scholarly journals High-resolution land-use land-cover change data for regional climate modelling applications over Europe – Part 2: Historical and future changes

2021 ◽  
Author(s):  
Peter Hoffmann ◽  
Vanessa Reinhart ◽  
Diana Rechid ◽  
Nathalie de Noblet-Ducoudré ◽  
Edouard L. Davin ◽  
...  
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Land Use Change ◽  
Land Cover ◽  
Land Cover Change ◽  
Environmental Changes ◽  
Regional Climate ◽  
Climate Modelling ◽  
Historical Changes ◽  
The Impact

Abstract. Anthropogenic land-use and land cover change (LULCC) is a major driver of environmental changes. The biophysical impacts of these changes on the regional climate in Europe are currently extensively investigated within the WCRP CORDEX Flagship Pilot Study (FPS) LUCAS – "Land Use and Climate Across Scales" using an ensemble of different Regional Climate Models (RCMs) coupled with diverse Land Surface Models (LSMs). In order to investigate the impact of realistic LULCC on past and future climates, high-resolution datasets with observed LULCC and projected future LULCC scenarios are required as input for the RCM-LSM simulations. To account for these needs, we generated the LUCAS LUC Version 1.0 at 0.1° resolution for Europe Hoffmann et al. (2021b,c). The plant functional type distribution for the year 2015 (i.e. LANDMATE PFT dataset) is derived from the European Space Agency Climate Change Initiative Land Cover (ESA-CCI LC) dataset. Details about the conversion method based on a cross-walking procedure and the evaluation of the LANDMATE PFT dataset are given in the companion paper by Reinhart et al. (submitted). Subsequently, we applied the land-use change information from the Land-Use Harmonization 2 (LUH2) dataset, provided at 0.25° resolution as input for CMIP6 experiments, to derive realistic LULC distribution at high spatial resolution and at annual timesteps from 1950 to 2100. In order to convert land use and land management change information from LUH2 into changes in the PFT distribution, we developed a Land Use Translator (LUT) specific to the needs of RCMs. The annual PFT maps for Europe for the period 1950 to 2015 are derived from the historical LUH2 dataset by applying the LUT backward from 2015 to 1950. Historical changes in the forest type changes are considered using an additional European forest species dataset. The historical changes in the PFT distribution of LUCAS LUC follow closely the land use changes given by LUH2 but differ in some regions compared to remotely-sensed PFT time series. From 2016 onward, annual PFT maps for future land use change scenarios based on LUH2 are derived for different Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) combinations used in the framework of the Coupled Modelling Intercomparison Project Phase 6 (CMIP6). The resulting LULCC maps can be applied as land use forcing to the next generation of RCM simulations for downscaling of CMIP6 results. The newly developed LUT is transferable to other CORDEX regions world-wide.

Generating long-term high-resolution land-use change datasets for regional climate modeling in CORDEX domains

2021 ◽  
Author(s):  
Peter Hoffmann ◽  
Diana Rechid ◽  
Vanessa Reinhart ◽  
Christina Asmus ◽  
Edouard L. Davin ◽  
...  
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Land Use Change ◽  
Land Cover ◽  
Climate Modeling ◽  
Regional Climate ◽  
Regional Climate Modeling ◽  
Local Scale ◽  
Modeling Studies

<p>Land-use and land cover (LULC) are continuously changing due to environmental changes and anthropogenic activities. Many observational and modeling studies show that LULC changes are important drivers altering land surface feedbacks and land-atmosphere exchange processes that have substantial impact on climate on the regional and local scale. Yet, most long-term regional climate modeling studies do not account for these changes. Therefore, within the WCRP CORDEX Flagship Pilot Study LUCAS (Land Use Change Across Scales) a new workflow was developed to generate high-resolution annual land cover change time series based on past reconstructions and future projections. First, the high-resolution global land cover dataset ESA-CCI LC (~300 m resolution) is aggregated and converted to a 0.1° resolution, fractional plant functional type (PFT) dataset. Second, the land use change information from the land-use harmonized dataset (LUH2), provided at 0.25° resolution as input for CMIP6 experiments, is translated into PFT changes employing a newly developed land use translator (LUT). The new LUT was first applied to the EURO-CORDEX domain. The resulting LULC maps for past and future - the LUCAS LUC dataset - can be applied as land use forcing to the next generation RCM simulations for downscaling CMIP6 by the EURO-CORDEX community and in the framework of FPS LUCAS. The dataset includes land cover and land management practices changes important for the regional and local scale such as urbanization and irrigation. The LUCAS LUC workflow is applied to further CORDEX domains, such as Australasia and North America. The resulting past and future land cover changes will be presented, and challenges regarding the application of the new workflow to different regions will be addressed. In addition, issues related to the implementation of the dataset into different RCMs will be discussed.</p>

scholarly journals Modelled land use and land cover change emissions – a spatio-temporal comparison of different approaches

2021 ◽  
Vol 12 (2) ◽  
pp. 635-670
Author(s):  
Wolfgang A. Obermeier ◽  
Julia E. M. S. Nabel ◽  
Tammas Loughran ◽  
Kerstin Hartung ◽  
Ana Bastos ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Environmental Conditions ◽  
Agricultural Land ◽  
Environmental Changes ◽  
Land Cover Changes ◽  
Environmental Forcing ◽  
The Impact ◽  
Global Carbon

