A new global land cover database for the year 2000 (GLC2000) has been produced by an international partnership of 30 research groups coordinated by the European Commission's Joint Research Centre. The database contains two levels of land cover information—detailed, regionally optimized land cover legends for each continent and a less thematically detailed global legend that harmonizes regional legends into one consistent product. The land cover maps are all based on daily data from the VEGETATION sensor on‐board SPOT 4, though mapping of some regions involved use of data from other Earth observing sensors to resolve specific issues. Detailed legend definition, image classification and map quality assurance were carried out region by region. The global product was made through aggregation of these. The database is designed to serve users from science programmes, policy makers, environmental convention secretariats, non‐governmental organizations and development‐aid projects. The regional and global data ar...

GLC2000: a new approach to global land cover mapping from Earth observation data

The carbon dioxide generated underground by plants and microbes and released into the atmosphere — termed soil respiration — comprises the second largest terrestrial carbon flux. It has been suggested that the flow of CO2 from this source should change with climate, but this has been difficult to confirm observationally. Ben Bond-Lamberty and Allison Thomson use a two-decade database of soil respiration measurements to show that not only is soil respiration increasing over time, but also that this increase is strongly associated with temperature changes. They estimate that total global soil respiration is increasing by about 0.1% per year, implying a moderate sensitivity to air temperature. This is consistent with an acceleration of the terrestrial carbon cycle in recent decades. Soil respiration (RS) is the flux of microbial- and plant-respired carbon dioxide from the soil surface to the atmosphere, and constitutes the second-largest terrestrial carbon flux. It has been suggested that RS should change with climate, but this has been difficult to confirm observationally. It is shown here, however, that the air temperature anomaly (the deviation from the 1961–1990 mean) correlates significantly and positively with changes in RS. Soil respiration, RS, the flux of microbially and plant-respired carbon dioxide (CO2) from the soil surface to the atmosphere, is the second-largest terrestrial carbon flux1,2,3. However, the dynamics of RS are not well understood and the global flux remains poorly constrained4,5. Ecosystem warming experiments6,7, modelling analyses8,9 and fundamental biokinetics10 all suggest that RS should change with climate. This has been difficult to confirm observationally because of the high spatial variability of RS, inaccessibility of the soil medium and the inability of remote-sensing instruments to measure RS on large scales. Despite these constraints, it may be possible to discern climate-driven changes in regional or global RS values in the extant four-decade record of RS chamber measurements. Here we construct a database of worldwide RS observations matched with high-resolution historical climate data and find a previously unknown temporal trend in the RS record after accounting for mean annual climate, leaf area, nitrogen deposition and changes in CO2 measurement technique. We find that the air temperature anomaly (the deviation from the 1961–1990 mean) is significantly and positively correlated with changes in RS. We estimate that the global RS in 2008 (that is, the flux integrated over the Earth’s land surface over 2008) was 98 ± 12 Pg C and that it increased by 0.1 Pg C yr-1 between 1989 and 2008, implying a global RS response to air temperature (Q10) of 1.5. An increasing global RS value does not necessarily constitute a positive feedback to the atmosphere, as it could be driven by higher carbon inputs to soil rather than by mobilization of stored older carbon. The available data are, however, consistent with an acceleration of the terrestrial carbon cycle in response to global climate change.

http://environmentportal.in/files/Temperature%20associated%20increases%20in%20the%20global%20soil.pdf

