Land use and land cover change (LULCC), including land management, has the capacity to alter the climate by disrupting land-atmosphere fluxes of carbon, water and energy. Thus, there is a particular interest in understanding the role of LULCC as it relates to climate mitigation and adaptation strategies. Much attention has been devoted to the biogeochemical impacts of LULCC, yet there is an increasing awareness that the biogeophysical mechanisms (e.g. changes in surface properties such as albedo, roughness and evapotranspiration) should also be considered in climate change assessments of LULCC impacts on weather and climate. However, characterizing biogeophysical land-climate interactions remains challenging due to their complexity. If a cooling or a warming signal emerges depends on which of the biogeophysical processes dominates and on the size and pattern of the LULCC perturbation. Recent advances exploiting Earth system modelling and Earth observation tools are opening new possibilities to better describe LULCC and its effects at multiple temporal and spatial scales. This session invites studies that improve our general understanding of climate perturbations connected to LULCC from both biogeophysical and biogeochemical standpoints, and particularly those focusing on their intersection. This includes studies focusing on LULCC that can inform land-based climate mitigation and adaptation policies. Both observation-based and model-based analyses at local to global scales are welcome.
vPICO presentations: Thu, 29 Apr
Forests are considered a major player in climate change mitigation since they influence local and global climate through biogeochemical and biogeophysical feedbacks. However, they are themselves vulnerable to future environmental changes. Thus, forest management needs to focus on both mitigation and adaptation. The special challenge is that decisions on management strategies must be taken today while still a broad range of emission pathways is possible, and a good decision regarding one assumed pathway might turn out to be a bad decision when a different one materializes.
With our study we try to aid this decision-making process by finding management portfolios that provide relevant ecosystem functions such as local and global climate regulation, water availability, flood protection, and timber production for a wide range of future climate scenarios. To simulate according ecosystem processes and functions, we run the dynamic vegetation model LPJ-GUESS for the most relevant forest types across Europe for four different RCPs and five different management options. We analyze our simulation outputs using robust optimization techniques to determine optimal forest management portfolios for each 0.5° grid cell in Europe that ensure a balanced provision of all considered ecosystem functions in the future under any of the four RCPs.
Generally, our simulations and optimizations show that diversified management portfolios are most suitable to provide the set of considered ecosystem functions in all climate scenarios everywhere in Europe. While the portfolios show different compositions in different regions, they are quite similar in adjacent grid cells. The suggested future forest composition in Europe tends to be fairly close to present day values except for Northern Europe where a much higher proportion of deciduous types is proposed.
Management as high forest (trees emerging from seeds) remains the most important form of management. The proposed share of coppice management is much higher in Central and Northern Europe (~20%) than in Southern Europe, where its disadvantages (e.g., high water consumption and its non-suitability to provide long-lived wood products) are more pronounced.
A succession of ~30% of managed forest to natural forest is proposed by the optimization as it provides highest carbon storage and surface roughness values. However, this infeasibly high share is reduced if the provision of wood harvest is valued higher in the optimization compared to the other ecosystem functions.
Current public focus on forests lies often on their potential for carbon sequestration, but future forest management must also address the other services that they provide. This work gives insights on how this may be done.
How to cite: Gregor, K., Knoke, T., Krause, A., Lindeskog, M., and Rammig, A.: European Forest Management Portfolios Optimized for Uncertain Future Climate, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1654, https://doi.org/10.5194/egusphere-egu21-1654, 2021.
Land cover and land management (LCLM) changes have been highlighted for their critical role in low-end warming scenarios, both in terms of global mitigation and local adaptation. Yet the overall potential of LCLM options and their combination is still poorly understood. Here we model the climatic effects of four LCLM options using three state-of-the-art Earth system models, including the Community Earth System Model (CESM), the Max Planck Institute Earth System Model (MPI-ESM) and the European Consortium Earth System Model (EC-EARTH). The considered LCLM options represent idealized conditions:(i) a fully afforested world, (ii) a fully deforested world, (ii) a fully afforested world with extensive wood harvesting, and (iv) a fully deforested world with extensive irrigation. In these idealized sensitivity experiments, ran under present-day climate conditions, the effects of the different LCLM strategies represent an upper bound of the potential for global mitigation and local adaptation. To disentangle the local and non-local effects from the LCLM changes, a checkerboard perturbation, as proposed by Winckler et al. (2017) is applied.
