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Abstract: The accuracy of land surface temperatures (LSTs) derived from the Advanced Along-Track Scanning Radiometer (AATSR) was assessed in a test site in Valencia, Spain from 2002 to 2008. AATSR LSTs were directly compared with concurrent ground measurements over homogeneous, full-vegetated rice fields in the conventional temperature-based (T-based) method. We also applied the new radiance-based (R-based) method over bare soil and water surfaces, where ground LST measurements were not available. In the R-based method, ground LSTs are simulated from AATSR brightness temperatures in the 11μm band and radiative transfer simulations using surface emissivity data and atmospheric water vapor and temperature profiles. The accuracy of the R-based ground LSTs depends on how well the profiles used in simulations represent the actual atmosphere at the time of AATSR observations. This can be checked with the difference δ(T11-T12) between the actual AATSR and the profile-based simulated difference in the 11 and 12μm brightness temperatures (T11 and T12, respectively). We found that for −0.6K<δ(T11-T12)<0.6K, the R-based LSTs were accurate within ±1.0K and can be used for LST validation. For the data analyzed here, the AATSR operational algorithm overestimated the ground LST by 2 to 5K, showing that the auxiliary data utilized within the retrieval scheme (biome classification and fractional vegetation cover maps at 0.5°×0.5° resolution) should be improved and provided at the same spatial resolution as the AATSR data (1km2). When the AATSR algorithm was optimized with biome and fractional vegetation cover selected according to the nature of each surface, LST errors showed negligible average biases and rmse=±0.5K for full vegetation and water, and ±1.1K for bare soil. Furthermore, we checked an alternative algorithm explicitly dependent on emissivity, which provided accurate LSTs for all the surfaces studied, with small biases, rmse from ±0.4 to ±0.6K and most LST errors within ±1.0K. The algorithm requires monthly emissivity maps at 1km2, which can be derived from classification and fractional vegetation cover estimated from optical AATSR data. The results of this paper show the high LST accuracy achievable with AATSR data in ideal conditions. While it is necessary to establish and maintain highly homogeneous T-based validation sites, the R-based method provides an alternative for the semi-operational, long-term evaluation of LST products at global scale, since it is applicable over surfaces with varied LST and atmospheric regimes where ground LST measurements are not feasible. [Copyright &y& Elsevier]

One of the main objectives of the European Union Emission Trading Scheme is the establishment of a market price level for allowances that show to European CO2 emitting installations the environmental impact of their polluting activities. The aim of this paper is to focus on the daily price changes during 2005 in un attempt to examine the underlying rationality of pricing behaviour. Specifically, we study the effect of those weather and non-weather variables that academic and market agents consider as the major determinants of the CO2, price levels. The results show that the energy sources are the principal factors in the determination of CO2 price levels, and that only extreme temperatures influence them. [ABSTRACT FROM AUTHOR]

In situ and autonomous measurements of sea surface temperature (SST) have been performed with a thermal infrared radiometer mounted on a fixed oil rig. The accuracy limit was established at ±0.3 K for these SST measurements in order to meet the requirements of the Tropical Ocean Global Atmosphere (TOGA) program for global climate research and the Soil Moisture and Ocean Salinity (SMOS) mission for salinity retrieval. With this aim, the optimal observation angle and spectral channel for SST measurements have been identified. Then, a methodology has been developed for the radiometer calibration and the emissivity correction, including the reflection of the downwelling sky radiance, which was directly measured simultaneously to the sea surface observation. The effect of the atmospheric path between the sea surface and the sensor has been also studied and found negligible for the particular viewing conditions. A sensitivity analysis of the proposed methodology has shown a precision of ±0.15 K in the retrieved SST. Finally, the measured SSTs have been validated with coincident buoy temperatures, resulting in an average difference of 0.0 K and a standard deviation of ±0.2 K. [ABSTRACT FROM AUTHOR]

Deals with employing single-factor stochastic models in estimating daily temperature variations for the valuation of weather derivatives. Application of financial models to fit temperature seasonality to a time series; General model containing features of temperature behavior; Estimation of models that could describe temperature behavior and test nesting restrictions; Use of estimated models to simulate derivative payoffs.

Land surface temperature retrieved with temperature-emissivity separation (TES) and split-window (SW) algorithms from six-channel Thermal Infrared Multispectral Scanner (TIMS) data in the HAPEX-Sahel experiment agreed with contemporaneous ground temperature measurements to within ±1 °C (TES and SW with channels at 10.8 and 11.7 μm, or SW-56). The SW algorithm used with TIMS channels at 8.4 and 8.7 μm (SW-12) underestimated ground temperatures by 2–5 °C. The TES method required atmospheric correction of at-sensor radiances, which was done with local radiosonde data and MODTRAN 4, and an empirical relationship between the spectral range of emissivity and its minimum value. Emissivity data required for the SW algorithms were obtained using vegetation cover estimates from near-coincident reflective remote sensing data. The temperature underestimation of the SW-12 algorithm could be caused by errors in the emissivity inputs calculated from the vegetation cover. Such errors were due to the high variability of surface emissivity in the 8–9-μm waveband, which was much larger than in the 10–12-μm region. This was checked using TES derived emissivities as inputs of the SW algorithms, and comparing the resulting temperatures with the TES temperatures. In this case, both the SW-56 and SW-12 temperatures agreed with TES within ±1 °C for all sites and scenes. [Copyright &y& Elsevier]