Global Irrigation Characteristics and Effects Simulated by Fully Coupled Land Surface, River, and Water Management Models in E3SM
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54 ENVIRONMENTAL SCIENCES↗
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The Energy Exascale Earth System Model Version 3: 2. Overview of the Coupled System
The Energy Exascale Earth System Model version 3 (E3SMv3) represents the latest advancement in Earth system modeling developed by the U.S. Department of Energy (DOE). Building upon previous versions, E3SMv3 introduces significant updates across its coupled components to enhance capability and improve fidelity. The atmosphere component incorporates advancements in chemistry, aerosol-cloud interactions, convection, and microphysics. The ocean features a new time-stepping scheme and a higher-resolution unstructured mesh with sub-ice-shelf cavities, while the sea ice model integrates advanced snow and ice physics for more realistic cryospheric simulations. The land model introduces prognostic vegetation dynamics and a new sub-grid topographic treatment of solar radiation. A new tri-grid configuration harmonizes the horizontal grids of the land and river components for improved process coupling. It is enabled by a new non-linear remapping between the atmosphere and land. E3SMv3 underwent extensive testing through a comprehensive simulation campaign, including pre-industrial control, idealized CO 2 experiments, and historical simulations spanning 1850–2024. The model demonstrates significant improvements in simulating the evolution of the historical surface temperature, particularly addressing the “pothole cooling” bias in earlier versions. Reduced aerosol-related forcing contributes to more realistic radiative forcing and better alignment with the observational record. Ocean heat content (OHC) and sea ice trends are also improved as a result.
54 ENVIRONMENTAL SCIENCES↗
Collaborative Research: Advancing Arctic Climate Projection Capability at Seasonal to Decadal Scales (Final Technical Report)
The Regional Arctic System Model (RASM) at process resolving configurations has been used to (i) advance understanding of physical processes and feedbacks involved in Arctic amplification and (ii) understand and potentially reduce uncertainty in prediction of arctic climate change at seasonal to decadal scales. RASM consists the atmosphere (Weather and Research Forecasting model, WRF), ocean (Parallel Ocean Program, POP), sea ice (CICE), land hydrology (Variable Infiltration Capacity model, VIC), river routing scheme (RVIC), marine biogeochemistry components and the coupling framework (CPL7). Its domain is pan-Arctic, with the atmosphere and land components configured on a 50-km or 25-km grid and four configurations of the ocean and sea ice components: 1/12°(~9.3km) or 1/48°(~2.4km) and 45 or 60 vertical layers. These RASM configurations have been motivated by the emerging exascale capability for high performance computing to improve model fidelity. The dynamical downscaling of reanalysis allows comparison of RASM results with observations in place and time to: (i) advance system level understanding of physical processes and coupling involved in an event, (ii) optimize model parameter space, (iii) diagnose and reduce model biases and (iv) produce realistic and consistent across all the components initial conditions for predictions and predictability studies, which are all unique capabilities not available in global Earth System Models (ESMs). An evaluation of RASM 1.0 (Cassano et al. 2017) revealed that it had a cold bias over the oceans and a warm bias over land areas due largely to cloud and radiation biases in the model, with too little cloud cover simulated over land and too much cloud cover simulated over sub-polar oceans. This study has motivated an upgrade to WRF version 3.7.1 in RASM and allowed for the inclusion of the radiative impact of convective clouds. A variety of atmospheric physics parameterizations were evaluated against observations (e.g. data from the Arctic Clouds in Summer Experiment (ACSE); Sedlar et al. 2020) to identify an optimal suite of WRF physics options in RASM. The RASM with the optimized WRF physics were used to study the impact of strong mesoscale winds over the ocean around the southern tip of Greenland (DuVivier and Cassano 2016) and their impact on oceanic convection (DuVivier et al. 2017a). Data from the PolarWinds field campaign were used to evaluate WRF boundary layer physics and resolution impacts on the simulation of a Greenland barrier wind event (DuVivier et al. 2017b). The RVIC streamflow routing model has been implemented in RASM to realistically represent high-resolution streamflow processes (Hamman et al. 2017) and to couple the land buoyancy fluxes to the ocean. The RASM-RVIC high-resolution data set