Remote sensing instruments are key players to map land surface temperature (LST) at large temporal and spatial scales. In this paper, we present how we combine passive microwave and thermal infrared data to estimate LST during summer snow-free periods over northern high latitudes. The methodology is based on the SSM/I–SSMIS 37GHz measurements at both vertical and horizontal polarizations on a 25km×25km grid size. LST is retrieved from brightness temperatures introducing an empirical linear relationship between emissivities at both polarizations as described in Royer and Poirier (2010). This relationship is calibrated at pixel scale, using cloud-free independent LST data from MODIS instruments. The SSM/I–SSMIS and MODIS data are synchronized by fitting a diurnal cycle model built on skin temperature reanalysis provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). The resulting temperature dataset is provided at 25km scale and at an hourly time step during the ten-year analysis period (2000–2011). This new product was locally evaluated at five experimental sites of the EU-PAGE21 project against air temperature measurements and meteorological model reanalysis, and compared to the MODIS LST product at both local and circumpolar scale. The results giving a mean RMSE of the order of 2.2K demonstrate the usefulness of the microwave product, which is unaffected by clouds as opposed to thermal infrared products and offers a better resolution compared to model reanalysis. The dataset can be downloaded from the PANGAEA website: http://doi.pangaea.de/10.1594/PANGAEA.833409. •Summer Arctic land surface temperature was estimated from SSM/I–SSMIS passive microwave sensors.•The product is available during snow-free periods for a ten-year period (2000–2011).•Method is based on modeling 37GHz emissivity polarization ratio at pixel scale.•Method calibration is based on the concurrent MODIS LST data.•Continuous time series at 25km resolution and hourly time step were produced.