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At least 343 records · Page 19

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DOE OSTI2026

Prognostic simulations of mixed-phase clouds with model AC-1D v1.0: the impact of aerosol types and freezing parameterizations on ice crystal budgets

Mixed-phase clouds at high latitudes contribute to the uncertainty in predicting cloud feedbacks and climate sensitivity, mainly due to the complexity of microphysical processes that influence the partitioning between the supercooled liquid and ice phases, and hence, cloud radiative effects on regional scales. Particularly in Arctic mixed-phase clouds, the activation of ice-nucleating particles (INPs) from various aerosol populations remains a leading source of uncertainty. We developed an aerosol-cloud one-dimensional (AC-1D) model, which provides a novel framework to prognostically treat INP and ice crystal budgets while explicitly accounting for polydisperse and multicomponent aerosol that activate INPs following different freezing parameterizations. The AC-1D model is informed by large-eddy simulations to probe the impact of INP representation on predicted ice crystal number concentrations (N i ) and ice crystal budgets in mixed-phase Arctic stratus. We apply three immersion freezing (IMF) parameterizations, two time-independent (singular) and one time-dependent (classical nucleation theory), to predict the evolution of the INP reservoir and resulting ice crystal budget from polydisperse mineral dust, organic (humic-like substances), and sea spray aerosol particle size distributions. Our analysis focuses on how variations in aerosol number concentration and cloud system parameters such as cloud cooling rate, cloud-top entrainment rate, and ice crystal fall speed influence the INP reservoir and ice crystal budgets. Furthermore, this study investigates the competitive ice nucleation dynamics in mixed aerosol environments and provides a process-level quantification of the INP budget terms, which directly controls ice crystal budgets. For all studied case scenarios, the aerosol types and associated particle size distributions significantly impact INP and N i , and the choice between a time-dependent and a singular freezing description yields orders-of-magnitude differences in the predicted INP and N i over the 10 h simulation time, reflecting typical cloud lifetimes. Our results show that the influence of cloud cooling, INP entrainment, and sedimentation varies significantly depending on the chosen freezing parameterization. These findings underscore the critical need for robust IMF parameterizations and precise cloud system observations to enhance the accuracy of models in predicting mixed-phase cloud structure and evolution.

Arctic clouds↗

DOE OSTI2023

The Marginal Ice Zone as a dominant source region of atmospheric mercury during central Arctic summertime

Atmospheric gaseous elemental mercury (GEM) concentrations in the Arctic exhibit a clear summertime maximum, while the origin of this peak is still a matter of debate in the community. Based on summertime observations during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition and a modeling approach, we further investigate the sources of atmospheric Hg in the central Arctic. Simulations with a generalized additive model (GAM) show that long-range transport of anthropogenic and terrestrial Hg from lower latitudes is a minor contribution (~2%), and more than 50% of the explained GEM variability is caused by oceanic evasion. A potential source contribution function (PSCF) analysis further shows that oceanic evasion is not significant throughout the ice-covered central Arctic Ocean but mainly occurs in the Marginal Ice Zone (MIZ) due to the specific environmental conditions in that region. Our results suggest that this regional process could be the leading contributor to the observed summertime GEM maximum. In the context of rapid Arctic warming and the observed increase in width of the MIZ, oceanic Hg evasion may become more significant and strengthen the role of the central Arctic Ocean as a summertime source of atmospheric Hg.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Scoping Study of Integrated Geothermal CO 2 Heat Pump and Water Well System in Cold Climate Region

This study evaluates the feasibility of using ground-source heat pumps (GSHPs) integrated with water wells for residential heating demands in cold regions of the United States. Four different heat pump systems were evaluated and compared: a CO 2 air-source heat pump (ASHP), a R-410A ASHP, a CO 2 GSHP integrated with well water, and a R-410A GSHP integrated with well water. Simulations were conducted at both equipment and building integration levels, followed by a nationwide analysis across 10 selected cities. Results indicate that integrating GSHP technology with existing water wells (e.g., artesian, bedrock, drilled, and collector wells) is a feasible heating solution because of their high flow rates, good water quality, stable temperatures, and low environmental impact. Although R-410A systems demonstrate higher efficiency, CO 2 systems are more suitable for heating from contamination-free and energy security perspective. The CO 2 GSHPs maintain better performance in colder climates compared with that of ASHPs, providing higher coefficient of performance and environmental benefits because CO 2 refrigerant leakage would not contaminate well water. A national analysis confirms that CO 2 GSHPs outperform furnaces, especially in cold climates, making them a promising solution for residential heating.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