of all coastal freshwater fluxes for the Arctic drainage basin and surrounding areas for 1979-2014 was published as a separate product (https://doi.org/10.5281/zenodo.293037). The fidelity of atmospheric momentum transfer to and the response of polar marine Ekman layer in RASM and Community Earth System Model (CESM) was investigated by Roberts et al. (2015). The increased frequency of oceanic flux exchange in CESM, following the RASM guidance, caused a considerable increase in the median inertial ice speed across the Southern Ocean and parts of the Arctic. A comprehensive evaluation of the RASM1.0 atmosphere-ocean-sea ice-land interface was completed by Brunke et al. (2018). RASM was also demonstrated for its capability to simulate extreme events in agreement with observations in space and time (Lee et al. submitted). In particular, the development of three open water events, known as polynyas, have been simulated north of Greenland in February of 2011, 2017 and 2018, in agreement with satellite observations for the past four decades. The optimized RASM sea ice results have been favorably evaluated against satellite observations and a subset of eleven CMIP6 models (Watts et al. submitted). In a complementary project, Jin et al. (2018) have shown that RASM with higher-resolution and new sea-ice processes contributed to lower model errors in sea-ice conditions, concentrations of nutrients and ice algae, in comparison to results from the coarse-resolution (1°) CESM. In two other complementary studies, RASM results were used (i) to explain areas of concentrated use by bowhead whales, the seasonal progression in the use, and the physical environment within those areas (Citta et al. 2015) and (ii) for a synthesis of fall bowhead whales distribution and migration in the Bering-Chukchi-Beaufort (BCB) Sea to investigate whale movements and feeding to the local ocean hydrography and currents (Citta et al. 2018). However, the multi-decadal output from the CESM Large Ensemble yielded unrealistic forcing. Instead, the shorter NCEP CFSv2 9-month forecasts were successfully tested and afforded an increased ensemble size (~30) to demonstrate gains of dynamical downscaling at sub-seasonal to intra-annual time scales. The improved model physics and coupling among RASM model components have yielded more realistic representation of the sea ice cover and consistent across all model components initial conditions. Consequently, RASM demonstrates significant gains compared to simulation of sea ice in the NCEP reanalysis. In addition, RASM 6-month ensemble forecasts yield very realistic sea ice distribution, which demonstrates both significant gains of dynamical downscaling and the continued impact of the initial conditions on forecasts out to 6 months (https://nps.edu/web/rasm/predictions). A follow up study using RASM for dynamical downscaling of the more realistic CESM initialized Decadal Prediction Large Ensemble output is currently ongoing as part of the DOE RGMA HiLAT-RASM project.
54 ENVIRONMENTAL SCIENCES↗
The 4DEnVar-based weakly coupled land data assimilation system for E3SM version 2
Abstract. A new weakly coupled land data assimilation (WCLDA) system based on the four-dimensional ensemble variational (4DEnVar) method is developed and applied to the fully coupled Energy Exascale Earth System Model version 2 (E3SMv2). The dimension-reduced projection four-dimensional variational (DRP-4DVar) method is employed to implement 4DVar using the ensemble technique instead of the adjoint technique. With an interest in providing initial conditions for decadal climate predictions, monthly mean anomalies of soil moisture and temperature from the Global Land Data Assimilation System (GLDAS) reanalysis from 1980 to 2016 are assimilated into the land component of E3SMv2 within the coupled modeling framework with a 1-month assimilation window. The coupled assimilation experiment is evaluated using multiple metrics, including the cost function, assimilation efficiency index, correlation, root-mean-square error (RMSE), and bias, and compared with a control simulation without land data assimilation. The WCLDA system yields improved simulation of soil moisture and temperature compared with the control simulation, with improvements found throughout the soil layers and in many regions of the global land. In terms of both soil moisture and temperature, the assimilation experiment outperforms the control simulation with reduced RMSE and higher temporal correlation in many regions, especially in South America, central Africa, Australia, and large parts of Eurasia. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought, highlighting the crucial role of land surface in drought lifecycle. The WCLDA system is intended to be a foundational resource for research to investigate land-derived climate predictability.
