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At least 811 records · Page 45

A Comparison of the Diel Cycle of Modeled and Measured Latent Heat Flux During the Warm Season in a Colorado Subalpine Forest

Abstract Precipitation changes the physiological characteristics of an ecosystem. Because land‐surface models are often used to project changes in the hydrological cycle, modeling the effect of precipitation on the latent heat flux λE is an important aspect of land‐surface models. Here we contrast conditionally sampled diel composites of the eddy‐covariance fluxes from the Niwot Ridge Subalpine Forest AmeriFlux tower with the Community Land Model (CLM, version 4.5). With respect to measured λE during the warm season: for the day following above‐average precipitation, λE was enhanced at midday by ≈40 W m −2 (relative to dry conditions), and nocturnal λE increased from ≈10 W m −2 in dry conditions to over 20 W m −2 in wet conditions. With default settings, CLM4.5 did not successfully model these changes. By increasing the amount of time that rainwater was retained by the canopy/needles, CLM was able to match the observed midday increase in λE on a dry day following a wet day. Stable nighttime conditions were problematic for CLM4.5. Nocturnal CLM λE had only a small (≈3 W m −2 ) increase during wet conditions, CLM nocturnal friction velocity u ∗ was smaller than observed u ∗ , and CLM canopy air temperature was 2°C less than those measured at the site. Using observed u ∗ as input to CLM increased λE ; however, this caused CLM λE to be increased during both wet and dry periods. We suggest that sloped topography and the ever‐present drainage flow enhanced nocturnal u ∗ and λE . Such phenomena would not be properly captured by topographically blind land‐surface models, such as CLM.

Burns, Sean P.↗

Enhanced water use efficiency in global terrestrial ecosystems under increasing aerosol loadings

Aerosols play a crucial role in the climate system, affecting incoming radiation and cloud formation. Based on a modelling framework that couples ecosystem processes with the atmospheric transfer of radiation, we analyze the effect of aerosols on surface incoming radiation, gross primary productivity (GPP), water losses from ecosystems through evapotranspiration (ET) and ecosystem water use efficiency (WUE, defined as GPP/ET) for 2003–2010 and validate them at global FLUXNET sites. The total diffuse radiation increases under relatively low or intermediate aerosol loadings, but decreases under more polluted conditions. We find that aerosol-induced changes in GPP depend on leaf area index, aerosol loading and cloudiness. Specifically, low and moderate aerosol loadings cause increases in GPP for all plant types, while heavy aerosol loadings result in enhancement (decrease) in GPP for dense (sparse) vegetation. On the other hand, ET is mainly negatively affected by aerosol loadings due to the reduction in total incoming radiation. Finally, WUE shows a consistent rise in all plant types under increasing aerosol loadings. Overall, the simulated daily WUE compares well with observations at 43 eddy-covariance tower sites (R 2 =0.84 and RMSE=0.01gC (kg H 2 O) -1 ) with better performance at forest sites. In addition to the increasing portions of diffuse light, the rise in WUE is also favored by the reduction in radiation- and heat-stress caused by the aerosols, especially for wet and hot climates.

54 ENVIRONMENTAL SCIENCES↗

Genomes to ecosystem function: Targeting critical knowledge gaps in methanogenesis and translation to updated global biogeochemical models

Natural freshwater temperate wetland systems currently represent the largest natural source of atmospheric methane, but are relatively understudied using systems biology tools (e.g. meta-omics) compared to other high producing methane systems (e.g. peat, tropical, or reconstructed wetlands). Using field investigations at the NOAA operated sentinel site on Lake Erie, methane producing activities and responses to geochemical conditions will be determined along seasonal and spatial gradients (Objective 1). Here, a combination of high-throughput activity and gas measurements, combined with high-resolution systems biology and analytical methods, will provide in depth knowledge of the microbiological, chemical, and physical constraints on methane production in wetlands. Using laboratory microcosms, the formation of anoxic microsites and their capacity to facilitate methane production in wetland soils will be simulated (Objective 2). This objective will validate the findings from the field investigations, offering a more controlled environment for teasing out the role of different yet interrelated variables. Lastly, these field and laboratory data will be used for multi-scale, process-level evaluation of an ecosystem biogeochemical model that accommodates these newly identified processes and parameterizes representation of these processes along relevant environmental gradients (Objective 3).This research will identify multiple interacting geochemical, ecological, and metabolic constraints that are poorly understood, oversimplified, or missing in global biogeochemical methane models. This proposal targets the role of oxygen limitation on methane processes in soil domains, to improve reactive transport models of microbial carbon cycling across terrestrial-aquatic soils and generate data on nutrient cycling activities in Great Lake wetlands. This information could provide new insights into the microbial controllers of Lake Erie eutrophication.