Climatic factors and human population changes in Eurasia between the Last Glacial Maximum and the early Holocene

Archaeological records document a significant expansion of populations from the Last Glacial Maximum (LGM, ~23–19 ka) to the early Holocene (EH, ~9 ka) in Eurasia, which is often attributed to the influence of orbital-scale climate changes. Yet, information remains limited concerning the climatic factor(s) which were responsible for conditioning demographic patterns. Here, in this work, we present results from an improved Minimalist Terrestrial Resource Model (MTRM), forced by a transient climate simulation from the LGM to the EH. Simulated potential hunter-gatherer population densities and spatial distributions across Eurasia are supported by observed archaeological sites in Europe and China. In the low latitudes, potential population size change was predominantly controlled by precipitation and its strong influence on plant and animal resources. In the middle-high latitudes, temperature was the dominant driver in influencing potential population size change and animal resource availability. Different regional responses of potential populations to climate change across Eurasia - owing to variations in available food resources between the LGM and EH - provide a better understanding of human dispersal during the Late Pleistocene.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Ground Heat Flux Reconstruction Using Bayesian Uncertainty Quantification Machinery and Surrogate Modeling

Ground heat flux (G 0 ) is a key component of the land-surface energy balance of high-latitude regions. Despite its crucial role in controlling permafrost degradation due to global warming, G 0 is sparsely measured and not well represented in the outputs of global scale model simulation. In this study, an analytical heat transfer model is tested to reconstruct G 0 across seasons using soil temperature series from field measurements, Global Climate Model, and climate reanalysis outputs. The probability density functions of ground heat flux and of model parameters are inferred using available G 0 data (measured or modeled) for snow-free period as a reference. When observed G 0 is not available, a numerical model is applied using estimates of surface heat flux (dependent on parameters) as the top boundary condition. These estimates (and thus the corresponding parameters) are verified by comparing the distributions of simulated and measured soil temperature at several depths. Aided by state-of-the-art uncertainty quantification methods, the developed G 0 reconstruction approach provides novel means for assessing the probabilistic structure of the ground heat flux for regional permafrost change studies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

In Situ Machine Learning for Intelligent Data Capture on Exascale Platforms. Final Report

In many dynamic systems, interesting events occur locally in time and space. Examples of such systems include ignition events in combustion simulations, material fractures in mechanics simulations, and extreme weather events in climate simulations. Due to memory constraints and data I/O costs, current simulation workflows save data at regularly spaced time-steps, at a fixed rate determined before the start of the simulation. Often this mode of operation results in missed events of interest, necessitating a simulation restart from before an event occurred with more frequent data saves. This data saving workflow is grossly inefficient and is already a bottleneck in the computing process. We propose to develop machine learning algorithms that can detect when interesting dynamical events are occurring, triggering data saves. These machine learning algorithms will perform in situ anomaly detection to flag regions with different dynamical properties than those previously recorded. The adaptive data saves would be local in time and space to match the event of interest, thereby enabling a much more efficient workflow that will reduce data I/O costs and data storage memory requirements. The algorithms will be tested on two applications: auto-ignition simulations and climate simulations. A critical component of this project will be developing machine learning algorithms that can be deployed efficiently in situ on HPC platforms with out-of-the-box functionality. The development of in situ machine learning methods to detect anomalous events would enable a more efficient and effective workflow, in which all the relevant data are saved in a single simulation run, without re-starts or scientist intervention.

42 ENGINEERING↗

DOE OSTI2025

Joint Modeling of Wind Speed and Wind Direction Through a Conditional Approach

Atmospheric near surface wind speed and wind direction play an important role in many applications, ranging from air quality modeling, building design, wind turbine placement to climate change research. It is therefore crucial to accurately estimate the joint probability distribution of wind speed and direction. In this work, we develop a conditional approach to model these two variables, where the joint distribution is decomposed into the product of the marginal distribution of wind direction and the conditional distribution of wind speed given wind direction. To accommodate the circular nature of wind direction, a von Mises mixture model is used; the conditional wind speed distribution is modeled as a directional dependent Weibull distribution via a two-stage estimation procedure, consisting of a directional binned Weibull parameter estimation, followed by a harmonic regression to estimate the dependence of the Weibull parameters on wind direction. A Monte Carlo simulation study indicates that our method outperforms two other approaches in estimation efficiency: one that utilizes periodic spline quantile regression and another that generates data from the commonly used Abe-Ley distribution for cylindrical data. We illustrate our method by using the output from a regional climate model to investigate how the joint distribution of wind speed and direction may change under some future climate scenarios. Our method indicates significant changes in the variation of wind speed with respect to some directions.