58 GEOSCIENCES↗
Uncertain Spatial Pattern of Future Land Use and Land Cover Change and Its Impacts on Terrestrial Carbon Cycle Over the Arctic–Boreal Region of North America
Land use and land cover change (LULCC) represents a key process of human-Earth system interaction and has profound impacts on terrestrial ecosystem carbon cycling. As a key input for ecosystem models, future gridded LULCC data is typically spatially downscaled from regional LULCC projections by integrated assessment models, such as the Global Change Analysis Model (GCAM). The uncertainty associated with the different spatial downscaling methods and its impacts on the subsequent model projections have been historically ignored and rarely examined. This study investigated this problem using two representative spatial downscaling methods and focused on their impacts on the carbon cycle over the Arctic-Boreal Vulnerability Experiment (ABoVE) domain, where extensive LULCC is expected. Specifically, we used the Future Land Use Simulation model (FLUS) and the Demeter model to generate 0.25° gridded LULCC data (i.e., LULCC FLUS and LULCC Demeter , respectively) with the same input of regional LULCC projections from GCAM, under both the low (i.e., SSP126) and high (i.e., SSP585) greenhouse gas emission scenarios. The two sets of downscaled LULCC were used to drive the Community Land Model version 5 and prognostically simulate the terrestrial carbon cycle dynamics over the 21st century. The results suggest large spatial-temporal differences between LULCC FLUS and LULCC Demeter , and the spatial distributions of the needleleaf evergreen boreal tree, broadleaf deciduous boreal tree, broadleaf deciduous boreal shrub, and C3 arctic grass are particularly different under both SSP126 and SSP585. Additionally, the spatiotemporal differences are larger under SSP126 than SSP585, due to more intensive LULCC under SSP126 than SSP585 from GCAM projection. The differences in LULCC further lead to large discrepancies in the spatial patterns of projected gross primary productivity, ecosystem respiration, and net ecosystem exchange, which represent more than 79% of the contributions of future LULCC in 2100. Additionally, the difference in carbon flux under SSP126 is generally larger than those under SSP585. This study highlights the importance of considering the uncertainties induced by the spatial downscaling process in future LULCC projections and carbon cycle simulations.
54 ENVIRONMENTAL SCIENCES↗
The Role of Interactive Soil Moisture in Land Drying Under Anthropogenic Warming
Abstract Relative humidity (RH) is projected to increase over ocean but decrease over land under anthropogenic warming. The land RH decrease was previously attributed to ocean influences on land changes. Here, we show that interactive soil moisture (SM) is necessary and may be sufficient for anthropogenic warming to reduce the land RH. The land RH decrease is absent in simulations with realistic land‐ocean geometry but fixed SM, and present in simulations with interactive SM but no oceans or changes in precipitation minus evaporation. The land RH decrease is coupled to the SM decline and the latter could be understood as a natural response of interactive SM to anthropogenic warming. Specifically, prior to adjustments in SM and RH, evaporation would increase by ∼6% K −1 following the Clausius–Clapeyron relation, outpacing the radiatively constrained ∼2% K −1 precipitation increase. This prior imbalance depletes SM and consequently reduces RH through the coupling between SM and RH.
