Climate information for food security in developing countries

Conveners: Abubakr A M Salih and Abdel Hannachi, Department of Meteorology, Stockholm University

Contact: abubakr@misu.su.se

Following the themes of the Development Research Conference on Food, Water and Climate that is planned to take place in Stockholm, 22-24 August 2016, we would like to propose a panel on “Climate Information and Food Security with Focus in Developing Countries”. We believe that the suggested panel fits with the objectives and complements the goals of the conference in building a research-based network on food security and climate in low-income countries. Most of these countries are under water stress and are threatened by food insecurity caused by climate variability and change, which can lead to serious social stresses and local conflicts. Our understanding of the climate system has advanced substantially and the wisdom gained can be geared towards the benefit of the affected societies.

The objective of the suggested session is to bring together researchers from developed and developing countries to foster a research-based network for providing support to developing countries suffering from the impact of climate variability and change. The panel will consider abstracts in the following topics:

1. Seasonal forecasting methods and application,
2. Decadal and longer lead-time forecasting,
3. Onset of the monsoon and sowing date,
4. Analysis of dry spells and rain days,
5. Impact of climate change on food production,
6. Climate and food security, including use of climate information in food production.

23 Aug., 11:00–12:30, Seminar Room U29

• Empirical statistical modeling of March-May rainfall prediction over southern nations, nationalities and people’s region of Ethiopia. Wondimu Tadiwos Hailesilassie and Gizaw Mengistu Tsidu, Botswana International University of Technology and Science.
• Sources of Sahelian-Sudan moisture: insights from a moisture-tracing atmospheric model. Abubakr A. M. Salih, Stockholm University.

• Nepalese farmers' adaptation strategies to climate change. Nandakaji Budhathoki, Nepal Economic Association (NEA).

• Exploring the potential of water harvesting and its impact on the rural livelihoods in Amhara region, Ethiopia. Staffan Rosell, University of Gothenburg.

• Use of Geonetcast near real time Earth Observation data and open tools for weather and climate observation and early warning. Chris M. Mannaerts, Ben H. P. Maathuis, and V. Retsios, University of Twente.

Abstracts

Empirical statistical modeling of March-May rainfall prediction over southern nations, nationalities and people’s region of Ethiopia. Wondimu Tadiwos Hailesilassie and Gizaw Mengistu Tsidu, Botswana International University of Technology and Science.

Statistical predictive models were developed to investigate how global rainfall predictors relate to the March-May (MAM) rainfall over Southern Nations, Nationalities and People's Region (SNNPR) of Ethiopia. Data utilized in this study include station rainfall data, oceanic and atmospheric indices. Because of the spatial variations in the interannual variability and the annual cycle of rainfall, an agglomerative hierarchical cluster analyses were used to delineate a network of 20 stations over study area into three homogeneous rainfall regions in order to derive rainfall indices. Time series generated from the delineated regions were later used in the rainfall/teleconnection indices analyses. The methods employed were correlation analysis and multiple linear regressions. The regression modes were based on the training period from 1987-2007 and the models were validated against observation for the independent verification period of 2008-2012. Results obtained from the analysis revealed that sea surface temperature (SST) variations were the main drivers of seasonal rainfall variability. Although SSTs account for the majority of variance in seasonal rainfall, a moderate improvement of rainfall prediction was achieved with the inclusion of atmospheric indices in prediction models. The techniques clearly indicate that the models were reproducing and describing the pattern of the rainfall for the sites of interest. For the forecast to become useful at an operational level, further development of the model will be necessary to improve skill and to determine the error bounds of the forecast.

Sources of Sahelian-Sudan moisture: insights from a moisture-tracing atmospheric model. Abubakr A. M. Salih, Stockholm University.

