scholarly journals Climate Data Records of Vegetation Variables from Geostationary SEVIRI/MSG Data: Products, Algorithms and Applications

2019 ◽  
Vol 11 (18) ◽  
pp. 2103 ◽  
Author(s):  
Francisco Javier García-Haro ◽  
Fernando Camacho ◽  
Beatriz Martínez ◽  
Manuel Campos-Taberner ◽  
Beatriz Fuster ◽  
...  
Keyword(s):  
Land Surface ◽  
Expert Knowledge ◽  
Terrestrial Ecosystems ◽  
Environmental Applications ◽  
Climate Data ◽  
Area Index ◽  
Infrared Imager ◽  
Statistical Relationships ◽  
Spectral Mixture

The scientific community requires long-term data records with well-characterized uncertainty and suitable for modeling terrestrial ecosystems and energy cycles at regional and global scales. This paper presents the methodology currently developed in EUMETSAT within its Satellite Application Facility for Land Surface Analysis (LSA SAF) to generate biophysical variables from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board MSG 1-4 (Meteosat 8-11) geostationary satellites. Using this methodology, the LSA SAF generates and disseminates at a time a suite of vegetation products, such as the leaf area index (LAI), the fraction of the photosynthetically active radiation absorbed by vegetation (FAPAR) and the fractional vegetation cover (FVC), for the whole Meteosat disk at two temporal frequencies, daily and 10-days. The FVC algorithm relies on a novel stochastic spectral mixture model which addresses the variability of soils and vegetation types using statistical distributions whereas the LAI and FAPAR algorithms use statistical relationships general enough for global applications. An overview of the LSA SAF SEVIRI/MSG vegetation products, including expert knowledge and quality assessment of its internal consistency is provided. The climate data record (CDR) is freely available in the LSA SAF, offering more than fifteen years (2004-present) of homogeneous time series required for climate and environmental applications. The high frequency and good temporal continuity of SEVIRI products addresses the needs of near-real-time users and are also suitable for long-term monitoring of land surface variables. The study also evaluates the potential of the SEVIRI/MSG vegetation products for environmental applications, spanning from accurate monitoring of vegetation cycles to resolving long-term changes of vegetation.

Potential natural vegetation dynamics driven by future long-term climate change and its hydrological impacts in the Hanjiang River basin, China

2012 ◽  
Vol 43 (1-2) ◽  
pp. 73-90 ◽  
Author(s):  
Fei Yuan ◽  
Liliang Ren ◽  
Zhongbo Yu ◽  
Yonghua Zhu ◽  
Jing Xu ◽  
...  
Keyword(s):  
Climate Change ◽  
River Basin ◽  
21St Century ◽  
Land Surface ◽  
Natural Vegetation ◽  
Potential Natural Vegetation ◽  
Area Index ◽  
Hanjiang River ◽  
Ipcc Sres

Vegetation and land-surface hydrology are intrinsically linked under long-term climate change. This paper aims to evaluate the dynamics of potential natural vegetation arising from 21st century climate change and its possible impact on the water budget of the Hanjiang River basin in China. Based on predictions of the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC-SRES) A1 scenario from the PRECIS (Providing Regional Climates for Impact Studies) regional climate model, changes in plant functional types (PFTs) and leaf area index (LAI) were simulated via the Lund-Potsdam-Jena dynamic global vegetation model. Subsequently, predicted PFTs and LAIs were employed in the Xinanjiang vegetation-hydrology model for rainfall–runoff simulations. Results reveal that future long-term changes in precipitation, air temperature and atmospheric CO2 concentration would remarkably affect the spatiotemporal distribution of PFTs and LAIs. These climate-driven vegetation changes would further influence regional water balance. With the decrease in forest cover in the 21st century, plant transpiration and evaporative loss of intercepted canopy water will tend to fall while soil evaporation may rise considerably. As a result, total evapotranspiration may increase moderately with a slight increase in annual runoff depth. This indicates that, for long-term hydrological prediction, climate-induced changes in terrestrial vegetation cannot be neglected as the terrestrial biosphere plays an important role in land-surface hydrological responses.