59 BASIC BIOLOGICAL SCIENCES↗

Panama Land Model (CLM/ELM) Site Drivers

This data package contains meteorological and surface data at the Barro Colorado Island (BCI) and Bosque Protector San Lorenzo (Fort Sherman) NGEE Tropics sites in Panama. Data has been converted into formats usable by the land-models driving the Functionally-Assembled Terrestrial Ecosystem Simulator (FATES). Surface datasets are model release dependent and may have to be re-processed for later versions of the model. Current surface datasets based off of "<>_16pfts_Irrig_CMIP6_simyr2000_c170824.nc" See the README_ngeet_lm_driver text file in the attached zip file for detailed descriptions of the included data files.

54 ENVIRONMENTAL SCIENCES↗

Water Hyacinth Report

Water hyacinth (Eichhornia crassipes) is a fast-growing, invasive aquatic species and represents a potential biomass resource for bioenergy production in the Togo and Kenya regions on the African continent. Literature shows multiple conversion pathways exist to produce energy from water hyacinth while supporting economic growth, job creation, and environmental sustainability. ECO2LIBRIUM (ECO2) is investigating the feasibility of developing feedstock logistics modelling capabilities to facilitate water hyacinth based bioenergy production. Developing a water hyacinth feedstock pipeline capable of supplying biomass at consistent quantity and quality requires sophisticated feedstock logistics modelling to minimize costs while maximizing ecosystem services. However, developing this type of modelling capability requires specific spatial data and analysis resources. Idaho National Laboratory (INL) maintains research capabilities in the areas of bioenergy, feedstock logistics, spatial analysis, and remote sensing. INL researchers have compiled spatial data and analysis resources in this report to back development of a water hyacinth biomass feedstock logistics model.

09 BIOMASS FUELS↗

Sensitivity of Spruce/Moss Boreal Forest Net Ecosystem Productivity to Seasonal Anomalies in Weather

Abstract. A process-oriented, daily time step model of a spruce/moss boreal ecosystem simulated 1994 and 1995 productivity for a Boreal Ecosystem-Atmosphere Study site near Thompson, Manitoba. Simulated black spruce net primary productivity (NPP) was 139 g C m(exp -2) in 1994 and 112 in 1995; feathermoss NPP was 13.0 g C m(exp -2) in 1994 and 9.7 in 1995; decomposition was 126 g C m(exp -2) in 1994 and 130 in 1995; net ecosystem productivity (NEP) was an uptake of 26.3 g C m(exp -2)in 1994 and 2.5 in 1995. A very dry period for the first half of the 1995 summer was the major cause of that year's lower productivity. Sensitivity simulations explored the impact of 2-month long warmer, cooler, wetter, and drier spells on ecosystem productivity. Warmer summers decreased spruce NPP, moss NPP, and NEP; cooler summers had the opposite effect. Earlier snowmelt (due to either warmer spring temperatures or reduced winter precipitation) increased moss and spruce NPP; later snowmelt had the opposite effect. The largest effect on decomposition was a 5% reduction due to a drier summer. One-month droughts (April through October) were also imposed on 1975 base year weather. Early summer droughts reduced moss annual NPP by -30-40%; summer droughts reduced spruce annual NPP by 10%; late summer droughts increased moss NPP by about 20% due to reduced respiration; May to September monthly droughts reduced heterotrophic respiration by about 10%. Variability in NEP was up to roughly +/- 35%. Finally, 1975 growing season precipitation was redistributed into frequent, small rainstorms and infrequent, large rainstorms. These changes had no effect on spruce NPP. Frequent rainstorms increased decomposition by a few percent, moss NPP by 50%, and NEP by 20%. Infrequent rainstorms decreased decomposition by 5%, moss NPP by 50% and NEP by 15%. The impact of anomalous weather patterns on productivity of this ecosystem depended on their timing during the year. Multiyear data sets are necessary to understand this behavior and test these types of models.