Abstract. Quantifying the net carbon flux from land use and land cover changes (fLULCC) is critical for understanding the global carbon cycle and, hence, to support climate change mitigation. However, large-scale fLULCC is not directly measurable and has to be inferred from models instead, such as semi-empirical bookkeeping models and process-based dynamic global vegetation models (DGVMs). By definition, fLULCC estimates are not directly comparable between these two different model types. As an important example, DGVM-based fLULCC in the annual global carbon budgets is estimated under transient environmental forcing and includes the so-called loss of additional sink capacity (LASC). The LASC results from the impact of environmental changes on land carbon storage potential of managed land compared to potential vegetation and accumulates over time, which is not captured in bookkeeping models. The fLULCC from transient DGVM simulations, thus, strongly depends on the timing of land use and land cover changes mainly because LASC accumulation is cut off at the end of the simulated period. To estimate the LASC, the fLULCC from pre-industrial DGVM simulations, which is independent of changing environmental conditions, can be used. Additionally, DGVMs using constant present-day environmental forcing enable an approximation of bookkeeping estimates. Here, we analyse these three DGVM-derived fLULCC estimations (under transient, pre-industrial, and present-day forcing) for 12 models within 18 regions and quantify their differences as well as climate- and CO2-induced components and compare them to bookkeeping estimates. Averaged across the models, we find a global fLULCC (under transient conditions) of 2.0±0.6 PgC yr−1 for 2009–2018, of which ∼40 % are attributable to the LASC (0.8±0.3 PgC yr−1). From 1850 onward, the fLULCC accumulated to 189±56 PgC with 40±15 PgC from the LASC. Around 1960, the accumulating nature of the LASC causes global transient fLULCC estimates to exceed estimates under present-day conditions, despite generally increased carbon stocks in the latter. Regional hotspots of high cumulative and annual LASC values are found in the USA, China, Brazil, equatorial Africa, and Southeast Asia, mainly due to deforestation for cropland. Distinct negative LASC estimates in Europe (early reforestation) and from 2000 onward in the Ukraine (recultivation of post-Soviet abandoned agricultural land), indicate that fLULCC estimates in these regions are lower in transient DGVM compared to bookkeeping approaches. Our study unravels the strong dependence of fLULCC estimates on the time a certain land use and land cover change event happened to occur and on the chosen time period for the forcing of environmental conditions in the underlying simulations. We argue for an approach that provides an accounting of the fLULCC that is more robust against these choices, for example by estimating a mean DGVM ensemble fLULCC and LASC for a defined reference period and homogeneous environmental changes (CO2 only).

scholarly journals The impact of anthropogenic land use and land cover change on regional climate extremes

2017 ◽  
Vol 8 (1) ◽  
Author(s):  
Kirsten L. Findell ◽  
Alexis Berg ◽  
Pierre Gentine ◽  
John P. Krasting ◽  
Benjamin R. Lintner ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Regional Climate ◽  
Climate Extremes ◽  
The Impact ◽  
Anthropogenic Land Use

scholarly journals The Change of Land Cover and Biocapacity of CO2 Gas Emission Absorption in Gresik Urban Area

2019 ◽  
Vol 1 (3) ◽  
pp. 3-14
Author(s):  
Achmad Ghozali ◽  
Fery Irfan Nurrahman ◽  
Eko Budi Santoso
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Urban Area ◽  
Land Cover Change ◽  
Gas Emission ◽  
Gas Emissions ◽  
Co2 Gas ◽  
The Impact

Gresik urban area is dominated by industrial, housing, trade and services activities. The growth of activities contributes to the land use change from green open spaces into built-up areas. The impact of land use change influence the level of air pollution and CO2 gas emission in Gresik urban area. The previous study briefly shows that this urban area produces 50.37% of the total CO2 gas emissions. The production of CO2 gas emissions should be controlled to reduce the impact of climate change in urban areas such as increasing urban temperature, hydrological cycle anomaly, drought, land degradation and other social and environmental issues. The green open space can recycle the CO2 gas emissions and can increase the absorption capacity of the CO2 gas emissions (bio-capacity). The land cover change for built-up area potentially reduces the absorption of CO2 gas emissions in Gresik urban area. Therefore the identification of the land cover change on CO2 emission absorption becomes an objective of this study. The preliminary study can formulate the strategic steps in the development of Gresik urban area that supports urban greenery and adaptive effort to respond the climate change. The study is conducted in two steps. The first step is to analysis the land cover change based on the Landsat satellite imagery analysis. The second step is to measure the dynamic change of the region's ability(bio-capacity) to absorb CO2 emissions by using ecological footprint analysis. The results show that Gresik urban area has a high development of developed land to the North area, Manyar Sub District. The growth of the developed land is more converting the fishpond land. The green areas in this regiontend to be influenced by farming activities which also convert into fishpond land. Bio-capacity of CO2 gas emission absorption increases from 2003 of 3.548 gha to 5.656 gha but the comparison between bio-capacity of CO2 gas emission absorption and developed land shows the declining tendency in each year. In 2003, the comparison score is 1.59 gha/ha of developed land. In 2014, the score is declining into 1.48 gha/ha or developed land.