54 ENVIRONMENTAL SCIENCES↗
Upscaling Methane Flux From Plot Level to Eddy Covariance Tower Domains in Five Alaskan Tundra Ecosystems
Spatial heterogeneity in methane (CH 4 ) flux requires a reliable upscaling approach to reach accurate regional CH 4 budgets in the Arctic tundra. In this study, we combined the CLM-Microbe model with three footprint algorithms to scale up CH 4 flux from a plot level to eddy covariance (EC) tower domains (200 m × 200 m) in the Alaska North Slope, for three sites in Utqiaġvik (US-Beo, US-Bes, and US-Brw), one in Atqasuk (US-Atq) and one in Ivotuk (US-Ivo), for a period of 2013–2015. Three footprint algorithms were the homogenous footprint (HF) that assumes even contribution of all grid cells, the gradient footprint (GF) that assumes gradually declining contribution from center grid cells to edges, and the dynamic footprint (DF) that considers the impacts of wind and heterogeneity of land surface. Simulated annual CH 4 flux was highly consistent with the EC measurements at US-Beo and US-Bes. In contrast, flux was overestimated at US-Brw, US-Atq, and US-Ivo due to the higher simulated CH 4 flux in early growing seasons. The simulated monthly CH 4 flux was consistent with EC measurements but with different accuracies among footprint algorithms. At US-Bes in September 2013, RMSE and NNSE were 0.002 μmol m −2 s −1 and 0.782 using the DF algorithm, but 0.007 μmol m −2 s −1 and 0.758 using HF and 0.007 μmol m −2 s −1 and 0.765 using GF, respectively. DF algorithm performed better than the HF and GF algorithms in capturing the temporal variation in daily CH 4 flux each month, while the model accuracy was similar among the three algorithms due to flat landscapes. Temporal variations in CH 4 flux during 2013–2015 were predominately explained by air temperature (67–74%), followed by precipitation (22–36%). Spatial heterogeneities in vegetation fraction and elevation dominated the spatial variations in CH 4 flux for all five tower domains despite relatively weak differences in simulated CH 4 flux among three footprint algorithms. The CLM-Microbe model can simulate CH 4 flux at both plot and landscape scales at a high temporal resolution, which should be applied to other landscapes. Integrating land surface models with an appropriate algorithm provides a powerful tool for upscaling CH 4 flux in terrestrial ecosystems.
54 ENVIRONMENTAL SCIENCES↗
Fire, dust, air and water: Improving aerosol biogeochemistry interactions in ACME. Final report
Aerosol-biogeochemistry interactions will have important consequences for human health, ecosystem services, and climate feedbacks over the next several decades. In this proposal we seek to link how human activities on land, including direct industrial emissions and landscape fires, impact the atmosphere and the biogeochemistry of the ocean and land. Our overall goal was to complement existing work at DOE labs to improve the capability and performance of the E3SM model in short-term, high-resolution projections of climate. Projections of ocean uptake of anthropogenic carbon are highly dependent on the details of the ocean physical and biogeochemistry parameterizations. Potentially equally important are the estimates of increases in iron and soluble nitrogen deposition in aerosols to the open ocean, but there are substantial uncertainties in these feedbacks. The E3SM land model simulates natural and anthropogenic fires, but improvement is needed to more accurately simulate fire responses to climate variability as well as fire contributions to terrestrial climate feedbacks. This proposal addressed four of the six priorities within the ACME/E3SM call by improving the representation of fire, industrial combustion sources, and desert dust and adding iron and soluble iron to the atmospheric chemistry (1). Our work focused on improving ocean biogeochemistry and the response of the oceans to anthropogenic atmospheric iron and nitrogen (3). We also improved the representation of land disturbance on fires and fire mediated carbon cycle feedbacks in the land model (4). Finally we had planned to couple the land, atmosphere and ocean biogeochemical systems (6) and explore how this coupling changes the feedbacks in the climate system. Our work under this proposal was separated into the following 5 tasks: i) improve representation of fire dynamics in both boreal and tropical ecosystems, ii) improve estimates of industrial emissions of iron and phosphorus, iii) improve representation of atmospheric iron, phosphorus and nitrogen transport, chemistry and deposition, iv) improve representation of iron, phosphorus and nitrogen deposition impacts on ocean biogeochemistry, and v) couple emissions into atmosphere, to deposition onto land and ocean biogeochemistry. For all 5 tasks, we conducted offline experiments of the historical period to enable comparison with available aerosol and land surface observations. We had planned to conduct fully coupled simulations, however, these will be conducted as part of the coupling in version 3 and 4 of the E3SM model, and thus have not been completed.
