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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

The Interplay Between Transpiration and Runoff Formulations in Land Surface Schemes Used with Atmospheric Models

The Project for Intercomparison of Land-surface Parameterization Schemes (PILPS) has shown that different land surface models (LSMS) driven by the same meteorological forcing can produce markedly different surface energy and water budgets, even when certain critical aspects of the LSMs (vegetation cover, albedo, turbulent drag coefficient, and snow cover) are carefully controlled. To help explain these differences, the authors devised a monthly water balance model that successfully reproduces the annual and seasonal water balances of the different PILPS schemes. Analysis of this model leads to the identification of two quantities that characterize an LSM's formulation of soil water balance dynamics: (1) the efficiency of the soil's evaporation sink integrated over the active soil moisture range, and (2) the fraction of this range over which runoff is generated. Regardless of the LSM's complexity, the combination of these two derived parameters with rates of interception loss, potential evaporation, and precipitation provides a reasonable estimate for the LSM's simulated annual water balance. The two derived parameters shed light on how evaporation and runoff formulations interact in an LSM, and the analysis as a whole underscores the need for compatibility in these formulations.

Koster, Rindal D.↗
NASA NTRS2010

Utilizing In Situ Directional Hyperspectral Measurements to Validate Bio-Indicator Simulations for a Corn Crop Canopy

Two radiative transfer canopy models, SAIL and the two-layer Markov-Chain Canopy Reflectance Model (MCRM), were coupled with in situ leaf optical properties to simulate canopy-level spectral band ratio vegetation indices with the focus on the photochemical reflectance index in a cornfield. In situ hyperspectral measurements were made at both leaf and canopy levels. Leaf optical properties were obtained from both sunlit and shaded leaves. Canopy reflectance was acquired for eight different relative azimuth angles (psi) at three different view zenith angles (Theta (sub v)), and later used to validate model outputs. Field observations of photochemical reflectance index (PRI) for sunlit leaves exhibited lower values than shaded leaves, indicating higher light stress. Canopy PRI expressed obvious sensitivity to viewing geometry, as a function of both Theta (sub v) and psi . Overall, simulations from MCRM exhibited better agreements with in situ values than SAIL. When using only sunlit leaves as input, the MCRM-simulated PRI values showed satisfactory correlation and RMSE, as compared to in situ values. However, the performance of the MCRM model was significantly improved after defining a lower canopy layer comprised of shaded leaves beneath the upper sunlit leaf layer. Four other widely used band ratio vegetation indices were also studied and compared with the PRI results. MCRM simulations were able to generate satisfactory simulations for these other four indices when using only sunlit leaves as input; but unlike PRI, adding shaded leaves did not improve the performance of MCRM. These results support the hypothesis that the PRI is sensitive to physiological dynamics while the others detect static factors related to canopy structure. Sensitivity analysis was performed on MCRM in order to better understand the effects of structure related parameters on the PRI simulations. Leaf area index (LAI) showed the most significant impact on MCRM-simulated PRI among the parameters studied. This research shows the importance of hyperspectral and narrow band sensor studies, and especially the necessity of including the green wavelengths (e.g., 531 nm) on satellites proposing to monitor carbon dynamics of terrestrial ecosystems.

Cheng, Yen-Ben↗
NASA NTRS1996

Development of a Land Use Mapping and Monitoring Protocol for the High Plains Region: A Multitemporal Remote Sensing Application

The purpose of this project was to develop a practical protocol that employs multitemporal remotely sensed imagery, integrated with environmental parameters to model and monitor agricultural and natural resources in the High Plains Region of the United States. The value of this project would be extended throughout the region via workshops targeted at carefully selected audiences and designed to transfer remote sensing technology and the methods and applications developed. Implementation of such a protocol using remotely sensed satellite imagery is critical for addressing many issues of regional importance, including: (1) Prediction of rural land use/land cover (LULC) categories within a region; (2) Use of rural LULC maps for successive years to monitor change; (3) Crop types derived from LULC maps as important inputs to water consumption models; (4) Early prediction of crop yields; (5) Multi-date maps of crop types to monitor patterns related to crop change; (6) Knowledge of crop types to monitor condition and improve prediction of crop yield; (7) More precise models of crop types and conditions to improve agricultural economic forecasts; (8;) Prediction of biomass for estimating vegetation production, soil protection from erosion forces, nonpoint source pollution, wildlife habitat quality and other related factors; (9) Crop type and condition information to more accurately predict production of biogeochemicals such as CO2, CH4, and other greenhouse gases that are inputs to global climate models; (10) Provide information regarding limiting factors (i.e., economic constraints of pumping, fertilizing, etc.) used in conjunction with other factors, such as changes in climate for predicting changes in rural LULC; (11) Accurate prediction of rural LULC used to assess the effectiveness of government programs such as the U.S. Soil Conservation Service (SCS) Conservation Reserve Program; and (12) Prediction of water demand based on rural LULC that can be related to rates of draw-down of underground water supplies.

