weatherdata_japan_AODH

Transcript

1. Asia Open Data Hackathon Weather-Driven Solution
2. Weather Data Common/general use“weather forecast” ［Actual conditions］ Weather maps ［Forecast］ source:JMA(Japan Meteorological Agency
3. Weather Data source:JMA(Japan Meteorological Agency Weather satellite (Himawari)
4. Weather Data source:JMA(Japan Meteorological Agency Wea th er ra d a r Radar nowcast
5. source:JMA(Japan Meteorological Agency AMeDAS Automated Meteorological Data Acquisition System Weather Data Warnings/Alarms
6. Weather Data source:JMA(Japan Meteorological Agency Weather forecast（short term）
7. source:JMA(Japan Meteorological Agency Weekly forecast Weather Data
8. Components of Weather Information: Time Period 過 去 Past 現 在 Present 未 来 Future
9. JMA (Japanese Meteorological Agency)・ Data Distribution Formats 現在 Present PNG Observation/ Analysis 過去Past CSV Records 未 来 Future XML Forecasts/ Estimates
10. Past: CSV (Numerical values) Various data Present: PNG （Images） Meteorological Satellite Center Future: XML （text） Information for disaster prevention Reading Distributed Data（Visualization) JMAHP http://www.jma.go.jp/jma/
11. Weather forecasts, distribution forecasts, time series forecasts, actual and expected weather maps, weekly weather forecasts, early warnings for abnormal weather events, seasonal forecasts Weather warnings & alarms, weather and typhoon information, flood forecasts for designated rivers, landslide warning information, tornado warning information, high temperature warning information, radar nowcasts (precipitaion/thunderstorms/tornados), high resolution precipitation nowcasts, analysis of rainfall amounts, short-term precipitation forecasts, etc. Information on dust and ultraviolet rays Information for Everyday Life Weather satellite(10 minutes/ 2.5 minutes) AMeDAS（Map/Table) Estimated distribution of weather events, airport weather Eruption warnings and forecasts, eruption bulletins, falling ash forecasts, information analyzing the state of volcanos, maritime warnings due to volcanic activity, volcanic gas forecasts XML Format: 68 kinds (JMA HP) Maritime warnings, maritime forecasts/regional maritime distribution forecasts, actual and expected maps for coastal wave conditions, observation information on tide levels and waves
12. XML Format: 68 kinds (JMA HP) ↓ ↓ Data contents source:JMA(Japan Meteorological Agency
13. Temperature (high and low) XML Formats: Text/Graphic Display Weather, winds, waves Chance of rain source:JMA(Japan Meteorological Agency
14. AMeDAS temperature CSV Format... Graphic Display Temperature, wind direction and speed, amount of precipitation, hours of sunlight, humidity, atmospheric pressure source:JMA(Japan Meteorological Agency
15. CSV Format... Table Display Temperature, wind direction and speed, amount of precipitation, hours of sunlight, humidity, atmospheric pressure, weather Source:JMA(Japan Meteorological Agency
16. CSV Format...Display as a Graph source:JMA(Japan Meteorological Agency Temperature, wind direction and speed, amount of precipitation, hours of sunlight, humidity, atmospheric pressure, weather
17. PNG Format... Images
18. Using the Data Utilization of the results Weather data (Measurements× forecasts) The effect of weather
19. Examples of Data Use ・Distribution of home electronics ・Soft drinks ・Supermarkets and convenience stores ・Drugstores ・Apparel and fashion ・Agriculture: To prevent crop damage due to extreme temperatures, to prevent red mold(Fusarium ear blight)
20. Examples of Data Use: Selling Clothing (Shoes) Analysis Data Collection Quantitative Analysis At what temperature, ▲▲℃, does some product, ••, begin to sell? Weather data (Temperature) × Product Data (Sales) Actual Conditions/Records
21. “Managing Weather Risks” Example ｓource:JMA(Japan Meteorological Agency Examples of Data Use 20 Sales increase significantly around an average temperature of 20℃ Quantitative Analysis: Sales ×Temperature (Recorded observations)
22. ”Manaing Weather Risk”Example source:JMA Examples of Data Use Quantitative analysis ×Temperature(Forecast: Two weeks in advance) Possibility of an increase in sales over the next two weeks Chance of temperature below 20℃ in the next two weeks: 83％
23. [Shop] Adjust displayed goods (increase/decrease) Proactively recommend products Increase VMD (Visual presentation effects) [Warehouse] Increase distribution of goods to the shop Examples of Data Use: Clothing Sales (Shoes) Application of the analysis and the predicted results
24. Possibilities and challenges concerning the use of data Weather has an effect on everything that goes on in society Health Emotions Medicine Housing Clothing Food Disaster Prevention Weather
25. Possibilities and challenges concerning the use of data Weather ? Health Emotions Medicine Housing Clothing ? Food Disaster Prevention ?
26. Possibilities and challenges concerning the use of data Weather ? Health Emotions Medicine Housing Clothing ? Food Disaster Prevention ? Weather × •••…Unlimited Possibilities
27. Conculusion ・Most important issues: Weather data is not being applied to many industries, even those in which it has strong potential. ・The weather data discussed here can be found at: http://odhack.asia/en/
28. Dataset
29. Dataset SAMPLE data 3rd to 5th on July 2017