The summer rainfall across Sahelian-Sudan is one of the main sources of water for agriculture, human, and animal needs. However, the rainfall is characterized by large interannual variability, which has attracted extensive scientific efforts to understand it. This study attempts to identify the source regions that contribute to the Sahelian-Sudan moisture budget during July through September. We have used an atmospheric general circulation model with an embedded moisture-tracing module (Community Atmosphere Model version 3), forced by observed (1979–2013) sea-surface temperatures. The result suggests that about 40% of the moisture comes with the moisture flow associated with the seasonal migration of the Intertropical Convergence Zone (ITCZ) and originates from Guinea Coast, central Africa, and the Western Sahel. The Mediterranean Sea, Arabian Peninsula, and South Indian Ocean regions account for 10.2%, 8.1%, and 6.4%, respectively. Local evaporation and the rest of the globe supply the region with 20.3% and 13.2%, respectively. We also compared the result from this study to a previous analysis that used the Lagrangian model FLEXPART forced by ERA-Interim. The two approaches differ when comparing individual regions, but are in better agreement when neighboring regions of similar atmospheric flow features are grouped together. Interannual variability with the rainfall over the region is highly correlated with contributions from regions that are associated with the ITCZ movement, which is in turn linked to the Atlantic Multidecadal Oscillation. Our result is expected to provide insights for the effort on seasonal forecasting of the rainy season over Sahelian Sudan.

Nepalese farmers' adaptation strategies to climate change. Nandakaji Budhathoki, Nepal Economic Association (NEA).

The study aims to find farmers’ perception of climate change with the actual historical climate change data of different meteorological stations of different agro ecological regions of Nepal for last three decades. More than four fifth of the households’ heads perception on seasonal climatic parameters' trends found to be inconsistent with the actual meteorological data except farmers' perception on day time temperature of  monsoon season. The study further revealed that no significant changes in seasonal cropping pattern were observed during last three decades. However, more than half of the survey households replaced traditional varieties by improved varieties of main crops during 1980-2014 basically due to the expectation of more yields and more profits. Despite being perceived climate change, adoption decisions were merely profit and market induced. The policy implication is that providing reliable predicted information on climatic parameters and climatic variability in advance will assist farming communities to take appropriate adaptation measures to reduce the climate impact on agricultural sector. 

Exploring the potential of water harvesting and its impact on the rural livelihoods in Amhara region, Ethiopia. Staffan Rosell, University of Gothenburg.

A majority of the Ethiopian population lives in the countryside and are dependent on agriculture as their main source of income. Rain-fed agriculture is predominant and the basic assets, such as access to farm land, ox for ploughing and labour is essential to be able to produce enough food for the households. The aim is to deepen the understanding and analyse the rural livelihoods problems with a focus on the water harvesting techniques in use and the problems farmers are facing in the Ethiopian highlands. Methods that will be used are interpretation of aerial photographs, field observations analysis of climatic data such as daily rainfall and daily temperature data and interviews. Analysis of the climatic data during three different decades.  Black and white aerial photographs comparing two different years from 1936 with photographs from the 2015 will be conducted. Interviews with farmers will also be conducted. The results shows that the sharp decline of Belg rainfall in the late 1990´s makes it more difficult to grow the staple crop teff during that season which is most important from a food security perspective. The climatic changes that has taken place in the central highlands of Ethiopia during past two decades has made cultivation during the Belg season more difficult and this study will make a contribution to understand if the water harvesting ponds can make a positive contribution to the food production in this vulnerable area.

Use of Geonetcast near real time Earth Observation data and open tools for weather and climate observation and early warning. Chris M. Mannaerts, Ben H. P. Maathuis, and V. Retsios, University of Twente.

Current weather and climate information and early warning systems are getting more accessible to users worldwide, also due to current fast global innovations in data and communication technologies. This can help save lives, improve livelihoods and build resiliency in countries and regions with high vulnerability to climate. The Ilwis Open Toolbox approach presents such an opportunity for delivery of timely, accurate and actionable weather and climate information from data collections and creation sources, such as the Geonetcast near real time earth observation (EO) dissemination system and other data streams. This presentation will show the use of near real time satellite data, coupled to in-situ or weather forecast model data for the monitoring and analysis of the water and food security situation in countries. The public domain signature of both the EO data and geospatial software tools permit the water and climate community to develop own applications at user-defined spatial and temporal scale, ranging from global, regional and county level to river basins and catchments.