Results of the ESA-DUE UHI project
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1 13/12/2011 Results of the ESA-DUE UHI project Bino Maiheu on behalf of the UHI project
2 Outline» Urban heat island problem» The ESA-DUE urban heat island project» UHI air temperature modeling approach» TIR user requirements analysis» Requirements for UHI modeling» Importance of synergetic observations for studying UHI 13/12/2011 2
3 The urban heat island» Discomfort : thermal stress & deaths» Energy Consumption, airconditioning» Atmospheric chemistry (O 3, emissions from energy consumption)» Local meteorology e.g. encreased rainfall downwind of cities» Increased mixing heights, urban plume» Higher temperature run-off water temperature stresses ecosystems London New Orleans,Tailor & Muñoz, /12/2011 3
4 Thermal remote sensing and UHI» Urban heat mitigation initiatives in many cities in Europe» Clear added value of TIR remote sensing : LST retrievals!» Optimize emergency response, reduce risk, asses mitigation measures» Study building energy efficiency (airborne thermography)» Aid in improving forecast, integration in urban climate modeling tools» J.A. Voogt, T.R. Oke, Thermal remote sensing of urban climates (2003), Remote Sensing of Environment 86 (2003) /12/2011 4
5 Multi-scale analysis Oke, 1997 AVHRR (1km) Airborne (10m) IR CAM (10cm) 13/12/2011 5
6 The UHI project» Project financed by ESA in framework of DUE program, started end 2008.» Quite ambitious goals :» Build archive of 10 years worth of LST retrievals for various sensors for 10 European cities : Madrid, Lisbon, Athens, Brussels, Budapest, Sevilla, Paris, London, Bari, Thessaloniki» Integration / assimilation of satellite remote sensing observations : Land Surface Temperature and ground weather stations data into urban meteorological and climate models, to facilitate preventing the impact of UHI and to reduce the risk of a heat wave» Study user requirements for new TIR satellite sensor from the UHI perspective» IEG : J. Sobrino, Benedicte Dousset, Kostas Kourtidis 13/12/2011 6
7 13/12/2011 7
8 Data sources UHI project Sensor TIR Spatial Resolution Night/Day Revisiting # TIR bands MSG-Seviri 3km (5km) ND Geostat., 15min 5 NOAA AVHRR 1.1 km ND [12hr] 2 MODIS (Terra AM, Aqua PM) 1 km ND Daily 10 Envisat-AATSR 1 km ND Daily 2 Landsat (TM/ETM+) 120 m / 60 m D, [N] 16 days 1 ASTER 90 m D 16 days 4 13/12/2011 8
9 Ensemble Stdev Surface Temp [K] Air temperature modeling approach /01 07/02 07/03 07/04 07/05 07/06 07/07 07/08 07/09 07/10 07/11 H Ts Model LST Ens STD Ens STD A LE 2 07/01 07/02 07/03 07/04 07/05 07/06 07/07 07/08 07/09 07/10 07/11 Ensemble data assimilation technique 13/12/2011 9
10 13/12/
11 Validation over Paris /12/
12 The UHI project of ESA Cities and User communities involved 10 European Municipalities Belgium: France: Greece (2): Italy: Brussels Paris, Athens, Thessaloniki Bari Spain (2): Portugal: UK: Hungary: Madrid, Seville Lisbon London Budapest» TIR requirements analysis (contribution to the mission requirements for a high resolution TIR (Thermal Infra Red) satellite sensor ('Reorientation of the Fuegosat Consolidation Phase') Health prevention, emergencies management and risk analysis Energy efficiency (including winter thermography) Urban planning Urban environmental quality Meteorological services 13/12/
13 Spatial resolution vs. revisit time gaps Source: INDRA 13/12/
14 Spatial resolution 10 m 50 m 100 m Madrid, Retiro park 2008 (DESIREX) 13/12/ m 1 km
15 TIR Requirements synthesis (INDRA) Meteorological services / Emergencies / Urban Environment al Quality Observation time Spatial resolution Revisit time The time of observation shall be at least of 2 images per day with a minimum amplitude of 6 hours, and ideally 3 images per day The spatial resolution should be < 500 m The revisit time should be < Daily Spectral Sampling At least two bands centred on 9 µm and 12 µm. Desirable: 4 Timeliness The delivery shall be NRT Energy Efficiency and Urban Planning Observation time Spatial resolution Spectral Sampling Revisit Time The time of observation should be ideally 2 images per day with a large amplitude (minimum amplitude of 6 hours) The spatial resolution should be between 1m and max 4 TIR Bands The revisit time should be weekly or more 13/12/ Source: INDRA
16 LST in urban climate modeling» MSG-SEVIRI too coarse, but still useful for UHI dynamics over large metropolitan areas, e.g. estimate kb -1» De Ridder, K., C. Bertrand, G. Casanova, W. Lefebvre, and S. Mekaoui, Estimating urban thermophysical properties using thermal infared geostationary remote sensing. In preparation» Revisit time of 1 km sensors, capturing the daily amplitude, night & day!» Uncertainty of urban surface emissivity» Temperature Emissivity Separation (TES) algorithms best suited» Multiple TIR bands needed» Anisotropy, directional effects in TIR radiance : nadir view vs. off nadir view» Make use of it / correct for it? 13/12/
17 Directional effects» J-P Lagouarde (Remote Sensing of Env. 93 (2004) ) : airborne» Directional effects of K!!!» Low res instruments (AVHRR, AATSR) can have incidence angles up to 60 13/12/
18 Importance of other synergetic observations Other important parameters for UHI modeling / studies» FVC, Albedo, urban surface characterization» Atmospheric Composition» Aerosol extinction & effect on UHI?» Effects on long wave radiation loss (greenhouse effect)» Photo-chemistry : T dependence of O 3 NO 2» Urban plume profile measurements 13/12/
19 13/12/
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