Frolking, Steve↗

Hidden Processes During Seasonal Isolation of a High-Altitude Watershed

Biogeochemical processes capable of altering global carbon systems occur frequently in Earth’s Critical Zone–the area spanning from vegetation canopy to saturated bedrock–yet many of these phenomena are difficult to detect. Observation of these processes is limited by the seasonal inaccessibility of remote ecosystems, such as those in mountainous, snow- and ice-dominated areas. This isolation leads to a distinct gap in biogeochemical knowledge that ultimately affects the accuracy and confidence with which these ecosystems can be computationally modeled for the purpose of projecting change under different climate scenarios. To examine a high-altitude, headwater ecosystem’s role in methanogenesis, sulfate reduction, and groundwater-surface water exchange, water samples were continuously collected from the river and hyporheic zones (HZ) during winter isolation in the East River (ER), CO watershed. Measurements of continuously collected ER surface water revealed up to 50 μM levels of dissolved methane in July through September, while samples from 12 cm deep in the hyporheic zone at the same location showed a spring to early summer peak in methane with a strong biogenic signature (<65 μM, δ13C-CH4, -60.76‰) before declining. Continuously collected δ 18 O-H 2 O and δ 2 H-H 2 O isotopes from the water column exhibited similar patterns to discrete measurements, while samples 12 cm deep in the hyporheic zone experienced distinct fluctuations in δ 18 O-H 2 O, alluding to significant groundwater interactions. Continuously collected microbial communities in the river in the late fall and early winter revealed diverse populations that reflect the taxonomic composition of ecologically similar river systems, including taxa indicative of methane cycling in this system. These measurements captured several biogeochemical components of the high-altitude watershed in response to seasonality, strengthening our understanding of these systems during the winter months.

54 ENVIRONMENTAL SCIENCES↗

Using Remotely Sensed Data and Watershed and Hydrodynamic Models to Evaluate the Effects of Land Cover Land Use Change on Aquatic Ecosystems in Mobile Bay, AL

Alabama coastal systems have been subjected to increasing pressure from a variety of activities including urban and rural development, shoreline modifications, industrial activities, and dredging of shipping and navigation channels. The impacts on coastal ecosystems are often observed through the use of indicator species. One such indicator species for aquatic ecosystem health is submerged aquatic vegetation (SAV). Watershed and hydrodynamic modeling has been performed to evaluate the impact of land cover land use (LCLU) change in the two counties surrounding Mobile Bay (Mobile and Baldwin) on SAV stressors and controlling factors (temperature, salinity, and sediment) in the Mobile Bay estuary. Watershed modeling using the Loading Simulation Package in C++ (LSPC) was performed for all watersheds contiguous to Mobile Bay for LCLU scenarios in 1948, 1992, 2001, and 2030. Remotely sensed Landsat-derived National Land Cover Data (NLCD) were used in the 1992 and 2001 simulations after having been reclassified to a common classification scheme. The Prescott Spatial Growth Model was used to project the 2030 LCLU scenario based on current trends. The LSPC model simulations provided output on changes in flow, temperature, and sediment for 22 discharge points into the estuary. These results were inputted in the Environmental Fluid Dynamics Computer Code (EFDC) hydrodynamic model to generate data on changes in temperature, salinity, and sediment on a grid throughout Mobile Bay and adjacent estuaries. The changes in the aquatic ecosystem were used to perform an ecological analysis to evaluate the impact on SAV habitat suitability. This is the key product benefiting the Mobile Bay coastal environmental managers that integrates the influences of temperature, salinity, and sediment due to LCLU driven flow changes with the restoration potential of SAVs. Data products and results are being integrated into NOAA s EcoWatch and Gulf of Mexico Data Atlas online systems for dissemination to coastal resource managers and stakeholders. Objective 1: Develop and utilize Land Use scenarios for Mobile and Baldwin Counties, AL as input to models to predict the affects on water properties (temperature,salinity,)for Mobile Bay through 2030. Objective 2: Evaluate the impact of land use change on seagrasses and SAV in Mobile Bay. Hypothesis: Urbanization will significantly increase surface flows and impact salinity and temperature variables that effect seagrasses and SAVs.