Price, Kevin P.↗
NASA NTRS1989

Using passive, thermal remote sensing techniques for detecting subsurface gravel accumulations in vegetated, unconsolidated sedimentary terrains

Multiband radiometric data from an airborne imaging thermal scanner are being studied for use in finding buried gravel deposits. The techniques are based on measuring relative differences in the thermal properties between gravel-laden targets and the surrounding gravelless background. These properties are determined from modeling the spectral radiant emittance recorded over both types of surfaces in conjunction with ground measurements of the most significant heat flows above and below the surface. Thermodynamic properties of sampled materials from control sites are determined, and diurnal and annual subsurface heat waves are recorded. Thermal models that account for heat exchange at the surface, as well as varying levels of soil moisture, humidity, and vegetation, are needed for adaptation and modification to simulate the physical and radiative environments of this region.

Burns, Gregory S.↗
NASA NTRS2013

The Utility of the Real-Time NASA Land Information System Data for Drought Monitoring Applications

Measurements of soil moisture are a crucial component for the proper monitoring of drought conditions. The large spatial variability of soil moisture complicates the problem. Unfortunately, in situ soil moisture observing networks typically consist of sparse point observations, and conventional numerical model analyses of soil moisture used to diagnose drought are of coarse spatial resolution. Decision support systems such as the U.S. Drought Monitor contain drought impact resolution on sub-county scales, which may not be supported by the existing soil moisture networks or analyses. The NASA Land Information System, which is run with 3 km grid spacing over the eastern United States, has demonstrated utility for monitoring soil moisture. Some of the more useful output fields from the Land Information System are volumetric soil moisture in the 0-10 cm and 40-100 cm layers, column-integrated relative soil moisture, and the real-time green vegetation fraction derived from MODIS (Moderate Resolution Imaging Spectroradiometer) swath data that are run within the Land Information System in place of the monthly climatological vegetation fraction. While these and other variables have primarily been used in local weather models and other operational forecasting applications at National Weather Service offices, the use of the Land Information System for drought monitoring has demonstrated utility for feedback to the Drought Monitor. Output from the Land Information System is currently being used at NWS Huntsville to assess soil moisture, and to provide input to the Drought Monitor. Since feedback to the Drought Monitor takes place on a weekly basis, weekly difference plots of column-integrated relative soil moisture are being produced by the NASA Short-term Prediction Research and Transition Center and analyzed to facilitate the process. In addition to the Drought Monitor, these data are used to assess drought conditions for monthly feedback to the Alabama Drought Monitoring and Impact Group and the Tennessee Drought Task Force, which are comprised of federal, state, and local agencies and other water resources professionals.

White, Kristopher D.↗
NASA NTRS2022

Haiti Agriculture: Utilizing NASA Earth Observations to Evaluate the Success of Reforestation Practices in Haiti

Haiti is one of the world’s most deforested and environmentally degraded countries. Over the past 30 years, the Haiti Reforestation Partnership (HRP) has provided resources, education, and expertise to support reforestation work in Haiti. The HRP has planted over 15 million trees through their partnership with Comprehensive Development Program (CODEP). However, they have yet to conduct a comprehensive analysis of forest stand survival. The NASA DEVELOP team partnered with the HRP to aid their future silvicultural decisions using satellite imagery. Through the creation of the Monitoring of Vegetation Presence (MVP) tool in Google Earth Engine, the team produced a time series showing trends in enhanced vegetation index (EVI) from 1984 to 2021, as well as a habitat suitability map using a general model for all tree species. These provided the partner with visuals to communicate their reforestation efforts and guidance on where to apply their future efforts. The team utilized Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Landsat 9 OLI-2 and Sentinel-2 Multispectral Instrument (MSI) vegetation indices as indicators of stand success over time. The team also incorporated WorldClim bioclimatic variables such as precipitation and temperature, Centre National de L’Information Geo-Spatiale (CNIGS) Airborne Lidar elevation, and ancillary datasets areas suitable for future reforestation efforts. Overall, the time series showed that the demonstration forest increased in EVI at a greater rate than the surrounding area and the habitat model suggested there are 49,000 hectares of suitable habitat for planting using slope, aspect and temperature as predictor variables.

