INCA nowcasting system precipitation fields as an alternative data source for H-SAF satellite precipitation products validation case study analysis

Transcription

1 INCA nowcasting system precipitation fields as an alternative data source for H-SAF satellite precipitation products validation case study analysis Rafał Iwański & Bożena Łapeta Satellite Remote Sensing Centre - IMWM-NRI IPWG-6 Workshop October 2012 São José dos Campos Brasil

2 presentation plan 1. Introduction to INCA nowcasting system: INCA, what is it?; INCA input data sources; INCA system modules; INCA-CE Project; INCA-CE pilot implementations; INCA-CE Project web page; precipitation module algorhytm; 2. Case study; 4. References.

3 introduction to INCA nowcasting system INCA Integrated Nowcasting through Comprehensive Analysis Integrated: uses all localy available data sources (ATS, SYNOP, MAWS, radar imagery, NWP forecasts, lightning detection data fields etc.) ; Nowcasting: produces forecast for very short period (up to 6h) with high accuracy and high resolution; Comprehensive: takes into account all relevant processes and its interactions; Created and developed at ZAMG (ZentralAnstalt für Meteorologie und Geodynamik) and operationally launched in 2005.

4 introduction to INCA nowcasting system INCA grid: Lambert projection; horizontal resolution 1km x 1km; 740 x 650 grid points in Poland; vertical resolution from 21 to 40 levels z ~ 200m; High resolution topography derived by bilinear interpolation of US Geological Survey dataset. Input data in Poland: ALADIN model custom prepared runs (0000 UTC and 1200 UTC) on 7,5km x 7,5km grid. ALADIN 36h forecast is used. Temperature, humidity, wind speed and direction, precip, dewpoint, pressure, insolation, cloudiness etc. data are derived from 475 ATS, 56 MAWS, and 126 stations working within SYNOP regime Radar Surface Rainfall Intensity [mm/h] composite map is used: 8 radars in Poland; 10 min. time pace; 1km horizontal resolution; 1km altitude cutoff plane.

5 introduction to INCA nowcasting system Module Fields Code inca_tq 2m temperature 2m dewpoint temperature 2m relative humidity Snowfall line Freezing level TT TD RH ZS Z0 inca_tg Ground temperature TG inca_uv inca_rr inca_co 10m wind Precipitation Solid precip Precip type CAPE CIN LCL Level of free convection Lifted Index Showalter Index Deep Convection Index Trigger Temperature Trigger Temperature deficit Equivalent pot. Temperature Moisture convergence Flow divergence Precipitable water UU VV RR RS PT CP CN LC LF LI SI DC TR DT TE MC DV PW inca_ch Wind chill CH inca_ic Icing potential IC

6 INCA-CE Project INCA-CE Project Integrated Nowcasting System for the Central European Area EU Programme : Central Europe (European Regional Development Fund) Total budget : EUR Duration : Partnership : 16 partners from 8 Central European countries Lead partner : Central Institute for Meteorology and Geodynamics (ZAMG), Austria Project Partners: 1. Central Institute for Meteorology and Geodynamics Austria 2. Slovak Hydrometeorological Institute 3. National Research Institute Poland 4. Czech Hydrometeorological Institute 5. Hungarian Meteorological Service 6. Regional Agency for Environmental Protection Italy 7. Environmental Agency of the Republic of Slovenia 8. Safety Centre Burgenland company Austria 9. Provincial Government of Lower Austria Fire Brigade and Civil Protection 10. Ministry of the Interior National Crisis and Disaster Management and Civil Protection Austria 11. Provincial Government of Lower Austria Department for Road Maintenance 12. Ministry of Interior of the Slovak Republic 13. Disaster Management Directorate of Somogy County Hungary 14. CGS plus d.o.o. Innovative IT and Environmental Technologies Slovenia 15. Department of Crisis Management Poland 16. Fraunhofer-Institute of Optronics, System Technologies and Image Exploitation Germany

7 INCA-CE Project Pilot implementations: Operational Hydrology - improved prediction of heavy rainfall and associated flooding risks will help to set up efficient procedures in the management of mitigating actions for the protection of buildings, roads, and other infrastructure; Civil Protection - more comprehensive assessment of meteorological threats and a more detailed and timely forecast, leading to more efficient warning protocols and dissemination strategies; Road Safety - enhancement by a more detailed road weather forecast made available both to the road management authorities as well as to the general public.

8 INCA-CE Project Objectives: developing of nowcasting system that is specifically adapted to its day-to-day application in operational hydrology, civil protection, and road safety; provision of common internet platform with forecasts which cover CE area; improvement of decision making process for end-users.

