1. Introduction to SARWeather Ólafur Rögnvaldsson – IMR/Belgingur or@belgingur.is Logi Ragnarsson – IMR/Belgingur logi@belgingur.is Cloud Computing Education series

2. Acknowledgement SARWeather is a joint research project led by IMR/Belgingur, in collaboration with NOAA/ESRL, the University of Bergen, and the private companies GreenQloud and DataMarket. To ensure maximum usability for SAR operators, SARWeather is developed in close collaboration with ICE-SAR and the Civil Protection Department of the Icelandic Police. SARWeather was initially funded in part by grant number 550-025 (Vejrtjeneste for Søberedskab) from NORA and by the European Commission under the 7th Community Framework Programme for Research and Technological Development (GalileoCast). GalileoCast is managed by GSA, the European GNSS Supervisory Authority. Current development of SARWeather is funded in part by the Icelandic Technical Development Fund – RANNÍS Development related to the SUMO has in part been funded by the COST project ES0802 SAR Weather – www.sarweather.comwww.sarweather.com Cloud Computing Education series

3. Atmospheric Models Global vs. regional The WRF model Importance of resolution Current Crisis Response System SARWeather demonstration Use of observations from UAS’s Conclusions and future work Overview SAR Weather – www.sarweather.comwww.sarweather.com Cloud Computing Education series

4. Atmospheric models Set of equations that describe the atmospheric flow and need to be integrated forward in time to produce a weather forecast Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com Global Regional

5. Atmospheric models Set of equations that describe the atmospheric flow and need to be integrated forward in time to produce a weather forecast Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com Regional Initial and boundary data come from global models

6. Open source model developed in collaboration of NCAR, NOAA, FSL, AFWA, NRL, Univ. of Oklahoma & FAA Five development teams with sixteen workgroups More than 160 official developer Additional development by academic and governmental institutions in the US and abroad Very large user community, excellent support Non-hydrostatic Regional and global applications Wide range of scales for both real time and idealized applications Optional data assimilation; 3D-VAR, 4D-VAR, EnKFM, and FDDA Has been modified for volcanic applications Includes a dust module (re-suspension of dust/ash) The WRF atmospheric model Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com

7. Importance of high resolution Cloud Computing Education series

8. Importance of high resolution How does the weather model “see” this mountain? Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com

9. Importance of high resolution Vatnajökull icecap, max height is 1675m. Top height of Mt. Öræfajökull is only 880m True height of Mt. Öræfajökull is 2119m Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com At 1km resolution the max height is 2020m. Top height of Mt. Öræfajökull is now 1945m

10. Importance of high resolution 9 km resolution 10 15 20 25 30 35 40 45 m/s Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com

11. Importance of high resolution 3 km resolution 10 15 20 25 30 35 40 45 m/s Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com

12. Importance of high resolution 1 km resolution Cloud Computing Education series

13. Simulation results are also affected by the choice of parameterization schemes Rögnvaldsson, Ó., Bao, J.- W., Ágústsson, H., and Ólafsson, H.: Downslope windstorm in Iceland – WRF/MM5 model comparison, Atmos. Chem. Phys., 11, 103-120, doi:10.5194/acp-11-103- 2011, 2011. SAR Weather – www.sarweather.comwww.sarweather.com Cloud Computing Education series

14. Importance of high resolution How is the wind flow over this mountainous peninsula simulated at 9 and 1 km resolution? Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com

15. Importance of high resolution When model resolution is increased to 1 km the true complexity and strength of the wind field becomes apparent Very high resolution – 1 km Medium resolution – 9 km SAR Weather – www.sarweather.comwww.sarweather.com Cloud Computing Education series

16. Why not always use 1km resolution? Need 1000-times more CPU power to simulate a 1 km resolution forecast than a 10 km one for the same region! Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com

17. You only need high very high resolution once in a while? Computer clouds (e.g. Azure, EC2 and GreenQloud) are starting to offer HPC service Offers great scalability Relatively cheap And there is already a solution out there What if SAR Weather – www.sarweather.comwww.sarweather.com Cloud Computing Education series

18. Quality weather information help improve decision making Current CRS uses the WRF model and consists of a Backend and Frontend Frontend is called SARWeather Easy to use Fast Flexible model output and presentation CF and ArcGIS compliant output files Interactive and static maps Crisis Response System SAR Weather – www.sarweather.comwww.sarweather.com Cloud Computing Education series

19. Simulated and observed surface winds on 15 July 2009 at 15 UTC WRF at a resolution of 500 m forced with ECMWF-data on model levels. Observed surface winds in red Mt. Esja High resolution not always sufficient Model simulates a see-breeze that is not seen in observations Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com

20. SUMO and WRF The SUMO (Small Unmanned Meteorological Observer) can measure winds, humidity, pressure, and temperature in a vertical profile up to a 4km height SAR Weather – www.sarweather.comwww.sarweather.com Can be operated in cold climates Cloud Computing Education series