Kelli Roberts↗
NASA NTRS2019

Dynamics and Variability of the Spring Dry Season in the United States Southwest as Observed in AmeriFlux and NLDAS-2 Data

The spring dry season occurring in an arid region of the Southwest United States, which receives both winter storm track and summer monsoon precipitation, is investigated. Bimodal precipitation and vegetation growth provide an opportunity to assess multiple climate mechanisms and their impact on hydroclimate and ecosystems.We detect multiple shifts from wet to drier conditions in the observational record and land surface model output. Focusing on the recent dry period, a shift in the late 1990s resulted in earlier and greater spring soil moisture draw down, and later and reduced spring vegetation green-up, compared to a prior wet period (1979 - 1997). A simple soil moisture balance model shows this shift is driven by changes in winter precipitation.The recent post-1999 dry period, as well as an earlier one from 1948 - 1966, are both related to the cool tropics phase of Pacific decadal variability which influences winter precipitation. In agreement with other studies for the Southwest United States, we find the recent drought cannot be explained in terms of precipitation alone, but also is due to the rising influence of temperature, thus highlighting the sensitivity of this region to warming temperatures. Future changes in the spring dry season will therefore be affected by how tropical decadal variability evolves, and also by emerging trends due to human-driven warming.

Pascolini-Campbell, Madeleine↗
NASA NTRS1990

A strategy to study regional hydrology and terrestrial ecosystem processes using satellite remote sensing, ground-based data and computer modeling

A strategy is presented for integrating scanning multichannel microwave radiometer data from the Nimbus-7 satellite with meteorological station records and computer simulations of land surface hydrology, terrestrial nutrient cycling, and trace gas emission. Analysis of the observations together with radiative transfer analysis shows that in the tropics the temporal and spatial variations of the polarization difference are determined primarily by the structure and phenology of vegetation and seasonal inundations of major rivers and wetlands. It is concluded that the proposed surface hydrology model, along with climatological records, and, potentially, 37-GHz data for phenology, will provide inputs to a terrestrial ecosystem model that predicts regional net primary production and CO2 gas exchange.

Vorosmarty, C.↗
NASA NTRS2016

The PRISM4 (mid-Piacenzian) Palaeoenvironmental Reconstruction

The mid-Piacenzian is known as a period of relative warmth when compared to the present day. A comprehensive understanding of conditions during the Piacenzian serves as both a conceptual model and a source for boundary conditions as well as means of verification of global climate model experiments. In this paper we present the PRISM4 reconstruction, a paleoenvironmental reconstruction of the mid-Piacenzian (approximately 3 Ma) containing data for paleogeography, land and sea ice, sea-surface temperature, vegetation, soils, and lakes. Our retrodicted paleogeography takes into account glacial isostatic adjustments and changes in dynamic topography. Soils and lakes, both significant as land surface features, are introduced to the PRISM reconstruction for the first time. Sea-surface temperature and vegetation reconstructions are unchanged but now have confidence assessments. The PRISM4 reconstruction is being used as boundary condition data for the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2) experiments.

soils↗
NASA NTRS2018

Remote Sensing of Evapotranspiration over the Central Arizona Irrigation and Drainage District, USA