54 ENVIRONMENTAL SCIENCES↗
Water balance model (WBM) v.1.0.0: a scalable gridded global hydrologic model with water-tracking functionality
Abstract. This paper describes the University of New Hampshire Water Balance Model, WBM, a process-based gridded global hydrologic model that simulates the land surface components of the global water cycle and includes water extraction for use in agriculture and domestic sectors. The WBM was first published in 1989; here, we describe the first fully open-source WBM version (v.1.0.0). Earlier descriptions of WBM methods provide the foundation for the most recent model version that is detailed here. We present an overview of the model functionality, utility, and evaluation of simulated global river discharge and irrigation water use. This new version adds a novel suite of water source tracking modules that enable the analysis of flow-path histories on water supply. A key feature of WBM v.1.0.0 is the ability to identify the partitioning of sources for each stock or flux within the model. Three different categories of tracking are available: (1) primary inputs of water to the surface of the terrestrial hydrologic cycle (liquid precipitation, snowmelt, glacier melt, and unsustainable groundwater); (2) water that has been extracted for human use and returned to the terrestrial hydrologic system; and (3) runoff originating from user-defined spatial land units. Such component tracking provides a more fully transparent model in that users can identify the underlying mechanisms generating the simulated behavior. We find that WBM v.1.0.0 simulates global river discharge and irrigation water withdrawals well, even with default parameter settings, and for the first time, we are able to show how the simulation arrives at these fluxes by using the novel tracking functions.
54 ENVIRONMENTAL SCIENCES↗
Increasing Functional Diversity in a Global Land Surface Model Illustrates Uncertainties Related to Parameter Simplification
Abstract Simulations of the land surface carbon cycle typically compress functional diversity into a small set of plant functional types (PFT), with parameters defined by the average value of measurements of functional traits. In most earth system models, all wild plant life is represented by between five and 14 PFTs and a typical grid cell (≈100 × 100 km) may contain a single PFT. Model logic applied to this coarse representation of ecological functional diversity provides a reasonable proxy for the carbon cycle, but does not capture the non‐linear influence of functional traits on productivity. Here we show through simulations using the Energy Exascale Land Surface Model in 15 diverse terrestrial landscapes, that better accounting for functional diversity markedly alters predicted total carbon uptake. The shift in carbon uptake is as great as 30% and 10% in boreal and tropical regions, respectively, when compared to a single PFT parameterized with the trait means. The traits that best predict gross primary production vary based on vegetation phenology, which broadly determines where traits fall within the global distribution. Carbon uptake is more closely associated with specific leaf area for evergreen PFTs and the leaf carbon to nitrogen ratio in deciduous PFTs.
58 GEOSCIENCES↗
DEMographic MicrOSimulation (DEMOS) v2.0
DEMOS is an agent-based simulation framework used to evolve population demographic characteristics or lifecycle events such as education, marital status etc. DEMOS modules are designed to capture the interdependencies of short-term and long-term lifecycle events often influential in downstream transportation and land use modeling. An important facet of DEMOS is that it is dynamic, meaning it captures the impact of an agent's demographic characteristics in year 't' on their demographic status in year 't+1'. This has important consequences on medium- and long-term downstream modeling in different domains, such as transportation where decisions such as household vehicle transactions (i.e., buying, selling, or replacing a vehicle) depend current or past household vehicle holdings as well as household transitions. Other downstream modeling that can be enabled by DEMOS include building technology adoption or retrofit decisions, and more. DEMOS modules include: individual age progression year by year, individual mortality events, household restructuring events including marriage match-making; household birth events; individual education participation; individual labor force participation; child leaving household; household in-migration and out-migration for the region; household residence location choice and household mandatory destination choice (work and school). This version of DEMOS is tailored to be integrated with the land use simulation software UrbanSim.