17 WIND ENERGY↗

DOE OSTI2022

Diurnal cycle of precipitation over global monsoon systems in CMIP6 simulations

Accurate simulation of the diurnal cycle of precipitation over different climate regimes, including global monsoon systems, is an ongoing challenge for current state-of-the-art climate models. Here, in this study, the diurnal cycles of summertime precipitation from 21 CMIP6 historical simulations are evaluated with the NASA IMERG data via the diurnal harmonic amplitude and phase from the Fourier analysis in seven regional monsoon systems: Northern and Southern Africa monsoons, South Asia monsoon, East Asia monsoon, Australia monsoon, and North and South America monsoons. Particularly, we focus on four subregions including ocean, coastal ocean, land, and coastal land considering the different underlying physical processes. It is found that the CMIP6 historical simulations perform fairly well on reproducing the diurnal cycle of precipitation over ocean and coastal ocean, while the simulated diurnal harmonic phase and amplitude over land and coastal land show larger biases and model spread compared to biases over ocean and coastal ocean. The simulation of precipitation diurnal cycle is substantially improved in the multi-model mean of both CMIP6 historical and CMIP6 AMIP simulations compared with that of CMIP5 historical simulations. But the model bias of precipitation diurnal cycle is in general similar between CMIP6 AMIP and CMIP6 historical simulations, which suggests that the impact of the interactive ocean on the simulated diurnal precipitation averaged over a large domain is generally minor. The influence of model resolution on the diurnal cycle is shown in mixed directions across various subregions, and significant improvement from the low- to high-resolution models is only notable over coastal ocean.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Investigating the effects of cooperative transmission expansion planning on grid performance during heat waves with varying spatial scales

There is growing recognition of the advantages of interregional transmission capacity to decarbonize electricity grids. A less explored benefit is potential performance improvements during extreme weather events. This study examines the impacts of cooperative transmission expansion planning using an advanced modeling chain to simulate power grid operations of the United States Western Interconnection in 2019 and 2059 under different levels of collaboration between transmission planning regions. Two historical heat waves in 2019 with varying geographical coverage are replayed under future climate change in 2059 to assess the transmission cooperation benefits during grid stress. The results show that cooperative transmission planning yields the best outcomes in terms of reducing wholesale electricity prices and minimizing energy outages both for the whole interconnection and individual transmission planning regions. Compared to individual planning, cooperative planning reduces wholesale electricity prices by 64.3 % and interconnection-wide total costs (transmission investments + grid operations) by 34.6 % in 2059. It also helps decrease greenhouse gas emissions by increasing renewable energy utilization. However, the benefits of cooperation diminish during the widespread heat wave when all regions face extreme electricity demand due to higher space cooling needs. Despite this, cooperative transmission planning remains advantageous, particularly for California Independent System Operator with significant diurnal solar generation capacity. This study suggests that cooperation in transmission planning is crucial for reducing costs and increasing reliability both during normal periods and extreme weather events. It highlights the importance of optimizing the strategic investments to mitigate challenges posed by wider-scale extreme weather events of the future.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Winter precipitation changes in California under global warming: Contributions of CO2, uniform SST warming, and SST change patterns

Climate models project a wetting winter over California, distinct from the drying in all other Mediterranean climate regions under warming. Dynamic effect via an eastward extension of the westerly jet stream over the North Pacific is the root cause for the wetting California. Utilizing four sets of prescribed-SST (sea surface temperature) simulations, the relative effects of direct CO2 radiative forcing, uniform SST warming, and SST change pattern are investigated. The wetting winter is dominated by uniform SST warming mainly through its effect on the jet extension. As a fundamental response to the enhanced upper-tropospheric warming in the tropics, the jet extension in coupled simulations is well reproduced under uniform SST warming and robust among models. An El Niño-like SST warming pattern has a secondary contribution to the jet extension via atmospheric teleconnection, but with large inter-model spread. Relative to the SST forcing, the direct CO2 radiative effect is negligible.