A review of the application of BRDF models to infer land cover parameters at regional and global scales

2001 ◽  
Vol 25 (4) ◽  
pp. 483-511 ◽  
Author(s):  
Gareth Roberts
Keyword(s):  
Land Surface ◽  
Lower Boundary ◽  
Terrestrial Ecosystems ◽  
Remotely Sensed Data ◽  
Area Index ◽  
Lower Boundary Condition ◽  
Surface Parameters ◽  
Case Examples ◽  
Global Circulation Models ◽  
Land Surface Parameters

This paper presents a review of the application of Bi-directional Reflectance Distribution Function (BRDF) models in the inference of land surface parameters at regional and global scales using remotely sensed data. Information on land surface parameters, such as Leaf Area Index (LAI), fraction of Absorbed Photosynthetically Active Radiation (fAPAR), aerodynamic surface roughness and albedo, are valuable for understanding the transfer of energy and mass between terrestrial ecosystems and the atmosphere (e.g., carbon, nitrogen and methane cycling) and for ingestion into the lower boundary condition of global circulation models (GCM)s. Conventional techniques for acquiring information on land surface parameters do not account for or utilize the directional nature of surface reflectance. This paper reviews empirical, semi-empirical and, to a lesser extent, physical BRDF models that describe the surface BRDF. In each case examples are given of their application in inferring land surface parameters. The review concludes by discussing the future prospects of BRDF modelling using spaceborne sensors.

scholarly journals Comprehensive Assessment of Performances of Long Time-Series LAI, FVC and GPP Products over Mountainous Areas: A Case Study in the Three-River Source Region, China

2021 ◽  
Vol 14 (1) ◽  
pp. 61
Author(s):  
Wenqi Zhang ◽  
Huaan Jin ◽  
Ainong Li ◽  
Huaiyong Shao ◽  
Xinyao Xie ◽  
...  
Keyword(s):  
Time Series ◽  
Global Change ◽  
Land Surface ◽  
Gross Primary Production ◽  
Source Region ◽  
Mountainous Areas ◽  
Area Index ◽  
Vegetation Activity ◽  
Long Time

Vegetation biophysical products offer unique opportunities to examine long-term vegetation dynamics and land surface phenology (LSP). It is important to understand the time-series performances of various global biophysical products for global change research. However, few endeavors have been dedicated to assessing the performances of long-term change characteristics or LSP extraction derived from different satellite products, especially in mountainous areas with highly fragmented and rugged surfaces. In this paper, we assessed the time-series characteristics and LSP detections of Global LAnd Surface Satellite (GLASS) leaf area index (LAI), fractional vegetation cover (FVC), and gross primary production (GPP) products across the Three-River Source Region (TRSR). The performances of products’ temporal agreements and their statistical relationship as a function of topographic indices and heterogeneous pixels, respectively, were investigated through intercomparison among three products during the period 2000 to 2018. The results show that the phenological differences between FVC and two other products are beyond 10 days over more than 35% of the pixels in TRSR. The long-term trend of FVC diverges significantly from GPP and LAI for 13.96% of the total pixels, and the percentages of mismatched pixels between FVC and two other products are 33.24% in the correlation comparison. Moreover, good agreements are observed between GPP and LAI, both in terms of LSP and interannual variations. Finally, the LSP and long-term dynamics of the three products exhibit poor performances on heterogeneous surfaces and complex topographic areas, which reflects the potential impacts of environmental factors and algorithmic imperfections on the quality and performances of different products. Our study highlights the spatiotemporal disparities in detections of surface vegetation activity in mountainous areas by using different biophysical products. Future global change studies may require multiple high-quality satellite products with long-term stability as data support.

scholarly journals Implementation and validation of a new irrigation scheme in the ISBA land surface model

2021 ◽  
Author(s):  
Arsène Druel ◽  
Simon Munier ◽  
Anthony Mucia ◽  
Clément Albergel ◽  
Jean-Christophe Calvet
Keyword(s):  
Land Surface ◽  
Vegetation Type ◽  
Spatial Scales ◽  
Terrestrial Ecosystems ◽  
Moisture Stress ◽  
Surface Model ◽  
Irrigation Scheme ◽  
Area Index ◽  
Natural Processes ◽  
The Impact