Caicedo, Juan [UrbanSim, Inc.]↗
Data for "Divergent urban land trajectories under alternative population projections within the shared socioeconomic pathways"
Datasets supporting findings and visualizations behind McManamay et al. (2024) Divergent urban land trajectories under alternative population projections within the shared socioeconomic pathways. Environmental Research Letters, DOI: 10.1088/1748-9326/ad2eec Using a spatial modeling experiment at high resolution (1-km), this study compared how two alternative US population projections, varying in the spatially explicit nature of demographic patterns and migration, affect urban land dynamics simulated by the Spatially Explicit, Long-term, Empirical City development (SELECT) model for SSP2, SSP3, and SSP5. The numerical experiment, inputs and outputs are fully described in McManamay et al. (2024). The datasets summarize SELECT model simulations within urban areas and rural areas of the conterminous United States. For code to reproduce the results, please refer to https://github.com/IMMM-SFA/mcmanamay_etal_2024_erl Please refer to the README file provided in Files for more details. Descriptions of the datasets are provided below. Dataset(s) Descriptions: Urban_Land_delta_UA_County.csv: Urban land area for original (default) population, updated population, and urban land delta (difference between the two) according to Shared Socioeconomic Pathways (SSPs) and year. Urban land is summarized for U.S. counties (FIPS code) and urban areas (GEOID) as unique areas within various counties. JO_Gao_pop_ufdelta.csv: Comparison of population differences and urban land differences between the origial (default) and updated population projections. City_Case_studies.csv: Differences in urban land areas arising from different population projections summarized for selected cities (Atlanta, Los Angeles, Houston, and New York) and their surrounding rural areas UA_county_FID.zip: Zipped folder of .tiff file depicting unique combination of urban areas and US counties used for summarizing urban land differences in urban and rural areas based on different population projections. ULD_clusters.zip: Zipped folder of .csv files depicting normalized changes in urban land delta (difference in urban land arising from population projections) and the respective Ward's hierarchical clusters, which group urban and rural areas based on similarities in temporal trends. Urban_Percent_change_2100.zip: Zipped folder of .csv files depicting percent changes in urban land area for year 2100 based on differences in the original (default) population and updated population. Each file is for SSPs and urban or rural areas.
Land↗
Strong Local Evaporative Cooling Over Land Due to Atmospheric Aerosols
Abstract Aerosols can enhance terrestrial productivity through increased absorption of solar radiation by the shaded portion of the plant canopy—the diffuse radiation fertilization effect. Although this process can, in principle, alter surface evaporation due to the coupling between plant water loss and carbon uptake, with the potential to change the surface temperature, aerosol‐climate interactions have been traditionally viewed in light of the radiative effects within the atmosphere. Here, we develop a modeling framework that combines global atmosphere and land model simulations with a conceptual diagnostic tool to investigate these interactions from a surface energy budget perspective. Aerosols increase the terrestrial evaporative fraction, or the portion of net incoming energy consumed by evaporation, by over 4% globally and as much as ∼40% regionally. The main mechanism for this is the increase in energy allocation from sensible to latent heat due to global dimming (reduction in global shortwave radiation) and slightly augmented by diffuse radiation fertilization. In regions with moderately dense vegetation (leaf area index >2), the local surface cooling response to aerosols is dominated by this evaporative pathway, not the reduction in incident radiation. Diffuse radiation fertilization alone has a stronger impact on gross primary productivity (+2.18 Pg C y −1 or +1.8%) than on land evaporation (+0.18 W m −2 or +0.48%) and surface temperature (−0.01 K). Our results suggest that it is important for land surface models to distinguish between quantity (change in total magnitude) and quality (change in diffuse fraction) of radiative forcing for properly simulating surface climate.