Al-Hamdan, Mohammad↗

A Generic Biogeochemical Module for Earth System Models: Next Generation BioGeoChemical Module (NGBGC), Version 1.0

Physical and biogeochemical processes regulate soil carbon dynamics and CO2 flux to and from atmosphere, influencing global climate changes. Integration of these processes into earth system models (e.g., community land models (CLM)), however, currently faces three major challenges: 1) extensive efforts are required to modify modeling structures and to rewrite computer programs to incorporate new or updated processes as new knowledge is being generated, 2) computational cost is prohibitively expensive to simulate biogeochemical processes in land models due to large variations in the rates of biogeochemical processes, and 3) various mathematical representations of biogeochemical processes exist to incorporate different aspects of fundamental mechanisms, but systematic evaluation of the different mathematical representations is difficult, if not possible. To address these challenges, we propose a new computational framework to easily incorporate physical and biogeochemical processes into land models. The new framework consists of a new biogeochemical module with a generic algorithm and reaction database so that new and updated processes can be incorporated into land models without the need to manually set up the ordinary differential equations to be solved numerically. The reaction database consists of processes of nutrient flow through the terrestrial ecosystems in plants, litter and soil. This framework facilitates effective comparison studies of biogeochemical cycles in an ecosystem using different conceptual models under the same land modeling framework. The approach was first implemented in CLM and benchmarked against simulations from the original CLM-CN code. A case study was then provided to demonstrate the advantages of using the new approach to incorporate a phosphorus cycle into the CLM model. To our knowledge, the phosphorus-incorporated CLM is a new model that can be used to simulate phosphorus limitation on the productivity of terrestrial ecosystems.

Fang, Yilin↗

Anaerobic microsites have an unaccounted role in soil carbon stabilization

Soils represent the largest carbon reservoir within terrestrial ecosystems. The mechanisms controlling the amount of carbon stored and its feedback to the climate system, however, remain poorly resolved. Global carbon models assume that carbon cycling in upland soils is entirely driven by aerobic respiration; the impact of anaerobic microsites prevalent even within well-drained soils is missed within this conception. Here, we show that anaerobic microsites are important regulators of soil carbon persistence, shifting microbial metabolism to less efficient anaerobic respiration, and selectively protecting otherwise bioavailable, reduced organic compounds such as lipids and waxes from decomposition. Further, shifting from anaerobic to aerobic conditions leads to a 10-fold increase in volume-specific mineralization rate, illustrating the sensitivity of anaerobically protected carbon to disturbance. The vulnerability of anaerobically protected carbon to future climate or land use change thus constitutes a yet unrecognized soil carbon-climate feedback that should be incorporated into terrestrial ecosystem models.

54 ENVIRONMENTAL SCIENCES↗

Green Ocean Amazon 2014/15 – Scaling Amazon Carbon Water Couplings Field Campaign Report

