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Virtual Climate & Weather Station for Smart Farming
Jai-Ho Oh
*, J.-H. Shim, J.-W. Oh and M.-R. Hue
Nano C&W Co. Ltd. , Seoul, Korea
Recently, IPCC has set a new strategic plan on climate war to stabilize the current global warming trend. The Paris Agreement central aim is to strengthen the global response to the threat of climate change by keeping a global temperature rise this century well below 2 degrees Celsius above pre-industrial levels and to pursue efforts to limit the temperature increase even further to 1.5 degrees Celsius. To reach these ambitious goals, the Paris Agreement requires all Parties to put forward their best efforts through nationally determined contributions (NDCs) and to strengthen these efforts in the years ahead
However, there is neither evidence that carbon removal could serve as a viable alternative to emissions reduction nor it could stabilize the warming trend. The polar ice caps have melted faster in last 20 years than in the last 10,000. The researchers found that the ice on the Greenland is vanishing four times faster than it was in 2003. The recent research has concluded that there’s only a 5 percent chance that the world can hold limiting below 2 degrees Celsius and a mere 1 percent chance that it can be limited below 1.5 degrees Celsius.
Agriculture is influenced by weather condition rather than other environmental factors. Many studies about the impact of weather or climate conditions to the output of agricultural products have been done (Burhan and Handan, 2002; Chen et al, 2004). Menza and Silva (2009) mentioned that meteorological variables affect resource availability and fundamental processes associated with crop growth and development. Yield of crop can be also determined by weather or climate conditions such as the amount of rainfall, seasonal trend, and meteorological disaster.
However, the future weather condition cannot be controlled, hence agrometeorological forecasting service is very important to help most of the cultivations. Ministry of Agriculture and Forestry (2001) conducted the development of regional climate prediction and application system for agriculture. Subsequently, Shin and Lee (2014) suggested the practical use of information on seasonal prediction to forecast agricultural productivity. Efforts have been vested towards advanced research pertaining to application of seasonal prediction for agricultural productivity.
For a practical usage to agricultural community for smart farming, daily prediction data is used in crop model. Moreover, ultra-high resolution prediction data is also useful especially over regions that are deprived of observational data. Therefore, considering the needs of agricultural community, we
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constructed virtual climate and weather station to provide seamless agricultural environmental condition from past to future. For prospect estimation of crop yield during growing season we have introduced a high resolution synthetic method for temperature, precipitation and winds.
