Presentation on theme: "Oriol Jorba1, Thomas Loridan2, Pedro Jiménez-Guerrero1,"— Presentation transcript:
1 Suitability of WRF for air quality simulations: comparison of two dynamical cores Oriol Jorba1, Thomas Loridan2, Pedro Jiménez-Guerrero1,José M. Baldasano1,3Corresponding author:1Barcelona Supercomputing Center, Earth Sciences Department, Barcelona2King’s College London, Department of Geography, London3Environmental Modelling Laboratory, Technical University of Catalonia, BarcelonaEGU 2008, Vienna, April 16th, 2008
2 Evaluation of the two dynamical cores of the WRF modelling system: ObjectiveTo analyse the skills of meteorological mesoscale models as drivers of air quality modelling systemsEvaluation of the two dynamical cores of the WRF modelling system:WRF-NMMWRF-ARW12 km horizontal resolution for a European domainAnnual simulation for 2004 – surface and boundary layerTemperatureMoistureWind speedWind direction
3 WRF-ARW current driver of CALIOPE air quality modelling system Sistema CALIOPE
4 Common air pollution episodes 2 important episodes of air quality pollution during 2004:February 2004: PM and primary pollutants episode over EuropeJuly-August 2004: O3 seasonStrong anthropogenic PM episode over western Europe - wintertimeStrong anthropogenic O3 episode over Europe - summertimeCommon characteristics: high pressure, low windsHigh stability, cold temperature High mixing, warm temperature
6 61 meteorological soundings from European network of radiosoundings Evaluation against 2 datasets931 surface meteorological stations from the NCEP ADP Global Surface Observations archive (includes METAR, SYNOP, AWOS and ASOS)61 meteorological soundings from European network of radiosoundings
8 931 surface meteorological stations from METAR and SYNOP network Surface evaluation:931 surface meteorological stations from METAR and SYNOP network8
9 Performance of the models: general overview ARW Temp MAE (C)ARW SPD MAE (m/s)We have identified problems with NMM simulation for May month related to technical aspects. For the following evaluation, the period 29/4/2004 to 26/5/2004 is not taken into account.NMM Temp MAE (C)NMM SPD MAE (m/s)
10 - + Monthly evolution of mean surface errors (MAE , MBE) (m/s)(ºC)(deg)-didiobs+Temperature and moisture: underprediction of ARW/ overprediction of NMM. Similar absolute errors.Increased underestimation of ARW during springWind speed overestimation – similar errors.Lower wind speed error during summertime
11 2m Temperature Monthly errors – January to March Lower MAE – NMMJan 2 m Temp MAE (ºC)Feb 2 m Temp MAE (ºC)Mar 2 m Temp MAE (ºC)ARWGood performance over continental flat terrainMajor problems - complex terrain and coastal areas with complex topography (Mediterranean sea).NMM
12 2m Temperature Monthly errors – July to September Jul 2 m Temp MAE (ºC)Aug 2 m Temp MAE (ºC)Sep 2 m Temp MAE (ºC)ARWStagnant situation over the Mediterranean and low baric gradients over EuropeSummertime - increased errors, but generally below 2.5ºCLower errors with NMM in western and central EuropeNMM
13 2m Temperature Monthly errors – October to December Oct 2 m Temp MAE (ºC)Nov 2 m Temp MAE (ºC)Dec 2 m Temp MAE (ºC)ARWCoastal areas:Good performance during the whole year in northwestern European coasts.Major problems in Mediterranean coasts – systematic error.Complex terrain:Higher errors during the whole yearNeed high resolution for a better representation of orography (mountains-valleys)Continental flat terrain:Overall best performance – larger errors related to meteorological conditionsNMM
14 Systematic errors of the models – annual mean RMSE, RMSEs 2m TemperatureARWLower errors over northern Europe – larger errors over southern Europe.Complex topographic areas and Mediterranean coasts – large errors.From the generally 1.5 to 2.5ºC total RMSE, 0.5 to 1.5ºC corresponds to systematic error.Higher systematic RMSE of ARW in western and central Europe.NMM14
15 Systematic errors of the models – annual mean RMSE, RMSEs 2m Dewpoint temperatureSimilar errors of both models ranging between 1.5-2ºCLower errors – northern European coastHigher errors – Alpine region.Homogeneous error distribution over flat continental terrain areas.Lower systematic RMSE in NMM (0 to 1ºC)ARWNMM15