Chakraborty, TC↗
Sensitivity of Precipitation Displacement of a Simulated MCS to Changes in Land Surface Conditions
Abstract This study investigates the role of the land surface on the precipitation produced by an elevated mesoscale convective system (MCS) in Iowa between 24–25 June 2015 during the Plains Elevated Convection at Night (PECAN) field campaign. Previous studies have shown a strong effect of low‐level atmospheric moisture on the location of this MCS. A series of semi‐idealized and realistic simulations with irrigation are conducted to understand the effect of moisture perturbations on the MCS precipitation displacement. In general, numerical simulations place the MCS east of the observed location. Adding moisture directly in the low‐level atmosphere in the semi‐idealized experiments reduces this displacement error. However, experiments with perturbed soil moisture result in drying over Iowa induced by moisture flux divergence from cooler low‐level temperatures and higher surface pressure, causing the MCS to move further to the east. The irrigation impact on low‐level moisture is highly dependent on the length of simulation period. Shorter simulations on the order of days generate similar drying over Iowa but the opposite is found for month‐long simulations. Despite the lack of low‐level moistening in the perturbed soil moisture and short‐term irrigation experiments, the sensitivity to low‐level moisture is similar in all runs. More low‐level moisture generates a more convectively unstable environment with less inhibition and a lower level of free convection that leads to more rapid MCS development and a change in MCS location.
54 ENVIRONMENTAL SCIENCES↗
High-resolution (30-m) urban land cover projections for Los Angeles California Urban Area: 2010 to 2100 under SSP5
These data represent simulations of future land use and land cover (LULCC) for Los Angeles urban area (U.S. Census Bureau defined area) as raster tiff images at a 30-m pixel resolution and at decadal time steps from 2010 to 2100. LULCC classes in this product follow the National Land Cover Dataset (NLCD) classification. NLCD 21-24 correspond to open developed, low developed, medium developed, and high developed urban land classes, respectively. Only urban land cover classes (NLCD class 21, 22, 23, and 24) are dynamic over time; however, all NLCD classes are included in the final product. Therefore, NLCD classes that do not convert to an urban class will be similar to year 2000. The products were developed using a hybridized statistical and cellular automata approach. Linear mixed models (LMMs) were used to estimate future urban land budgets based on 1-km urban land fraction projections from Gao and Pesaresi (2021), whereas separate generalized linear mixed models (GLMMs) were used to estimate shifts in urban land intensities based on retrospective shifts in NLCD urban class intensities over a 20- year period. Based on urban land allocations from the statistical models, a cellular-automata and downscaling routine was used to simulate dynamic urban land expansion at a 30-m resolution based on suitability criteria. Scenarios of future urban landcover change projections include variant solutions for the Shared Socioeconomic Pathway 5 (SSP5) based on different population assumptions, different land use intensification assumptions, variable land zoning constraints, and iterative adjustments to correct for over allocation of urban expansion across decadal time periods from 2010 to 2100. This results in 320 raster products.
Land↗
Divergent urban land trajectories under alternative population projections within the Shared Socioeconomic Pathways
Population change is a main driver behind global environmental change, including urban land expansion. In future scenario modeling, assumptions regarding how populations will change locally, despite identical global constraints of Shared Socioeconomic Pathways (SSPs), can have dramatic effects on subsequent regional urbanization. Using a spatial modeling experiment at high resolution (1 km), this study compared how two alternative US population projections, varying in the spatially explicit nature of demographic patterns and migration, affect urban land dynamics simulated by the Spatially Explicit, Long-term, Empirical City development (SELECT) model for SSP2, SSP3, and SSP5. The population projections included: (1) newer downscaled state-specific population (SP) projections inclusive of updated international and domestic migration estimates, and (2) prevailing downscaled national-level projections (NP) agnostic to localized demographic processes. Our work shows that alternative population inputs, even those under the same SSP, can lead to dramatic and complex differences in urban land outcomes. Under the SP projection, urbanization displays more of an extensification pattern compared to the NP projection. This suggests that recent demographic information supports more extreme urban extensification and land pressures on existing rural areas in the US than previously anticipated. Urban land outcomes to population inputs were spatially variable where areas in close spatial proximity showed divergent patterns, reflective of the spatially complex urbanization processes that can be accommodated in SELECT. Although different population projections and assumptions led to divergent outcomes, urban land development is not a linear product of population change but the result of complex relationships between population, dynamic urbanization processes, stages of urban development maturity, and feedback mechanisms. These findings highlight the importance of accounting for spatial variations in the population projections, but also urbanization process to accurately project long-term urban land patterns.