Dong, Lu↗

DOE OSTI2023

Ship-based Observations and Climate Model Simulations of Cloud Phase over the Southern Ocean

The Southern Ocean (SO) clouds exert a significant influence on the Earth’s radiation budget. Here we analyzed ship-based remote sensing observations of SO clouds over a five-month long DOE ARM Measurements of Aerosols, Radiation and Clouds over the Southern Oceans (MARCUS) field campaign to better understand cloud phase variability. We developed a method to classify eight categories of hydrometeors (ice, liquid, mixed phase, rain, drizzle, snow, aerosols, and clear sky) based on measurements of lidar, radar and radiosondes. Cloud thermodynamic phases (liquid, ice and mixed phase) at coarser scales were further derived to compare with the DOE Energy Exascale Earth System Model version 1 (E3SMv1) simulation and the Earth Model Column Collaboratory (EMC 2 ) instrument simulator. For a scale-aware comparison with climate model simulations, we found that spatially averaging the raw remote sensing data (e.g., backscatter, reflectivity) results in increased cloud cover and cloud liquid, whereas, directly averaging cloud phase from higher to lower resolution maintains clear air regions and is thus recommended for in-cloud frequency comparisons. For cloud thermodynamic phases in stratiform clouds, the E3SM underestimates cloud ice and overestimates cloud liquid at temperatures between -40 and 0°C. When latitudes increase, both observations and simulations show a transition of dominant phase from liquid to ice for cloud tops as well as for the entire cloud columns, but the model underestimation of ice phase is more severe at higher latitudes. Such model bias is unlikely caused by spatial scale differences or lack of heterogeneity in cloud vertical structure in the simulation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Effect of dust on rainfall over the Red Sea coast based on WRF-Chem model simulations

Water is the single most important element of life. Rainfall plays an important role in the spatial and temporal distribution of this precious natural resource, and it has a direct impact on agricultural production, daily life activities, and human health. One of the important elements that govern rainfall formation and distribution is atmospheric aerosol, which also affects the Earth's radiation balance and climate. Therefore, understanding how dust compositions and distributions affect the regional rainfall pattern is crucial, particularly in regions with high atmospheric dust loads such as the Middle East. Although aerosol and rainfall research has garnered increasing attention as both an independent and interdisciplinary topic in the last few decades, the details of various direct and indirect pathways by which dust affects rainfall are not yet fully understood. Here, we explored the effects of dust on rainfall formation and distribution as well as the physical mechanisms that govern these phenomena, using high-resolution WRF-Chem simulations (~1.5 km × 1.5 km) configured with an advanced double-moment cloud microphysics scheme coupled with a sectional eight-bin aerosol scheme. Our model-simulated results were realistic, as evaluated from multiple perspectives including vertical profiles of aerosol concentrations, aerosol size distributions, vertical profiles of air temperature, diurnal wind cycles, and spatio-temporal rainfall patterns. Rainfall over the Red Sea coast is mainly caused by warm rain processes, which are typically confined within a height of ~6 km over the Sarawat mountains and exhibit a strong diurnal cycle that peaks in the evening at approximately 18:00 local time under the influence of sea breezes. Numerical experiments indicated that dust could both suppress or enhance rainfall. The effect of dust on rainfall was calculated as total, indirect, and direct effects, based on 10-year August-average daily-accumulated rainfall over the study domain covering the eastern Red Sea coast. For extreme rainfall events (domain-average daily-accumulated rainfall of ≥ 1.33 mm), the net effect of dust on rainfall was positive or enhancement (6.05 %), with the indirect effect (4.54 %) and direct effect (1.51 %) both causing rainfall increase. At a 5 % significance level, the total and indirect effects were statistically significant whereas the direct effect was not. For normal rainfall events (domain-average daily-accumulated rainfall < 1.33 mm), the indirect effect enhanced rainfall (4.76 %) whereas the direct effect suppressed rainfall (-5.78 %), resulting in a negative net suppressing effect (-1.02 %), all of which were statistically significant. We investigated the possible physical mechanisms of the effects and found that the rainfall suppression by dust direct effects was mainly caused by the scattering of solar radiation by dust. The surface cooling induced by dust weakens the sea breeze circulation, which decreases the associated landward moisture transport, ultimately suppressing rainfall. For extreme rainfall events, dust causes net rainfall enhancement through indirect effects as the high dust concentration facilitates raindrops to grow when the water vapor is sufficiently available. Our results have broader scientific and environmental implications. Specifically, although dust is considered a problem from an air quality perspective, our results highlight the important role of dust on sea breeze circulation and associated rainfall over the Red Sea coastal regions. Our results also have implications for cloud seeding and water resource management.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Simulating Marine Ecosystem Dynamics and Biogeochemical Cycling With Multiple Plankton Functional Types