Abstract. With an increase in the number of natural processes represented, global land surface models (LSMs) have become more and more accurate in representing natural terrestrial ecosystems. However, they are still limited, especially in the representation of the impact of agriculture on land surface variables. This is particularly true for agro-hydrological processes related to a strong human control on freshwater. While most LSMs consider natural processes only, the development of human-related processes, e.g. crop phenology and irrigation in LSMs, is key. In this study we present the implementation of a new irrigation scheme in the ISBA (Interaction between Soil, Biosphere, and Atmosphere) LSM. This highly flexible scheme is designed to account for various configurations and can be applied at different spatial scales. For each vegetation type within a model grid cell, three irrigation systems can be used at the same time. A limited number of parameters are used to control (1) the amount of water used for irrigation, (2) irrigation triggering (based on the soil moisture stress) and (3) crop seasonality (emergence, harvesting). After a presentation of the simulations of the new scheme at a plot scale, an evaluation is proposed over Nebraska (USA). This region is chosen for its high irrigation density and because independent observations of irrigation practices can be used to verify the simulated irrigation amounts. The ISBA simulations with and without the irrigation scheme are compared to different satellite-based observations. The comparison shows that the irrigation scheme improves the simulated vegetation variables such as leaf area index and gross primary productivity and other variables largely impacted by irrigation such as evapotranspiration and land surface temperature. In addition to a better representation of land surface processes, the results point to potential applications of this new version of the ISBA model for water resource monitoring and climate change impact studies.

GBOV (Ground-Based Observation for Validation): A Copernicus service for validation of Land Products

2020 ◽  
Author(s):  
Gabriele Bai ◽  
Christophe Lerebourg ◽  
Marco Clerici ◽  
Nadine Gobron ◽  
Jan-Peter Muller ◽  
...  
Keyword(s):  
Land Surface ◽  
Data Access ◽  
Earth Observation ◽  
Free Access ◽  
In Situ Observation ◽  
Area Index ◽  
First Case ◽  
New Instrumentation ◽  
Reference Measurements

<p>Copernicus is a European Union Earth Observation program, dedicated to monitor our planet and its environment, giving free access to remote sensing data and derived Earth Observation products. For proper use in environmental monitoring and scientific applications, it is fundamental to guarantee high quality and consistency of these satellite derived products. One of the possibilities to ensure product quality is to perform quantitative comparisons of satellite derived products with the corresponding in situ observation. Two options can then be considered for ground data sources: through intensive field campaigns or making use of permanent ground stations deployed and maintained on the long term. In the first case, a large variety of variable can be assessed, but logistical challenges and financial resources limit in time and space the products validation. More over meteorological constrains often limit the number of data that can actually be used for Earth Observation products. The second option is from far the most cost effective although it is not yet possible to cover all ground variables with permanent field deployment.</p><p>To achieve these objectives of systematic and long-term data validation, the <strong>Ground-Based Observations for Validation</strong> (GBOV) service has been implemented, facilitating the use of observations from operational ground-based monitoring networks and their comparison to EO products. The service is guaranteed through 3 different components:</p><ul><li>Collection of multi-year ground-based observations (<strong>Reference Measurements</strong> - RMs) of high relevance for the understanding of land surface processes from more than 50 existing sites. These RMs are then upscaled to generate <strong>Land Products</strong> (LPs), in order to validate the Copernicus products. In particular, the LPs distributed through the GBOV portal are: Top of Canopy Reflectance (ToC-R), surface albedo, Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Available Radiation (FAPAR), Fraction of Covered ground (FCover), Surface Soil Moisture (SSM) and Land Surface Temperature (LST).</li> <li>Upgrade of existing sites with new instrumentation or establishing entirely new monitoring sites to close thematic or geographical gaps. In 2019 new instrumentation has been installed in three different sites: Hainich (Germany), Valencia (Spain) and Tumbarumba (Australia). Litchfield (Australia), Dahra (Senegal) and Skukuza (South Africa) will be equipped with new instrumentation in the course of 2020.</li> <li>Implementation and maintenance of a database for the distribution of the Reference Measurements and the corresponding Land Products, available through the website https://land.copernicus.eu/global/gbov. GBOV data access is completely free, after registration and acceptation of the terms of use and the data policy.</li> </ul>

scholarly journals Land Surface Albedo from Geostationary Satelites: A Multiagency Collaboration within SCOPE-CM

2013 ◽  
Vol 94 (2) ◽  
pp. 205-214 ◽  
Author(s):  
Alessio Lattanzio ◽  
Jörg Schulz ◽  
Jessica Matthews ◽  
Arata Okuyama ◽  
Bertrand Theodore ◽  
...  
Keyword(s):  
Satellite Data ◽  
Land Surface ◽  
Surface Albedo ◽  
Global Climate ◽  
The United States ◽  
Japan Meteorological Agency ◽  
Climate Data ◽  
Climate Monitoring ◽  
Governmental Institutions

