By Naveen P. Singh, Cynthia Bantilan, Kattarkandi Byjesh, Swamikannu Nedumaran
This e-book emphasizes the position of farm point model as a key in developmental pathways which are challenged via weather dangers within the semi-arid tropics of Asia and Africa. It throws mild on key matters that come up in farm point affects, model and vulnerability to weather switch and discusses Q2 methodological techniques undertaken in learn domain names of Asia and Africa
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Additional info for Climate change challenges and adaptations at farm-level : case studies from Asia and Africa
2. A systematic planned methodology was adopted for this study and it was uniformly followed for all the countries. Five rounds of training and coaching support were provided to the lead partner organization on: (i) climate data and socio-economic quantitative data analytical methods; (ii) geo-statistical environmental data analysis; (iii) qualitative data collection and analysis; (iv) cropenvironmental modelling; and (v) econometric modelling to assess climatic impact on net revenue. This was undertaken to ensure uniformity in research processes and outputs among the six country cases.
The type of data, data source and analysis for these countries are given below. P. Singh et al. parameters such as maximum temperature, minimum temperature, rainfall, relative humidity (morning and evening), sunshine hours and wind speed for 300 stations spread across the country for the period of 1951–1980. Application programs were developed for computing potential evapotranspiration (PET) using a modified Penman method and a water balance parameters computation using the Thornthwaite and Mather (1955) method.
However, as data sets were limited in some country cases, findings for these countries are analysed from a regional perspective. The research approach encompasses all the three components of climate agenda: namely exposure, sensitivity and adaptive capacity. The activities of the project include: 1. , from representative samples of target countries. 2. Survey and comparison of farmers’ perceptions about climate change and variability compared with detailed trend analyses of long-term climate data from nearby stations.