Our first results show that deforestation leads to a pronounced warming in 2m air temperature in CESM over most regions, being most pronounced in the tropics (up to 4°C). In contrast, in the boreal regions of North America and Asia, deforestation causes a ~1°C cooling in 2m air temperature. In CESM, the local effect seems to dominate the temperature response from deforestation, while the resulting non-local effect overall has a smaller magnitude. This contrasts to the effect from afforestation, of which the non-local component dominates the 2m air temperature signal. Afforestation indeed shows a strong local cooling in the tropics and a slight local warming in the temperate and boreal regions, yet, the local cooling is regionally offset by a global, non-local warming of up to 2 °C. In a next step, we will extend this analysis to the ensemble of Earth system models and increase our process-based understanding of these results and their implications on hot extremes as well as the effects on other temperature metrics (surface temperature and temperature of the lowest level of atmospheric column). Finally, we will perform a subgrid-scale comparison of the effects of LCLM on temperature.
Winckler, J., Reick, C.H., Pongratz, J., 2017. Robust identification of local biogeophysical effects of land-cover change in a global climate model, American Meteorological society, 30(2), DOI: 10.1175/JCLI-D-16-0067.1
How to cite: De Hertog, S., Vanderkelen, I., Havermann, F., Guo, S., Pongratz, J., Manola, I., Coumou, D., Davin, E., Seneviratne, S., Lejeune, Q., Menke, I., Schleussner, C.-F., and Thiery, W.: Biogeophysical effects of idealised land cover and land management changes on the climate, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2818, https://doi.org/10.5194/egusphere-egu21-2818, 2021.
Land use and land cover change (LULCC) is one of the most important forcings affecting climate in the past century. This study evaluates the global biogeophysical LULCC impacts in 1950–2015 by employing an annually updated LULCC map in a coupled land–atmosphere–ocean model. The difference between LULCC and control experiments shows an overall land surface temperature (LST) increase by 0.48 K in the LULCC regions and a widespread LST decrease by 0.18 K outside the LULCC regions. A decomposed temperature metric (DTM) is applied to quantify the relative contribution of surface processes to temperature changes. Furthermore, while precipitation in the LULCC areas is reduced in agreement with declined evaporation, LULCC causes a southward displacement of the intertropical convergence zone (ITCZ) with a narrowing by 0.5°, leading to a tripole anomalous precipitation pattern over the warm pool. The DTM shows that the temperature response in LULCC regions results from the competing effect between increased albedo (cooling) and reduced evaporation (warming). The reduced evaporation indicates less atmospheric latent heat release in convective processes and thus a drier and cooler troposphere, resulting in a reduction in surface cooling outside the LULCC regions. The southward shift of the ITCZ implies a northward cross-equatorial energy transport anomaly in response to reduced latent/sensible heat of the atmosphere in the Northern Hemisphere, where LULCC is more intensive. Tropospheric cooling results in the equatorward shift of the upper-tropospheric westerly jet in both hemispheres, which, in turn, leads to an equatorward narrowing of the Hadley circulation and ITCZ.
How to cite: Huang, H., Xue, Y., Chilukoti, N., Liu, Y., Chen, G., and Diallo, I.: Assessing global biogeophysical effects of reconstructed land use and land cover change on climate since 1950 using a coupled land–atmosphere–ocean model, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3552, https://doi.org/10.5194/egusphere-egu21-3552, 2021.
The role of Land Cover and Land Management (LCLM) changes in shaping the climate has garnered increasing interest, particularly in light of its potential for climate adaptation and mitigation. Earth System Models (ESMs), however, have hitherto handled LCLM-climate interactions as a unidirectional process, lacking explicit treatment of LCLM-Climate feedbacks. These feedbacks nevertheless are linked to extreme climate events such as heat waves and drought, which in turn carry economic costs through worker productivity, crop yields and food prices. It is thus essential to integrate LCLM processes and their feedbacks into a ESMs, in order to build consistent storylines for future development pathways that take into account their potential for adaptation and mitigation. Emulators represent a computationally cheap but effective way of approximating ESM with an added advantage of agility in scenario exploration. Here we outline an emulator approach to represent LCLM-Climate feedbacks based on a framework developed by Beusch et al. (2020). The emulator provides monthly, spatially explicit data from yearly global mean temperature and uses Generalised Additive Models (GAMs) to represent LCLM-Climate feedbacks. The emulator is to be used in the LAnd MAnagement for CLImate Mitigation and Adaptation (LAMACLIMA) project, and is trained on dedicated ESM simulations that isolate the effects of key land management practices focussed on by LAMACLIMA: irrigation, de/reforestation and wood. Key variables produced by the emulator include temperature, Wet Bulb Globe Temperature and labour productivity.