Temperature-associated increases in the global soil respiration record

A new version of the general circulation model CNRM-CM has been developed jointly by CNRM-GAME (Centre National de Recherches Meteorologiques—Groupe d’etudes de l’Atmosphere Meteorologique) and Cerfacs (Centre Europeen de Recherche et de Formation Avancee) in order to contribute to phase 5 of the Coupled Model Intercomparison Project (CMIP5). The purpose of the study is to describe its main features and to provide a preliminary assessment of its mean climatology. CNRM-CM5.1 includes the atmospheric model ARPEGE-Climat (v5.2), the ocean model NEMO (v3.2), the land surface scheme ISBA and the sea ice model GELATO (v5) coupled through the OASIS (v3) system. The main improvements since CMIP3 are the following. Horizontal resolution has been increased both in the atmosphere (from 2.8° to 1.4°) and in the ocean (from 2° to 1°). The dynamical core of the atmospheric component has been revised. A new radiation scheme has been introduced and the treatments of tropospheric and stratospheric aerosols have been improved. Particular care has been devoted to ensure mass/water conservation in the atmospheric component. The land surface scheme ISBA has been externalised from the atmospheric model through the SURFEX platform and includes new developments such as a parameterization of sub-grid hydrology, a new freezing scheme and a new bulk parameterisation for ocean surface fluxes. The ocean model is based on the state-of-the-art version of NEMO, which has greatly progressed since the OPA8.0 version used in the CMIP3 version of CNRM-CM. Finally, the coupling between the different components through OASIS has also received a particular attention to avoid energy loss and spurious drifts. These developments generally lead to a more realistic representation of the mean recent climate and to a reduction of drifts in a preindustrial integration. The large-scale dynamics is generally improved both in the atmosphere and in the ocean, and the bias in mean surface temperature is clearly reduced. However, some flaws remain such as significant precipitation and radiative biases in many regions, or a pronounced drift in three dimensional salinity.

/pdf/the-cnrm-cm5-1-global-climate-model-description-and-basic-vx5kg93mbd.pdf

The CNRM-CM5.1 global climate model: description and basic evaluation

The Soil Moisture and Ocean Salinity (SMOS) mission is European Space Agency (ESA's) second Earth Explorer Opportunity mission, launched in November 2009. It is a joint program between ESA Centre National d'Etudes Spatiales (CNES) and Centro para el Desarrollo Tecnologico Industrial. SMOS carries a single payload, an L-Band 2-D interferometric radiometer in the 1400-1427 MHz protected band. This wavelength penetrates well through the atmosphere, and hence the instrument probes the earth surface emissivity. Surface emissivity can then be related to the moisture content in the first few centimeters of soil, and, after some surface roughness and temperature corrections, to the sea surface salinity over ocean. The goal of the level 2 algorithm is thus to deliver global soil moisture (SM) maps with a desired accuracy of 0.04 m3/m3. To reach this goal, a retrieval algorithm was developed and implemented in the ground segment which processes level 1 to level 2 data. Level 1 consists mainly of angular brightness temperatures (TB), while level 2 consists of geophysical products in swath mode, i.e., as acquired by the sensor during a half orbit from pole to pole. In this context, a group of institutes prepared the SMOS algorithm theoretical basis documents to be used to produce the operational algorithm. The principle of the SM retrieval algorithm is based on an iterative approach which aims at minimizing a cost function. The main component of the cost function is given by the sum of the squared weighted differences between measured and modeled TB data, for a variety of incidence angles. The algorithm finds the best set of the parameters, e.g., SM and vegetation characteristics, which drive the direct TB model and minimizes the cost function. The end user Level 2 SM product contains SM, vegetation opacity, and estimated dielectric constant of any surface, TB computed at 42.5°, flags and quality indices, and other parameters of interest. This paper gives an overview of the algorithm, discusses the caveats, and provides a glimpse of the Cal Val exercises.

The SMOS Soil Moisture Retrieval Algorithm

. EURO-CORDEX is an international climate downscaling initiative that aims to provide high-resolution climate scenarios for Europe. Here an evaluation of the ERA-Interim-driven EURO-CORDEX regional climate model (RCM) ensemble is presented. The study documents the performance of the individual models in representing the basic spatiotemporal patterns of the European climate for the period 1989–2008. Model evaluation focuses on near-surface air temperature and precipitation, and uses the E-OBS data set as observational reference. The ensemble consists of 17 simulations carried out by seven different models at grid resolutions of 12 km (nine experiments) and 50 km (eight experiments). Several performance metrics computed from monthly and seasonal mean values are used to assess model performance over eight subdomains of the European continent. Results are compared to those for the ERA40-driven ENSEMBLES simulations. The analysis confirms the ability of RCMs to capture the basic features of the European climate, including its variability in space and time. But it also identifies nonnegligible deficiencies of the simulations for selected metrics, regions and seasons. Seasonally and regionally averaged temperature biases are mostly smaller than 1.5 °C, while precipitation biases are typically located in the ±40% range. Some bias characteristics, such as a predominant cold and wet bias in most seasons and over most parts of Europe and a warm and dry summer bias over southern and southeastern Europe reflect common model biases. For seasonal mean quantities averaged over large European subdomains, no clear benefit of an increased spatial resolution (12 vs. 50 km) can be identified. The bias ranges of the EURO-CORDEX ensemble mostly correspond to those of the ENSEMBLES simulations, but some improvements in model performance can be identified (e.g., a less pronounced southern European warm summer bias). The temperature bias spread across different configurations of one individual model can be of a similar magnitude as the spread across different models, demonstrating a strong influence of the specific choices in physical parameterizations and experimental setup on model performance. Based on a number of simply reproducible metrics, the present study quantifies the currently achievable accuracy of RCMs used for regional climate simulations over Europe and provides a quality standard for future model developments.

