ALBERT

Description: Time series of a wide range of biogeophysical parameters from satellite data are available to date on a global scale. A few initiatives focus on their improvement and validation in high latitudes. For example the DUE Permafrost and STSE ALANIS-Methane, which are activities funded by the European Space Agency, focus on this issue. ALANIS Methane is a research project to produce and use a suite of relevant earth observation (EO) derived information to validate and improve one of the next generation land-surface models and thus reduce current uncertainties in wetland-related CH4 emissions. The task of the ESA DUE Permafrost project is to build up an Earth observation service for high-latitudinal permafrost applications. Results which are shown in this paper contribute to both. Microwave sensors are of special interest in this context due to their independence on cloud conditions and illumination of the Earth Surface. They can be used for derivation of land surface temperature, snow properties and land surface hydrology. The latter includes near surface soil moisture and inundation. Such parameters are of importance for studies on e.g. permafrost and land-atmosphere exchange. Datasets derived from active microwave instruments operating in C-band have been analysed with respect to their usability at high latitudes. Several examples from western Siberia are discussed.

Description: The Meteorological Synthesizing Centre-West (MSC-W) of the European Monitoring and Evaluation Programme (EMEP) has been performing model calculations in support of the Convention on Long Range Transboundary Air Pollution (CLRTAP) for more than 30 years. The EMEP MSC-W chemical transport model is still one of the key tools within European air pollution policy assessments. Traditionally, the model has covered all of Europe with a resolution of about 50 km × 50 km, and extending vertically from ground level to the tropopause (100 hPa). The model has changed extensively over the last ten years, however, with flexible processing of chemical schemes, meteorological inputs, and with nesting capability: the code is now applied on scales ranging from local (ca. 5 km grid size) to global (with 1 degree resolution). The model is used to simulate photo-oxidants and both inorganic and organic aerosols. In 2008 the EMEP model was released for the first time as public domain code, along with all required input data for model runs for one year. The second release of the EMEP MSC-W model became available in mid 2011, and a new release is targeted for summer 2012. This publication is intended to document this third release of the EMEP MSC-W model. The model formulations are given, along with details of input data-sets which are used, and a brief background on some of the choices made in the formulation is presented. The model code itself is available at www.emep.int, along with the data required to run for a full year over Europe.

Description: The Meteorological Synthesizing Centre-West (MSC-W) of the European Monitoring and Evaluation Programme (EMEP) has been performing model calculations in support of the Convention on Long Range Transboundary Air Pollution (CLRTAP) for more than 30 yr. The EMEP MSC-W chemical transport model is still one of the key tools within European air pollution policy assessments. Traditionally, the EMEP model has covered all of Europe with a resolution of about 50 × 50 km2, and extending vertically from ground level to the tropopause (100 hPa). The model has undergone substantial development in recent years, and is now applied on scales ranging from local (ca. 5 km grid size) to global (with 1 degree resolution). The model is used to simulate photo-oxidants and both inorganic and organic aerosols. In 2008 the EMEP model was released for the first time as public domain code, along with all required input data for model runs for one year. Since then, many changes have been made to the model physics, and input data. The second release of the EMEP MSC-W model became available in mid 2011, and a new release is targeted for early 2012. This publication is intended to document this third release of the EMEP MSC-W model. The model formulations are given, along with details of input data-sets which are used, and brief background on some of the choices made in the formulation are presented. The model code itself is available at www.emep.int, along with the data required to run for a full year over Europe.

