Understanding User Needs for Climate Services in Agriculture

by Michele Bernardi*

Climate is both a resource and a hazard. By harnessing climate information and services for decision-makers, the agriculture sector will be better placed to provide food for a more crowded and increasingly urban world.

Technology for gathering and disseminating reliable climate information has improved. However, the information does not necessarily reflect what users need. For example, while significant advances have been made in operational seasonal climate forecasts, these are mostly global-scale products and do not provide reliable information on user-relevant scales. In today’s constantly changing environment, farmers need accessible as well as usable climate services for managing climate risks and exploiting climate resources.

Climate and agriculture

If resources are to be used in a sustainable way, they must be known, understood, assessed in quantitative terms and properly managed. Climate is no exception. Solar radiation, rainfall and temperature, together with mineral nutrition and management, are critical to primary agricultural production potential. Science-based climate information generated through observations, data and diagnostics can be used to assist farmers in planning their activities.

Agriculture constitutes the principal livelihood of 70 per cent of the world’s poor. Many of the world’s poor and hungry are smallholder farmers, herders, fisherfolk and forest dwellers, including indigenous people living in climate-sensitive vulnerable areas. Nearly half of the economically active population in developing countries relies on agriculture for its livelihood.

On average, agriculture accounts for about 30 per cent of Gross Domestic Product in agriculture-based countries and for 50 per cent of employment in the developing world. Developing countries, which represent 80 per cent of the world’s population, are home to about 500 million small farms, supporting around 2 billion people. Three out of four poor people live in rural areas, and most depend on agriculture for their daily livelihoods.

Climate variability and climate change are the main causes of stress on food production and availability. About 50 per cent of the inter-annual variability of production is due to weather variability and 5–10 per cent of national agricultural production is lost annually due to unfavourable weather conditions. Chronic losses and indirect negative effects, such as diseases and pests, by far exceed those due to extreme and statistically rare climatic events. Production losses due to pests, diseases and weeds are estimated at 26–30 per cent for sugar beet, barley, soybean, wheat and cotton; and 35 per cent, 39 per cent and 40 per cent for maize, potatoes and rice, respectively (Oerle et al., 1994).

Feeding a more demanding world

To feed a larger, more urban population in the coming years, food production – net of food used for biofuels – must increase by 70 per cent. By 2050 the world’s population is expected to reach 9.1 billion, 34 per cent higher than today. Most growth will occur in developing countries. Urbanization will continue to accelerate. About 70 per cent of the world’s population will be urban, compared to 49 per cent today. Annual cereal production will need to rise to about 3 billion tonnes from 2.1 billion today and annual meat production will need to rise by over 200 million tonnes to reach 470 million tonnes (FAO, 2009b).

At the same time, increasing demand from consumers in rapidly growing economies for more resource-intensive agricultural products (moving from grains to meat) will also add stress to global food production.

These population trends will put enormous pressure on agriculture, forestry and fisheries sectors to provide food, feed and fibre as well as income, employment and ecosystem services. At the same time, these sectors must also respond to the challenge of climate change. The challenge is to dramatically increase agricultural production to ensure global food security, while maintaining the natural resource base and responding to climate change through adaptation and mitigation measures (FAO, 2009a).

Outlining needs

Agriculture provides work in many sectors, including education, research, extension services, agro-industries and processing, commodities and trade, infrastructure, transport and pharmaceutical. Agricultural extension services provide technical guidance to farmers and are typically under the administration of each country’s ministry of agriculture. These extension services also provide useful climate information to farmers in coordination with National Meteorological and Hydrological Services (NMHSs). There are three main climate services required for the agriculture sector.

Assessment of extreme weather and climate events: Specialists use statistics on the frequency, duration and intensity of extreme weather and climate events and their expected changes to make informed decisions. They use it for long-term investment in infrastructure and land settlements such as dams for irrigation and disaster mitigation and decide on where to locate buildings. This information also helps in making cost-effective choices for which construction methods to use, and how much heating and cooling is needed for critical infrastructure.

Climate predictions: Climate predictions on monthly to seasonal to decadal (10-year) time scales help with decisions on which variety to plant and when, how much water is needed for irrigation, when and where disease outbreaks are likely to occur, or whether to reduce livestock numbers in case of drought.

Climate change projections: This information is used to indicate precipitation and temperature patterns in the time frame of 30–50 years. Projections can be used to guide major investment decisions relating to long-term water management, such as whether and where to build new reservoirs. Crop yield scenarios are also available based on climate change projections, which can guide policy on food security aspects.