Beusch, L., Gudmundsson, L., & Seneviratne, S. I. (2020). Emulating Earth System Model temperatures: from global mean temperature trajectories to grid-point level realizations on land. Earth System Dynamics, 11(1), 139–159. https://doi.org/10.5194/esd-11-139-2020
How to cite: Lejeune, Q., Nath, S., Schleussner, C., Schwaab, J., and Seneviratne, S.: Integrating Land Cover and Land Management feedbacks into climate models: an emulator approach, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5789, https://doi.org/10.5194/egusphere-egu21-5789, 2021.
It is widely accepted in the scientific, business and policy communities that meeting the Paris Agreement targets will require a large-scale deployment of negative emission technologies and practices. As a result, nature-based climate solutions, including carbon sequestration (Cseq) in soils and forests, have received much attention in the literature recently. Several national and global assessments have identified considerable potential for terrestrial Cseq, while other studies have raised doubts regarding its practical limits in the face of the likely future pressures from climate change and land use change. In general, the existing Cseq assessments lack sensitivity to climate change, perspective on local land use and nutrient limitations. Accounting for these factors requires process-based modelling, and is feasible only at national to regional scales at present, underpinned by a wide body of local evidence. Here, we apply an integrated terrestrial C-N-P cycle model (N14CP) with representative ranges of high-resolution climate and land use scenarios to estimate Cseq potential in temperate regions, using the UK as a national-scale example. Meeting realistic UK targets for grassland restoration and forestation over the next 30 years is estimated to sequester an additional 120 TgC by 2100 (similar to current annual UK greenhouse gas emissions), conditional on climate change of <2°C. Conversely, UK arable expansion would reduce Cseq by a similar magnitude, while alternative arable management practices such as extensive rotations with grass leys would have a comparatively small effect on country-wide Cseq outcomes. Most importantly, the simulations suggest that warmer climates will cause net reductions in Cseq as soil carbon losses exceed gains from increased plant productivity. Our analysis concludes that concerted land use change can make a moderate contribution to Cseq, but this is dependent on us cutting emissions from fossil fuels, soil degradation and deforestation in line with a <2°C pathway.
How to cite: Yumashev, D., Janes-Bassett, V., Redhead, J., Rowe, E., and Davies, J.: Carbon storage in soils and plant biomass under future climate and land use pressures, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6002, https://doi.org/10.5194/egusphere-egu21-6002, 2021.
The deforestation rate in the Maritime Continent (MC) has been accelerating during the past several decades. Understanding the changes in local hydro-climatological cycles as deforestation takes place is essential because the MC is suffering from frequent and extreme droughts and fires, which often occur during the dry season and are more severe during El Niños. Therefore, this study explores how deforestation affects the hydrological cycle and precipitation in the MC during El Niños, focusing on the boreal autumn season and using the coupled atmosphere-land model simulations. It is found that the precipitation over the MC increases in the deforestation experiments, and the precipitation responses can be magnified during El Niño events. A strong subsidence anomaly associated with El Niño does not prevent enhanced convection associated with local deforestation. Instead, the subsidence reduces the cloud cover in the MC region during El Niño, which increases the incoming solar radiation and increases surface temperatures. Under a warmer environment induced by El Niño, the nonlinear biogeophysical feedbacks associated with deforestation also play a critical role in more substantial land surface warming. A warmer land surface induces a more unstable atmospheric environment associated with a tendency toward enhanced local convection and lateral moisture convergence. This study highlights how the different mean climate states may modulate the impact of local land-use changes on hydroclimatological cycles in the Maritime Continent, and sheds light on the state of our knowledge of interactions between the local land surface and remote large-scale atmospheric circulations.
How to cite: lee, T. and lo, M.: The Role of El Niño in Modulating the Effects of Deforestation in the Maritime Continent, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7085, https://doi.org/10.5194/egusphere-egu21-7085, 2021.
