Climate Exchange

Of course it isn’t as simple as that. The first task is to estimate what

information can be forecast. Actors come from various domains and

cultures, and communication is a long-term endeavour. Data are

sparse, missing, and unavailable or often considered as assets that

cannot be released. The approach is probabilistic and results are not

guaranteed at each trial, so a long-term view is needed to appreci-

ate the benefits; but understanding and accepting the principle of a

decision-making process with uncertainties is not that straightfor-

ward. And last but not least, the road is long between geophysical or

impact forecasts, and decisions or results involve many other factors,

quite often having to deal with policy, culture, economy or opportu-

nity. The devil hides in the details, and the value of the forecast must

be assessed in the real and complex chain of decision-making – for

example, can seasonal forecasting provide manageable information

for health when major decisions are taken years in advance? Many

difficulties lie ahead when climatologists and users start to consider

taking advantage of seasonal climate forecasting, but the potential

for applications and success is important and worth the effort.

For climatologists dealing with past and future climates, seasonal

forecasting is the application of climate sciences and modelling

that permits very quick feedback, and hence continuous progress

and development of skills and services. Seasonal forecasting takes

full advantage of the entire climatologist’s toolbox (numerical

climate models, downscaling, observations, statistics, etc). It also

implies a deeper knowledge of climate dynamics and geophysics,

considers the atmosphere, ocean, continental surfaces, their inter-

actions and climate dynamics. Atmosphericians, oceanographers,

agronomists and other impact sectors’ specialists have to interact

closely. For climatologists, who get involved in forecasting and can

be exposed to users’ feedback – as well as meteorologists, who can

extend the range of their capabilities from weekly or monthly to

seasonal timescales – the benefit of elaborating seasonal forecast

is tremendous, because of the exchanges and feedbacks. This also

explains why capacity building is a key aspect of seasonal forecast-

ing, which definitely must be perceived as a major climate service

to develop knowledge and know-how for meteorological services

and their users. Seasonal forecasting is a complicated activity and

using it requires a real partnership involving mutual education and

confidence as well as long-term commitment.

Water management in Western Africa

A flagship application of seasonal forecasting is the yearly fore-

cast for the Organisation pour la mise en valeur du fleuve Sénégal

(OMVS), which was created in 1972 to manage the Senegal River

basin. The Senegal River is of vital importance for the bordering

countries: Senegal, Mali and Mauritania. One of the river’s main

characteristics is its strong inter-annual variability. During the twen-

tieth century, the average yearly flow varies by a factor of six between

dry and humid years, with record flows in 1936-1937 (1,349 m

/s)

and 1984-1985 (above 220 m

/s). Such variability of course makes

water management more difficult.

Water is decisive for agriculture and irrigation. In order to opti-

mize its use, a dam was inaugurated in 1988, close to Manantali. A

few years later, the dam started to supply electricity, adding to its

expected benefits which were to improve river navigability and stim-

ulate improved agriculture through irrigation. Seasonal forecasting

is used to help manage the dam, as described in the Madrid confer-

ence proceedings.

The water resource management of the Manantali

dam is notably based on the scheduling of water releases to flood

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ealth

Cattle at Barkedji’s pond, Ferlo, Senegal

Image: © Centre de Suivi Ecologique (CSE), Dakar

the downstream valley and consequently to allow reces-

sion cultures. Will the end of the rainy season be good

enough to allow a sufficient water release for recession

cultures and the safety of hydropower production along

the dry season? An outlook before the autumn for the

next three months helps in taking relevant decisions,

making it possible to answer that key question. The

natural flow is forecast at Bakel station, far from the

dam down the river.

Luckily, the Senegal River has been monitored for a long

time. Based on historical flow records, a correlation could

be established between seasonal forecasting and flows.

Good scores are obtained, including for extreme events.

Seasonal forecasting is especially able to capture the critical

events – good or bad rainy years – for the dam manage-

ment. The information is delivered by mid-August each

year to OMVS, which can then contribute to the decision-

making process, especially on the artificial flooding of the

Senegal floodplain, allowing recession culture to start by

mid-November.

The Manantali dam seasonal forecast is a brilliant

example of climate information being fully integrated

to the decision process, and is considered to be one

of the necessary inputs leading to decision and then

action. IRD and Météo-France also forecast the natural

flow of the Niger river, at the Koulikouro station, far

from the Sélingué and the future Fomi dams. The

correlation is slightly weaker, one of the reasons

being that the length of the observations is smaller.

Such integrated application illustrates the ingredients

required for a successful climate service while deliver-

ing benefits of high value:

• Optimization of electricity production with increases

up to 40 per cent (in relationship with the year)

• Securing of 50,000 hectares for recession culture

four years out of five (compared to one out of five

with climatology alone)

• Savings of around 10 per cent of water resources.