 In the last class we had a discussion on role of climate managers, since their role is to disseminate the developed agro-adversary to the farmers at the village level. That is for mass communication. In the last weeks, we have learned the weather forecast and how to prepare the agro advisories. That type of exercise is being done through human intervention. People signed this to work at the weather forecasting center. They develop a forecast through computer and communicate with the regional meteorological center. Then it comes to the agro met field units. Those people are examining their forecast and they prepare the agro advisory based on the crop weather interaction. Information received from the district officials, indigenous knowledge, thumb rules. And they communicate to the farmers through SMS. This is me happened. The present stage also like that. But today we take you to something wonderful way of future activity. This has been tried, a prototype has been tried in Tamil Nadu. How to prepare agro advisory along with preparation of the forecast for 5 days. And send to the farmers on direct mode. No human intervention is required. This will be discussed in today's class. Before that we have to do some exercise. That exercise means we have to learn something on selected weather window. This is highly useful for the preparation of agro advisory on computer mode. Now you may ask what is weather window. The weather window is defined here. It is nothing but combination of weather elements with threshold level. If you take rainfall 0 or 15 millimeter or 40 millimeter some threshold level. From permutation and combination exercise done against individual selected weather elements. That will be seen. For example we like to select weather elements for developing or generating weather windows. That weather elements must have higher impact on crop production. Or must have a higher risk with crop production. For example rainfall. If rain is there there is no problem. If rain does not occur there is a problem. Likewise in the maximum temperature, minimum temperature, cloud cover, mean relative humidity. And also wind speed are considered for selecting the weather window. But in Tamil Nadu case study something different that we will be discussing later. Now why it is required? Why the weather window is required? So developing agro advisories in advance for selected crops. Normally in the case of the human intervention in earlier classes. After the receipt of your forecast you prepare agro advisories. Here when weather window is prepared already. And also you will be preparing agro advisories in advance. And you put it in computer. So these weather windows provide an opportunity to prepare our agro advisories in advance. So that people can adopt in mass way. In mass adoption is highly possible through this way. Now coming to the usefulness of the weather window. So preparation of agro advisories in advance as I told earlier. Once in the weather window occurs in reality. You have already stock of agro advisories. That will be picked up by the computer and communicate to the farmers with no time loss immediately. But in the case of our man-made agro advisories minimum it takes 2 to 3 hours to prepare the agro advisories. Everything is prepared. This is like a cooked meal. You can eat very well. You need not wait for cooking. So waiting time is not available. There is 100% hope to reduce the crop production risk under this Mali-Voland weather situation. Mali-Voland means it is a bad weather situation. So how it was developed for Tamil Nadu this is very very important. See we have to prepare a set of weather elements under single weather window system. Now in the case of the Tamil Nadu Agriculture University we have taken rainfall as one among the weather elements to be considered important on developing crop production risk. Maximum temperature, minimum temperature, mean orgage that is morning orgage and evening orgage will be added divided by 2 mean orgage and wind speed. These are the selected weather elements considering their importance in Tamil Nadu crop production. Then next step is I have selected 1, 2, 3, 4 levels of rainfall. This is the amount of rainfall that is being received in Tamil Nadu across the seasons or across the whole of the year. So 1 level is 0 mm. This is a dry level. Then 0.1 to 20 mm. Then 20.1 to 30 mm and greater than 30.1 mm. Likewise there is 3 levels of maximum temperature selected. 3 levels of minimum temperature selected and 3 levels of mean orgage selected. Then wind speed also 3 levels. If you multiply these 4 rainfall, 3 temperature, 3 minimum temperature, 3 orgage, 3 your wind speed you get 324 combination, permutation and combination that I have given. So this permutation combination we get by involving all those selected weather elements we get 324. So after arriving these 324 weather windows, if you select all mean same, it may not be useful, it is very hard to use it on practical purposes. That is why what we did, we selected and collected weather data from the Tamil Nadu Agricultural University Meteorological Observatory and we validated. See we have selected different weather elements for different over years and it was validated with the 324 weather windows now developed. We could see only 24 weather windows were found valid with real-time data of the past years. Then again we had an exercise with weather data from some other centre and this was verified again. Then we felt that it is deficit to accommodate all the weather scenarios of Tamil Nadu. Then some re-exercise was done, we have selected another 30 from 324 combination already made and put it as 54 that is given in the next slide. So the 54 weather windows now selected were validated with block level data. In Tamil Nadu they have established automatic weather station in 385 blocks. So from the each block selected block we collected weather data as per the recommendation given by Mooli 1994. That is 6 stage were selected from January for cold weather period, April for summer months, July for your south-east monsoon season and October for north-east monsoon season. So these 6 stage weather data were validated with our 54 weather windows and we found that our selected 54 weather windows were really good to accommodate all seasonal influence that occur in Tamil Nadu. Then we stopped doing that, then I like to show the 54 weather windows for your observations, weather window 1, rainfall 0, maximum temperature lesser than 20, minimum lesser than 20, mean horoscope greater than 40, wind speed is lesser than 5. Like that we have developed 54 weather windows. So these weather windows would be able to accommodate all weather situation across seasons of Tamil Nadu. So this is a package, weather window package we have developed. This package will be effective into computer or your server specially meant to accommodate weather windows and this was done as a first step. So with this I complete this class and we will continue the remaining in the next class.