Royal Netherlands Meteorological Institute Ministry of Infrastructure and the Environment

Transcription

1 Royal Netherlands Meteorological Institute Ministry of Infrastructure and the Environment 3D Exploration of Weather Data in Combination with IASI L2 Products for Better Understanding of Potential Applications Michal Koutek, S. de Haan, I. van der Neut, F. Debie, P. de Valk (KNMI), S. Tjemkes (EUMETSAT) Date:

2 Preliminary Visualization study for the MTG IRS project MTG-IRS objectives: To support regional NWP in Europe, through detailed 3D fields of temperature, humidity, and wind at high vertical, horizontal and temporal resolution To support now-casting and very-short range forecasting Obviously, a lot of effort is put into development of L2 algorithms and products. Dwell L0 Earth Detection element Interferogram time wave number Spectral sounding L0 L1 processing L1

3 IASI as proxy for IRS IASI: Polar-Orbiting Hyper-Spectral Sounder

4 Input data for our visualization study: MTG-IRS L2 Proxy (IASI) Data EUMETSAT provided us with: Point-profiles at ECMWF levels with prior fields (ECMWF) and retrieved fields (IASI L2): Temperature, specific humidity, and relative humidity Quality control indicators We have computed derived fields such as Theta-W. Besides pressure information we need geometric height for 3D grid. Note on retrieval algorithm: EUMETSAT implemented the UWPHYSRET algorithm as the IRS Level 2 Development and Validation Processor (IRS-L2DVP).

5 Statistics: Important step in understanding Statistical methods such bias and standard deviation provide a global overview of the numerical quality of the retrievals. What can be the next step beyond statistics and numerical analysis? bias std. deviation bias std. deviation [KNMI: Siebren de Haan, Gert-Jan Marseille, Paul de Valk]

6 Next Step: Visualization and Exploration Our approach: Apply a well-established concept of interactive 3D visualization of meteorological data that uses Virtual Reality. => Weather 3D Explorer application [KNMI] Provide meteorological context to the IASI retrieval data with actual satellite and RADAR images, and NWP models such as ECMWF and HARMONIE. Let the forecasters and the scientists interactively explore the weather situation and study the 3D profile data.

7 Selection of weather cases Which MetOpA/B swath to take for a detailed exploration? :00 utc :00 utc :00 utc

8 Selection of weather cases Valid retrieval points and cloude-free areas :00 utc :00 utc

9 Putting the pieces together :00 utc :00 utc

10 Iso-contours of CLOUDS (HARMONIE model)

11 Iso-contours of RAIN intensity (HARMONIE model)

12 Cross-section Theta-W (HARM) Cross-section Theta-W (IASI L2) Cross-section Theta-W (IASI L2)

13 Method: Bring the 3D point-profile data into 3D grid.

14 Method: Bring the 3D point-profile data into 3D grid.

15 Method: Bring the 3D point-profile data into 3D grid. Specific humidity L2VDP (IASI)

16 Visualize the gridded profile data in 3D Specific humidity L2VDP (IASI) NOTE: SPARSE DATASET

17 Visualize the gridded profile data in 3D Specific humidity L2VDP (IASI) 3D cross-sections, color-mapping 3D iso-surfaces NOTE: IT IS A SPARSE DATASET

18 For context provide satellite images, ECMWF model clouds

19 Exploring retrieved fields: Temperature Temperature IASI

20 Exploring retrieved fields: Temperature Temperature ECMWF

21 Exploring retrieved fields: Temperature Temperature DIFF = IASI - ECMWF

22 Exploring retrieved temperature and model temperature ECMWF ECMWF IASI IASI

23 Exploring retrieved fields: Relative humidity Rel. humidity IASI

24 Exploring retrieved fields: Relative humidity Rel. humidity ECMWF

25 Exploring retrieved fields: Relative humidity Rel. humidity DIFF = IASI - ECMWF

26 Exploring retrieved fields: Specific humidity Spec. humidity IASI

27 Exploring retrieved fields: Specific humidity Spec. humidity ECMWF

28 Exploring retrieved fields: Specific humidity Spec. humidity DIFF = IASI - ECMWF

29 Interesting observations: Specific humidity

30 Interesting observations: Temperature

31 Interesting observations: Theta-w :00utc

32 Interesting observations: Theta-w :00utc

33 Interesting observations: Theta-w :00utc

34 Interesting observations: Theta-w :00utc

35 Interesting observations: Theta-w :00utc Theta-w (IASI)

36 Interesting observations: Theta-w :00utc Theta-w (ECMWF)

37 Interesting observations: Theta-w :00utc Theta-w (DIFF) IASI - ECMWF

38 Exploring differences: Temperature Background: ECMWF cross-section Foreground: IASI data points

39 Exploring differences: Relative humidity Background: ECMWF cross-section Foreground: IASI data points

40 Exploring differences: Specific humidity Background: ECMWF cross-section Foreground: IASI data points

41 Time for short videos

42 Conclusions Interactive 3D exploration may be very helpful for understanding of actual weather situation and interpretation of retrieved atmospheric profiles. We cannot make the data better than they actually are, but we can make the relevant data clearly visible in the right context. The difference between prior and posterior fields has to be studied and better understood.

43 More information: Or just google: w3dx iasi knmi ;-) Thank you for your attention.