Seasonal rainfall totals of Australian stations can be modelled with distributions from the Tweedie family

2014 ◽  
Vol 35 (10) ◽  
pp. 3093-3101 ◽  
Author(s):  
Md Masud Hasan ◽  
Peter K. Dunn
2016 ◽  
Vol 68 (2-3) ◽  
pp. 243-255 ◽  
Author(s):  
EM de Jesus ◽  
RP da Rocha ◽  
MS Reboita ◽  
M Llopart ◽  
LM Mosso Dutra ◽  
...  

Author(s):  
Pundra Chandra Shaker Reddy ◽  
Alladi Sureshbabu

Aims & Background: India is a country which has exemplary climate circumstances comprising of different seasons and topographical conditions like high temperatures, cold atmosphere, and drought, heavy rainfall seasonal wise. These utmost varieties in climate make us exact weather prediction is a challenging task. Majority people of the country depend on agriculture. Farmers require climate information to decide the planting. Weather prediction turns into an orientation in farming sector to deciding the start of the planting season and furthermore quality and amount of their harvesting. One of the variables are influencing agriculture is rainfall. Objectives & Methods: The main goal of this project is early and proper rainfall forecasting, that helpful to people who live in regions which are inclined natural calamities such as floods and it helps agriculturists for decision making in their crop and water management using big data analytics which produces high in terms of profit and production for farmers. In this project, we proposed an advanced automated framework called Enhanced Multiple Linear Regression Model (EMLRM) with MapReduce algorithm and Hadoop file system. We used climate data from IMD (Indian Metrological Department, Hyderabad) in 1901 to 2002 period. Results: Our experimental outcomes demonstrate that the proposed model forecasting the rainfall with better accuracy compared with other existing models. Conclusion: The results of the analysis will help the farmers to adopt effective modeling approach by anticipating long-term seasonal rainfall.


2007 ◽  
Vol 22 (2) ◽  
pp. 229-241 ◽  
Author(s):  
Mohammad Karamouz ◽  
Saman Razavi ◽  
Shahab Araghinejad

2000 ◽  
Vol 22 (4) ◽  
pp. 24-28 ◽  
Author(s):  
Carla Roncoli ◽  
Keith Ingram ◽  
Paul Kirshen

In this article we bring anthropological reflections to bear on a recent event we participated in, whereby farmers and scientists came together to discuss the possibility of applying rainfall seasonal forecasts to improve agricultural production and livelihood security in West Africa. In so doing, We also report on the research findings from the project that organized this encounter and that we have been working with for the last three years. Our intent is to highlight the complexities and challenges inherent in this process of integrating scientific information and farmers' production decisions, while also pointing to practical issues to be considered in implementing such initiatives.


Nature ◽  
1974 ◽  
Vol 248 (5448) ◽  
pp. 464-464 ◽  
Author(s):  
Derek Winstanley

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