Current representations of marine ecosystems in Earth System Models are greatly simplified, neglecting key interactions between dynamic food webs, biogeochemistry, and climate change. We use the Marine Biogeochemistry Library code base within the Community Earth System Model 2.2.2 to create an expanded ecosystem model with eight phytoplankton groups and four zooplankton size classes (MARBL-8P4Z). Incorporating more specific plankton types and size classes has the potential to capture a wider range of possible behaviors of the ecosystem, its complex interactions with biogeochemistry, and its feedback to climate change. It also permits stronger observational constraints, including in situ group-specific biomass and various observational estimates of plankton community composition. MARBL-8P4Z broadly captures observed global-scale patterns in biomass and community composition for both phytoplankton and zooplankton, with a good performance in simulating broad biogeochemistry fields. The model shows comparable spatial patterns and magnitudes to the observed picophytoplankton biomass (Prochlorococcus, Synechococcus, picoeukaryotes), and captures the seasonal cycle of mesozooplankton biomass. Picophytoplankton groups and microzooplankton dominate biomass and production in oligotrophic, subtropical regions, while nano-phytoplankton, diatoms and the larger zooplankton groups prevail at higher latitudes and within upwelling zones. The model simulates reasonable energy transfer efficiency through the food web, with tight linkages between the phytoplankton community composition, zooplankton grazing, and carbon export, with the potential to link to fisheries models. Thus, MARBL-8P4Z has the potential to account for key climate-driven ecological shifts in the plankton that will modify ocean biogeochemistry in the future.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Observed humidity trends in dry regions contradict climate models

Arid and semi-arid regions of the world are particularly vulnerable to greenhouse gas–driven hydroclimate change. Climate models are our primary tool for projecting the future hydroclimate that society in these regions must adapt to, but here, we present a concerning discrepancy between observed and model-based historical hydroclimate trends. Over the arid/semi-arid regions of the world, the predominant signal in all model simulations is an increase in atmospheric water vapor, on average, over the last four decades, in association with the increased water vapor–holding capacity of a warmer atmosphere. In observations, this increase in atmospheric water vapor has not happened, suggesting that the availability of moisture to satisfy the increased atmospheric demand is lower in reality than in models in arid/semi-arid regions. This discrepancy is most clear in locations that are arid/semi-arid year round, but it is also apparent in more humid regions during the most arid months of the year. Here, it indicates a major gap in our understanding and modeling capabilities which could have severe implications for hydroclimate projections, including fire hazard, moving forward.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Tropical Cirrus in Global Storm-Resolving Models: 1. Role of Deep Convection

Pervasive cirrus clouds in the upper troposphere and tropical tropopause layer (TTL) influence the climate by altering the top-of-atmosphere radiation balance and stratospheric water vapor budget. These cirrus are often associated with deep convection, which global climate models must parameterize and struggle to accurately simulate. By comparing high-resolution global storm-resolving models from the Dynamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) intercomparison that explicitly simulate deep convection to satellite observations, we assess how well these models simulate deep convection, convectively generated cirrus, and deep convective injection of water into the TTL over representative tropical land and ocean regions. The DYAMOND models simulate deep convective precipitation, organization, and cloud structure fairly well over land and ocean regions, but with clear intermodel differences. All models produce frequent overshooting convection whose strongest updrafts humidify the TTL and are its main source of frozen water. Intermodel differences in cloud properties and convective injection exceed differences between land and ocean regions in each model. We argue that, with further improvements, global storm-resolving models can better represent tropical cirrus and deep convection in present and future climates than coarser-resolution climate models. To realize this potential, they must use available observations to perfect their ice microphysics and dynamical flow solvers.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Does Regional Hydroclimate Change Scale Linearly With Global Warming?

Many aspects of climate change scale linearly with global warming. However, nonlinear changes are possible, especially in the context of hydroclimate, and under emissions scenarios with stabilized global temperature, as aspired to by current climate targets. In CMIP5 and 6, a progressively larger land area shows nonlinear changes as a function of global warming when considering precipitation, evaporation, and soil moisture, with the latter showing nonlinearity over ~50% of global land. Here, using ensemble simulations with the Community Earth System Model 1, in which individual forcing factors are held constant, we illustrate how nonadditive responses to anthropogenic greenhouse gases and industrial and fire-related aerosols can yield complex soil moisture changes in certain regions. This complexity contributes to uncertainty in regional soil moisture projections and suggests that the timing of, as well as model response uncertainty to, future aerosol reductions will have significant impacts on regional hydroclimate change as global temperatures stabilize.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Scoping Study of Integrated Geothermal CO 2 Heat Pump and Water Well System in Cold Climate Region (CRADA Final Report)

15 GEOTHERMAL ENERGY↗

DOE OSTI2021

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

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).

54 ENVIRONMENTAL SCIENCES↗