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NASA NTRS1991

Climate and the equilibrium state of land surface hydrology parameterizations

For given climatic rates of precipitation and potential evaporation, the land surface hydrology parameterizations of atmospheric general circulation models will maintain soil-water storage conditions that balance the moisture input and output. The surface relative soil saturation for such climatic conditions serves as a measure of the land surface parameterization state under a given forcing. The equilibrium value of this variable for alternate parameterizations of land surface hydrology are determined as a function of climate and the sensitivity of the surface to shifts and changes in climatic forcing are estimated.

Entekhabi, Dara↗

NASA NTRS1993

Session on coupled land surface/hydrological/atmospheric models

The current model capabilities in the context of land surface interactions with the atmosphere include only one-dimensional characteristics of vegetation and soil surface heat, moisture, momentum, and selected other trace gas fluxes (e.g., CO2). The influence of spatially coherent fluxes that result from landscape heterogeneity were not included. Valuable representations of several aspects of the landscape pattern currently exist. These include digital elevation data and measures of the leaf area index (i.e., Normalized Difference Vegetation Index (NDVI) from Advanced Very High Resolution Radiometer (AVHRR) data). A major deficiency, however, is the lack of an ability to sample spatially representative shallow and (especially) deep soil moisture. Numerous mesoscale modeling and observed studies demonstrated the sensitivity of planetary boundary layer structure and deep convection to the magnitude of the surface moisture flux.

Pielke, Roger↗

NASA NTRS2012

Evaluating the Contribution of NASA Remotely-Sensed Data Sets on a Convection-Allowing Forecast Model

The Short-term Prediction Research and Transition (SPoRT) Center is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service forecast offices. SPoRT provides real-time NASA products and capabilities to help its partners address specific operational forecast challenges. One challenge that forecasters face is using guidance from local and regional deterministic numerical models configured at convection-allowing resolution to help assess a variety of mesoscale/convective-scale phenomena such as sea-breezes, local wind circulations, and mesoscale convective weather potential on a given day. While guidance from convection-allowing models has proven valuable in many circumstances, the potential exists for model improvements by incorporating more representative land-water surface datasets, and by assimilating retrieved temperature and moisture profiles from hyper-spectral sounders. In order to help increase the accuracy of deterministic convection-allowing models, SPoRT produces real-time, 4-km CONUS forecasts using a configuration of the Weather Research and Forecasting (WRF) model (hereafter SPoRT-WRF) that includes unique NASA products and capabilities including 4-km resolution soil initialization data from the Land Information System (LIS), 2-km resolution SPoRT SST composites over oceans and large water bodies, high-resolution real-time Green Vegetation Fraction (GVF) composites derived from the Moderate-resolution Imaging Spectroradiometer (MODIS) instrument, and retrieved temperature and moisture profiles from the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI). NCAR's Model Evaluation Tools (MET) verification package is used to generate statistics of model performance compared to in situ observations and rainfall analyses for three months during the summer of 2012 (June-August). Detailed analyses of specific severe weather outbreaks during the summer will be presented to assess the potential added-value of the SPoRT datasets and data assimilation methodology compared to a WRF configuration without the unique datasets and data assimilation.

Zavodsky, Bradley T.↗

DOE OSTI2021

Historical global Earth System Model simulations with E3SM's dynamic root module

This data package contains global-scale Earth System Model simulations run with DOE's E3SM Model. The package includes one set of simulations run in the default configuration and a second set of simulations run with the dynamic root module enabled. These two datasets can be used to assess the impact that dynamic roots have on Land Surface fluxes such as carbon and water. The outputs are provided here on a 0.5 x 0.5 global grid at monthly resolution. The simulations were run with atmospheric forcing from the Global Soil Wetness Project. We provide specifically here Gross Primary Production, Transpiration, relative root fraction per soil layer as well as Air Temperature, Precipitation and all the parameterizations used for the simulations. Our purpose for generating and analyzing these simulations was to assess the role that root dynamics and foraging for water has in the recovery timescale of ecosystems following climate perturbation. All data provided are in the "netcdf" format using standard CF-1 (Climate and Forecast) Convention. The data are broken up into 20 year chunks to facilitate easier read-in. The data are all machine readable using various software platforms including Matlab, NCO, Panoply and GrADS.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Science Plan for the Deployment of the Third ARM Mobile Facility to the Southeastern United States at the Bankhead National Forest, Alabama (AMF3 BNF)