Forests soak up 25% of the carbon dioxide (CO2) emitted by anthropogenic fossil energy use (10 Gt C y-1), moderating its atmospheric accumulation. How this terrestrial CO2 uptake will evolve with climate change in the 21st Century is largely unknown. Rainforests are the most active ecosystems, with the Amazon basin storing 120 Gt C as biomass and exchanging 18 Gt C y-1 of CO2 via photosynthesis and respiration and fixing carbon at 2-3 kg C m-2 y-1. Furthermore, the intense hydrologic and carbon cycles are tightly coupled in the Amazon where about half of the water is recycled by evapotranspiration and the other half imported from the ocean by Northeasterly trade winds. Climate models predict a drying in the Amazon with reduced carbon uptake while observationally guided assessments indicate sustained uptake. We set out to resolve this huge discrepancy in the size and sign of the future Amazon carbon cycle by performing the first simultaneous regional-scale high-frequency measurements of atmospheric CO2, H2O, HOD, CH4, N2O, and CO at the T3 site in Manacupuru, Brazil, as part of DOE's GoAmazon 2014/15 project. Our data will be used to inform and develop DOE's Community Land Model (CLM) on the tropical carbon-water couplings at the appropriate grid scale (10-50 km). Our measurements will also validate the CO2 data from Japan's Greenhouse gases Observing Satellite (GOSAT) and NASA's Orbiting Carbon Observatory (OCO)-2 satellite (launched in July, 2014). Our data addresses these science questions: 1. How does ecosystem heterogeneity and climate variability influence the rainforest carbon cycle? 2. How well do current tropical ecosystem models simulate the observed regional carbon cycle? 3. Does nitrogen deposition (from the Manaus, Brazil, plume) enhance rainforest carbon uptake?

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Using long‐term data from a whole ecosystem warming experiment to identify best spring and autumn phenology models

Abstract Predicting vegetation phenology in response to changing environmental factors is key in understanding feedbacks between the biosphere and the climate system. Experimental approaches extending the temperature range beyond historic climate variability provide a unique opportunity to identify model structures that are best suited to predicting phenological changes under future climate scenarios. Here, we model spring and autumn phenological transition dates obtained from digital repeat photography in a boreal Picea ‐ Sphagnum bog in response to a gradient of whole ecosystem warming manipulations of up to +9°C, using five years of observational data. In spring, seven equally best‐performing models for Larix utilized the accumulation of growing degree days as a common driver for temperature forcing. For Picea , the best two models were sequential models requiring winter chilling before spring forcing temperature is accumulated. In shrub, parallel models with chilling and forcing requirements occurring simultaneously were identified as the best models. Autumn models were substantially improved when a CO 2 parameter was included. Overall, the combination of experimental manipulations and multiple years of observations combined with variation in weather provided the framework to rule out a large number of candidate models and to identify best spring and autumn models for each plant functional type.

Schädel, Christina↗

Using Remotely Sensed Data and Watershed and Hydrodynamic Models to Evaluate the Effects of Land Cover Land Use Change on Aquatic Ecosystems in Mobile Bay, AL

Alabama coastal systems have been subjected to increasing pressure from a variety of activities including urban and rural development, shoreline modifications, industrial activities, and dredging of shipping and navigation channels. The impacts on coastal ecosystems are often observed through the use of indicator species. One such indicator species for aquatic ecosystem health is submerged aquatic vegetation (SAV). Watershed and hydrodynamic modeling has been performed to evaluate the impact of land cover land use (LCLU) change in the two counties surrounding Mobile Bay (Mobile and Baldwin) on SAV stressors and controlling factors (temperature, salinity, and sediment) in the Mobile Bay estuary. Watershed modeling using the Loading Simulation Package in C++ (LSPC) was performed for all watersheds contiguous to Mobile Bay for LCLU scenarios in 1948, 1992, 2001, and 2030. Remotely sensed Landsat-derived National Land Cover Data (NLCD) were used in the 1992 and 2001 simulations after having been reclassified to a common classification scheme. The Prescott Spatial Growth Model was used to project the 2030 LCLU scenario based on current trends. The LSPC model simulations provided output on changes in flow, temperature, and sediment for 22 discharge points into the estuary. These results were inputted in the Environmental Fluid Dynamics Computer Code (EFDC) hydrodynamic model to generate data on changes in temperature, salinity, and sediment on a grid throughout Mobile Bay and adjacent estuaries. The changes in the aquatic ecosystem were used to perform an ecological analysis to evaluate the impact on SAV habitat suitability. This is the key product benefiting the Mobile Bay coastal environmental managers that integrates the influences of temperature, salinity, and sediment due to LCLU driven flow changes with the restoration potential of SAVs. Data products and results are being integrated into NOAA s EcoWatch and Gulf of Mexico Data Atlas online systems for dissemination to coastal resource managers and stakeholders.

