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Future guidelines the meteorological view - Isabel Martínez (AEMet)

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Solar Energy future guidelines the meteorological view - Isabel Martínez (AEMet)

Solar Energy future guidelines the meteorological view - Isabel Martínez (AEMet)

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  • 1. Future Guidelines on solarforecasting: the meteorological viewIsabel Martínez Marcoimartinezm@aemet.esAEMETIn collaboration with Emilio Cuevas, Pilar Fernández,Enric Terradellas and Javier Calvo
  • 2. Outline• Introduction• Nowcasting:• Cloud and irradiance nowcasting from Total-Sky cameras• SAF of Nowcasting (NWC SAF)• Forecasting:• HIRLAM and HARMONIE Models• ECMWF Model• Quick overview of the MACC/ECMWF aerosol analysis andforecasting system• WMO SDS-WAS program• Dust forecast
  • 3. 3Nowcasting is a technique for very short-range forecasting (normallywithin 6h ahead) covering only a very specific geographic region.In cloud nowcasting we map the current cloudiness and, using anestimate of its speed and direction of movement, we forecast thecloudiness a short period ahead (1-2h) for a specific site (1 km2) —assuming the weather will move without significant changes.10 20 30 40 50 60 70 80 90 100 120 130 140150 minutesNowcastingForecastingIn-situ observationsSatelliteNeural network modelsSatellite informationPost-processed Numerical Weather Prediction Model DaNowcasting concept
  • 4. 4 Total sky imagery can be used to make forecasts in quasi-real time (with a delayof only 15-30 minutes) by applying image processing and cloud tracking techniquesto digitized sky photographs. Hazy skies can make difficult to properly identifyclouds. Under cloudless skies, when most Concentrated Solar Power (CSP) andConcentrated Photovoltaics (CPV) plants operate, aerosol optical depth (AOD)becomes the driver factor. Large portion of uncertainty can be attributed to the lackof accurate aerosol data used to model DNI. Satellite imagery applies total sky imagery methods to cloud scenes (e.g. theSEVIRI cloud-motion winds derived from successive satellite images can be usedto predict the DNI at ground level with sufficient accuracy. DNI and GHI attenuation by different types of clouds and aerosols must beparameterized by sensitivity studies using Radiative Transfer Models (RTF).So, a combined approach using in-situ observations (total-sky cameras andradiometers), satellite observations (SEVIRI), and RTF models appears to be ableto provide the most accurate results for cloud-DNI-GHI nowcasting at CSPs andCPVsMain considerations
  • 5. 5- CCD sensor. 640x480 pixels, 8 bit, color response from 400 to700nm and monochrome response from 400 to 1000nm.- Very durable aluminium housing.- Borosilitate dome.- Rotating shadow band.- Cooling/heating system (-10º to +50ºC).- Fast frame rates (up to 70 fps).- Adjustable JPEG compressed still-images or live MJPEGstreaming video.- Transfer of images via FTP, RTP or HTTP.- Camera control via HTTP, XML-RPC, TelnetComponent#1: SONACloud Observation Automatic System
  • 6. 6Cloud detection: Neural networkCloud flow determination:To cluster the motion field we havebased on a Density-Based Algorithmfor Discovering Clusters in LargeSpatial Databases with Noise(DBSCAN)
  • 7. 7Component #2: In-situ column aerosol content determinationPreliminary (excellent)results of total columnaerosol content obtainedwith a new inexpensive CIradiometercompared with AOD fromAERONET
  • 8. 8Cloud Mask Cloud TypeCloud Top Height Cloud Top PressureComponent#3: NWC SAF cloud products
  • 9. 9Component#4: Cloud and dustsensitivity analysis with neuralnetwork models and LibRadtranDNI attenuation by altocumulusGHIDNIDHI
  • 10. 10Summarizing the nowcasting state of the artNeural networkmodelingDNI/GHInowcastingCloudobservationDNI, GHIobservationAerosol/dustobservationOptical flowCloudheight/typeDNI/GHICloudattenuationAerosol, Dustand water vaporsensitivityanalysisSAF/NWCDevelopmentof low-costinstruments
  • 11. SAF de Nowcasting(NWC SAF)The Nowcasting Satellite Application Facility (SAF) wasestablished in 1996 between EUMETSAT and formerInstituto Nacional de Meteorología (Spanish NationalWeather Service, AEMET (Agencia Estatal de Meteorología)since 2008).Under the leadership of the Spanish MeteorologicalAgency (AEMET), the NWC SAF is developed by aProject Team involving France (Météo-France), Sweden(SMHI) and Austria (ZAMG) Meteorological Services.