Forest cover change can cause strong local biophysical feedbacks on climate. Satellite observations of land surface temperature (T) and land cover distribution or forest cover change have been widely used to examine the effects of afforestation/deforestation on local surface temperature change (ΔT). However, different approaches were used by previous analyses to quantifying ΔT, and it remains unclear whether results of ΔT by these approaches are comparable. We identified three influential approaches to quantifying ΔT used by previous studies, namely the actual ΔT resulting from actual changes in forest coverage over time and accounting for changes in background climate (ΔTa proposed by Alkama and Cescatti, 2016), potential ΔT by hypothesizing potential shifts between non-forest and forest at given native spatial resolutions of satellite products (ΔTp1 by Li et al., 2015), and potential ΔT, but using the singular value decomposition technique to derive ΔT by hypothesizing a shift between a 100% complete non-forest and 100% forest (ΔTp2 by Duveiller et al., 2019). China realized large-scale afforestation making it a suitable test case to compare satellite-based approaches for estimating ΔT following afforestation. We hypothesize that (1) ΔTa depends on the fraction of ground area that’s been afforested (Faff). (2) The relative magnitude between different approaches should be: ΔTa < ΔTp1 < ΔTp2. (3) When ΔTa is extended to a hypothetical case that Faff reaches 100%, it should be comparable to ΔTp1 or ΔTp2. We used multiple satellite observation products to test these hypotheses. The results show that the magnitude of actual daytime surface cooling by afforestation (ΔTa) increases with Faff, and is significantly lower than ΔTp1 and ΔTp2. But no significant difference was found between ΔTp1 and ΔTp2. A linear regression model established between ΔTa and Faff extends the ΔTa, when Faff reaches 100%, to a comparable magnitude than ΔTp1 and ΔTp2. Our study thus highlights the importance to consider the actual surface cooling impact by afforestation projects in contrast to the potential effects, and provides a first study to reconcile different approaches to quantify the land surface temperature change due to afforestation.
How to cite: Wang, H., Yue, C., Luyssaert, S., Zhao, J., and Zhao, H.: Reconciling different approaches to quantifying surface cooling induced by afforestation in China using satellite observations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7715, https://doi.org/10.5194/egusphere-egu21-7715, 2021.
Mountains are some of the most inaccessible regions, where not many weather stations located due to the high altitudes. Thus, the amount of available mountain meteorological data is limited. One of the modern solutions to data insufficiency is modelling. However, it remains challenging to assess how well a model simulates local climate conditions.
The main goal of this study was to check the model accuracy by comparing its results to observed data, with a focus on the radiation budget.
The Community Land Model 4.5 (CLM4.5) provided by the University of Oslo was used. It is a one-dimensional model and the default land component in the Community Earth System Model 1.2. CLM4.5 simulates various biogeophysical and biogeochemical processes based on surface energy, water, and carbon balances [Oleson et al. 2013]. Here, the model was run from 1901 to 2014 in the offline mode, meaning it was getting input from a pre-existing dataset. Modelled fluxes from the radiation budget, such as incoming (Kin) and outgoing shortwave (Kout) radiation, incoming (Lin) and outgoing (Lout) longwave radiation, net all-wave (Q*), net shortwave (K*) and net longwave (L*) radiation, were used for compassion with observations.
A 2.5×0.2 km site on Mount Imingfjell (1191 m) in southern Norway was selected as the study object. Different microclimatic parameters, including radiation fluxes, were measured separately over lichens and shrubs for 44 days in the 2018-2019 summers [Aartsma et al. 2020]. These vegetation types were chosen to understand the differences between them and see the potential impact of “shrubification” on surface albedo. Since there was no time overlap between modelled and observed data, we had to make datasets more comparable. 44 days from field data were used to create composite datasets that represent three temperature regimes based on data from the nearest weather station: “cold”, “normal” and “warm”. Each observation was assigned to one of these temperature regimes. In CLM4.5, recently available years were analysed to find ones with average summer temperatures closest to the stated temperature regimes. Statistical analysis, such as a two-sample t-test, was performed to see if there were any significant differences between the datasets.
T-tests showed that modelled Kin, Lin and K* were always similar to measurements, except for Lin and K* in “cold” conditions. CLM4.5 Kout differed from observed ones in almost all regimes. Simulated L*, Q* and Lout varied between temperature conditions and vegetation types. Still, about 70% of the modelled fluxes closely resembled the shrub ones, while only around 50% resembled lichens. Modelled albedo was also closer to shrub albedo.
In conclusion, CLM4.5 most likely modelled credible values for radiation fluxes, but further research is needed for greater clarity.