scholarly journals High-resolution land-use land-cover change data for regional climate modelling applications over Europe – Part 1: The plant functional type basemap for 2015

2021 ◽  
Author(s):  
Vanessa Reinhart ◽  
Peter Hoffmann ◽  
Diana Rechid ◽  
Jürgen Böhner ◽  
Benjamin Bechtel
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Land Cover ◽  
Plant Communities ◽  
Regional Climate ◽  
Climate Modelling ◽  
Climate Information ◽  
Climate Data ◽  
Lulc Change ◽  
European Continent

Abstract. The concept of plant functional types (PFTs) is shown to be beneficial in representing the complexity of plant characteristics in land use and climate change studies using regional climate models (RCMs). By representing land use and land cover (LULC) as functional traits, responses and effects of specific plant communities can be directly coupled to the lowest atmospheric layers. To meet the requirements of RCMs for realistic LULC distribution, we developed a PFT dataset forEurope (LANDMATE PFT Version 1.0 Reinhart et al., 2021b, ;). The dataset is based on the high-resolution ESA-CCI land cover dataset and is further improved through the the additional use of climate information. Within the LANDMATE PFT dataset, satellite-based LULC information and climate data are combined to achieve the best possible representation of the diverse plant communities and their functions in the respective regional ecosystems while keeping the dataset most flexible for application in RCMs. Each LULC class of ESA-CCI is translated into PFT or PFT fractions including climate information by using the Holdridge Life Zone concept. Through the consideration of regional climate data, the resulting PFT map for Europe is regionally customized. A thorough evaluation of the LANDMATE PFT dataset is done using a comprehensive ground truth database over the European Continent. A suitable evaluation method has been developed and applied to assess the quality of thenew PFT dataset. The assessment shows that the dominant LULC groups, cropland and woodland, are well represented within the dataset while uncertainties are found for some less represented LULC groups. The LANDMATE PFT dataset provides a realistic, high-resolution LULC distribution for implementation in RCMs and is used as basis for the LUCAS LUC dataset introduced in the companion paper by Hoffmann et al. (submitted) which is available for use as LULC change input for RCM experiment setups focused on investigating LULC change impact.

Impact of land use land cover change on East Asia

2020 ◽  
Author(s):  
Ui-Yong Byun ◽  
Eun-Chul Chang
Keyword(s):  
Land Use ◽  
Land Cover ◽  
East Asia ◽  
Land Cover Change ◽  
Land Surface ◽  
Temporal Change ◽  
Weather Prediction ◽  
Regional Climate ◽  
Land Use Land Cover ◽  
The Impact

<p>  Many socioeconomic changes have occurred in East Asia in recent decades. Due to the economic structural change and economic growth, a large population has been concentrated in the cities, resulting in rapid urban expansion. Besides, the surrounding agricultural land for food resources has also expanded, and deforestation has also been active at the same time. These land use/land cover change (LULCC) significantly alter the energy properties of the land surface. Although land surface characteristics that have vigorous variability over time, it is common in a numerical model to treat the information as a static condition. In a numerical weather prediction model aiming at short-term forecasting, the ground characteristics without temporal change are valid; however, in the numerical climate model integrated over several decades, consideration of such variability is essential.<br>   In this study, we examine the impact of LULCC using the GRIMs (Global/Regional Integrated Model system), which covered regional climate simulation. Temporal change LULC over East Asia, especially cropland and urban, is constructed based on Land Use Harmonization data. Through the comparison of sensitivity experiments considered the LULCC overtime or not, it is confirmed that land surface effect on regional climate change over East Asia. </p>

Progress in modeling the impact of land cover change on the global climate

2006 ◽  
Vol 30 (6) ◽  
pp. 737-749 ◽  
Author(s):  
Haydee Salmun ◽  
Andrea Molod
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Land Cover Change ◽  
General Circulation ◽  
Global Climate ◽  
New Technique ◽  
Anthropogenic Land Use Change ◽  
The Impact ◽  
Anthropogenic Land Use

The prediction of the impact of anthropogenic land use change on the climate system hinges on the ability to properly model the interaction between the heterogeneous land surface and the atmosphere in global climate models. This paper contains a review of techniques in general use for modeling this interaction in general circulation models (GCMs) that have been used to assess the impact of land use change on climate. The review includes a summary of GCM simulations of land cover change using these techniques, along with a description of the simulated physical mechanisms by which land cover change affects the climate. The vertical extent to which surface heterogeneities retain their individual character is an important consideration for the land-atmosphere coupling, and the description of a recently developed technique that improves this aspect of the coupling is presented. The differences in the simulated climate between this new technique and a technique in general use include the presence of a boundary layer feedback mechanism that is not present in simulations with the standard technique. We postulate that the new technique when implemented in a GCM has the potential to guide an improved understanding of the mechanisms by which anthropogenic land use change affects climate.

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