  • 12. Objectives Development of Nowcasting products derived from bothGeostationary (MSG) and Polar Platform (PPS) satellitesystems To be delivered to users as SW Packages Products are generated locally at user premisesResponsible for Development and maintenance of the NWC products Development and maintenance of the SW Packages Users support and training tasks89 users at the datehttp://www.nwcsaf.org
  • 13. Clear Air, Precipitation & Wind MSG productsClouds & Convection MSG productsCloud & Precipitation PPS productsMeteorological Systems MSG productsProducts responsibility
  • 14. Cloud Products MSGCloud Top Temperature & Height (CTTH)Detailed cloud analysis with information onthe major cloud classes for all the pixelsidentified as cloudy.Information on the cloud top temperature,pressure and height for all pixels identifiedas cloudy.Cloud Type (CT)Cloud-free pixels delineation in a satellitescene with a high confidence.Also: snow/sea ice, dust clouds andvolcanic plumes.Cloud Mask (CMa)
  • 15. Cloud Products PPSCloud Type (CT)Cloud Mask (CMa) Cloud Top Temperature &Height (CTTH)
  • 16. Precipitation & Convection Products (MSG&PPS)Precipitating Clouds (PC)Probability of precipitation intensities in pre-defined intensity intervals.Convective Rainfall Rate (CRR)Precipitation estimated rate associated toconvective clouds. Instantaneous rain rateand hourly accumulations.Rapid Development Thunderstorm (RDT)Identification, monitoring and tracking ofintense convective systems, and detection ofrapidly developing convective cellsPPSMSG
  • 17. Clear Air Products MSGSAFNWC Physical Retrieval (SPhR)Optimal estimation algorithm to obtain Stability Parameters:Total and Layered Precipitable Water and Instability IndexesTPWLPW-HLLPW-MLLPW-BLLI KI SHW
  • 18. HRW v2011HRW v2012 Up to 7 SEVIRI Channels Improved Height assignmentWind Products MSGDetailed and frequently updatedsets of Automatic Motion Windsincluding wind pressure levelinformation and quality controlflags.
  • 19. 1910 20 30 40 50 60 70 80 90 100 120 130 140150 minutesNowcastingForecastingIn-situ observationsSatelliteNeural network modelsSatellite informationPost-processed Numerical Weather Prediction Model DaForecasting
  • 20. Numerical weather prediction• The behaviour of the atmosphere is governed by a set of physical lawswhich express how the air moves, the process of heating and cooling, therole of moisture, and so on.• Equations cannot be solved analytically, numerical methods are needed.• Given a description of the current state of the atmosphere, numericalmodels can be used to propagate this information forwards to produce aforecast for future weather.• Additionally, knowledge of initial conditions of system is necessary.• Incomplete picture from observations can be completed by dataassimilation.• Resolution of the model is determined by available computing resources.It does not correspond to any natural scale separation.
  • 21. Numerical Weather Prediction• Processes not resolved by the model must be ‘parametrized’.• Effective resolution is not same as model grid spacing.• Numerical algorithms are compromise between accuracy and speed; careneeded to ensure numerical stability.• Interactions between atmosphere and land/ocean important
  • 22. Forecast ranges• Short-range weather forecast (0-2 days ahead)• Detailed prediction - regional forecasting system• Produce forecast few hours after observations are made• Medium-range weather forecast (2 days - 2 weeks ahead)• Less detailed prediction - global forecasting system• Produce forecast up to several hours afterobservations are made• Long-range weather forecast (more than 2 weeks ahead)• Predict statistics of weather for coming month or season• Climate prediction• Predicts the climate evolution on the basis of pre-definedscenarios (CO2, O3, …)
  • 23. HIRLAM (High Resolution Limited Area Model)• Model Formulation:• Horizontal resolution: 0.16º latxlon (ONR) and 0.05º latxlon(HNR)• Boundary Conditions:• ONR: from ECMWF with 0.25º• HNR and CNN: from ONR with 0.16º (nesting models)• Analysis: 3-dimensional variational method (3D-VAR)• The Resolution in space• Vertical Resolution: 40 hybrid levels• Horizontal grid: regular rotated longitude/latitude