Description: Wetlands are a major emission source of methane (CH4) globally. In this study, we have evaluated wetland emission estimates derived using the UK community land surface model (JULES, the Joint UK Land Earth Simulator) against atmospheric observations of methane, including, for the first time, total methane columns derived from the SCIAMACHY instrument on board the ENVISAT satellite. Two JULES wetland emission estimates were investigated: (a) from an offline run driven with CRU-NCEP meteorological data and (b) from the same offline run in which the modelled wetland fractions were replaced with those derived from the Global Inundation Extent from Multi-Satellites (GIEMS) remote sensing product. The mean annual emission assumed for each inventory (181 Tg CH4 per annum over the period 1999–2007) is in line with other recently-published estimates. There are regional differences as the unconstrained JULES inventory gave significantly higher emissions in the Amazon and lower emissions in other regions compared to the JULES estimates constrained with the GIEMS product. Using the UK Hadley Centre's Earth System model with atmospheric chemistry (HadGEM2), we have evaluated these JULES wetland emissions against atmospheric observations of methane. We obtained improved agreement with the surface concentration measurements, especially at northern high latitudes, compared to previous HadGEM2 runs using the wetland emission dataset of Fung (1991). Although the modelled monthly atmospheric methane columns reproduced the large–scale patterns in the SCIAMACHY observations, they were biased low by 50 part per billion by volume (ppb). Replacing the HadGEM2 modelled concentrations above 300 hPa with HALOE–ACE assimilated TOMCAT output resulted in a significantly better agreement with the SCIAMACHY observations. The use of the GIEMS product to constrain JULES-derived wetland fraction improved the description of the wetland emissions in JULES and gave a good description of the seasonality observed at surface sites influenced by wetlands, especially at high latitudes. We found that the annual cycles observed in the SCIAMACHY measurements and at many of the surface sites influenced by non-wetland sources could not be reproduced in these HadGEM2 runs. This suggests that the emissions over certain regions (e.g., India and China) are possibly too high and/or the monthly emission patterns for specific sectors are incorrect. The comparisons presented in this paper have shown that the performance of the JULES wetland scheme is comparable to that of other process-based land surface models. We have identified areas for improvement in this and the atmospheric chemistry components of the HadGEM Earth System model. The Earth Observation datasets used here will be of continued value in future evaluations of JULES and the HadGEM family of models.

Description: Wetlands are a major emission source of methane (CH4) globally. In this study, we evaluate wetland emission estimates derived using the UK community land surface model (JULES, the Joint UK Land Earth Simulator) against atmospheric observations of methane, including, for the first time, total methane columns derived from the SCIAMACHY instrument on board the ENVISAT satellite. Two JULES wetland emission estimates are investigated: (a) from an offline run driven with Climatic Research Unit–National Centers for Environmental Prediction (CRU-NCEP) meteorological data and (b) from the same offline run in which the modelled wetland fractions are replaced with those derived from the Global Inundation Extent from Multi-Satellites (GIEMS) remote sensing product. The mean annual emission assumed for each inventory (181 Tg CH4 per annum over the period 1999–2007) is in line with other recently published estimates. There are regional differences as the unconstrained JULES inventory gives significantly higher emissions in the Amazon (by ~36 Tg CH4 yr−1) and lower emissions in other regions (by up to 10 Tg CH4 yr−1) compared to the JULES estimates constrained with the GIEMS product. Using the UK Hadley Centre's Earth System model with atmospheric chemistry (HadGEM2), we evaluate these JULES wetland emissions against atmospheric observations of methane. We obtain improved agreement with the surface concentration measurements, especially at high northern latitudes, compared to previous HadGEM2 runs using the wetland emission data set of Fung et al. (1991). Although the modelled monthly atmospheric methane columns reproduce the large-scale patterns in the SCIAMACHY observations, they are biased low by 50 part per billion by volume (ppb). Replacing the HadGEM2 modelled concentrations above 300 hPa with HALOE–ACE assimilated TOMCAT output results in a significantly better agreement with the SCIAMACHY observations. The use of the GIEMS product to constrain the JULES-derived wetland fraction improves the representation of the wetland emissions in JULES and gives a good description of the seasonality observed at surface sites influenced by wetlands, especially at high latitudes. We find that the annual cycles observed in the SCIAMACHY measurements and at many of the surface sites influenced by non-wetland sources cannot be reproduced in these HadGEM2 runs. This suggests that the emissions over certain regions (e.g. India and China) are possibly too high and/or the monthly emission patterns for specific sectors are incorrect. The comparisons presented in this paper show that the performance of the JULES wetland scheme is comparable to that of other process-based land surface models. We identify areas for improvement in this and the atmospheric chemistry components of the HadGEM Earth System model. The Earth Observation data sets used here will be of continued value in future evaluations of JULES and the HadGEM family of models.