Presentation on theme: "The Global Observing System"— Presentation transcript:
1The Global Observing System Stephen EnglishWith material kindly provided by Peter Bauer, Cristina Lupu, Tony McNally, Mohamed Dahoui, Erland Kallen, Enza di Tomaso, Niels Bormann, Sabatino di Michele and Richard EngelenEuropean Centre for Medium-Range Weather Forecasts
2Role of observationsObservations limit error growth and make forecasting possible….Every 12 hours we assimilate ~7,000,000 observations to correct the 100,000,000 variables that define the model’s virtual atmosphere.We monitor an additional 12,000,000.SEVIRI 6.2 µmRMS error (m)Time (hours)
3The state space MASS (temperature, pressure…) Radiosondes, surface observations, satellite sounders, aircraftMOISTURE (humidity, clouds, precipitation…)Radiosondes, surface observations, satellite sounders and imagers, aircraft, radar, lidarDYNAMICS (wind, vorticity, convergence…)Radiosondes, surface observations, satellite imagers, satellite scatterometer/radar/lidar, aircraftCOMPOSITION (ozone, aerosol…)Ozone sondes, surface observations, satellite soundersSURFACE (surface type, temperature, moisture, homogeneity…)Satellite active and passive systems, surface observations
4Composition Mass Moisture Wind Ozone sondes Air quality stations Soil moistureRain gaugeRadiosondeSynopShipAircraftBuoysProfilersWind
6What types of satellites are used in NWP? Advantages DisadvantagesGEO - Regional coverage No global coverage by single satellite- Temporal coverageLEO - Global coverage with single satellite
7Composition Mass Moisture Wind IR = InfraRed MW = MicroWave Ultraviolet sensorsSub-mm,and near IR plusVisible (e.g. Lidar)PolarIR + MWsoundersMassRadar andGPS total path delayMoistureRadio occultationGeo IR SounderGeo IR and Polar MW ImagersFeature tracking in imagery (e.g. cloud track winds), scatterometers and doppler windsIR = InfraRedMW = MicroWaveWind
13Combined impact of all satellite data EUCOS Observing System Experiments (OSEs):2007 ECMWF forecasting system,winter & summer season,different baseline systems:no satellite data (NOSAT),NOSAT + AMVs,NOSAT + 1 AMSU-A,general impact of satellites,impact of individual systems,all conventional observations. 500 hPa geopotential height anomaly correlation3/4 day3 days
14User requirements and satellite data: OSCAR www.wmo-sat.info Vision for the GOS in 2025 adopted June 2009GOS user guide WMO-No. 488 (2007)Manual of the GOS WMO-No. 544 (2003) (updated for ET-SAT Geneva April 2012)
15Using DA to help design the GOS Examples questions we use Data Assimilation techniques to study:Would it be beneficial for the Chinese FY3 program to move to the “early morning orbit” with the Europeans occupying the “morning orbit” and the Americans the “afternoon orbit”?Preparation for future instruments such as lidar and radar (EarthCARE).Study using Ensemble of Data Assimilations to estimate the number of GPSRO soundings needed in future (discuss with Sean Healy if interested).
162009 Experiments Enza Di Tomaso* and Niels Bormann MetOp-AAMEarly AMPMNOAA-17TimeNOAA-16NOAA-15NOAA-18NOAA-19Aqua
17FY3 orbit: what is the optimal orbit configuration? “NOAA-15 experiment”* MetOp-A * NOAA * NOAA-15“two-satellite experiment”* MetOp-A * NOAA-18“NOAA-19 experiment”* MetOp-A * NOAA * NOAA-19
18Are 3 satellites better than 2? 3.5 months 107 casesCY36R1 T511“no-MW sounder experiment”GOOD“two-”, “three-”, “all-satellite experiment”Are 3 satellites better than 2?YESBoth the assimilations of NOAA-15 and NOAA-19 data have a clearly positive forecast impact in the Southern Hemisphere compared to the use of two satellites onlytwo-satellite RMSE – no-Mw sounder RMSEthree-satellite RMSE – no-Mw sounder RMSEall-satellite RMSE – no-Mw sounder RMSE
19RMS difference forecast – analysis for NOAA-15 and NOAA-19 experiments Do orbital positions matter?YESNOAA-19 experimentGOODNOAA-15 experimentWhen averaged over the extra-Tropics the impact for the forecast of the geopotential of “NOAA-15 experiment” versus “NOAA-19 experiment” is neutral to slightly positiveRMS difference forecast – analysis forNOAA-15 and NOAA-19 experiments
202012 Experiments Tony McNally MetOp-ANOAA-17AMEarly AMPMNOAA-16NOAA-15NOAA-18NOAA-19Aqua NPP
24New requirements in GOS for atmospheric composition Combining NWP with CTM models and data assimilation systemsNew requirements in GOS for atmospheric composition
25Monitoring of observations WebpagesAutomatic warningsCollaboration between users and providersJ = ½(y-H(x))TR-1(y-H(x)) + JbAt beginning and end of minimisation, with and without QC, plus bias corrections.
26Data monitoring – automated warnings Selected statistics are checked against an expected range.E.g., global mean bias correction for GOES-12 (in blue):-alertSoft limits (mean ± 5 stdev being checked, calculated from past statistics over a period of 20 days, ending 2 days earlier)Hard limits (fixed)alert:(M. Dahoui & N. Bormann)
29Global Observing System is essential to weather forecasting Technology driven….a more integrated approach now?Mass is well observed.Moisture – satellite observations are data rich but poorly exploited. Radar and lidar will become more important.Dynamics – even wind observations are scarce.Composition – NWP techniques have been successfully extended to environmental analysis and prediction but more observations are needed.Surface – DA for surface fields is being attempted.
30Thank you for your attention Thanks again to Peter Bauer, Cristina Lupu, Tony McNally, Mohamed Dahoui, Erland Kallen, Enza di Tomaso, Niels Bormann, Sabatino di Michele and Richard Engelen
31Backup slidesDetailed list of instruments for NWP and atmospheric composition(not shown but included for information)
34Data sources: Geostationary Satellites ProductStatusSEVIRI Clear sky radianceAssimilatedSEVIRI All sky radianceBeing tested for overcast radiances, and cloud-free radiances in the ASR datasetSEVIRI total column ozoneMonitoredSEVIRI AMVsIR, Vis, WV-cloudy AMVs assimilatedGOESAMVsMTSAT