BSC Data Assimilation Updates

Transcription

1 BSC Data Assimilation Updates Enza Di Tomaso*, Nick Schutgens, Oriol Jorba *Severo Ochoa fellow Earth Sciences Department Barcelona Supercomputing Center Special thanks to Francesco Barcelona, 18 June 2015

2 The Barcelona Model in ICAP DA on the dust module NMMB Mineral DUST Pérez et al., ACP, 2011 NMMB/BSC-CTM CHEMISTRY Jorba et al., JGR, 2012 BSC-CTM SEA-SALT Spada et al, ACP, fully on-line coupled meteorology-chemistry - computationally efficient BC/OM/SULFATE in progress - multi-scale thanks to its unified non-hydrostatic dynamical core

3 Motivations for caring about mineral dust even where ICAP meetings are held! Querol et al., 2009 Studies performed with measurements taken in Barcelona show that Saharan dust outbreaks have adverse health effects (Perez et al. 2008, Pandolfi et al., 2014)

4 Ensemble-Based DA Technique (LETKF) (courtesy of Takemasa Miyoshi)

5 Current Operational Flow Data Assimilation Flow 00 IC +06 FC +12 FC +18 FC +24 FC day 1 day 2 day 3 time 00 IC FC

6 Data Assimilation Flow Data Assimilation Flow 00 IC +06 FC +12 FC +18 FC +24 FC day 1 day 2 day 3 time 06 obs 12 obs 18 obs 24 obs M D A 2 M D A D A 06 AN 12 AN 18 AN 24 AN 00 IC FC aerosol treatment by Nick Schutgens (Schutgens et al. 2010) - core function by Takemasa Miyoshi (Ott et al. 2004, Hunt et al. 2005)

7 Data Assimilation Flow Data Assimilation FlowOutline dust observations 00 IC +06 FC +12 FC +18 FC +24 FC day 1 day 2 day 3 time localisation QC 1 06 obs 12 obs 18 obs 24 obs 1 departure statistics 2 M D A 2 M D A D A perturbations 06 AN 12 AN 18 AN 24 AN 00 IC FC quality of the analysis quality of the forecast - aerosol treatment by Nick Schutgens (Schutgens et al. 2010) - core function by Takemasa Miyoshi (Ott et al. 2004, Hunt et al. 2005)

8 Creation of the Ensemble Vertical mass flux of dust into a transport bin k 3 F k = C S 1 V α H m i M i,k k = 1,, 8 i=0

9 NRL MODIS L3 Product Aerosol Optical Depth Uncertainty OMI Aerosol Index Selected Aerosol Optical Depth AE and AI selection

10 MODIS Deep Blue L3 Product, Coll 6 Aerosol Optical Depth Uncertainty σ m 2 + σ r 2 Ångström Exponent Selected Aerosol Optical Depth AE, AI and Counts selection

11 Dust Selected Observations Selected NRL MODIS observations Selected MODIS DB observations

12 Dust Analysis (NRL MODIS) 12

13 Dust Analysis (NRL MODIS + DB) 13

14 Dust Analysis (NRL MODIS + DB) Free Run DA NRL MODIS DA NRL MODIS+DB May Jun Jul Aug 14

15 Mean Increments MODIS NRL MODIS NRL +DB

16 Mean Increments MODIS NRL Localisation function MODIS NRL +DB

17 Departure Statistics (assimilating NRL MODIS) corr. coef. = 0.61 corr. coef. = 0.79 counts counts Scatter in the analysis is smaller than for the first guess; Analysis performs better in reducing too high value than increasing too low values

18 Departure Statistics (assimilating NRL MODIS + DB) corr. coef. = 0.49 corr. coef. = 0.71 counts counts Departure statistics are improved after QC

19 Inside the box assimilated observations Dakar (Senegal) background obs uncertainty analysis independent observations smaller spread associated with low AOD values

20 Background Ensemble (assimilating NRL MODIS) Dakar (Senegal) members FG spread increases towards the end of the window

21 Analysis Ensemble (assimilating NRL MODIS) Dakar (Senegal) members AN spread generally smaller than FG spread

22 Validation against Level 2 AERONET CTL RMSE 0.67 FG RMSE 0.41 AN (NRL MODIS) RMSE 0.65 AN (NRL MODIS+DB) RMSE 0.36 (4 months data)

23 Validation against Level 2 AERONET CTL BIAS 0.25 FG BIAS AN (NRL MODIS) BIAS 0.19 AN (NRL MODIS +DB) BIAS (4 months data)

24 Analysis versus AERONET DA NRL+DB CTL DA NRL other aerosols dust aerosol

25 Free run FC DA FC other aerosols dust aerosol Forecast versus AERONET FC+12 FC+60 FC+108 Free run RMSE 0.84 RMSE 0.84 RMSE 1.13 DA RMSE 0.52 RMSE 0.64 RMSE 1.02

26 Conclusions First foundations have been built for a DA capability for the Barcelona participating in ICAP; Not yet there to perform an operational forecast but more than ready to produce dust reanalysis. 26

27 Thank you! For further information please contact 27