Why farmers in Sub-Saharan Africa may not use seasonal forecasts Constraint to seasonal forecast use and benefits by farmers

Coarse spatial scale lacks local information

Lack of information about timing of rainfall

Lack of information about season onset or length

Ambiguity about forecast categories

Forecasts not in local language

Accuracy not sufficient

Inequitable access

Forecasts available too late

Neglected communication of favourable forecasts, bias toward adverse conditions

Access to draft power

Access to seed of desired cultivars

Access to financing

Access to land

Access to labour

Input or marketing costs

Information is not reaching users

While climate information services are essential to help address the growing demand for food in a changing climate, the information does not always reach the users who need it most. Several impediments limit the generation and the dissemination of climate information at the required quantity, quality and timeliness (WMO, 2006). These include:

• Existing data policies in several cases inhibit free and open data dissemination, either because there is financial pressure leading to institutional cost recovery, privatization, or limited resources due to low prioritization in national budgets.
• Despite the efforts in modernizing data managements systems worldwide, climate archives still need to be completely digitized, quality controlled, and homogenized especially to cover all climate elements, not solely temperature and precipitation, as well as all old climate records (WMO, 2007).
• Gaps may exist for climate observations when meteorological stations in critical areas have stopped functioning and time series have been discontinued. This has serious implications for analysis, especially for quantifying observed climate variability and change which is essential for operational management and early warning systems.
• Lack of capacity in using satellite data services

Seasonal forecasts

Intra-and inter-seasonal variability has a major impact on agriculture. Farmers may be unprepared for expected weather conditions and make decisions based on an understanding of general climate patterns in their regions. Better climate predictions three to six months in advance can help shape appropriate decisions, reduce impact and take advantage of forecasted favourable conditions. Seasonal forecasts provide probability distribution for monthly to seasonal means of climate parameters (in terms of their anomalies from climatological normals), such as rainfall and temperature, several months in advance.

Seasonal climate forecasts are mostly based on the El Niño-Southern Oscillation (ENSO) that refers to shifts in surface temperatures (SST) in the Eastern Equatorial Pacific and related shifts in barometric pressure gradients and wind patterns in the Tropical Pacific (the Southern Oscillation). ENSO activity is characterized by warm (El Niño), neutral or cool (La Niña) phases identified by SST anomalies. Although the ENSO phenomenon occurs within the Tropical Pacific, it affects inter-annual weather variability in many other regions of the world.

Good teleconnections with ENSO do exist with the regional climate during cropping seasons in West Africa, Southern Africa and the October-December “short rains” in East Africa. Forecasts based on such teleconnections and other approaches are jointly assessed by countries in the respective regions through the well-known regional climate outlook forums (RCOF), to develop a consensus-based seasonal climate outlook. For example, the map below, shows such a seasonal rainfall forecast prepared by the Southern Africa Regional Climate Outlook Forum (SARCOF), which delineates areas of expected rainfall anomalies in probabilistic form, in tercile categories (above-normal, normal and below-normal).

However, such regional-scale outlooks are far from being a climate service adapted to farmers’ needs. The output of the model was originally developed to support national meteorological and hydrological services to spatially downscale the forecasts. However, in actual practice, regional-scale seasonal forecasts reach national stakeholders in the original form, format and scale without any improvement and adaptation to the needs of users within their countries (Hansen et al., 2011).

Seasonal forecasts as prepared by the Southern Africa Regional Climate Outlook Forum (SARCOF). The climate scientists determined likelihoods of above-normal, normal and below-normal rainfall for each area. Above-normal rainfall is defined as within the wettest third of historically recorded rainfall amounts; below-normal is defined as within the driest third of rainfall amounts and normal is the middle third, centred on the climatologically median.

Bridging the digital divide

Farmers experience a “digital divide” in the use of seasonal forecasts due to content, resources, access and attention to specific needs. Obstacles that must be addressed include lack of predictability of climate and crop response at a farm scale, inadequate infrastructure to inform and support producers’ choices, inability to adjust management in response to new information, and inability to tolerate the risk of a wrong forecast. For seasonal forecasts to influence action, users must perceive the climate information service as:

• Credible – strong technical quality and authority;
• Salient – relevant to decision-makers; and
• Legitimate – in the interest of users (Hansen et al., 2011).

Improving seasonal forecasts

A big gap exists between what is needed by farmers and the seasonal forecast information that is routinely available. To respond to practical needs, the structure of seasonal forecasts should take into account: downscaling and local interpretation; growing season weather beyond the seasonal average; accuracy expressed in transparent, probabilistic terms; and interpretation of results in terms of agricultural impacts and management implications.

For example, research suggests that seasonal forecast information at the local level should at least:

• Forecast probability distribution of seasonal rainfall total plotted against the climatological distribution;
• Compare time series of historic climate observations such as monthly rainfall amount against hindcasts (i.e., results of statistical calculation determining probable past conditions); and
• Provide some information for the number of rain days (Hansen et al., 2011).