Al-Hamdan, Mohammad Z.↗

Research Priorities to Incorporate Terrestrial-Aquatic Interfaces in Earth System Models. Workshop Report, September 7-9, 2016

The terrestrial-aquatic interface (TAI) is a highly dynamic component of the Earth system, developed from a near balance between terrestrial and aquatic conditions and forming unique processes and community assemblages. Furthermore, TAIs are known to play a critical role in carbon biogeochemical cycling and have the potential to provide major feedbacks to the Earth system (e.g., methane production). However, there is a lack of basic data and multiscale models to adequately describe how a changing climate can influence the key processes (also an unknown) related to Earth system–relevant feedbacks in these unique, ubiquitous ecosystems. In general, Earth system models (ESMs) have excluded TAI ecosystem processes, thus creating tremendous uncertainty as to how TAIs will influence climate feedbacks across a range of scales, spanning from local to global. For example, ESMs represent wetlands very simplistically at best (e.g., the Accelerated Climate Modeling for Energy project) and include only a static fraction of dry land or open water, entirely lacking key processes in these hybrid areas and critical climate and biological feedbacks between land and water. This new area of research, therefore, must integrate a variety of important research topics—plants, soil, hydrology, reactive transport, microbiology, genomics, and modeling—into a systems-level understanding that can be extended to improve predictive modeling capabilities. The goal of the September 2016 Research Priorities to Incorporate Terrestrial-Aquatic Interfaces in Earth System Models Workshop was to engage the scientific community in an open discussion about critical scientific gaps. These gaps and research topics demand immediate field investigations to gather data for representing these important, yet understudied and underrepresented, ecosystems in ESMs. Workshop results will inform the U.S. Department of Energy’s Office of Biological and Environmental Research (BER) as it plans and prepares for future research efforts that address the TAI gap through model-informed and model-inspired field studies. The resulting data will enable iterative refinement of high-resolution, next-generation ESMs. Specifically, the workshop (1) summarized past and current field, process, and modeling TAI research; (2) identified critical sensitivities and uncertainties in the systems; (3) identified key processes, traits, existing data, and environmental variables needed to adequately characterize these systems; and (4) discussed idealized strategies that couple models and experiments to advance the state of the science in TAI modeling, including potential experiments that would test and improve land model fidelity.

54 ENVIRONMENTAL SCIENCES↗

Evaluating ecosystem water use efficiency and recovery dynamics during flash droughts: insights from observations and model simulations

Flash droughts (FD), rapidly emerging in a warming future, disrupt ecosystems, agriculture, and water security. Ecosystem water use efficiency (WUE), the ratio of gross primary production (GPP) to actual evapotranspiration (AET), balances carbon assimilation and water loss. FD rapidly disrupts this balance, making WUE critical for assessing plant stress and recovery. Here, this study investigates the dynamics of landscape-scale WUE, and the components of GPP and AET under FD utilizing both observed data from the Missouri Ozark AmeriFlux site (US-MOz) and version 2 of the U.S. Department of Energy’s Earth, Energy, Exascale System Model (E3SM) Land Model (ELMv2). Observations and simulations reveal GPP as dominant for WUE during earlier FD events (2005, 2007, 2012), shifting to AET in recent events (2014, 2018). This agreement indicates that the ELM can capture the shifting dynamics of GPP and AET in regulating WUE under FD conditions. However, the ELM systematically underestimates both GPP and AET and does so in a manner that does not preserve their ratio. As a result, WUE is also underestimated, suggesting that GPP is more strongly underestimated than AET. Furthermore, the ELM also underestimates the speed of GPP recovery, producing an artificially prolonged GPP recovery time following FD events. Observed environmental drivers such as vapor pressure deficit (VPD), soil moisture (SM), and predawn leaf water potential (PLWP) effectively predict WUE, but ELM primarily highlights SM, underestimating VPD’s role. This study demonstrates that relying solely on soil moisture fails to capture the rapid hydraulic recovery observed in PLWP, underscoring the necessity of integrating plant hydraulics into land surface models to improve flash drought predictability.