54 ENVIRONMENTAL SCIENCES↗
Carbon and Water Fluxes of the Boreal Evergreen Needleleaf Forest Biome Constrained by Assimilating Ecosystem Carbonyl Sulfide Flux Observations
Gross primary production (GPP) by boreal forests is highly sensitive to environmental changes. However, GPP simulated by land surface models (LSMs) remains highly uncertain due to the lack of direct photosynthesis observations at large scales. Carbonyl sulfide (COS) has emerged as a promising proxy to improve the representation of GPP in LSMs. Because COS is absorbed by vegetation following the same diffusion pathway as CO2 during photosynthesis and not emitted back to the atmosphere, incorporating a mechanistic representation of vegetation COS uptake in LSMs allows using COS observations to refine GPP representation. Here, we perform ecosystem COS flux and GPP data assimilations to constrain the COS- and GPP-related parameters in the ORCHIDEE LSM for boreal evergreen needleleaf forests (BorENF). Assimilating ecosystem COS fluxes at Hyytiälä forest increases the simulated net ecosystem COS uptake by 14%. This increase largely results from changes in the internal conductance to COS, highlighting the need to improve the representation of COS internal diffusion and consumption. Moreover, joint assimilation of ecosystem COS flux and GPP at Hyytiälä improves the simulated latent heat flux, contrary to the GPP-only data assimilation, which fails to do so. Finally, we scaled this assimilation framework up to the boreal region and find that the joint assimilation of COS at Hyytiälä and GPP fluxes at 10 BorENF sites increases the modeled vegetation COS uptake up to 18%, but not GPP. Therefore, this study encourages the use of COS flux observations to inform GPP and latent heat flux representations in LSMs.
54 ENVIRONMENTAL SCIENCES↗
Early warm-season mesoscale convective systems dominate soil moisture–precipitation feedback for summer rainfall in central United States
Land–atmosphere interactions play an important role in summer rainfall in the central United States, where mesoscale convective systems (MCSs) contribute to 30 to 70% of warm-season precipitation. Previous studies of soil moisture–precipitation feedbacks focused on the total precipitation, confounding the distinct roles of rainfall from different convective storm types. Here, we investigate the soil moisture–precipitation feedbacks associated with MCS and non-MCS rainfall and their surface hydrological footprints using a unique combination of these rainfall events in observations and land surface simulations with numerical tracers to quantify soil moisture sourced from MCS and non-MCS rainfall. Furthermore, we find that early warm-season (April to June) MCS rainfall, which is characterized by higher intensity and larger area per storm, produces coherent mesoscale spatial heterogeneity in soil moisture that is important for initiating summer (July) afternoon rainfall dominated by non-MCS events. On the other hand, soil moisture sourced from both early warm-season MCS and non-MCS rainfall contributes to lower-level atmospheric moistening favorable for upscale growth of MCSs at night. However, soil moisture sourced from MCS rainfall contributes to July MCS rainfall with a longer lead time because with higher intensity, MCS rainfall percolates into deeper soil that has a longer memory. Therefore, early warm-season MCS rainfall dominates soil moisture–precipitation feedback. This motivates future studies to examine the contribution of early warm-season MCS rainfall and associated soil moisture anomalies to predictability of summer rainfall in the major agricultural region of the central United States and other continental regions frequented by MCSs.
54 ENVIRONMENTAL SCIENCES↗