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MSG Tmax and Tmin

Version 1.0.1 now available - uses ESA Land Use CCI data set.

This data set contains estimates of the maximum and minimum daily surface skin and air temperatures at a spatial scale of 4-10 km over Europe. Data are provided for each pixel at the native resolution of the satellite used to produce this data set for 2012 to the recent past; data from 2009 are available by request. The data were produced as part of the EURO4M project (deliverable d1.11). They are updated on an ad-hoc basis but the aim is to keep in line with ECA&D data, which are required for the construction of this data set. Please email any feedback/comments to elizabeth.good@metoffice.gov.uk.


Brief description of the data

Daily minimum and maximum surface temperatures have been estimated using data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Metosat Second Generation (MSG) satellite platform, which is the operational weather satellite at 0 degrees longitude/latitude. Both the land surface skin temperature (LSTmin and LSTmax) and and estimated air temperature (Tmin and Tmax) are provided in this data set, with Tmin and Tmax being derived from the LSTmin and LSTmax data through an empirical regression-based approach. Fifteen-minute LST data from SEVIRI, provided by the Land Surface Analysis Satellite Applications Facility (LSA-SAF) are used to estimate daily cloud-free LSTmin and LSTmax. These LST data are then regressed with observed daily vegetation fraction, latitude, urban fraction, elevation and distance from coast against collocated station Tmin and Tmax data from ECA&D. Separate regression models are produced for Tmin and Tmax for a rolling 11-day window to account for temporal variation in the relationships between air temperature and the regression predictor variables. The derived regression coefficients are applied to every available cloud-free SEVIRI LSTmin/max observation for the central day in the analysis window, providing estimates of Tmin and Tmax where station data are unavailable. Assessing both the model residuals and using independent station data from the UK and Germany not used in the regression formulation suggests that for most days, at least 50% of the estimated LSATs are within 3 deg C of collocated station observations, with around 80% within 4 deg C and 90% within 5 deg C (2012-2013 all data: mean satellite-minus-station bias is 0.0 to 0.5 deg C with root-mean-square difference of 2.3 to 2.7 deg C). Results for Tmax are slightly better than for Tmin. The mean bias of the satellite-estimated Tmin/Tmax oscillates around zero and shows little seasonal variation, although the variance is noted to be lower during summer months. The satellite data sets used for the regression are sourced from the Land Surface Analysis Satellite Applications Facility (LSA SAF), with 300-m land cover data from ESA Land Cover CCI used to provide an estimate water fraction, and the urban fraction parameter used in the regression.

The data derived here are not designed to replace traditional gridded station air temperature data sets, but to augment them. Satellite surface temperature data usually have larger uncertainties than in situ data sets, but they can offer spatial detail and coverage that the latter may not provide.


Minimum and maximum temperatures from SEVIRI for 21 August 2013

Example of satellite temperature data on 21 August 2013 showing
(a) LSTmin, (b) Tmin, (c) Tmin, (d) LSTmax, (e) Tmax, and (f) Tmax for the Iberian Peninsular and north-western Africa. Grey areas correspond to missing data (e.g. ocean or cloud).



Minimum and maximum air temperatures for 27 March 2012

Air temperatures data on 27 March 2012 showing
(a) E-OBS Tmin, (b) ECA&D Tmin, (c) SEVIRI Tmin, (d) E-OBS Tmax, (b) ECA&D Tmax, (c) SEVIRI Tmax over France. Grey areas correspond to missing data (e.g. ocean or cloud).



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References

Please cite the following publication if you use these data:

Good, E. (2015), Daily minimum and maximum surface air temperatures from geostationary satellite data, JGR-Atmospheres, doi:10.1002/2014JD022438.

Dataset produced in collaboration with:

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