Land Surface Temperature Observations

Transcrição

1 Land Surface Temperature Observations EUMETSAT Land Surface Analysis SAF GMES Geoland-2 Isabel F. Trigo Instituto de Meteorologia Thanks to the LSA SAF and Geoland-2 Teams

2 Outline LST from Geostationary platforms Ø SEVIRI/MSG retrievals (LSA SAF) ü Algorithm ü LST uncertainties ü Availabitiy & Distribution Ø Towards Global Coverage (Geoland2) ü GOES; MTSAT - Algorithm & constraints Ø Validation Ø Requirements & Further Development

3 EUMETSAT LSA SAF The Satellite Applications Facility on Land Surface Analysis, is a consortium dedicated to algorithm development, validation and operational production of land surface related products based (primarily) on European meteorological satellites (MSG and METOP) Ø Real time Ø Off-line distribution Ø Reviewed (~annually) by technical and scientific review panels

4 Land Surface Temperature LST Algorithm Requirements: ü Maximize the use of available channels, in order to... ü Minimize the incertainty of the retrievals, and... ü being Computacionally Efficient. SEVIRI - MSG

5 Solar contamination High emissivity uncertainty SEVIRI/Meteosat channels & LST Response function of channels

6 LST from SEVIRI/Meteosat Generalised Split-Window 10.8µm and 12.0µm (Wan & Dozier, 1996) Trained using CLEAR SKY synthetic SEVIRI/MSG data 1 ε Δε T T ε Δε T10.8 T12. 0 T s = ( A1 + A2 + A3 ) + ( B1 + B2 + B3 ) + C 2 2 ε ε 2 ε ε 2 GSW parameters depend on: 1. total column water vapour 2. viewing angle ECMWF fc Channel Emissivity Land Type + Fraction Vegetation Cover

7 LST from SEVIRI/Meteosat Generalised Split-Window Trained using CLEAR SKY TOA Tb s - MODTRAN Verified against independent dataset ( ~ profiles). Algorithm uncertainty increases with view angle & water vapour, i.e., with optical path. LST_Errors (K) ~ NADIR Zenith Ang ~ 40º Zenith Ang ~ 75º (cm) (cm) (cm) TCWV

8 Emissivty LST from SEVIRI/Meteosat Pixel MSG VEGETATION COVER METHOD ε = ε veg FVC+ ε ground (1-FVC) + δε LSA SAF Product Sfc Reflectances VIS Non- accounted effects (mul2ple reflec2ons at sfc) Variability of bare ground/ vega within pixel

9 LST Uncertainty Generalized Split-Windows - LST Errors S 2 LST 2 f 2 = X + i i X σ i j f θ j 2 σ 2 θ j + ΔLST 2 Input errors Sensor noise; emissivity Algorithm uncertainty Retrieval conditions Model parameters/ Implicit input variables TCWV (ECMWF); view angle

10 Land Surface Temperature - SEVIRI LSA SAF LST Product ü Genera2on Frequency - 15 min ü clear sky pixels... ü over land... ü where es2mated errors < 4K ü Available since Ø Europe Feb 2005 Ø Full disk Jul

11 Land Surface Temperature - SEVIRI LST Error Bars And error bars es2mated taking into account: ü Uncertainty of the GSW regressions ü Propaga2on of input uncertain2es: Emissivity Sensor noise TCWV ECMWF forecasts ºC Masked out δlst > 4K Trigo et al (2008) in J. Geophys. Res. Freitas et al (2010) in IEEE Trans. Remote Sens. Geosc.

12 Towards Global Coverage GOES-E MSG Met7 MTSAT Dual-Channel Generalized Split-Window Dual-Channel Geostationary data ü High temporal sampling capable of describing LST diurnal cycle û Limited area coverage

13 Towards Global Coverage Most relevant Channels for LST retrieval Channels / Resolution SEVIRI GOES Imager MTSAT Middle IR µm µm µm Thermal IR µm µm µm Thermal IR µm µm ( * ) Total 12 channels 5 channels Significantly impact the quality of the cloud screening Night-time retrievals Regression based on MIR & TIR Daytime retrievals Regression based on TIR

14 Towards Global Coverage GOES-E MSG MTSAT Met7 ü Hourly projected onto 0.05 x 0.05º ü Available with uncertainty ü since 2010 Freely Distributed within GMES project isabel.trigo@meteo.pt Caveats - not global processing of Meteosat7 under preparation - quality of retrieval varies with sensor - observation times do not match exactly in overlapping areas

15 LST - Validation Valida1on ü con2nuous ac2vity ü main source of info on product compliance with requiremets Comparison with similar products derived from other satellites : MODIS Useful to assess product consistency AATSR Comparison against in situ observa1ons: Within MSG disk - LSA SAF team: Portugal (Evora, since 2005) Namibia (Gobabeb + Kalahari farm) Field Campaigns; SURFRAD; BSRN; Sites must be representative of pixel measurements

16 LST - Validation Senegal Rasmussen et al (2011), TGRS, doi /TGRS Instituto de Meteorologia, I. P. Rua C Aeroporto de Lisboa Lisboa Portugal Tel.: (351) Fax: (351) informacoes@meteo.pt URL:

17 LST - Validation Evora (Portugal) 2005 Daytime (ºC) BIAS RMSD SEVIRI MODIS Night-time (ºC) BIAS RMSD SEVIRI MODIS Correction in level 1.5 processing at EUMETSAT (May 2008): conversion of digital counts to effective radiances (impact small, but reaching significant values for high brightness temperatures);... Morning green; afternoon red; night - blue Evora Aug 2009 (F. Goettsche) Generalized Split-Windows wider calibration dataset; treatment of input unceratainties and impact on LST errors.

18 LST - Validation Namibia Instituto de Meteorologia, I. P. Rua C Aeroporto de Lisboa Lisboa Portugal Tel.: (351) Fax: (351) informacoes@meteo.pt URL:

19 LST - Validation LST MSG/SEVIRI (Land-SAF) versus in situ Obs In Situ (ºC) May 2008 Bias: -0.31ºC RMS: 1.16ºC LST SEVIRI/MSG (ºC) Obs In Situ (ºC) Jul 2008 Bias: -0.91ºC RMS: 1.67ºC LST SEVIRI/MSG (ºC) Obs In Situ (ºC) Nov 2008 Bias: +0.24ºC RMS: 1. 44ºC LST SEVIRI/MSG (ºC) Obs In Situ (ºC) Mar 2009 Bias: -1.20ºC RMS: 1.74ºC LST SEVIRI/MSG (ºC)

20 LST - Validation GOES-E SURFRAD Crops Grass In situ LST (ºC) In situ LST (ºC) MTSAT BSRN Urban

21 Publications Download Data Documentation (User Manuals, Validation Reports) Helpdesk

22 Ø Merging satellite products GEO + LEO ü Cover poles ü Spatial down-scaling: keep high temporal sampling (hourly or higher) & LEO spatial resolution ( 1km) for regions of interest ü Decrease dependence of retrievals on viewing geometry Ø Improvement of product accuracy Further Development ü Better characterization of emissivity maps Ø LST All Weather ü Explore micro-wave ü Modelling cloudy areas (using radiation & vegetation parameters from remote sensing) Ø REPROCESSING