/pdf/regional-climate-modeling-on-european-scales-a-joint-3rq3kb8508.pdf

Regional climate modeling on European scales: a joint standard evaluation of the EURO-CORDEX RCM ensemble

Ecoclimap, a new complete surface parameter global dataset at a 1-km resolution, is presented. It is intended to be used to initialize the soil–vegetation–atmosphere transfer schemes (SVATs) in meteorological and climate models (at all horizontal scales). The database supports the “tile” approach, which is utilized by an increasing number of SVATs. Two hundred and fifteen ecosystems representing areas of homogeneous vegetation are derived by combining existing land cover maps and climate maps, in addition to using Advanced Very High Resolution Radiometer (AVHRR) satellite data. Then, all surface parameters are derived for each of these ecosystems using lookup tables with the annual cycle of the leaf area index (LAI) being constrained by the AVHRR information. The resulting LAI is validated against a large amount of in situ ground observations, and it is also compared to LAI derived from the International Satellite Land Surface Climatology Project (ISLSCP-2) database and the Polarization and Direc...

https://journals.ametsoc.org/doi/pdf/10.1175/1520-0442-16.9.1261

A Global Database of Land Surface Parameters at 1-km Resolution in Meteorological and Climate Models

A land cover classification product over France at 1 km resolution using SPOT4/VEGETATION data

The purpose of this paper is to describe the methods used to map homogeneous biomes using the synergy between land cover maps (Corine Land Cover) and the temporal information of the SPOT/VEGETATION data. This study is first led on South-West of France. Hierarchical and non-hierarchical clustering are applied to each type of landcover and the characterization of the clusters is made through the analyses of the temporal SPOT/VEGETATION NDVI profiles from 1999 to 2003. An interpretation of the results for the main landcover themes (crops, forest, urban) is performed. In a second step, this information is used to initialize surface parameters for atmospheric modelling. KeywordsNDVI; land cover ; vegetation ; surface parameters ; classification; k-means.

Spatio-temporal characterization of biomes over sw of france using SPOT/VEGETATION and corine land cover datasets

The objective of this paper is to describe the methods used to derive surface parameters at 1 km resolution using land cover maps, climate maps, and NDVI datasets. At global scale, the GLC2000 product and the associated regional legends are used and bring up improvement compared with previous maps made with AVHRR. A new concept of classification using the SPOT/VEGETATION NDVI profiles, in order to define homogeneous ecosystems, is presented. The method is applied to Africa. Then, all surface parameters are derived for each of these ecosystems with look-up tables; the annual cycle of the Leaf Area Index (LAI) is constrained by the SPOT/VEGETATION information; an example over France is shown

Ecoclimap2: a new approach at global and European scale for ecosystems mapping and associated surface parameters database using SPOT/VEGETATION data - first results

Soil vegetation atmosphere transfer schemes (SVATS) require a few primary parameters as inputs (leaf area index, vegetation fraction, albedo ) The objective of this paper is to describe the method used to derive these parameters from land cover maps, climate maps and NDVI datasets The resolution of these new surface parameters is 1 km at a global scale; over Europe, a land cover map with a finer resolution (250 m) is available

J.-L. Champeaux

Papers

A Global Database of Land Surface Parameters at 1-km Resolution in Meteorological and Climate Models

A land cover classification product over France at 1 km resolution using SPOT4/VEGETATION data

Spatio-temporal characterization of biomes over sw of france using SPOT/VEGETATION and corine land cover datasets

Ecoclimap2: a new approach at global and European scale for ecosystems mapping and associated surface parameters database using SPOT/VEGETATION data - first results

Global surface parameter database at 1 km resolution derived from land cover and climatic maps and used in meteorological models