Land surface albedo and downwelling shortwave radiation from MSG: Retrieval, validation and impact assessment in NWP and LSM models

Transcription

1 Land surface albedo and downwelling shortwave radiation from MSG: Retrieval, validation and impact assessment in NWP and LSM models Jean-Louis ROUJEAN, Dominique CARRER, Xavier CEAMANOS, Olivier HAUTECOEUR, Jure CEDILNIK, Bernhard GEIGER, and Jean-François MAHFOUF Météo France - CNRM/GAME 5th LSA SAF User WOrkshop

2 Albedo products Outline Current family of AL products Characteristics Algorithm overview Validation effort Status of the products during CDOP Foreseen activities during CDOP-2

3 Current family of AL products (1/2) Content of the SP surface albedo product files Albedo products in SEVIRI bands : VIS006, VIS008, IR016 AL-SP-BH AL-SP-BH-ERR AL-SP-DH AL-SP-DH-ERR ALbedo SPectral Bi-Hemispherical ALbedo SPectral Directional-Hemispherical internal products not disseminated, nor subject to review

4 Current family of AL products (2/2) Content of the BB surface albedo product files Albedo products in large bands : VIS,NIR,SW AL-BB-BH AL-BB-BH-ERR AL-BB-DH AL-BB-DH-ERR AL-NI-DH AL-NI-DH-ERR AL-VI-DH AL-VI-DH-ERR ALbedo BroadBand Bi-Hemispherical ALbedo BroadBand Directional-Hemispherical ALbedo Near-Infrared Directional-Hemispherical ALbedo Visible Directional-Hemispherical products disseminated, subject to review

5 5 Albedo - Characteristics Spatial resolution: 3 km at the equator Projection: MSG/SEVIRI native Production frequency: daily and 10-day Effective temporal resolution: 5 days

6 Uncertainty Estimates and Processing Flag Uncertainty estimates = non-correlated (random) errors. Depend on number of observations, estimated TOC-reflectance errors, and angular configuration. Quality flag includes: the land/water mask processed/unprocessed pixels instruments used (MSG, EPS) snow flag from NWC cloud mask

7 7 Albedo - Inputs Radiances at 0.6 µm, 0.8 µm, 1.6 µm (SEVIRI) Solar and satellite zenith angles (SEVIRI) Cloud mask (NWC-SAF) Water vapor column and pressure (ECMWF) Ozone content (Climatology) Aerosol optical thickness (Climatology or MACC-II) Aerosol optical depth at 550 nm on February 28 th at 15h00, 2013

8 Algorithm overview for each day for each slot Geometry Geometry TOA-Radiances 0.6µm, 0.8µm, 1.6µm Atmospheric Correction (SMAC) TOC-Reflectances 0.6µm, 0.8µm, 1.6µm BRDF Model Inversion Model Parameters 0.6µm, 0.8µm, 1.6µm Angular Integration Spectral Albedo 0.6µm, 0.8µm, 1.6µm Spectral Integration Cloud Mask Atmospheric Constituents Previous Model Estimate s v Isotropic iso geometric v vol s v volume scattering R ( ϑ, ϑ, φ ) = k + k f ( ϑ, ϑ, φ ) + k f ( ϑ, ϑ, φ ) s volume scattering + + ρ θ,θ,φ =k +k.f θ,θ,φ +k.f θ,θ,φ +...+k.f θ,θ,φ ( s s ) ( s s 2 2 ) ( s s ) n n ( s s ) B R D F k 0 : Lambertian coefficient k 1 : roughness coefficient k 2 : volume scattering coefficient k n : specular coefficient (snow) specular Broadband Albedo [0.3µm,4µm], [0.4µm,0.7µm], [0.7µm,4µm]

9 9 Albedo - Assessment VIS LSA-SAF albedo (climatol. AER) MODIS albedo LSA-SAF AL VIS LSA-SAF albedo (MACC-II AER) MODIS albedo MODIS AL Fires in Russia LSA-SAF AL MODIS AL

10 10 Albedo - Assessment VIS LSA-SAF albedo (climatol. AER) MODIS albedo LSA-SAF AL VIS LSA-SAF albedo (MACC-II AER) MODIS albedo MODIS AL Uncorrected aerosol effects in MODIS product LSA-SAF AL MODIS AL

11 11 Albedo - Assessment VIS LSA-SAF albedo (climatol. AER) POLDER albedo LSA-SAF AL VIS LSA-SAF albedo (MACC-II AER) POLDER albedo MODIS AL POLDER does correct for aerosols over bright targets LSA-SAF AL MODIS AL

12 12 Albedo - Assessment Temporal series compared to MODIS and in situ measurements Evora station from February to September 2010

13 13 Albedo - Assessment Temporal series compared to MODIS and in situ measurements Evora station from February to September 2010 High albedo uncertainties due to cloudy conditions

14 14 Albedo - Assessment Temporal series compared to MODIS and in situ measurements Evora station from February to September 2010 Good agreement between MACC-II and AERONET data

15 15 Albedo - Assessment Temporal series compared to MODIS and in situ measurements Evora station from February to September 2010 MODIS slightly overestimates surface albedo

16 16 Albedo - Assessment Temporal series compared to MODIS and in situ measurements Evora station from February to September 2010 Malfunctioning of ground station