Climate has been recognized to have direct and indirect impact on society and economy, both in the long term and daily life. The challenge of understanding the climate system, with its variability and changes, is enormous and requires a joint long-term international commitment from research and governmental institutions. An important international body to coordinate worldwide climate monitoring efforts is the World Meteorological Organization (WMO). The Global Climate Observing System (GCOS) has the mission to provide coordination and the requirements for global observations and essential climate variables (ECVs) to monitor climate changes. The WMO-led activity on Sustained, Coordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE-CM) is responding to these requirements by ensuring a continuous and sustained generation of climate data records (CDRs) from satellite data in compliance with the principles and guidelines of GCOS. SCOPE-CM represents a new partnership between operational space agencies to coordinate the generation of CDRs. To this end, pilot projects for different ECVs, such as surface albedo, cloud properties, water vapor, atmospheric motion winds, and upper-tropospheric humidity, have been initiated. The coordinated activity on land surface albedo involves the operational meteorological satellite agencies in Europe [European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT)], in Japan [the Japan Meteorological Agency (JMA)], and in the United States [National Oceanic and Atmospheric Administration (NOAA)]. This paper presents the first results toward the generation of a unique land surface albedo CDR, involving five different geostationary satellite positions and approximately three decades of data starting in the 1980s, and combining close to 30 different satellite instruments.

scholarly journals Root foraging alters global patterns of ecosystem legacy from climate perturbations

2021 ◽  
Author(s):  
Max Berkelhammer ◽  
Beth Drewniak ◽  
Benjamin Ahlswede ◽  
Miquel Gonzalez-Meler
Keyword(s):  
Land Surface ◽  
Climate Extremes ◽  
Terrestrial Ecosystems ◽  
Arid Ecosystems ◽  
Earth System ◽  
Area Index ◽  
Ecosystem Sensitivity ◽  
Initial Event ◽  
Global Patterns ◽  
Rain Events

The response of terrestrial ecosystems to climate perturbations typically persist longer than the timescale of the forcing, a phenomenon that is broadly referred to as ecosystem legacy. Understanding the strength of legacy is critical for predicting ecosystem sensitivity to climate extremes and the extent to which persistent changes in land surface-atmosphere exchange might feedback onto the climate, for example, extending drought. The cause of ecosystem legacy has been tied to numerous factors such as changes in leaf area index, however, few studies have tested how changes in root profiles in response to stress might alter an ecosystem's recovery time. We utilize an Earth System Model that includes a dynamic root module where vegetation can forage for water and nutrients by altering their root profiles. As expected, the simulations show that in response to water stress events most ecosystems deepen their root profiles. In semi-arid ecosystems, this response expedites recovery (i.e. less legacy) relative to simulations without dynamics roots because access to deeper water pools after the initial event remains favorable. In wetter ecosystems, the development of deeper root profiles slows down the recovery timescale (i.e. more legacy) because the deeper root profile reduces access to nutrients. The recovery of hyperarid systems is also delayed presumably to the loss of shallow roots and ability to access water from smaller rain events. The results show that the response of root profiles to external forcing is a critical component of global patterns of legacy that is not typically represented in Earth System Models.

scholarly journals Generation of High Resolution Vegetation Productivity from a Downscaling Method

2018 ◽  
Vol 10 (11) ◽  
pp. 1748 ◽  
Author(s):  
Tao Yu ◽  
Rui Sun ◽  
Zhiqiang Xiao ◽  
Qiang Zhang ◽  
Juanmin Wang ◽  
...  
Keyword(s):  
High Resolution ◽  
Primary Production ◽  
Land Surface ◽  
Net Primary Production ◽  
Gross Primary Production ◽  
Terrestrial Ecosystems ◽  
Vegetation Productivity ◽  
Area Index ◽  
Multi Scale ◽  
Downscaling Method

