocean correlations between Atlantic Ocean SSTs and area-averaged rainfall in Southern Africa have been relatively weak for operational usage (e.g., Walker, Pathack, Landman, Rocha, Mason, Makarau, Zhakata)

.Central Atlantic SST are however positively correlated with early summer rainfall over western South Africa, Namibia, Angola and DRC