17 17 Albedo - Accuracy Accuracy: Daily albedo: bias of 20% in the VIS (mainly due to the presence of aerosols) and of 5% in the SW and NIR 10-day albedo: maximum bias of 10% Publications: D. Carrer et al., Evaluating operational MSG/SEVIRI land surface albedo products from LSA-SAF with ground measurements and MODIS, IEEE Transactions on Geoscience and Remote Sensing, 2010 B. Geiger, Land Surface Albedo derived on a daily basis from Meteosat Second Generation Observations, IEEE Transactions on Geoscience and Remote Sensing, 46, , 2008 Product User Manual and Validation Report

18 18 Albedo - Application to NWP and LSM Context: Satellite products: total surface albedo NWP and LSM inputs: bare soil and vegetation albedo components

19 19 Albedo - Application to NWP and LSM Context: Satellite products: total surface albedo NWP and LSM inputs: bare soil and vegetation albedo components Method: Kalman filter for daily analysis of albedo components Evora station Analyzed bare soil albedo Climatological bare soil albedo (ECOCLIMAP) Rainfall [J. Cedilnik, D. Carrer, J.-F. Mahfouf, and J.-L. Roujean, Analysis of satellite derived surface albedo for numerical weather prediction, J. Climate Appl., 2012]

20 20 Surface albedo 15/02/ UTC+12 LSA-SAF - reference Albedo - Impact on NWP Weather forecast model: ALADIN (~9.5 km) Two experiments: using ALADIN albedo and LSA-SAF albedo Run every day at 00h (2007) 54 h forecast LSA-SAF albedo is lower than ALADIN albedo [J. Cedilnik, D. Carrer, J.-F. Mahfouf, and J.-L. Roujean Analysis of satellite derived surface albedo for numerical weather prediction, J. Climate Appl., 2012]

21 21 Albedo - Impact on NWP Weather forecast model: ALADIN (~9.5 km) Two experiments: using ALADIN albedo and LSA-SAF albedo Run every day at 00h (2007) 54 h forecast Surface albedo 15/02/ UTC+12 LSA-SAF - reference Temp. at 2m 15/02/ UTC+12 LSA-SAF - reference LSA-SAF albedo is lower than ALADIN albedo This induces a higher temperature at 2m Conclusions: satellite data can reduce the cold bias in winter of the weather forecast model. [J. Cedilnik, D. Carrer, J.-F. Mahfouf, and J.-L. Roujean Analysis of satellite derived surface albedo for numerical weather prediction, J. Climate Appl., 2012]

22 DSSF : method of estimation

23 Cloudy Sky Parameterisation F F 0 v( j)cosθ sun T atm 1 T T cloud atm _ below_ cloud A surf A cloud

24 24 LSA-SAF product DSSF DSSF - Characteristics Spectral range: [0.25 µm, 4.0 µm] LSA-SAF flag DSSF Spatial resolution: 3 km at the equator Projection: MSG/SEVIRI native Production frequency: 30 min. and daily Effective temporal resolution: instantaneous Retrieval method Physical parametrization «Clear sky» and «cloudy sky» Inputs : similar to those used for the albedo product

25 Validation with in situ measurements

26 Validation of DSSF with RADOME network (8 km) 15/01/ h 15/06/ h 15/10/ h

27 DSSF product Land SAF (4km) ECMWF (0.5 )

28 28 DSSF - Impact on LSM Simulation of net radiation at Aurade station with the land surface model ISBA and four different forcings (1) atmospherical analysis with SAFRAN, (2) LSA-SAF DSSF, (3) LSA-SAF DSLF, or (4) LSA-SAF DSSF and DSLF Publication: D. Carrer et al., 2012: Incoming solar and infrared radiation derived from METEOSAT: impact on the modelled land water and energy budget over France, J. Of Hydrometeorology]

29 29 DSSF - Impact on LSM Simulation of net radiation at Aurade station with the land surface model ISBA and four different forcings (1) atmospherical analysis with SAFRAN, (2) LSA-SAF DSSF, (3) LSA-SAF DSLF, or (4) LSA-SAF DSSF and DSLF Comparison with in situ data taken by FLUXNET station Publication: D. Carrer et al., 2012: Incoming solar and infrared radiation derived from METEOSAT: impact on the modelled land water and energy budget over France, J. Of Hydrometeorology]

30 30 Future work Continuous algorithm improvement Better characterization of aerosols effects (i.e., load and type) in both albedo and DSSF products. Polar coverage using MetOp data -> Global coverage! Development of new surface products Direct and diffuse DSSF, bare soil and vegetation albedos + snow-free. Preparation for the arrival of MTG (scheduled launch in 2017) New access to LSA-SAF data through HyMeXsat (CNES/IPSL) The LSA-SAF program allows the scientific community to constrain the climatic trends in Europe, Africa and South America thanks to an assured production until 2017 at least.

31 EPS / AVHRR development chain for albedo Selected zone «High latitudes North» extended Projection LAEA (Lambert Azimutal Equal Area) - Resolution 2.5 km Sea Ice albedo mapped Algorithm is the same for MSG Data reprocessing since march 2010.

32 THANK YOU FOR YOUR ATTENTION