NRT Core Services. KNMI scatterometer team

Transcription

1 NRT Core Services KNMI scatterometer team Vongfong, 8 October 2014

2 Outline Scatterometer wind services Nowcasting Global NWP Regional NWP

3 Satellite Wind at Sea Services NWP SAF software users 24/7 Wind product services (OSI SAF) Constellation of satellites Africa High quality winds, QC China Timeliness 30 min. 2 hours Europa Service messages India QA, monitoring Other Asia Software Russia services (NWP SAF) South America Portable Wind Processors USA Weather model comparison Organisations involved: KNMI, EUMETSAT, EU, ESA, NASA, NOAA, ISRO, SOA, WMO, CEOS,.. Users: NHC, JTWC, ECMWF, NOAA, NASA, NRL, BoM, UK MetO, M.France, DWD, CMA, JMA, CPTEC, NCAR, NL,... More information: Wind Scatterometer Help Desk scat@knmi.nl

4 What we do, R&D 4 Help build a constellation for increased temporal coverage Cal/val, NWP ocean calibration, e.g., OSCAT, HY2A, ASCAT-B, RapidScat QC, e.g., QC near rain (AS Marcos Portabella) Operational status First VH GMF in extreme winds to support EPS-SG Analysis of C-band GMF at extreme winds First analysis of structures at sea Increased resolution (EUM NWP SAF) FA with EUMETSAT and Un. Vienna on coastal soil moisture CDR sampling error Stress-equivalent winds (EU MyOcean) scat@knmi.nl OSI SAF User Workshop November 2014 OSI SAF Wind Products ASCAT-A 25-km winds Operational status ASCAT-A 12.5-km winds ASCAT-A coastal winds Operational status ASCAT-B 25-km winds Operational status ASCAT-B coastal winds Operational status Oceansat-2 winds Discontinued status QuikSCAT winds Discontinued status Wind Products Processing Status Other Wind Services at KNMI ASCAT-A 25-km winds (EARS) Operational status ASCAT-A 12.5-km winds (EARS) Operational status ASCAT-B 25-km winds (EARS) Operational status ASCAT-B 12.5-km winds (EARS) Operational status ERS-2 winds (EARS) Discontinued status Scatterometer work at KNMI

5 RapidScat Mounted last week! Data in 2015 (Copernicus) ws.php?feature=4325

6 OceanSat-2 scatterometer OSCAT International collaboration and lead cal/val team Exchange of resources, support to increase temporal sampling Winds at ~12 and ~00 LST

7 HY2A Scatterometer Evaluation Anton Verhoef Same approach as for OSCAT Data exchange Offer expert and GS support At ~6:00 and ~12 LST

8 Independent Verification Compare products with other producers Product improvements Standards (speed scale) Naoto Ebuchi, Tokai Un., Japan coaps.fsu.edu/scatterometry/ meeting/past.php#2013 OSI SAF User Workshop November 2014

9 F M A MetOp ASCAT High Resolution Processing Workshop Investigate ASCAT Spatial Response Functions, SRF Detect structures Improve knowledge of aggregated SRFs for geophysical processing Ad.Stoffelen@knmi.nl

10 Stress-equivalent wind U10N: equivalent-neutral 10m wind For the same U10N, cold heavy air will produce more stress (and roughness) than lighter warmer air. This effect is expressed by the surface stress equation. The surface wind stress τ = ρ u * 2 indeed depends on the air density ρ. Assuming that σ 0 measurements are more a measure of τ than U10N, the ρ correction for U10N takes the form where U10S denotes the current set of stress-equivalent scatterometer wind retrievals and <ρ> is the average air density as defined in a standard atmosphere ( kg/m 3 ). ρ variations, which depend on surface pressure, air temperature, and humidity, are generally small (1-2%) and can exceptionally increase locally in cases such as cold air outflow.

11 Hurricane wind extremes Discussion on highest ever peak winds from tyfoon Haiyan in the media, but impossible to measure! Maximum 1-minute sustained winds are difficult to know, but used for category! Scatterometer winds are mentioned in 20% of ALL NHC TC discussions Scatterometers measure 25-km scale winds and are thus much lower extremes than 1-minute peak winds Current scatterometers either capture rain and/or saturate at 40 m/s; The impact of a hurricane surge is catastrophic and depends on wind speed, wind direction, wind duration and wind fetch, less on maximum 1- minute peak wind (Sandy) TC Rita

