by Dept. of Agricultural Meteorology, Centre for Soil and Crop Management Studies, Tamil Nadu Agricultural University in Coimbatore .
Written in English
Contributed articles with reference to India.
Includes bibliographical references.
|Statement||course director T.N. Balasubramanian].|
|Contributions||Balasubramanian, T. N., Tamil Nadu Agricultural University. Dept. of Agricultural Metreology., Tamil Nadu Agricultural University. Centre for Soil and Crop Management Studies.|
|LC Classifications||S600.64.I4 S56 2001|
|The Physical Object|
|Pagination||196 p. :|
|Number of Pages||196|
|LC Control Number||2002291703|
The chapters contributed to this book express a wealth of knowledge and experience on generating and applying seasonal climate forecasts in agricultural and natural ecosystems. In the introductory section the impact of climate variability and the potential for using seasonal forecasts in managing climate Cited by: Introduction. Recent advances in climate modeling have resulted in increased ability to predict rainfall in many parts of the world with a lead time ranging from a few days to a few months, by using dynamical forecasts or statistical methods ().Seasonal rainfall forecasts are particularly suited for rainfed farming systems, which constitute the main source of livelihood for African rural Cited by: Access to seasonal climate forecasts can benefit farmers by allowing them to make more informed decisions about their farming practices. However, it is unclear whether farmers realize these benefits when crop choices available to farmers have different and variable costs and returns; multiple countries have programs that incentivize production of certain crops while other crops are Cited by: Climate Action Benefits: Agriculture and Forestry Learn more: The U.S. has a robust agriculture sector that produces nearly $ billion per year in agricultural commodities. 1 The sector ensures a reliable food supply and supports job growth and economic development. 2 In addition, as the U.S. is currently the world’s leading exporter of.
The U.S. Climate Prediction Center (CPC) has been issuing long-range forecasts for the contiguous U.S. since (), for example for crop producers or natural gas suppliers (Kerr, 30).Until , these forecasts had no lead-time (i.e., the forecast started with the issue date), and forecasts were three-month aggregated and based on three probabilistic categories (above, below, . 1. Introduction. Climate change is altering the statistics of temperature and precipitation. More frequent and severer weather extreme events are anticipated to impose greater damages to ecosystems and agricultural systems (Easterling et al, , Katz, Brown, , Wigley, ).Recent analyses show that changes in climate partly contributed to stagnating crop yields in the EU since the . CLIMATE PREDICTION Farmers, ski-resort operators, and heating-oil suppliers would very much like to know what the coming winter will be like. If a strong El Niño were brewing in the tropical Pacific, at least some of them would be in luck. The official United States winter forecast could warn them, with considerable reliability, that the Southeast and the Gulf Coast will be cooler and wetter. The changing climate presents challenges and opportunities for U.S. agricultural production, forest resources, and rural economies. These threats have significant implications not just for farmers, ranchers, and forest landowners, but for all Americans. Land managers across the country are observing the effects on seasons due to a changing climate.
Assessing impacts of climate variability and use of seasonal climate forecasts have become increasingly important elements in the management "toolkit" for many Australian farmers. In the case of climate, this includes observation, research, and prediction. For example, the societal impacts experienced during the – El Niño event accelerated monitoring programs to improve understanding of the physical system, and led to the development of seasonal forecasts for societal benefit. The need to educate farmers about weather and climate impacts on agriculture is even more urgent given the devastating impacts that recent weather disasters have had on agriculture locally and predictions of increasing weather and climate variability. If these forecasts verify, annual agricultural production is likely to become increasingly. Purpose: This paper documents and evaluates collaborative learning processes aimed at developing farmer's knowledge, skills and aspirations to use seasonal climate forecasting (SCF). Methodology: Thirteen workshops conducted in engaged over stakeholders across Australian sugar production regions. Workshop design promoted participant interaction, stimulated discussion, .