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

2003 ◽  
Vol 16 (9) ◽  
pp. 1261-1282 ◽  
Author(s):  
Valéry Masson ◽  
Jean-Louis Champeaux ◽  
Fabrice Chauvin ◽  
Christelle Meriguet ◽  
Roselyne Lacaze
Keyword(s):  
Land Cover ◽  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Climate Modeling ◽  
Area Index ◽  
Surface Parameters ◽  
Global Database ◽  
Climate Maps ◽  
Land Cover Maps

Abstract 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 Directionality of the Earth's Reflectance (POLDER) satellite. The comparison shows that this new LAI both reproduces values coherent at large scales with other datasets, and includes the high spatial variations owing to the input land cover data at a 1-km resolution. In terms of climate modeling studies, the use of this new database is shown to improve the surface climatology of the ARPEGE climate model.

scholarly journals Biophysical Evaluation of Land-Cover Products for Land–Climate Modeling

2009 ◽  
Vol 13 (6) ◽  
pp. 1-16 ◽  
Author(s):  
Jianjun Ge ◽  
Nathan Torbick ◽  
Jiaguo Qi
Keyword(s):  
Land Cover ◽  
Land Surface ◽  
Climate Models ◽  
Climate Modeling ◽  
Spatial Scales ◽  
Scale Space ◽  
Atmospheric Modeling ◽  
Biophysical Characterization ◽  
Area Index ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract The need for accurate characterization of the land surface as boundary conditions in climate models has been recognized widely in the climate modeling community. A large number of land-cover datasets are currently used in climate models either to better represent surface conditions or to study the impacts of surface changes. Deciding upon land-cover datasets can be challenging because the datasets are made with different sensors, ranging methodologies, and varying classification objectives. A new statistical measure Q was developed to evaluate land-cover datasets in land–climate interaction research. This measure calculates biophysical precision of land-cover datasets using 1-km monthly Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) product. This method aggregates within-class biophysical consistency, calculated as LAI variation, across a study domain and over multiple years into a single statistic. A smaller mean Q value for a land-cover product indicates more precise biophysical characterization within the classes. As an illustration, four land-cover products were assessed in the East Africa region: Global Land Cover 2000 (GLC2000), MODIS land cover, Olson Global Ecosystems (OGE), and Land Ecosystem–Atmosphere Feedback (LEAF) model. The evaluation was conducted at three different spatial scales corresponding to 30 × 30, 50 × 50, and 100 × 100 km quadrates. The Q measure found that GLC2000 ranked higher compared to the other three land-cover products for every quadrate size. For the 30 × 30 km quadrate size GLC2000 was significantly better than LEAF, which is currently used in the Regional Atmospheric Modeling System. The statistic ranks MODIS land cover above OGE, which is above LEAF. As quadrate size increases, differences between Q decrease indicating greater uncertainty at coarser resolution. The utility of the measure is that it can be applied to any continuous parameter over any scale (space or time) to evaluate the biophysical precision of any land-cover dataset.

scholarly journals ECOCLIMAP-II/Europe: a twofold database of ecosystems and surface parameters at 1 km resolution based on satellite information for use in land surface, meteorological and climate models

2013 ◽  
Vol 6 (2) ◽  
pp. 563-582 ◽  
Author(s):  
S. Faroux ◽  
A. T. Kaptué Tchuenté ◽  
J.-L. Roujean ◽  
V. Masson ◽  
E. Martin ◽  
...  
Keyword(s):  
Land Cover ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Climate Models ◽  
Area Index ◽  
Surface Parameters ◽  
Climatic Environment

Abstract. The overall objective of the present study is to introduce the new ECOCLIMAP-II database for Europe, which is an upgrade for this region of the former initiative, ECOCLIMAP-I, already implemented at global scale. The ECOCLIMAP programme is a dual database at 1 km resolution that includes an ecosystem classification and a coherent set of land surface parameters that are primarily mandatory in meteorological modelling (notably leaf area index and albedo). Hence, the aim of this innovative physiography is to enhance the quality of initialisation and impose some surface attributes within the scope of weather forecasting and climate related studies. The strategy for implementing ECOCLIMAP-II is to depart from prevalent land cover products such as CLC2000 (Corine Land Cover) and GLC2000 (Global Land Cover) by splitting existing classes into new classes that possess a better regional character by virtue of the climatic environment (latitude, proximity to the sea, topography). The leaf area index (LAI) from MODIS and normalized difference vegetation index (NDVI) from SPOT/Vegetation (a global monitoring system of vegetation) yield the two proxy variables that were considered here in order to perform a multi-year trimmed analysis between 1999 and 2005 using the K-means method. Further, meteorological applications require each land cover type to appear as a partition of fractions of 4 main surface types or tiles (nature, water bodies, sea, urban areas) and, inside the nature tile, fractions of 12 plant functional types (PFTs) representing generic vegetation types – principally broadleaf forest, needleleaf forest, C3 and C4 crops, grassland and bare land – as incorporated by the SVAT model ISBA (Interactions Surface Biosphere Atmosphere) developed at Météo France. This landscape division also forms the cornerstone of a validation exercise. The new ECOCLIMAP-II can be verified with auxiliary land cover products at very fine and coarse resolutions by means of versatile land occupation nomenclatures.