1. Aartsma, P., Asplund, J., Odland, A., Reinhardt, S., & Renssen, H. (2020). Surface albedo of alpine lichen heaths and shrub vegetation. Arctic, Antarctic, and Alpine Research, 52(1), 312-322.
2. Oleson, K., Lawrence, D., Bonan, G., Drewniak, B., Huang, M., Koven, C., . . . Yang, Z.-L. (2013). Technical description of version 4.5 of the Community Land Model (CLM).
How to cite: Vasiakina, A., Renssen, H., and Aartsma, P.: Comparison of modelled radiation budgets with observations over lichens and shrubs at Mount Imingfjell, Norway, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8053, https://doi.org/10.5194/egusphere-egu21-8053, 2021.
Many studies have been carried out to quantify the trend of terrestrial ecosystem respiration (Re) in a warming world, but a conclusive answer has not yet been confirmed because the temperature sensitivity of Re was found inconsistent under different scales or regarding different types of respiratory flux. Aiming at clarifying the relationship between temperature and Re across different scales, we proposed a method to counteract the confounding effect and applied nine empirical models to a 1,387 site-years FLUXNET dataset. Regarding the temperature sensitivity of half-hourly Re records, we found a surprisingly consistent result that the sigmoid functions outcompeted other statistical models in almost all datasets (account for 82%), and on average, achieved a staggering R2 value of 0.92, indicating the positive correlation between Re and temperature on fine time scale (within one site-year dataset). Even though Re of all biomes followed sigmoid functions, the parameters of the S-curve varied strongly across sites. This explains why measured Q10 value (an index denote temperature sensitivity) largely depends on observation season and site. Furthermore, on the interannual variation of Re, we did not find any relationship between mean annual temperature (MAT) and mean annual Re within any site, which implies that the small year-to-year variation of the sigmoid pattern is large enough to counteract the warming effect on Re. This study thereby put forward a conceptual model to integrate the relationship between temperature and Re under different scales. It also provided evidences to support the argument that the relationship between MAT and mean annual Re (i.e., respiration under global warming) should not be inferred from studies on other temporal or spatial scales.
How to cite: Zhang, H., Zhang, Z., Cui, Z., Tao, F., Chen, Z., Chang, Y., Magliulo, V., Wohlfahrt, G., and Zhao, D.: Global consistency in response of terrestrial ecosystem respiration to temperature, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9690, https://doi.org/10.5194/egusphere-egu21-9690, 2021.
Land cover and land management (LCLM) changes are important sources and sinks for anthropogenic CO2 fluxes. Current earth system models (ESMs) are capable to simulate the globally most sensitive LCLM changes (strong effects or large spatial extent in the earth system) such as de- and afforestation, wood harvest and irrigation, however, a comprehensive analysis between these ESMs is still absent. The present study aims to quantify the biogeochemical effects of forest cover changes, wood harvesting and irrigation of croplands on the global carbon cycle.
Therefore, we conducted coupled atmosphere-ocean-land experiments of idealized global deforestation with and without cropland irrigation as well as global re-/afforestation with and without wood harvest over a 150-year period under present day solar and trace gas forcing. All experiments were simulated by three different ESMs (MPI-ESM, EC-EARTH and CESM) to quantify inter-model uncertainty and potentially uncover specific model biases. The analysis focuses on the transient response of land carbon fluxes and pools after an abrupt LCLM practice change, in order to track the emergence of signals that could potentially mitigate climate change. Additionally, we want to unravel model differences concerning the temporal dynamics of LCLM change effects. Since greenhouse gases (GHG) concentration is kept constant at present-day level, the climate changes here arise from the biogeophysical effects of LCLM changes. We use a checkerboard approach to separate local and non-local components of the climate changes as proposed by Winckler et al., 2017, i.e. we separate the changes in climate induced locally by the LCLM changes from those induced remotely by advection and changes in atmospheric circulation.
First results with the MPI-ESM show that immediate global deforestation starting from present-day land-use distribution causes a 824 GtC loss of the total land carbon pool throughout the simulation period of 150 years, about 46% of which stem from tropical regions (17°S–17°N). Land carbon stocks are not balanced until the end of the simulation, which indicates that the land will continue to emit CO2 to the atmosphere and a long-term commitment by deforestation for climate change. Non-local effects lead to a loss of 26 GtC from land, again with largest losses found for the tropical regions. Even though it is a small part compared to the total loss (local plus non-local effect), it reveals potentially substantial consequences that LCLM changes at large scale can have unintendedly on other regions, including remote pristine ones, through biogeophysical climate change.