Knowledge of baseline water use for irrigated crops in the U.S. Southwest is important for understanding how much water is consumed under normal farm management and to help manage scarce resources. Remote sensing of evapotranspiration (ET) is an effective way to gain that knowledge: multispectral data can provide synoptic and time-repetitive estimates of crop-specific water use, and could be especially useful for this arid region because of dominantly clear skies and minimal precipitation. Although multiple remote sensing ET approaches have been developed and tested, there is not consensus on which of them should be preferred because there are still few intercomparison studies within this environment. To help build the experience needed to gain consensus, a remote sensing study using three ET models was conducted over the Central Arizona Irrigation and Drainage District (CAIDD). Aggregated ET was assessed for 137 wheat plots (winter/spring crop), 183 cotton plots (summer crop), and 225 alfalfa plots (year-round). The employed models were the Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC), the Two Source Energy Balance (TSEB), and Vegetation Index ET for the US Southwest (VISW). Remote sensing data were principally Landsat 5, supplemented by Landsat 7, MODIS Terra, MODIS Aqua, and ASTER. Using district-wide model averages, seasonal use (excluding surface evaporation) was 742 mm (millimeters) for wheat, 983 mm for cotton, and 1427 mm for alfalfa. All three models produced similar daily ET for wheat, with 6-8 mm per day mid-season. Model estimates diverged for cotton and alfalfa sites. Considering ET over cotton, TSEB estimates were 9.5 mm per day, METRIC 6 mm per day, and VISW 8 mm per day. For alfalfa, the ET values from TSEB were 8.0 mm per day, METRIC 5 mm per day, and VISW 6 mm per day. Lack of local validation information unfortunately made it impossible to rank model performance. However, by averaging results from all of them, ET model outliers could be identified. They ranged from minus 10 percent to plus 18 percent, values that represent expected ET modeling discrepancies. Relative to the model average, standardized ET-estimators - potential ET (ET (sub 0)), FAO-56 ET, and USDA-SW gravimetric-ET - showed still greater deviations, up to 35 percent of annual crop water use for summer and year-round crops, suggesting that remote sensing of actual ET could lead to significantly improved estimates of crop water use. Results from this study highlight the need for conducting multi-model experiments during summer-months over sites with independent ground validation.

Alfalfa↗
NASA NTRS2018

Soil Moisture Active Passive (SMAP) Project Assessment Report for Version 4 of the L4_SM Data Product

This report provides an assessment of Version 4 of the SMAP Level 4 Surface and Root Zone Soil Moisture (L4_SM) product, released on 14 June 2018. The assessment includes comparisons of L4_SM soil moisture and temperature estimates with in situ measurements from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product, including observation-minus-forecast (O-F) brightness temperature residuals and soil moisture analysis increments.Together, the core validation site comparisons and the statistics of the assimilation diagnostics areconsidered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to upscaling errors from the point-scale to the grid-cell scale of the data product.The Version 4 L4_SM product benefits from an improved land surface modeling system and from retrospective surface meteorological forcing data that are as consistent as possible with the present-day datain terms of their climatology. Specifically, the model changes include revised parameters and parameterizations for (i) the surface energy balance, (ii) recharge from below of the model's surface excess reservoir, and (iii) the snow depletion curve. Updated ancillary inputs include improved datasets for landcover, topography, and vegetation height. The Version 4 algorithm further includes a revised approach to precipitation corrections that improves the precipitation climatology in Africa and the high-latitudes. Moreover, for system calibration the model is forced retrospectively with MERRA-2 reanalysis data, which are more consistent with the near-real time GEOS forward processing (FP) data used during the SMAP period than the retrospective GEOS data that were available for previous L4_SM versions. An analysis of the time-average surface and root zone soil moisture shows that the global pattern ofarid and humid regions is captured by the Version 4 L4_SM estimates. Owing to the changes in the landsurface modeling system, surface soil moisture is typically drier by several volumetric percent in Version 4 compared to Version 3, whereas root zone soil moisture is wetter in Version 4 in some regions and drierin others. Because of these climatological differences, the Version 3 and Version 4 products should not be combined into a single dataset for use in applications.Results from the core validation site comparisons indicate that Version 4 of the L4_SM data product meets the self-imposed L4_SM accuracy requirement, which is formulated in terms of the RMSE after removal of the long-term mean difference (ubRMSE). The overall ubRMSE of the 3-hourly L4_SM dataat the 9 km scale is 0.039 m3 m-3 for surface soil moisture and 0.029 m3 m-3 for root zone soil moisture,below the 0.04 m3 m-3 requirement. The L4_SM estimates are an improvement over estimates from a model-only Nature Run version 7.2 (NRv7.2), which demonstrates the beneficial impact of the SMAP brightness temperature data. Overall, L4_SM surface and root zone soil moisture estimates are more skillful than NRv7.2 estimates, with statistically significant improvements at the 5% level for surface soil moisture R and anomaly R values. Results from comparisons of the L4_SM product to i

Reichle, Rolf H.↗
NASA NTRS1981

Thermal IR exitance model of a plant canopy

A thermal IR exitance model of a plant canopy based on a mathematical abstraction of three horizontal layers of vegetation was developed. Canopy geometry within each layer is quantitatively described by the foliage and branch orientation distributions and number density. Given this geometric information for each layer and the driving meteorological variables, a system of energy budget equations was determined and solved for average layer temperatures. These estimated layer temperatures, together with the angular distributions of radiating elements, were used to calculate the emitted thermal IR radiation as a function of view angle above the canopy. The model was applied to a lodgepole pine (Pinus contorta) canopy over a diurnal cycle. Simulated vs measured radiometric average temperatures of the midcanopy layer corresponded with 2 C. Simulation results suggested that canopy geometry can significantly influence the effective radiant temperature recorded at varying sensor view angles.