12 ASCAT hits on Vongfong ASCAT B ASCAT A Peak around midnight on 7/8 October 2014 of 42 m/s (150 km/h) ASCAT-A appears low as compared to ASCAT-B Current calibration bias B-A of 0.1 db (0.1 m/s) Required accuracy is 0.2 db 30 Due to GMF saturation, 0.1 db at 40 m/s is 4 m/s! : : : : : : :03 For extremes more careful instrument calibration is needed

13 Trends in extreme wind speed QuikSCAT Trend in 90 th Percentile Trend in Wind Speed (in 0.1 m/s per 10 year) Controversy in trends of mean and extremes Wentz, F. J., and L. Ricciardulli, 2011, Science Young, I. R., S. Zieger, and A. V. Babanin, 2011: Science QuikScat CDR: unexplained 0.1 m/s decadal falling trend of mean wind? Figure by Jason Keefer and Mark Bourassa, FSU

14 Key Flight level S dropsonde Time (UTC) SFMR WS Go out there! With the NOAA hurricane hunters Feb 4, 2010 HF drops HF SFMR High Winds Research validation set for remotely sensed winds ASCAT, OceanSat-2, future instruments NWP forecast models Instrumentation GPS dropsondes, Step Freq. Mirowave Radiometer UMASS Imaging Wind and Rain Air-borne Profiler (IWRAP) Feb 23, 2010 AGU Ocean Sciences 2010, Portland, OR 14

15 SFMR versus ASCAT Distance to centre [km] Distance to centre [km] CMOD5 winds are lower than SFMR (VV pol) add ln(v ASCAT ) However, CMOD5 winds equal buoy winds for 15 to 20 m/s; which to trust? SFMR winds go up when it rains -ln(rr); NOAA is recalibrating

16 Calibration strategy 1. GPS dropsondes provide true measure of local wind 2. GPS dropsondes calibrate SFMR on its basic footprint 3. Calibrated SFMR data are integrated over a scatterometer WVC length to provide a resource for satellite scatterometer calibration Error attribution in all steps

17 CEOS Virtual Constellation

18 Winds when it matters

19 high water Delfzijl 0.5 m underpredicted surge (NL) by HiRLAM (blue) and ECMWF winds (green) OSI SAF QuikScat winds (red) are stronger and/or more directed into the harbour NRT needed R&D on mesoscales needed 1/11/ 06 4:03 1/11/ 06 6:14

20 Requirement for visualisation 14:42Z

21 Weersverwachtingen worden steeds beter NH ZH Beter gebruik van waarnemingen Grotere computers Verbeterde weermodellen 21

22 Substantial NWP Forecast Error Reduction by Scatterometers Great success of OSCAT; grateful to ISRO The forecast sensitivity to observations measures the impact of the observations on the short-range forecast (24 hours). The forecast sensitivity tool developed at ECMWF computes the Forecast Error Contribution (FEC) that is a measure (%) of the variation Much of information the forecast error is (as lost defined in through data the assimilation; dry energy norm) due only to the a assimilated few % observations. used May 2013 versus May % Smaller Global FcError 2% FcError Reduction due to GOS [C. Cardinali ] OSI SAF User Workshop November 2014

23 From plume to probability esurge UCM3 2015

24 Improve meteorology? Greg.J. Tripoli, Un. Wisconsin

25 Why high resolution? Example: Simulation of a storm in 1990 HARMONIE ERA-Interim 25 High resolution modelling affects more than just the coastal zone Baas and De Waal, 2012 from R. Boers, KNMI

26 WMO CGMS International Winds Working group See also Relevant scatterometer splinter group actions: All: Share experimental results among participants. Further experiments on timing errors, thinning, more aggressive QC in inner/outer loops and background error structure are encouraged. NWP SAF (KNMI): Investigate 2DVar sensitivity to: timing errors, thinning, QC, background error structure, background (provided by participants) with the aim to provide guidance to NWP centres. NWP SAF: Make above points more prominent on web site: bias correction guidance, guidance, data and tools (as is) on spatial/spectral analyses and triple collocation. NWP SAF: Organize NWP SAF workshop on scatterometer data assimilation. HARMONIE WW, 13-16/10/2014, Santander

27 NRT Core Storm Service Provides basic underlying information when alarm codes turn red Real-time for deterministic nowcasting Satellite winds are successfully used in global NWP; global NWP provides probabilistic ensemble forecasts Use of satellite winds is challenging in regional NWP; coordinated effort in IWWg Consistent provision of core winds, waves and surges for Disaster Risk Reduction in a one-stop shop? Both observations and models? One-stop shop portal?

28 Haiyan