scholarly journals ECOCLIMAP-II/Europe: a twofold database of ecosystems and surface parameters at 1-km resolution based on satellite information for use in land surface, meteorological and climate models

2012 ◽  
Vol 5 (4) ◽  
pp. 3573-3620 ◽  
Author(s):  
S. Faroux ◽  
A. T. Kaptué Tchuenté ◽  
J.-L. Roujean ◽  
V. Masson ◽  
E. Martin ◽  
...  
Keyword(s):  
Land Cover ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Land Surface ◽  
Urban Areas ◽  
Climate Models ◽  
Weather Forecasting ◽  
Area Index ◽  
Surface Parameters ◽  
Climatic Environment

Abstract. The overall objective of the present study is to introduce the new ECOCLIMAP-II database for Europe, which is an upgrade for this region of the former initiative, ECOCLIMAP-I, already implemented at global scale. The ECOCLIMAP programme is a dual database at 1-km resolution that includes an ecosystem classification and a coherent set of land surface parameters that are primarily mandatory in meteorological modelling (notably leaf area index and albedo). Hence, the aim of this innovative physiography is to enhance the quality of initialisation and impose some surface attributes within the scope of weather forecasting and climate related studies. The strategy for implementing ECOCLIMAP-II is to depart from prevalent land cover products such as CLC2000 (Corine Land Cover) and GLC2000 (Global Land Cover) by splitting existing classes into new classes that possess a better regional character by virtue of the climatic environment (latitude, proximity to the sea, topography). The leaf area index (LAI) from MODIS and NDVI from SPOT/Vegetation yield the two proxy variables that were considered here in order to perform a multi-year trimmed analysis between 1999 and 2005 using the K-means method. Further, meteorological applications require each land cover type to appear as a partition of fractions of 4 main surface types or tiles (nature, water bodies, sea, urban areas) and, inside the nature tile, fractions of 12 Plant Functional Types (PFTs) representing generic vegetation types – principally broadleaf forest, needleleaf forest, C3 and C4 crops, grassland and bare land – as incorporated by the SVAT model ISBA developed at Météo France. This landscape division also forms the cornerstone of a validation exercise. The new ECOCLIMAP-II can be verified with auxiliary land cover products at very fine and coarse resolutions by means of versatile land occupation nomenclatures.

Use of satellite-based sensing in land surface climatology

1994 ◽  
Vol 18 (1) ◽  
pp. 1-15 ◽  
Author(s):  
David Greenland
Keyword(s):  
Satellite Data ◽  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Meteorological Data ◽  
Sensible Heat Flux ◽  
Longwave Radiation ◽  
Climate Modelling ◽  
Area Index ◽  
Surface Climate

Common types of satellite-derived measurements are reviewed with respect to how they are used to provide information on variables important to land surface climatology. The variables considered include solar radiation, surface albedo, surface temperature, outgoing longwave radiation, cloud cover, net radiation, soil moisture, latent and sensible heat flux, surface cover and leaf area index. A selection of land surface climate modelling schemes is identified and considered with a view to their practicality for use with satellite-derived data. Issues arising from the foregoing considerations include the absence from satellite data of some variables required by land surface climate models, the importance of extreme pixel values in model parameterization, the importance of matching spatial resolution in satellite data and climate model, and the need to have concurrent, independently observed, meteorological data in order to make full use of the satellite data.

scholarly journals Gross and net land cover changes based on plant functional types derived from the annual ESA CCI land cover maps

2017 ◽  
Author(s):  
Wei Li ◽  
Natasha MacBean ◽  
Philippe Ciais ◽  
Pierre Defourny ◽  
Céline Lamarche ◽  
...  
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Land Surface ◽  
Climate Models ◽  
Plant Functional Types ◽  
Forest Loss ◽  
Land Cover Changes ◽  
Cropland Area ◽  
Functional Types ◽  
Land Cover Maps