  • 24. Integration Domains
  • 25. HIRLAM (High Resolution Limited Area Model)• In development: HARMONIEHirlam Aladin Regional/Meso-scale Operational NWP In Europe• A new model formulation:• Horizontal resolution: 2.5km• Vertical resolution: 65 hybrid levels• Analysis: 4-dimensional variational method (4D-VAR)• Horizontal grid: Spectral representation• Vertical grid: finite differences• Non-hydrostatic dynamical kernel from ALADIN Model
  • 26. The ECMWF Numerical WeatherPrediction (NWP) Model• High-resolution model• T1279 spectralresolution• 16 km global grid• 91 hybrid levels fromthe surface to a heightof 80km• Variables at each gridpoint• Wind• Temperature• Humidity• Cloud water, ice, cloudfraction• Ozone• Pressure at surface
  • 27. • A number of radiation schemes are in use at ECMWF. As of January 2011 areactive• McRad including RRTM_LW and RRTM_SW is used in the forward model foroperational 10-day forecasts at TL1279 L91, EPS 15-day forecasts at TL639L62, and seasonal forecasts at TL159 L62.• The tangent linear and adjoint of the “old” SW radiation scheme in a 2-spectral interval version is used for Data Assimilation.• The tangent linear and adjoint of the “old” LW radiation scheme with 6spectral intervals, replacing a neural network version of the same “old” LWradiation scheme (Morcrette, 1991; Janiskova and Morcrette, 2005), is usedfor DA.• … and all the dedicated RT scheme used to simulate radiances (RTTOV-based) in the analysis of satellite data.The ECMWF radiation schemes
  • 28. The ECMWF radiation schemesAdiabatic processesWinds Temperature HumidityCloud FractionCloud WaterDiffusion Radiation CumulusconvectionStratiformprecipitationFriction Sensibleheat fluxEvaporationGroundroughnessGroundtemperatureSnow GroundhumiditySnowmelt
  • 29. The ECMWF radiation schemes• Differences with other physical processes• There exists a well known theory (from Quantum Mechanics toSpectroscopy to Radiation Transfer).• Radiation is exchanged with the outside space: radiative balancedetermines the climate.• The sun providing the energy input, radiation undergoes regularforcings: seasonal, diurnal.• Radiation at ToA has been globally measured since the 60’s (byoperational satellites), with real flux measurements from ERB (1978),ERBE (1985), ScaRaB (1993), CERES (1998).• Surface radiation has been (roughly) measured at points over almost 40years. Present programs like ARM, BSRN, SURFRAD measure it with highaccuracy. Also satellite-derived SW (and LW) radiation is becomingavailable.• Therefore, there exist some relatively extended possibilities ofvalidation/verification (radiation in the SW visible and near-IR, in theLW, … in the mW).
  • 30. The ECMWF radiation schemes• What is required to build a radiation transfer scheme fora GCM?• 5 elements, the last, in principle in any order:• a formal solution of the radiation transfer equation• an integration over the vertical, taking into account thevariations of the radiative parameters with the verticalcoordinate• an integration over the angle, to go from a radiance to a flux• an integration over the spectrum, to go from monochromatic tothe considered spectral domain• a differentiation of the total flux w.r.t. the vertical coordinateto get a profile of heating rate
  • 31. The ECMWF radiation schemes• In the ECMWF model, the 3-D distributions of T, H2O, cloud fraction(CF), cloud liquid water (CLW), cloud ice (CIW) are given for everytime-step by the prognostic equations.• Other parameters, i.e., O3, CO2 and other uniformly mixed gases ofradiative importance (O2, CH4, N2O, CFC-11, CFC-12 and aerosols)have to be specified (prognostic O3 soon interactive with rad?).• Prognostic aerosols (as part of GEMS/MACC project)Radiation blackboxEfficient radiationtransferalgorithmsProfiles of T,q, CF, CLW,CIW,O3Climatologicaldata:other tracegases, aerosolsOUTPUTupdatedfromtime to timeto be used inthethermodynamicequationDFLW, DFSW to beused in the surface(soil) energybalance equationRadtT
  • 32. MACC Daily Service ProvisionAirqualityGlobalPollutionAerosol UV indexBiomassburninghttp://www.gmes-atmosphere.eu