16 Systematic errors of the models – annual mean RMSE, RMSEs 10m Wind speedARWNo clear spatial pattern of the annual error for wind speed.RMSE ranges from 1 to 3 m/sSimilar absolute and systematic errors between ARW and NMM.Systematic error ranges from 0.5 to 1.5 m/s, accounting for the half part of total error.NMM16
17 Monthly MAE – Wind speed (10 m) FebJulyARWMajor problems in complex terrain regions, and coastal regions with near mountain ranges (Mediterranean, Scandinavia, north UK)NMM17
18 Different performance in northern and southern Europe Major skills over the wetter continental Europe
19 Vertical structure evaluation: 61 meteorological soundings from European network of radiosoundings19
20 Temperature profile 0-2000 m evaluation (MAE, MBE, RMSEs) MAE errors ranging around 2.5ºC for ARW and 1.5ºC for NMM during the whole 2004.Larger underestimation of ARW.Larger diurnal errors in ARW but similar for NMM.Both models presents an underestimation of temperature in lower layers that is increased in upper levels of the ABL.NMM presents a regular MAE from 0 to 2000 m, while ARW tends to have higher errors in upper levels.
21 Major differences during summertime Mixing ratio vertical structure evaluation (MAE, MBE, RMSEs)Moisture errors higher under dryer conditions.NMM has slightly larger errors during summertimeBoth models presents an homogeneous overestimation of moisture for winter and spring and a slight underestimation in summer.Day-night conditions over-underestimation.Overestimation to underestimation from 0 to 2000 m for NMMMajor differences during summertime
22 Wind speed Vertical structure evaluation (MAE, MBE, RMSEs) Similar pattern of both models – general overestimation of wind speed.Daytime larger errors under wintertime conditions of ARW.Nighttime same performance.Larger overestimation at surface levels (0-500 m).
23 Summary of results and impacts over an air quality modelling system 2004 Annual evaluation of the two dynamical cores of WRF modelling system over Europe:WRF-NMMWRF-ARWResults have highlighted:Coastal areas:Good performance during the whole year in northwestern European coasts.Major problems in Mediterranean coasts – systematic error.Complex terrain:Higher errors during the whole year for temperature, but reasonable good wind results.Need high resolution for a better representation of topography (mountains-valleys)Continental flat terrain:Overall best performance – larger errors related to meteorological conditionsLarger errors over southern Europe and under high pressure or stagnant conditions situationSystematic errors higher with ARW, more work for improvement than NMM
24 Summary of results and impacts over an air quality modelling system (cont.) Normal range of mean absolute errors:Temperature: 1º to 3 ºC – ARW underestimation : NMM overestimationDewpoint: 1º to 2.5ºC – ARW underestimation : NMM overestimationWind speed: 1 to 5 m/s – ARW and NMM overestimationWind direction: 30 to 70 degreesImpacts of accurate meteorological fields for air quality modelling:From Pérez et al. (2006): increase in 3ºC of temperature leads to an increase of g m-3 of ozone concentration in background areas.Moisture errors impact in the formation of secondary organic aerosols and in the aqueous chemistry by modifying the OH radical concentrations.Overestimation of wind speed will produce an increase mixing of pollutants within the boundary layer and a major advective effect, the result will be a simulation of lower background pollutant concentrations over the affected areas.The direction will strongly impact with the geographical accuracy and the levels of the polluted air mass.
25 THANK YOU FOR YOUR ATTENTION Suitability of WRF model for air quality simulations:comparison of two dynamical cores on a yearly basisTHANK YOU FOR YOUR ATTENTIONCONTACTAcknowledgmentsThis work was funded by the project CALIOPE project 441/2006/ and A357/200/ of the Spanish Ministry of the Environment. The FNL analysis and verification data are provided by the NCAR’s Data Support Section. WRF-ARW and WRF-NMM simulations were performed with the MareNostrum supercomputer held by the Barcelona Supercomputing Center.
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