Evapotranspiration↗

Predicting Chronic Climate-Driven Disturbances and Their Mitigation

Society increasingly demands the stable provision of ecosystem resources to support our population. Resource risks from climate-driven disturbances--including drought, heat, insect outbreaks, and wildfire--are rising as a chronic state of disequilibrium results from increasing temperatures and a greater frequency of extreme events. This confluence of increased demand and risk may soon reach critical thresholds. We explain here why extreme chronic disequilibrium of ecosystem function is likely to increase dramatically across the globe, creating no-analog conditions that challenge adaptation. We also present novel mechanistic theory that combines models for disturbance mortality and metabolic scaling to link size-dependent plant mortality to changes in ecosystem stocks and fluxes. Efforts must anticipate and model chronic ecosystem disequilibrium to properly prepare for resilience planning.

disequilibrium↗

NASA’s Prototype Spectral Water Inversion Processor and Emulator (SWIPE): Towards Global Coastal and Inland Water Quality and Algal Biodiversity Monitoring

Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will provide updates on NASA’s prototype open-source aquatic modeling platform, Spectral Water Inversion Processor and Emulator (SWIPE), which is a comprehensive, multi-faceted modeling platform for both forward and inverse modeling of diverse aquatic ecosystems from the benthos to top-of-atmosphere (TOA). SWIPE provides a cohesive application which leverages recent advancements in particle modeling, Big Data analytics, and machine learning to develop a high-fidelity synthetic training ground for sensitivity studies and algorithm development for multispectral or upcoming hyperspectral missions. Some of the prominent features of SWIPE to be discussed include: 1. Advanced hyperspectral modeling of globally diverse algal and non-algal particles using a novel two-layer coated sphere scattering model and radiative transfer modeling, 2. Massive, highly detailed synthetic spectral libraries of Analysis-Ready-Data (ARD) which include spectral libraries of particle microphysics, water biogeophysical and optical properties, as well as surface and TOA reflectances at 1 nm resolution, 3. An ensemble of pre-built analytic, machine learning, and deep learning inversion algorithms for various water quality and biodiversity related retrieval parameters and uncertainty quantification, 4. Sensor-agnostic water quality inversion at wide ranging spatial and spectral resolutions including a codebase for seamless application in the Google Earth Engine and NASA Earth Exchange (NEX) for planetary scale analysis. SWIPE will be a fully open-source platform based in python with comprehensive documentation, tutorials, and options for distributed computing on high performance computing clusters or on single, local machines. Further, we will discuss how we envision SWIPE contributing towards a global analysis of coastal and inland water quality dynamics.

top-of-atmosphere (TOA)↗

Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes

We describe an implementation of the Ecosystem Demography (ED) concept in the Community Land Model. The structure of CLM(ED) and the physiological and structural modifications applied to the CLM are presented. A major motivation of this development is to allow the prediction of biome boundaries directly from plant physiological traits via their competitive interactions. Here we investigate the performance of the model for an example biome boundary in Eastern North America. We explore the sensitivity of the predicted biome boundaries and ecosystem properties to the variation of leaf properties determined by the parameter space defined by the GLOPNET global leaf trait database. Further, we investigate the impact of four sequential alterations to the structural assumptions in the model governing the relative carbon economy of deciduous and evergreen plants. The default assumption is that the costs and benefits of deciduous vs. evergreen leaf strategies, in terms of carbon assimilation and expenditure, can reproduce the geographical structure of biome boundaries and ecosystem functioning. We find some support for this assumption, but only under particular combinations of model traits and structural assumptions. Many questions remain regarding the preferred methods for deployment of plant trait information in land surface models. In some cases, plant traits might best be closely linked with each other, but we also find support for direct linkages to environmental conditions. We advocate for intensified study of the costs and benefits of plant life history strategies in different environments, and for the increased use of parametric and structural ensembles in the development and analysis of complex vegetation models.

54 ENVIRONMENTAL SCIENCES↗