# Designing and Implementing Weather Generators as Web Services
## 4 Case Study
The Sample of HTTP GET Request and Parameters are Described in Table 9  
One hundred weather realizations were generated. The return from the service is the list of URL of the weather realizations encoded in XML document. The graph of hundred weather realizations is visualized in Figure 7. Each weather realization contains daily maximum temperature, daily minimum temperature, daily solar exposure and daily precipitation from 1 March to the end of December, which covers one rice season. The graph shows mean, minimum, maximum, 33 rd percentile and 67 th percentile of each climate variable. Discontinuity in solar exposure, as seen at the beginning of June and the end of July (rainy period), occurs because the weather generator simulated SRAD conditioned on rainfall, i.e., when it is a wet day, SRAD is generated from a wet-day model, and vice versa. Since June and July is the Baiu period, the drop in simulated SRAD was expected. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Climate Element** & **January** & **February** & **March** & **April** & **May** & **June** \\ \hline SRAD & 9.64 & 11.95 & 14.52 & 16.66 & 17.34 & 14.71 \\ TMIN & 1.89 & 2.16 & 4.93 & 10.17 & 14.84 & 18.94 \\ TMAX & 9.28 & 10.19 & 13.6 & 18.92 & 23.15 & 26.02 \\ RAIN & 68 & 94 & 161 & 175 & 212 & 255 \\ \hline  & **July** & **August** & **September** & **October** & **November** & **December** \\ \hline SRAD & 15.98 & 17.70 & 14.27 & 12.21 & 9.92 & 9.24 \\ TMIN & 22.79 & 23.94 & 20.78 & 15.09 & 9.66 & 4.47 \\ TMAX & 29.72 & 31.34 & 28.00 & 22.69 & 17.31 & 11.89 \\ RAIN & 231 & 192 & 272 & 201 & 104 & 67 \\ \hline \hline \end{tabular}  
Unit: SRAD is MJ/m2, TMIN is C, TMAX is C and RAIN is mm.  
\end{table} 
Table 8: Statistical data of climatological data in the study area. \begin{table}
\begin{tabular}{c l} \hline \hline
**HTTP GET Request** & [[http://ee2-52-69-188-223.ap-northeast-1.compute.amazonaws.com:8080/DISAGWS/](http://ee2-52-69-188-223.ap-northeast-1.compute.amazonaws.com:8080/DISAGWS/)]([http://ee2-52-69-188-223.ap-northeast-1.compute.amazonaws.com:8080/DISAGWS/](http://ee2-52-69-188-223.ap-northeast-1.compute.amazonaws.com:8080/DISAGWS/)) \\  & rest/generate?num=100&from=2016,3&to=2016,12&kweatherhistory=http: \\  & /ec2-52-69-188-223.ap-northeast-1.compute.amazonaws.com: \\  & 8080/DataTransformation/rest/transform/http: \\  & /ec2-52-69-188-223.ap-northeast-1.compute.amazonaws.com: \\  & 8080/HW\_SOS\_2/service?service=SOS\&version=2.0.0@request=GetObservation\& \\  & MergeObservationsIntoDataArray=true\&offering=weatherhistory\_urm:IBUNYA: \\  & AMeDSAS-NIAES:GAMAGOORI-51281 \\ \hline
**Parameter** & **Value** \\ \hline Service endpoint & [[http://ec2-52-69-188-223.ap-northeast-1.compute.amazonaws.com](http://ec2-52-69-188-223.ap-northeast-1.compute.amazonaws.com)]([http://ec2-52-69-188-223.ap-northeast-1.compute.amazonaws.com](http://ec2-52-69-188-223.ap-northeast-1.compute.amazonaws.com)): \\  & 8080/DISAGWS/rest/generate? \\ \hline num & 100 \\ \hline from & 2016, 3 \\ \hline to & 2016, 12 \\ \hline weatherhistory & Data transformation service is called to translate historical data in O&M format to be WTD format. The URL of historical climatological data is [[http://ec2-52-69-188-223.ap-northeast-1.compute.amazonaws.com](http://ec2-52-69-188-223.ap-northeast-1.compute.amazonaws.com)]([http://ec2-52-69-188-223.ap-northeast-1.compute.amazonaws.com](http://ec2-52-69-188-223.ap-northeast-1.compute.amazonaws.com)): \\  & 8080/HW\_SOS\_2/service?service=SOS\&version=2.0.0@request=GetObservation\& \\  & MergeObservationsIntoDataArray=true\&offering=weatherhistory\_urm:IBUNYA: \\  & AMeDSAS-NIAES:GAMAGOORI-51281 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: DISAG Web Service Request. Case Study 2: Generating a Hundred Weather Realizations Using PDISAG Web Service by Considering Seasonal Forecast Scenarios. HTTP GET Request and Parameters Are in Table 10. The Climatological Input to the Service is Same as the Case Study 1  
We assume that climate forecast scenarios are BN = 15, NN = 32 and AN = 53.