Kimes, D. S.↗
NASA NTRS1991

Vegetation Canopies and Objects of Arbitrary Shapes: Computer Generation and Bidirectional Reflectance Calculations

A general computer graphics based model is presented for computer generation of objects of arbitrary shape and for calculating Bidirectional Reflectance Factor (BRF) and scattering from them, in the optical region. The computer generation uses a modified Lindemayer system (L system) approach. For rendering on a computer screen, the object is divided into polygons, and innovative computer graphics techniques are used to display the object and to calculate the scattering and reflectance from the object. The use of the technique is illustrated with scattering from canopies of simulated corn plants and from a snow covered mountain. The scattering is quantified using measures like BRF and albedo and by rendering the objects with brightness of each of the two facets of a polygon proportional to the amount of light scattered from the object in the viewer's direction.

Goel, Narenda S.↗
NASA NTRS2010

Diurnal and Directional Responses of Chlorophyll Fluorescence and the PRI in a Cornfield

Determining the health and vigor of vegetation using high spectral resolution remote sensing is an important goal which has application to monitoring agriculture and ecosystem productivity and carbon exchange. Two spectral indices used to assess whether vegetation is performing near-optimally or exhibiting symptoms of environmental stress (e.g., drought or nutrient deficiency, non-optimal temperatures, etc.) are the Photochemical Reflectance Index (PRI) and solar-induced red and far-red Chlorophyll Fluorescence (Fs). Both the PRI and Fs capture the dynamics of photoprotection mechanisms within green foliage: the PRI is based on the association of the reflected radiation in the green spectrum with the xanthophyll cycle, whereas Fs measures the emitted radiation in the red and far-red spectrum. Fs was determined from retrievals in the atmospheric oxygen absorption features centered at 688 and 760 nm using a modified Fraunhofer Line Depth (FLD) method. We previously demonstrated diurnal and seasonal PRI differences for sunlit vs. shaded foliage in a conifer forest canopy, as expressed in the hotspot and darkspot of the Bidirectional Reflectance Function (BRF). In a USDA-ARS experimental field site located in Beltsville, MD, USA, measurements were acquired over a corn crop from a nadir view in 2008 with an ASD FieldSpec Pro (Analytical Spectral Devices, Inc., Boulder, CO, USA) to study the behavior of the PRI for sunlit and shaded foliage as captured in reflectance variations associated with the BRF, in a I m tall canopy in the vegetative growth stage. Those observations were compared to simulations obtained from two radiative transfer models. Measurements were then acquired to examine whether the PRI and Fs were influenced by view zenith and azimuth geometries at different times of day. Those measurements were made in 2010 with the Ocean Optics USB4000 Miniature Fiber Optic Spectrometer (Ocean Optics Inc., Dunedin, Florida, USA) at several times during the day on multiple days throughout the growing season. We found that the PRI consistently had higher values, indicating lower stress, in the BRF darkspot associated with shaded foliage than in the hotspot associated with sunlit foliage. We also found that Fs exhibited differences associated with sunlit and shaded canopy sectors, which were most pronounced for the red/far-red Fs ratio. Values indicated greater physiological stress in afternoons compared to mornings, and in the early senescent canopy as compared to the vegetative growth stage, BRFs for both the PRI and the red/far-red Fs ratio were bowl-shaped for the full azimuth sweep of the canopy. These two spectral indices (PRI, Fs ratio) provided complementary information on the photosynthetic function of the corn canopy.

Middleton, Elizabeth↗
NASA NTRS1986

Radar scene generation for tactical decision aids

The Mueller matrix and polarization covariance matrix for polarimetric radar systems was studied. The clutter was modeled by a layer of random permittivity, described by a three-dimensional correlation function, with variance, and horizontal and vertical correlation lengths. This model was applied, using the wave theory with Born approximations carried to the second order, to find the backscattering elements of the polarimetric matrices. Theoretical predictions are matched with experimental data for vegetation fields. The strong fluctuation theory was used to derive the backscattering cross sections. A two-layer anisotropic random medium model was developed for the active and passive microwave remote sensing of ice fields. A three-layer random medium model was adopted to study the volume scattering effects for the active and passive microwave remote sensing of snow-covered ice fields.