Several studies confirm that farmers can and actually do get substantial benefits when there is communication with those who produce climate information products, and when farmers’ needs are taken into account. Field surveys indicate that between 30 per cent and 80 per cent of farmers who reported receiving seasonal forecast information have changed their management practices, such as the time of planting and crop variety, based on the forecasts (Hansen et al., 2011).

Frequency of weather and climate forecasts is also an important element to be taken into account. The frequency for weather forecasts should be daily, three day and weekly. For intra-seasonal and seasonal forecasts, the frequency should be monthly and seasonal. For climate change projections, there should be a 10-year medium-term projection, as well as scenarios covering 20 to 30 years.

Climate information should include the revelant spatial and temporal resolution detail to support the needs of users at local, sub-national, national, regional and global levels. Following are some examples of needs at various levels.

Local needs encompass information for decisions on agronomic, livestock and fishery management practices. Sub-national needs include food availability, monitoring, storage and input supply, marketing, procurement and credit. National needs include information to develop policies, planning and action plans.

Among regional and international needs are food security, managing transboundary pests and diseases, river water monitoring, and tracking for extreme events such as drought and river floods.

 

Strengthening connections with users

The key elements of climate services for agriculture are: monitoring, data, tools and methods; managing risks of climate variability and climate change; managing food systems and resources; advancing payment for environmental services and risk transfer mechanisms; and contributing to food security information and emergency response.

These climate services can only be relevant if they reach the user effectively. Farmers receive information in various ways, mainly through bulletins, radio (as in Zambia), or in the best cases, by advisories and extension services.

Information providers should consider the following priorities to ensure their information is being used in a way that will generate positive action. First, they should engage user communities and work to bridge communications gaps. Second, they should build institutional and technical capacity, concentrating on mechanisms that improve better interface with users. Third, they should consider decentralizing climate services to be closer to user needs, with feedback and dissemination options. Finally, they should consciously strive to integrate advocacy and policy decision-making.

Finally, because each provider has a different purpose, they will need to focus on different approaches to improve user outreach. National Meteorological and Hydrological Services should consider the needs of agriculture support services and farmers when developing weather and climate information products.

Agronomic and agro-meteorological researchers should consider temporal and spatial dimensions of climate impacts, contingency plans incorporating new technologies and better impact data collection, as well as monitoring and analysis – including climate change.

Agriculture extension and community-based organizations should consider impact outlooks and management alternatives addressing local needs, as well as communicating information and receiving feedback.

Recommendations – opportunities for improvement

If the agriculture sector is to make the best use of climate information and services, providers should address opportunities for improvement in four areas.

Improve meteorological and climate data collection and use

• Upgrade the monitoring and data collection network in rural areas, as well as systematic data archival and management; and
• Use modern information products and implement forecasts from regional and international centres at the national level.

Increase farm level productivity to bridge yield gaps and reduce risks

• Farmers should be at the centre of the analysis of the climate impacts and response strategies.
• Deliver reliable, timely, locally understandable climate information with response options to farmers, considering inputs, credit, market and financial aspects.

Strengthen climate and agriculture services

• Integrate climate information into insurance, credit provision, crop monitoring and yield forecasting, and humanitarian response.
• Establish reliable communication mechanisms to provide needs-based information and feedback to National Meteorological and Hydrological Services and agronomic research and extension services.

Strengthen the capacity of farmers and institutions to better respond to price shocks

• Build social capital and raise awareness. These are key to enhancing trust at the community level.
• Pre-requisites must be in place such as capacity building, awareness and collaboration.

References

J.W. Hansen, S.J. Mason, L. Sun and A. Tall, 2011: Review of Seasonal Climate Forecasting for Agriculture in sub-Saharan Africa. Experimental Agriculture, Volume 47 (2), Cambridge University Press.

Oerke E., H.W. Dehne, F. Schonbeck and A. Weber, 1994: Crop Production and Crop Protection. Estimated Losses in Major Food and Cash Crops. Elsevier, Amsterdam.

FAO, 2009a: How to Feed the World in 2050. High-Level Expert Forum, FAO, Rome.

FAO, 2009b: Profile for Climate Change. FAO, Rome.

WMO, 2006: Climate Information for Development Needs: An Action Plan for Africa, Report and Implementation Strategy. GCOS 108, WMO/TD No. 1358, Geneva.

WMO, 2007: Guidelines on Climate Data Management. World Climate and Data Management Programme. (No. 60, WMO-TD No. 1376), Geneva.

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* Formerly a Senior Agro-meteorologist, Food and Agriculture Organization of the United Nations, (FAO)