In 2018, the U.S. Department of Energy (DOE) held a workshop for the Atmospheric Radiation Measurement (ARM) (Mather and Voyles 2013) user facility to discuss critical climate challenges and locations where key ARM Mobile Facility (AMF) observational assets could impact Earth system modeling (ESM). As an outcome, the southeast United States (SE U.S.) was identified as a high-priority region to target climate-process studies that promote a deeper understanding of the climate system and bolster ARM interactions with the community to drive ESM advancement. The DOE ARM user facility is a globally recognized leader in deploying and operating strategically located observation sites around the world for studying the properties of aerosols and clouds and their interaction with radiation, precipitation, and the Earth’s surface. In partnering with the DOE Atmospheric System Research (ASR) program, ARM solicited a multi-agency Site Science Team approach to provide input and close interaction with ARM management towards a successful SE U.S. deployment of the ARM third Mobile Facility (AMF3) (Miller et al. 2016). These efforts included identifying key locations, science drivers and instruments, and measurement strategies to address the wider climate-process needs and ESM improvement. Community input served a vital role in establishing, refining, and informing the relevant drivers and decisions regarding this AMF3 deployment. The team has identified Northern Alabama (N. AL) as regionally representative to unlock the key opportunities that will improve our understanding and model representation of aerosol, cloud, and land surface processes and their couplings in the SE U.S. A defining aspect of the AMF3 deployment is its commitment to long-term (anticipated five-year) observations to mitigate potential seasonal-to-annual variability that often limits appropriate attribution of phenomena to local or larger-scale processes. The proposed location may leverage nearby surface networks and multi-agency and partner assets to enrich this multi-year deployment. One motivation is to understand the role of spatiotemporal variability (thermodynamic, land-surface) across aspects of the climate system, with our AMF3 team anticipating future demands on characterizing the relationships between local-to-regional cloud development and surface processes across a diverse patchwork of natural, managed, and urban landscapes as found throughout the N. AL regions. The main site targets an intact, representative, forested region – the Bankhead National Forest (BNF) – underscoring further team commitment to regionally important land atmosphere two-way interactive studies “from the canopy to the clouds”, with enhanced tower instrumentation augmenting traditional ARM capabilities adjacent to this site. Multiple supplemental sites will also be distributed across this region, prioritizing added needs for biodiversity. Anticipated high-priority cloud science themes will target N. AL as a regional SE U.S. hotbed for high-impact weather, convective cloud onset, and shallow to-deep cloud transitioning. Anticipated aerosol drivers will focus on chemical processes that control the evolution of organic aerosol, the seasonality and spatial distribution of water vapor and particle-phase water, and its role on aerosol optical properties. Anticipated land atmosphere drivers consider the two-way feedbacks between surface influence on aerosols, clouds, and precipitation properties and the associated radiative impacts on plant physiology and canopy-scale fluxes. Emphasis will include the study of the impact of surface processes on aerosols via precursor emission, and on clouds via moisture flux and thermal development.

Doppler lidar, aerosols, convection↗

NASA NTRS2006

Spatially Complete Global Surface Albedos Derived from Terra/MODIS Data

Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. , Over five years of land surface anisotropy, diffuse bihemispherical (white-sky) albedo and direct beam directional hemispherical (black-sky) albedo from observations acquired by the MODIS instruments aboard NASA s Terra and Aqua satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal information on the land surface s radiative characteristics. However, roughly 30% of the global land surface, on an annual equal-angle basis, is obscured due to persistent and transient cloud cover, while another 207% is obscured due to ephemeral and seasonal snow effects. This precludes the MOD43B3 albedo products from being directly used in some remote sensing and ground-based applications, climate models, and global change research projects. To provide researchers with the requisite spatially complete global snow-free land surface albedo dataset, an ecosystem-dependent temporal interpolation technique was developed to fill missing or lower quality data and snow covered values from the official MOD43B3 dataset with geophysically realistic values. The method imposes pixel-level and local regional ecosystem-dependent phenological behavior onto retrieved pixel temporal data in such a way as to maintain pixel-level spatial and spectral detail and integrity. The phenological curves are derived from statistics based on the MODIS MOD12Q1 IGBP land cover classification product geolocated with the MOD43B3 data.

King, Michael D.↗

NASA NTRS2011

Design and Impacts of Land-Biogenic-Atmosphere Coupling in the NASA-Unified WRF (NU-WRF) Modeling System