How to cite: Guo, S., Pongratz, J., Havermann, F., De Hertog, S., Thiery, W., Manola, I., Coumou, D., Lejeune, Q., and Schleussner, C.-F.: Simulated biogeochemical effects of idealized land cover and land management changes, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9826, https://doi.org/10.5194/egusphere-egu21-9826, 2021.
Land-use change (LU) is a major regional climate forcing that affects carbon-water-energy fluxes and, therefore, near-surface air temperature. Although there are uncertainties in LU impacts in the historical climate, there is a growing consensus towards a cooling influence in the mid-latitudes. However, how a drier and warmer land surface condition in the future climate can change the LU impacts are not investigated well.
We use a comprehensive set of five coupled climate models from the CMIP6-LUMIP project to assess the changing influence of the LU change. We use two methodologies: (1) direct method – where LU impacts are estimated by subtracting the ‘no-LU’ climate experiment from the control experiment that includes LU, and (2) Kumar et al., 2013 (K13) method where LU impacts are estimated by comparing climate change impacts between LU and no-LU neighboring regions.
First, we compared the LU impacts in the historical climate and between the direct method and K13 methods using the multi-model analysis. In the North America LU change region, the direct method shows a cooling impact of (-0.14 ± 0.13°C). The K13 methods show a smaller cooling impact (-0.09 ± 0.08°C). In terms of energy balance, the direct method shows a reduction of net shortwave radiation (-0.82 ± 0.91 watts/m2) the K13 method shows a cleaner result of (-1.25 ± 0.60 watts/m2), as expected. We suspect that a more substantial influence of the LU change in the direct method is due to large-scale circulation driven response or due to the internal variability that has been canceled out in the K13 method.
Next, we extend the K13 method to assess the LU impacts in the future climate. Direct methods are not available for the future climate experiment in CMIP6-LUMIP datasets. We find that a cooling impact of LU change has become statistically insignificant in the future climate (-0.17 ± 0.19°C). A similar influence is also found in the reduction of the net shortwave radiation (-1.92 ± 3.34 watts/m2). We also found that climate change impacts on temperature are an order of magnitude greater than LU impact in the future climate. Hence, we hypothesize that higher warming has contributed to the larger uncertainty in LU impacts. We will also discuss LU impacts in Eurasia and Indian subcontinent.
Kumar, S., Dirmeyer, P. A., Merwade, V., DelSole, T., Adams, J. M., & Niyogi, D. (2013). Land use/cover change impacts in CMIP5 climate simulations: A new methodology and 21st century challenges. Journal of Geophysical Research: Atmospheres, 118(12), 6337-6353.
How to cite: Singh, A. and Kumar, S.: Increased uncertainty in Land-Use change impacts on temperature due to Global Warming in CMIP6-LUMIP experiments, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10313, https://doi.org/10.5194/egusphere-egu21-10313, 2021.
It has been widely recognized that land use/land cover changes have great potential to influence climate at different scales. However, their local and non-local impacts have not been well understood. First, previous studies are limited by the assumption that the local impacts of land use do not modify the atmospheric background states. Second, land-use impacts may vary if simulations are conducted at a different spatial scale. In this study, we investigate the local and non-local impacts of historical land use using the Community Earth System Model version 2, and explore the possible influence of model resolutions on the local and non-local impacts. The local and non-local impacts of land use are separated using atmospheric nudging, in which the horizontal winds in the upper atmosphere are forced to follow the ERA-Interim reanalysis, whereas the nudging strength is zero at the surface. The multi-resolution experiments suggest that the local impacts of land use are consistent at different spatial scales, but the non-local impacts are influenced by the model resolution. We will also discuss the local and non-local impacts of land use on climate extremes across scales. This study presents a new way to distinguish the local and non-local impacts and highlights the uncertainty in simulated land-use impact in climate studies.
How to cite: Chen, L.: Local and non-local climatic impacts of land use across scales, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10471, https://doi.org/10.5194/egusphere-egu21-10471, 2021.