  • 33. Radiation Transfer in NWP: Lecture 4Forward modelling of aerosols• As part of the GEMS/MACC/MACC II projects, the IFS has been modified to includeprognostic aerosols (sea-salt SS, dust DU, organic OM and black carbon BC, sulphateSO4).• Sources for SS and DU are linked to some of the model surface parameters (U10,soil moisture, UVis albedo, stdev orography, snow mask).• Sources for OM, BC and SO4 are taken from climatologies and/or inventories(GFEDm, GFED8d, SPEW, EDGAR databases). For NRT FCs, OC, BC and SO4 linked tofire emissions are linked to an analysis of the MODIS and Geostationary Satellites“fire hot spots”• Aerosols are transported by advection, vertical diffusion and convection, andundergo their specific processes, i.e., sedimentation, dry deposition, wetdeposition by large-scale and convective precipitation, and for OM and BChygroscopic effects. Transfer between SO2 and SO4 is handled with a time-scalesimply dependent on latitude.• The TL159 (GEMS) and the TL255 (MACC) L60 models have been simulating aerosolsfor the 2003-2008 (GEMS) and 2003-2010 (MACC)-AER reference period. SinceSeptember 2008, an experimental pre-operational near-real time aerosol analysisfollowed by a 5-day FC is produced every day.• Comparisons with MODIS and AERONET data.http://www.gems-atmosphere.eu/d/services/gac/nrt/nrt_opticaldepth/
  • 34. Prognostic AERosols in the ECMWF IFS
  • 35. Prognostic AERosols in the ECMWF IFS• Aerosol model to represent the main characteristics of the 4D distribution ofaerosols, while keeping the computational burden within the parameters of afuture operational configuration.• Aerosol model formulation originally taken from the LOA/LMD-Z model (Reddy etal., 2005, JGR), and adapted to the IFS• Adapted to the ECMWF IFS model dynamics and physics:• with original developments to include N (=12) new prognostic variables forthe aerosols• and original developments/upgrades to the sedimentation, wet depositionand radiative diagnostics.• Extensive validation against MODIS t550 (aerosol optical depth at 550 nm),AERONET t500, t865, CALIPSO aerosol/cloud mask• ECMWF IFS model including prognostic aerosols can be run in twoconfigurations:• In aerosol free-wheeling mode: aerosol advection and “full” (but simplified)aerosol physics using temperature, humidity, winds etc. from theanalyses/forecasts every 12 hours• In analysis mode with subsequent forecasts
  • 36. Quick overview of the MACC/ECMWFaerosol analysis and forecastingsystem••••Forward model Analysis
  • 37. Evaluation with MODIS/SEVIRI and AERONETSaharan dust outbreak: 6 March 2004Model simulation Assimilation MODISSEVIRICape Verde DakarAERONETAssimilationSimulationAerosol optical depth at 550nm (upper)and 670/675nm (lower)
  • 38. Comparison of GEMS simulated andanalysed aerosol optical depth withMODIS and MISR for July 2003
  • 39. WMO SDS-WAS programmeRegional Center forNorthern Africa, Middle Eastand Europehttp://sds-was.aemet.essdswas@aemet.es• WMO SDS-WAS program• Dust forecast
  • 40. WMO SDS-WAS programMission:Improve the capacity of countries to produce and deliver to endusers timely and precise atmospheric dust forecastsStructure:•Regional Center for Northern Africa, Middle East and Europe.Barcelona, Spain•Regional Center for Asia, Beijing, China•Regional Center for Pan America, Orange, Ca, USA
  • 41. The Regional Center is managed by the Spanish Met. Agency(AEMET) AND THE Barcelona Supercomputing Center (BSC-CNS)Nexus II buildingCatalonia Tech. University MareNostrum supercomputerThe Regional Center NA-ME-E
  • 42. http://sds-was.aemet.essdswas@aemet.es eterradellasj@aemet.es
  • 43. Forecast products
  • 44. MODEL INSTITUTION RUNTIMEDOMAIN DATAASSIMILATIONBSC-DREAM8bBSC-CNS 12 Regional NoCHIMERE LMD 00 Regional NoLMDzT-INCA LSCE 00 Global NoMACC ECMWF 00 Global MODIS AODDREAM-NMME-MACCSEEVCCC 12 Regional MACC analysisNMMB/BSC-DustBSC-CNS 12 Regional NoMetUM U. K. MetOffice00 Global MODIS AODGEOS-5 NASA 00 Global MODISreflectancesNGAC NCEP 00 Global NoDust models
  • 45. Dust optical depth at 550 nmRUN: 15 Apr 2013VALID: 15 Apr 2013 12:00 – 18 Apr 2013 00:00
  • 46. Surface concentrationRUN: 15 Apr 2013VALID: 15 Apr 2013 12:00 – 18 Apr 2013 00:00
  • 47. Numerical productsnetCDF formatSFCconcentrationDust AOD 550 µm
  • 48. Evaluation with AERONET dataSANTA_CRUZ_TENERIFE
  • 49. Evaluation with satellite products24 Apr 2013