Kong, J. A.↗
NASA NTRS1988

Use of LANDSAT images of vegetation cover to estimate effective hydraulic properties of soils

The estimation of the spatially variable surface moisture and heat fluxes of natural, semivegetated landscapes is difficult due to the highly random nature of the vegetation (e.g., plant species, density, and stress) and the soil (e.g., moisture content, and soil hydraulic conductivity). The solution to that problem lies, in part, in the use of satellite remotely sensed data, and in the preparation of those data in terms of the physical properties of the plant and soil. The work was focused on the development and testing of a stochastic geometric canopy-soil reflectance model, which can be applied to the physically-based interpretation of LANDSAT images. The model conceptualizes the landscape as a stochastic surface with bulk plant and soil reflective properties. The model is particularly suited for regional scale investigations where the quantification of the bulk landscape properties, such as fractional vegetation cover, is important on a pixel by pixel basis. A summary of the theoretical analysis and the preliminary testing of the model with actual aerial radiometric data is provided.

Eagleson, Peter S.↗
NASA NTRSDate not supplied

Influence of regional anthropogenic changes over Nile region on the climate system during the late Holocene (~2500 years before present)

The societal impacts of climate change during the late Holocene leads to regional anthropogenic changes over the Nile region floodplain and could have acted in tandem with natural factors like major volcanic eruptions on the regional climate system to magnify the local climatic impacts. This study aims to explore and investigate the sensitivity of climatic changes to the regional anthropogenic changes due to various factors over the Nile river floodplains during the late-Holocene (2.5K years before present). The GISS ModelE Earth system model will be used to simulate the various scenarios of regional increasing/decreasing river fraction, changes in vegetation type and cover, along with changes in land surface type against the no-changes scenario in absence of volcanic eruptions. The spatial coverage of the Nile river basin is estimated using the GIS shapefile based on elevation data from Shuttle Radar Topography Mission (SRTM) at 3 Arc-seconds (approx. 90-meter) horizontal resolution. The extent of flooding in the model grid (2.0°x2.5° in latitude and longitude) is estimated using the existing high-resolution (0.125°x0.125°) gridded topographic elevation information and mapped over the Nile river floodplains. This study also focuses on evaluating the NASA GISS ModelE for resolving the climate feedbacks and response on climate system due to anthropogenic changes and volcanic eruptions. It is also aimed to analyze and quantify the impact of various anthropogenic factors over the African monsoon system and rainfall over the region, which feeds the Nile River.

Anthropogenic changes↗
NASA NTRS2024

Assessing Acetone for the GISS ModelE2.1 Earth System Model

Acetone is an abundant volatile organic compound (VOC) in the atmosphere, with important influences on ozone and oxidation capacity. Direct sources include chemical production from other VOCs and anthropogenic emissions, terrestrial vegetation, biomass-burning emissions, and ocean production. Sinks include chemical loss, deposition onto the land surface, and ocean uptake. Acetone also has a lifetime that is long enough to allow transport and reactions with other compounds remote from its sources. The NASA Goddard Institute for Space Studies (GISS) Earth system model ModelE2.1 simulates a variety of Earth system interactions. Previously, acetone had a very simplistic representation in the ModelE chemical scheme. This study assesses a more sophisticated acetone scheme in which acetone is a full 3-dimensional tracer with explicit sources, sinks, and atmospheric transport. We first evaluate the new global acetone budget in the context of past literature. Estimated source and sink fluxes fall within the range of previous models, although total atmospheric burden and lifetime are at the lower end of the published literature. Acetone's new representation in ModelE2.1 also results in more realistic spatial and vertical distributions, which we compare against previous models and field observations. The seasonality of acetone-related processes was also studied in conjunction with field measurements, and these comparisons show promising agreement but also shortcomings at high-emission urban locations, where the model's resolution is too coarse to capture the true behavior. Finally, we conduct a variety of sensitivity studies that explore the influence of key parameters on the acetone budget and its global distribution. An impactful finding is that the production of acetone from precursor hydrocarbon oxidation has strong leverage on the overall chemical source, indicating the importance of accurate molar yields. Overall, our implementation is one that corroborates with previous studies and marks a significant improvement in the development of the acetone tracer in GISS ModelE2.1.

Acetone↗