9 INCA-CE Project

10 precipitation module algorythm radar precip data ground station precip data inverse weighting function interpolation to regular INCA grid using 8 nearest stations only + unhomogenous station layout consideration bilinear interpolation to INCA grid + climatological scaling for each month + spatial smoothing with use of 10km x 10km running average re-scaling of radar data using the latest observations precipitation analysis field as a weighted mean

11 H-SAF PR-OBS-3 Sensor: SEVIRI onboard Meteosat-8, Meteosat-9, Meteosat-10, Meteosat-11 (i.e., Meteosat Second Generation); Instrument type: Multi-purpose imaging VIS/IR radiometer - 12 channels (11 narrow-bandwidth, 1 high-resolution broad-bandwidth VIS). Coverage/cycle: full disk every 15 min. Limited areas in correspondingly shorter time intervals. Resolution: 4.8 km IFOV, 3 km sampling for narrow channels; 1.4 km IFOV, 1 km sampling for broad VIS channel. SSM/I-SSMIS ~ 3-hourly sequence of MW observations AMSU-MHS SEVIRI 15-min images Lookup tables updating Rapid-update algorithm LEO/MW-GEO/IR-blending precipitation rate processing chain. PRECIPITATION RATE Extraction of dynamical info

12 case study

13 case study Enter name Rafałyour Iwański

14 case study RADAR SRI [mm/h] RADAR SRI [mm/h] ATS rain rate [mm/h] INCA rain rate [mm/h] 80 INCA rain rate [mm/h] Just one H-03 slot at 1927! ATS rain rate [mm/h]

15 case study PDF RG RD INCA < PR 1 1< PR 2 2< PR 3 3< PR 4 4< PR 5 5< PR 6 6< PR 7 7< PR 8 8< PR 9 9< PR 10 10< PR 11 11< PR 12 12< PR 13 13< PR 14 14< PR 15 15< PR 16 16< PR 17 17< PR 18 18< PR 19 19< PR 20 20< PR 21 21< PR 22 22< PR 23 23< PR 24 24< PR 25 25< PR 26 26< PR 27 27< PR 28 28< PR 29 29< PR 30 Enter your name Rafał Iwański

16 case study ME [mm/h] ATS RD INCA RMSE ATS RD INCA 25 [0.25,1) [1,10) >=10 >= [0.25,1) [1,10) >=10 >=0.25 Precipitation classes Precipitation classes POD FAR ATS RD INCA

17 conclusions INCA precipitation field is strongly dependant on radar data input; radar data influence on INCA performance is reduced by rain gauge climatological scaling; the use of ATS precipitation data field can fill in the lacks caused by radar beam blocking; both radar and INCA precip fields overestimate the precipitation measured by ATS rain gauges maintaining constant mutual dependency defined by climatological scalling variable; H-03 overestimates light and moderate precipitation in reference to all three data sources at the same time strongly underestimates heavy precipitation >=10; the H-03 quality depends on the reference data source (the worst results were obtaind for INCA precip field and best for ATS) for light and moderate precipitation; The H-03 quality is consistent for all three ground data sources in reference to heavy precipitation >=10; FAR values are much higher then POD in all cases.

18 references Browning, K. A., and C. G. Collier, 1989: Nowcasting of precipitation systems. Rev. Geophys., 27, Frei, C., and C. Schär, 1998: A precipitation climatology of the Alps from high-resolution rain-gauge observations. Int. J. Climatol., 18, T. Haiden, A. Kann, G. Pistotnik, K. Stadlbacher, C. Wittmann, 2010, Integrated Nowcasting through Comprehensive Analysis (INCA) - System description, ZAMG; Haiden, T., and G. Pistotnik, 2008: Parameterization of elevation effects in short-duration precipitation analysis. Preprints, 13th Conference on Mountain Meteorology, Amer. Meteor. Soc., Whistler, Canada, 4p. Li, L., W. Schmid, and J. Joss, 1995: Nowcasting of motion and growth of precipitation with radar over a complex topography. J. Appl. Meteor., 34, Pierce, C. E., P. J. Hardaker, C. G. Collier, and C. M. Haggett, 2000: GANDOLF: a system for generating automated nowcasts of convective precipitation. Meteorol. Appl., 7, Steinheimer, M., and T. Haiden, 2007: Improved nowcasting of precipitation based on convective analysis fields. Adv. Geosci., 10, Wang, Y., T. Haiden, and A. Kann, 2006: The operational limited area modelling system at ZAMG: ALADIN- AUSTRIA, Österr. Beiträge zu Meteorologie und Geophysik, Heft 37, 33p.

19 Thank you for your attention Rafał Iwański IMWM-NRI Satellite Remote Sensing Centre Kraków 14 Piotra Borowego, str.