Abstract
[1] Land surface skin temperature Ts plays a key role in meteorological and climatological processes but the availability and the accuracy of Ts measurements over land are still limited, especially under cloudy conditions. Ts estimates from infrared satellite observations can only be derived under clear sky. Passive microwave measurements are much less affected by clouds and can provide Ts regardless of the cloud conditions. A neural network inversion including first guess information has been previously developed to retrieve Ts, along with atmospheric water vapor, cloud liquid water, and surface emissivities over land from Special Sensor Microwave/Imager measurements, with a spatial resolution of 0.25° × 0.25°, at least twice daily. In this study, Ts estimates are evaluated through careful comparisons with in situ measurements in different environments over a full annual cycle. Under clear sky conditions, the quality of our microwave neural network retrieval is equivalent to the infrared International Satellite Cloud Climatology Project products, for most in situ stations, with errors ∼3 K as compared to in situ measurements. The performance of the microwave algorithm is similar under clear and cloudy conditions, confirming the potential of the microwaves under clouds. The Ts accuracy does not depend upon the surface emissivity, as the variability of this parameter is accounted for in the processing. Our microwave Ts have been calculated for more than 15 years (1993 to mid-2008). These “all weather” Ts are a very valuable complement to the IR-derived Ts, for use in atmospheric and surface models.
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