The use of a dynamic vegetation model, CARAIB, to estimate carbon sequestration from land-use and land-cover change (LULCC) offers a new approach for spatial and temporal details of carbon sink and for terrestrial ecosystem productivity affected by LULCC. Using the remote sensing satellite imagery (Landsat) we explore the role of land use land cover change (LULCC) in modifying the terrestrial carbon sequestration. We have constructed our LULCC data over Wallonia, Belgium, and compared it with the ground-based statistical data. However, the results from the satellite base LULCC are overestimating the forest data due to the single isolated trees. We know forests play an important role in mitigating climate change by capturing and sequestering atmospheric carbon. Overall, the conversion of land and increase in urban land can impact the environment. Moreover, quantitative estimation of the temporal and spatial pattern of carbon storage with the change in land use land cover is critical to estimate. The objective of this study is to estimate the inter-annual variability in carbon sequestration with the change in land use land cover. Here, with the CARAIB dynamic vegetation model, we perform simulations using remote sensing satellite-based LULCC data to analyse the sensitivity of the carbon sequestration. We propose a new method of using satellite and machine learning-based observation to reconstruct historical LULCC. It will quantify the spatial and temporal variability of land-use change during the 1985-2020 periods over Wallonia, Belgium at high resolution. This study will give the space to analyse past information and hence calibrate the dynamic vegetation model to minimize uncertainty in the future projection (until 2070). Further, we will also analyse the change in other climate variables, such as CO2, temperature, etc. Overall, this study allows us to understand the effect of changing land-use patterns and to constrain the model with an improved input dataset which minimizes the uncertainty in model estimation.
How to cite: Verma, A., Francois, L., Jacquemin, I., Tölle, M., Zhang, H., and Lanssens, B.: Assessing the effects of climate and land use land cover changes on recent carbon storage in terrestrial ecosystem using model-satellite approach over Wallonia, Belgium, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11207, https://doi.org/10.5194/egusphere-egu21-11207, 2021.
Land use and land cover change (LULCC) has a significant role for the global carbon cycle. Despite big improvements in LULCC emission modelling, related uncertainties remain relatively high. Major uncertainties in quantifying LULCC emissions stem from uncertainties in underlying LULCC datasets. The novel, high-resolution (~1 km×1 km) LULCC dataset HIstoric Land Dynamics Assessment+ (HILDA+) reflects gross transitions derived from multiple remote sensing products and offers an alternative to existing land use change datasets, serving as forcing for process-based and bookkeeping models. By incorporating HILDA+ in the “bookkeeping of land use emissions” (BLUE) model, which is one of the three bookkeeping models used in the Global Carbon Budget 2020, we gain a different temporal and spatial perspective on LULCC estimates and related sources of uncertainty.
We compare our results to emission estimates based on LUH2, which is broadly used as LULCC forcing for process-based and bookkeeping models. First results of our analysis show overall lower LULCC emissions for the estimates based on HILDA+. For the time period 1990-2019, mean yearly emission estimates based on HILDA+ are 0.595 GtC yr−1 compared to 1.368 GtC yr−1 based on LUH2. Reasons are lower emissions from cropland expansion and less carbon uptake from vegetation regrowth after abandonment of managed land (i.e. a smaller carbon sink). Furthermore, fewer discontinuities in the BLUE runs with the HILDA+ forcing compared to the LUH2-based estimates suggests a better representation of land use dynamics and their effects. Overall, the simulations based on HILDA+ capture spatial heterogeneity to a greater degree and provide a more detailed picture of local sources and sinks, which is crucial for (1) a better representation of component fluxes (e.g. deforestation, degradation) and (2) effective mitigation and adaptation policies.
How to cite: Ganzenmüller, R., Bultan, S., Winkler, K., Fuchs, R., and Pongratz, J.: Updated land use and land cover change (LULCC) emission estimates based on new high-resolution LULCC forcing data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12112, https://doi.org/10.5194/egusphere-egu21-12112, 2021.
Land surface models are used to provide global estimates of soil organic carbon (SOC) changes after past and future land use change (LUC). To evaluate how well the models capture decadal scale changes in SOC after LUC, we provide the first consistent comparison of simulated time series of LUC by six land models all of which participated in the Coupled Model Intercomparison Project Phase 6 (CMIP6) with soil carbon chronosequences (SCC). For this comparison we use SOC measurements of adjacent plots at four high-quality data sites in temperate and tropical regions. We find that initial SOC stocks differ among models due to different approaches to represent SOC. Models generally meet the direction of SOC change after reforestation of cropland but the amplitude and rate of changes vary strongly among them. Further, models simulate SOC losses after deforestation for crop or grassland too slow due to the lack of crop harvest impacts in the models or an overestimation of the SOC recovery on grassland. The representation of management, especially nitrogen levels is important to capture drops in SOC after land abandonment for forest regrowth. Crop harvest and fire management are important to match SOC dynamics but more difficult to quantify as SCC hardly report on these events. Based on our findings, we identify strengths and propose potential improvements of the applied models in simulating SOC changes after LUC.