Abstract. Land-use and land-cover change (LULCC) impacts local energy and water balance and contributes at global scale to a net carbon emission to the atmosphere. The newly released annual ESA CCI land cover maps provide continuous land cover changes at 300 m resolution from 1992 to 2015, and can be used in land surface models (LSMs) to simulate LULCC effects on carbon stocks and on surface energy budgets. Here we investigate the absolute areas, gross and net changes of different plant functional types (PFTs) derived from ESA CCI products. The results are compared with other datasets. Global areas of forest, cropland and grassland PFTs from ESA are 30.4, 19.3 and 35.7 million km2 in 2000. The global forest area is lower than that from LUH2v2h (Hurtt et al., 2011), Hansen et al. (2013) and Houghton and Nassikas (2017) while cropland area is higher than LUH2v2h (Hurtt et al., 2011), in which cropland area is from HYDE3.2 (Klein Goldewijk et al., 2016). Gross forest loss and gain during 1992–2015 are 1.5 and 0.9 million km2 respectively, resulting in a net forest loss of 0.6 million km2, mainly occurring in South and Central America. The magnitudes of gross changes of forest, cropland and grassland PFTs in ESA CCI are smaller than those in other datasets. The magnitude of global net cropland gain for the whole period is consistent with HYDE3.2 (Klein Goldewijk et al., 2016), but most of the increases happened before 2004 in ESA while after 2007 in HYDE3.2. Brazil, Bolivia and Indonesia are the countries with the largest net forest loss from 1992 to 2015, and the decreased areas are generally consistent with those from Hansen et al. (2013) based on Landsat 30 m resolution images. Despite discrepancies compared to other datasets, and uncertainties in converting into PFTs, the new ESA CCI products provide the first detailed long time-series of land-cover change and can be implemented in LSMs to characterize recent carbon dynamics, and in climate models to simulate land-cover change feedbacks on climate. The annual ESA CCI land cover products can be downloaded from http://maps.elie.ucl.ac.be/CCI/viewer/download.php (Land Cover Maps – v2.0.7; see details in Section 2.5).

Sensitivity of the ECMWF Land surface model to vegetation and LU/LC maps

2020 ◽  
Author(s):  
Souhail Boussetta ◽  
Gianpaolo Balsamo ◽  
Emanuel Arduini ◽  
Miguel Nogueira ◽  
Gabriele Arduini ◽  
...  
Keyword(s):  
Land Cover ◽  
Vegetation Cover ◽  
Land Surface ◽  
Land Surface Model ◽  
Global Scale ◽  
Surface Model ◽  
Land Use Land Cover ◽  
Area Index ◽  
Land Cover Map ◽  
Land Cover Maps

<p><span><span>The effects of vegetation and land use/land cover maps on surface energy and carbon fluxes predictions from land surface model are investigated. The model is applied at global scale and a comparison between two configurations using different land cover maps is performed. In the first configuration, the land cover is based on the operational GLCCv1.2 map, in the second the ESA-CCI land cover map is used.</span></span></p><p><span><span>Based on these two configurations, the observation operator that disaggregates the satellite-based leaf area index into high and low vegetation components is also modified to ensure optimal conservation of the observed LAI. The Seasonal variability of the vegetation cover is also investigated by introducing a modified lamber-beer formulation that allows varying the vegetation cover as a function of the LAI. </span></span></p>

scholarly journals Mapping Biophysical Parameters for Land Surface Modeling over the Continental US Using MODIS and Landsat

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Lahouari Bounoua ◽  
Ping Zhang ◽  
Kurtis Thome ◽  
Jeffrey Masek ◽  
Abdelmounaime Safia ◽  
...  
Keyword(s):  
Land Cover ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climate Modeling ◽  
Surface Fluxes ◽  
Biophysical Parameters ◽  
Area Index ◽  
Spatial And Temporal Scales ◽  
The North

In terms of the space cities occupy, urbanization appears as a minor land transformation. However, it permanently modifies land’s ecological functions, altering its carbon, energy, and water fluxes. It is therefore necessary to develop a land cover characterization at fine spatial and temporal scales to capture urbanization’s effects on surface fluxes. We develop a series of biophysical vegetation parameters such as the fraction of photosynthetically active radiation, leaf area index, vegetation greenness fraction, and roughness length over the continental US using MODIS and Landsat products for 2001. A 13-class land cover map was developed at a climate modeling grid (CMG) merging the 500 m MODIS land cover and the 30 m impervious surface area from the National Land Cover Database. The landscape subgrid heterogeneity was preserved using fractions of each class from the 500 m and 30 m into the CMG. Biophysical parameters were computed using the 8-day composite Normalized Difference Vegetation Index produced by the North American Carbon Program. In addition to urban impact assessments, this dataset is useful for the computation of surface fluxes in land, vegetation, and urban models and is expected to be widely used in different land cover and land use change applications.

scholarly journals Development of high resolution land surface parameters for the Community Land Model