21. SUMO and WRF This data can be assimilated with the WRF weather forecast Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com

22. The SUMO-data is incorporated into the WRF-simulation, via obs-nudging SUMO and WRF Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com

23. Simulated and observed surface winds on 15 July 2009 at 13 UTC WRF at a resolution of 500 m forced with ECMWF-data on model levels and SUMO data Observed surface winds in red Effects of additional observations The flow structure is now in much better agreement with available observations Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com

24. Simulated flow in N-S section across Mt. Esja A major difference in flow pattern extending far above mountain top leve 23 km Wind speed, ranging from 0 to 12 m/s Effects not just at the surface Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com

25. Effects can be far reaching CTRL - ObsNudge Marius O. Jonassen, Haraldur Ólafsson, Hálfdán Ágústsson, Ólafur Rögnvaldsson, and Joachim Reuder (2012). Improving a high resolution numerical weather simulation by assimilating data from an unmanned aerial system. Accepted for publication in Monthly Weather Review “Substantial improvements of winds, temperatures and humidity in the region are achieved” SAR Weather – www.sarweather.comwww.sarweather.com Cloud Computing Education series

26. Transmitting data from the field SAR Weather – www.sarweather.comwww.sarweather.com Three profiles used to nudge the forecast at times 11:55, 12:58 and 14:38 UTC Site altitudes ~ 1300 m.a.s.l. Profile heights ~ 2000 m.a.g.l. From 860hPa to 650/680hPa One profile used for comparison at 16:30 UTC Observations made over Myrdalsjokull ice cap in South Iceland on 17 May 2012 Data can be transmitted via 3G mobile connection Cloud Computing Education series

27. Transmitting data from the field SAR Weather – www.sarweather.comwww.sarweather.com Observations made over Myrdalsjokull ice cap in South Iceland on 17 May 2012 Obs in black WRF - noSUMO in red WRF - withSUMO in blue Profile used for nudging @ 14:38 UTC Profile used for comparison @ 16:30 UTC 850 hPa 750 hPa 850 hPa 750 hPa Temperature Wind- speed Temperature Wind- speed -20°C -10°C 0°C 5m/s 10m/s Problems with low-level windspeed and a cold bias 2hrs after last profile Cloud Computing Education series

28. The SUMO has been equipped with an optical dust sensor Additional sensors GP2Y1010AU0F is a dust sensor by optical sensing system: An infrared emitting diode (IRED) and an phototransistor are diagonally arranged into the device It detects the reflected light of dust in air Especially effective to detect very fine particle In addition it can distinguish smoke from house dust by pulse pattern of output voltage Saturation at about 500μg/m 3 Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com

29. The SUMO dust sensor has been tested in France and Iceland Preliminary results SAR Weather – www.sarweather.comwww.sarweather.com Cloud Computing Education series

30. The SUMO dust sensor has been tested in France and Iceland Preliminary results Sensor is now being calibrated and tested with ash from Mt. Eyjafjallajökull Ascending Descending Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com

31. Calibration – preliminary results The sensor (BU) readings show high sensitivity in the range 125 – 300. After that the sensitivity is rather low in the range 350 to 700. Using the meter for ash surveillance for jet aircrafts, the best thing would be to designate below 300 as “safe” but above 400 as “unsafe” SAR Weather – www.sarweather.comwww.sarweather.com Cloud Computing Education series

32. Various uses of model output To correctly simulate distribution of pollutants, it is very important to correctly simulate the atmospheric conditions close to the source. Data courtesy of Prof. Saji Hameed at the University of Aizu, Fukushima. Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com

33. Various uses of model output Output from SARWeather could also be used as input to coastal waves and circulation and storm surge models such as the coupled SWAN+ADCIRC system Simulated maximum water level for hurricane Gustav, September 2008. Taken from www.adcirc.orgwww.adcirc.org Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com

34. Misc. datasources (optional) Current research and development Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com

35. Current research and development Cloud Computing Education series SAR Weather – www.sarweather.comwww.sarweather.com

36. Model resolution is important Especially in the vicinity of complex terrain On-Demand CR system has been developed Called SARWeather – www.sarweather.comwww.sarweather.com Data from SARWeather can be used as a driver for a number of other modeling systems Additional observations can improve the simulation Vertical profiles made by the SUMO, radiosondes or other means The SUMO is a low-cost system with many advantages Proof of concept before investing in a more durable and expensive UAS Additional sensors are being added to the system Is currently being integrated to the SARWeather CR system Conclusions SAR Weather – www.sarweather.comwww.sarweather.com Cloud Computing Education series

37. Continue improving usability Re-occurring forecasts Add output at different vertical levels Add weather parameters for aviation Visibility, icing potential, turbulence severity Better support for mobile devices Location based services Add support for different modeling systems, e.g. Dispersion models Wave and storm surge models Flash-flood modeling What would you like to see? Interest in developing add-on solutions for SARWeather? Future work, collaboration? SAR Weather – www.sarweather.comwww.sarweather.com Cloud Computing Education series