How to cite: Brovkin, V., Boysen, L., Wårlind, D., Peano, D., Lansø, A. S., Delire, C., Burke, E., Poeplau, C., and Don, A.: Evaluation of soil carbon dynamics after land use change in CMIP6 land models using chronosequences, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12561, https://doi.org/10.5194/egusphere-egu21-12561, 2021.
The aim of this study is to estimate the net carbon fluxes from agriculture-related land-use and land cover change (LULCC) activities, which are referred to as emissions from the land due to human activities. These include land use (LU, e.g., farmland for food and feed production, including management) and land cover changes (LCC, e.g., deforestation for and reforestation of agricultural land, and conversion of grasslands and pastureland to agriculture land or vice versa). Agriculture land-use practices could be a source of atmospheric CO2. However, the management of agricultural practices may reduce carbon emissions and increase soil carbon sequestration. Simultaneously, land-cover change activities clear existing ecosystems, their biomass and disturb the soil, generating carbon emissions. Previous earth system models usually have a simple or no representation of land agriculture practices, such as planting crops, fertilization, irrigation, harvesting grains for food and livestock-feed, recovering crop residue for feed and other usages, and grazing, livestock-feed, and manure cycle. This study uses a land surface model with spatially heterogeneous representations of such agricultural land use activities, in addition to land cover change, such as the change from forest to agricultural land. Our study shows the net agricultural land area increase of 0.11 million hectares/yr during 2007-2013, including 2.12 million hectares/yr of other land converted to agricultural land and 2.01 million hectares/yr of agricultural land converted to other lands. The results show that global net carbon flux due to agriculture-related LULCC is 2.26 Pg C/yr (net emission), consisting of 38% due to land-use activities and 62% due to land cover change. South America (22%), North America (19%), and South and Southeast Asia (13%) are the top contributing regions for net carbon flux induced by LULCC. South America has contributed the most flux from land cover change (18%), while North America has generated the most carbon flux due to land-use activities (12%) among all macro geopolitical regions. By quantifying the carbon fluxes induced by different agriculture activities this study provides a complete estimate of the yearly carbon cycle in the agriculture system at the spatial scale, which may improve the representations of agriculture land use activities in Earth System Models.
How to cite: Jain, A., Xu, X., and Shu, S.: Global Carbon Fluxes Induced by Agriculture-Related Land-Use and Land Cover Change Activities, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13361, https://doi.org/10.5194/egusphere-egu21-13361, 2021.
Continued scientific study has revealed that land use and land cover change play a key role in climate and that the application of irrigation is an important biogeophysical contributor to climate modification across spatial scales. The Great Plains Irrigation Experiment (GRAINEX) was conducted in the spring and summer of 2018 to investigate Land-Atmosphere interactions just prior to and through the growing season across adjacent, but distinctly unique, soil moisture regimes (contrasting irrigated and rainfed fields). GRAINEX was uniquely designed for the development and analysis of an extensive observational dataset for comprehensive process studies of Land-Atmosphere interactions, by focusing on irrigated and rainfed croplands in a ~100 x 100 km domain in southeastern Nebraska. Observation platforms included multiple NCAR EOL Integrated Surface Flux Systems and Integrated Sounding Systems, NCAR CSWR Doppler Radar on Wheels, 1200 radiosonde balloon launches from 5 sites, the NASA GREX airborne L-Band radiometer, and 75 University of Alabama-Huntsville Environmental Monitoring Economic Monitoring Sensor Hubs (EMESH mesonet stations). The presentation will provide an overview of the field campaign, the dataset collected, and investigate the contrast of L-A intractions across an irrigation gradient through observations and mesoscale/microscale modeling on timescales ranging from the diurnal to the seasonal. Attention will be given to how variations in the land surface state, as a function of irrigation fraction, impacts near-surface meteorology and atmospheric boundary layer evolution at local and regional scales.
How to cite: Rappin, E., Mahmood, R., Udaysankar, N., and Pielke Sr., R.: Observational and Modeling Analysis of Land-Atmosphere Interactions over Adjacent Irrigated and Rainfed Cropland During the GRAINEX Field Campaign., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13385, https://doi.org/10.5194/egusphere-egu21-13385, 2021.
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