2012 ◽  
Vol 5 (2) ◽  
pp. 1435-1481 ◽  
Author(s):  
Y. Ke ◽  
L. R. Leung ◽  
M. Huang ◽  
A. M. Coleman ◽  
H. Li ◽  
...  
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Land Surface ◽  
Remotely Sensed ◽  
Remotely Sensed Data ◽  
Area Index ◽  
Surface Parameters ◽  
Community Land Model ◽  
Source Data ◽  
Land Surface Parameters

Abstract. There is a growing need for high-resolution land surface parameters as land surface models are being applied at increasingly higher spatial resolution offline as well as in regional and global models. The default land surface parameters for the most recent version of the Community Land Model (i.e. CLM 4.0) are at 0.5° or coarser resolutions, released with the model from the National Center for Atmospheric Research (NCAR). Plant Functional Types (PFTs), vegetation properties such as Leaf Area Index (LAI), Stem Area Index (SAI), and non-vegetated land covers were developed using remotely-sensed datasets retrieved in late 1990's and the beginning of this century. In this study, we developed new land surface parameters for CLM 4.0, specifically PFTs, LAI, SAI and non-vegetated land cover composition, at 0.05° resolution globally based on the most recent MODIS land cover and improved MODIS LAI products. Compared to the current CLM 4.0 parameters, the new parameters produced a decreased coverage by bare soil and trees, but an increased coverage by shrub, grass, and cropland. The new parameters result in a decrease in global seasonal LAI, with the biggest decrease in boreal forests; however, the new parameters also show a large increase in LAI in tropical forest. Differences between the new and the current parameters are mainly caused by changes in the sources of remotely sensed data and the representation of land cover in the source data. The new high-resolution land surface parameters have been used in a coupled land-atmosphere model (WRF-CLM) applied to the western US to demonstrate their use in high-resolution modeling. Future work will include global offline CLMsimulations to examine the impacts of source data resolution and subsequent land parameter changes on simulated land surface processes.

scholarly journals Gross and net land cover changes in the main plant functional types derived from the annual ESA CCI land cover maps (1992–2015)

2018 ◽  
Vol 10 (1) ◽  
pp. 219-234 ◽  
Author(s):  
Wei Li ◽  
Natasha MacBean ◽  
Philippe Ciais ◽  
Pierre Defourny ◽  
Céline Lamarche ◽  
...  
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Land Surface ◽  
Climate Models ◽  
Plant Functional Types ◽  
Forest Loss ◽  
Land Cover Changes ◽  
Cropland Area ◽  
Functional Types ◽  
Land Cover Maps

Abstract. Land-use and land-cover change (LULCC) impacts local energy and water balance and contributes on global scale to a net carbon emission to the atmosphere. The newly released annual ESA CCI (climate change initiative) land cover maps provide continuous land cover changes at 300 m resolution from 1992 to 2015, and can be used in land surface models (LSMs) to simulate LULCC effects on carbon stocks and on surface energy budgets. Here we investigate the absolute areas and gross and net changes in different plant functional types (PFTs) derived from ESA CCI products. The results are compared with other datasets. Global areas of forest, cropland and grassland PFTs from ESA are 30.4, 19.3 and 35.7 million km2 in the year 2000. The global forest area is lower than that from LUH2v2h (Hurtt et al., 2011), Hansen et al. (2013) or Houghton and Nassikas (2017) while cropland area is higher than LUH2v2h (Hurtt et al., 2011), in which cropland area is from HYDE 3.2 (Klein Goldewijk et al., 2016). Gross forest loss and gain during 1992–2015 are 1.5 and 0.9 million km2 respectively, resulting in a net forest loss of 0.6 million km2, mainly occurring in South and Central America. The magnitudes of gross changes in forest, cropland and grassland PFTs in the ESA CCI are smaller than those in other datasets. The magnitude of global net cropland gain for the whole period is consistent with HYDE 3.2 (Klein Goldewijk et al., 2016), but most of the increases happened before 2004 in ESA and after 2007 in HYDE 3.2. Brazil, Bolivia and Indonesia are the countries with the largest net forest loss from 1992 to 2015, and the decreased areas are generally consistent with those from Hansen et al. (2013) based on Landsat 30 m resolution images. Despite discrepancies compared to other datasets, and uncertainties in converting into PFTs, the new ESA CCI products provide the first detailed long-term time series of land-cover change and can be implemented in LSMs to characterize recent carbon dynamics, and in climate models to simulate land-cover change feedbacks on climate. The annual ESA CCI land cover products can be downloaded from http://maps.elie.ucl.ac.be/CCI/viewer/download.php (Land Cover Maps – v2.0.7; see details in Sect. 5). The PFT map translation protocol and an example in 2000 can be downloaded from https://doi.org/10.5281/zenodo.834229. The annual ESA CCI PFT maps from 1992 to 2015 at 0.5∘×0.5∘ resolution can also be downloaded from https://doi.org/10.5281/zenodo.1048163.

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