Accurately estimating vegetation productivity is important in the research of terrestrial ecosystems, carbon cycles and climate change. Although several gross primary production (GPP) and net primary production (NPP) products have been generated and many algorithms developed, advances are still needed to exploit multi-scale data streams for producing GPP and NPP with higher spatial and temporal resolution. In this paper, a method to generate high spatial resolution (30 m) GPP and NPP products was developed based on multi-scale remote sensing data and a downscaling method. First, high resolution fraction photosynthetically active radiation (FPAR) and leaf area index (LAI) were obtained by using a regression tree approach and the spatial and temporal adaptive reflectance fusion model (STARFM). Second, the GPP and NPP were estimated from a multi-source data synergized quantitative algorithm. Finally, the vegetation productivity estimates were validated with the ground-based field data, and were compared with MODerate Resolution Imaging Spectroradiometer (MODIS) and estimated Global LAnd Surface Satellite (GLASS) products. Results of this paper indicated that downscaling methods have great potential in generating high resolution GPP and NPP.

scholarly journals Comparison of different sequential assimilation algorithms for satellite-derived leaf area index using the Data Assimilation Research Testbed (version Lanai)

2019 ◽  
Vol 12 (7) ◽  
pp. 3119-3133 ◽  
Author(s):  
Xiao-Lu Ling ◽  
Cong-Bin Fu ◽  
Zong-Liang Yang ◽  
Wei-Dong Guo
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Land Surface ◽  
Terrestrial Ecosystems ◽  
Time Step ◽  
Area Index ◽  
Community Land Model ◽  
Better Than

Abstract. The leaf area index (LAI) is a crucial parameter for understanding the exchanges of mass and energy between terrestrial ecosystems and the atmosphere. In this study, the Data Assimilation Research Testbed (DART) has been successfully coupled to the Community Land Model with explicit carbon and nitrogen components (CLM4CN) by assimilating Global Land Surface Satellite (GLASS) LAI data. Within this framework, four sequential assimilation algorithms, including the kernel filter (KF), the ensemble Kalman filter (EnKF), the ensemble adjust Kalman filter (EAKF), and the particle filter (PF), are thoroughly analyzed and compared. The results show that assimilating GLASS LAI into the CLM4CN is an effective method for improving model performance. In detail, the assimilation accuracies of the EnKF and EAKF algorithms are better than those of the KF and PF algorithm. From the perspective of the average and RMSD, the PF algorithm performs worse than the EAKF and EnKF algorithms because of the gradually reduced acceptance of observations with assimilation steps. In other words, the contribution of the observations to the posterior probability during the assimilation process is reduced. The EAKF algorithm is the best method because the matrix is adjusted at each time step during the assimilation procedure. If all the observations are accepted, the analyzed LAI seem to be better than that when some observations are rejected, especially in low-latitude regions.

scholarly journals A Functional Response Metric for the Temperature Sensitivity of Tropical Ecosystems

2018 ◽  
Vol 22 (7) ◽  
pp. 1-20 ◽  
Author(s):  
Gretchen Keppel-Aleks ◽  
Samantha J. Basile ◽  
Forrest M. Hoffman
Keyword(s):  
Growth Rate ◽  
Time Scales ◽  
Northern Hemisphere ◽  
Temperature Sensitivity ◽  
Land Surface ◽  
Model Development ◽  
Terrestrial Ecosystems ◽  
Carbon Fluxes ◽  
Hemisphere Winter

Abstract Earth system models (ESMs) simulate a large spread in carbon cycle feedbacks to climate change, particularly in their prediction of cumulative changes in terrestrial carbon storage. Evaluating the performance of ESMs against observations and assessing the likelihood of long-term climate predictions are crucial for model development. Here, we assessed the use of atmospheric growth rate variations to evaluate the sensitivity of tropical ecosystem carbon fluxes to interannual temperature variations. We found that the temperature sensitivity of the observed growth rate depended on the time scales over which atmospheric observations were averaged. The temperature sensitivity of the growth rate during Northern Hemisphere winter is most directly related to the tropical carbon flux sensitivity since winter variations in Northern Hemisphere carbon fluxes are relatively small. This metric can be used to test the fidelity of interactions between the physical climate system and terrestrial ecosystems within ESMs, which is especially important since the short-term relationship between ecosystem fluxes and temperature stress may be related to the long-term feedbacks between ecosystems and climate. If the interannual temperature sensitivity is used to constrain long-term temperature responses, the inferred sensitivity may be biased by 20%, unless the seasonality of the relationship between the observed growth rate and tropical fluxes is taken into account. These results suggest that atmospheric data can be used directly to evaluate regional land fluxes from ESMs, but underscore that the interaction between the time scales for land surface processes and those for atmospheric processes must be considered.

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