Land-Atmosphere coupling is typically designed and implemented independently for physical (e.g. water and energy) and chemical (e.g. biogenic emissions and surface depositions)-based models and applications. Differences in scale, data requirements, and physics thus limit the ability of Earth System models to be fully coupled in a consistent manner. In order for the physical-chemical-biological coupling to be complete, treatment of the land in terms of surface classification, condition, fluxes, and emissions must be considered simultaneously and coherently across all components. In this study, we investigate a coupling strategy for the NASA-Unified Weather Research and Forecasting (NU-WRF) model that incorporates the traditionally disparate fluxes of water and energy through NASA's LIS (Land Information System) and biogenic emissions through BEIS (Biogenic Emissions Inventory System) and MEGAN (Model of Emissions of Gases and Aerosols from Nature) into the atmosphere. In doing so, inconsistencies across model inputs and parameter data are resolved such that the emissions from a particular plant species are consistent with the heat and moisture fluxes calculated for that land cover type. In turn, the response of the atmospheric turbulence and mixing in the planetary boundary layer (PBL) acts on the identical surface type, fluxes, and emissions for each. In addition, the coupling of dust emission within the NU-WRF system is performed in order to ensure consistency and to maximize the benefit of high-resolution land representation in LIS. The impacts of those self-consistent components on' the simulation of atmospheric aerosols are then evaluated through the WRF-Chem-GOCART (Goddard Chemistry Aerosol Radiation and Transport) model. Overall, this ambitious project highlights the current difficulties and future potential of fully coupled. components. in Earth System models, and underscores the importance of the iLEAPS community in supporting improved knowledge of processes and innovative approaches for models and observations.

Tan, Qian↗

DOE OSTI2026

CMIP7 data request: land and land ice priorities and opportunities

The Land and Land Ice Theme in the Coupled Model Intercomparison Project Phase 7 (CMIP7) represents the current understanding of physical processes in land surface ecosystems, hydrology, cryosphere, and their physical interactions with other Earth system components. Simulations from Earth system models (ESMs) could provide crucial information for assessing planetary safety, such as critical tipping elements, and be used to inform climate risks for improving climate impact assessments and policy decisions. This paper presents a collaborative effort to identify scientific opportunities in the Land and Land Ice Theme of the CMIP7 Data Request. The proposed opportunities build upon advances in ESMs, including new freshwater system and land ice processes being included in CMIP7, as well as the scientific community's demand for high-frequency and sub-grid-scale land surface outputs. In total, 25 variable groups that contain 716 variables have been identified to be potentially available to the broad scientific audience for performing analysis in land–atmosphere coupling, hydrological processes and freshwater systems, glacier and ice sheet mass balance and their influence on the sea levels, land use, and plant phenology. Key reflections from this data request effort include advocacy for closer engagement between the user community and modeling groups, reduction in the technical barriers to tracking existing parameters and defining new variables, and more streamlined variable management. These will be essential to enhance the usability and reliability of CMIP7 outputs for climate and Earth system research and applications to a broad audience that relies on the CMIP7 endeavor.

Li, Yue [Univ. of California, Los Angeles, CA (Uni↗

NASA NTRS1993

Scaling, soil moisture and evapotranspiration in runoff models

The effects of small-scale heterogeneity in land surface characteristics on the large-scale fluxes of water and energy in the land-atmosphere system has become a central focus of many of the climatology research experiments. The acquisition of high resolution land surface data through remote sensing and intensive land-climatology field experiments (like HAPEX and FIFE) has provided data to investigate the interactions between microscale land-atmosphere interactions and macroscale models. One essential research question is how to account for the small scale heterogeneities and whether 'effective' parameters can be used in the macroscale models. To address this question of scaling, the probability distribution for evaporation is derived which illustrates the conditions for which scaling should work. A correction algorithm that may appropriate for the land parameterization of a GCM is derived using a 2nd order linearization scheme. The performance of the algorithm is evaluated.

Wood, Eric F.↗

DOE OSTI2024

Model output from simulations of manganese-carbon interactions in temperate forest soil profiles

This archive contains model output, code, and scripts for simulations of coupled manganese-carbon cycling in temperate forest soil profiles. These model results were generated as part of a study investigating how manganese availability influences soil organic carbon stocks and demonstrating a new model framework for coupling carbon and manganese cycling. The simulations were in support of a manuscript: "Modeling interactive effects of manganese bioavailability, nitrogen deposition, and warming on soil carbon storage." The study addresses the research questions: How does Mn bioavailability, as driven by subsurface mineral properties, pH, and redox status, affect temperate forest soil organic carbon and litter carbon stocks?How is the relationship between Mn bioavailability and carbon cycling affected by changes in temperature and nitrogen deposition?"Model simulations were conducted in a reactive transport modeling framework using PFLOTRAN coupled to python. Multiple model simulations testing different Mn-bearing mineral solubilities, hydrological patterns, nitrogen deposition rates, and temperatures are included. Soil properties, including total and exchangeable Mn concentrations, are based on values reported for the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO), a temperate forested watershed in central Pennsylvania, U.S.A where Mn cycling through vegetation has been documented.File formats include netCDF (.nc), python script (.py), shell script (.sh), plain text PFLOTRAN input file (.in), and plain text PFLOTRAN database file (.dat), and gzipped tar archive (tar.gz).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Changes in Precipitation and Air Temperature Contribute Comparably to Permafrost Degradation in a Warmer Climate: Modeling Archive

The dataset contains "ecosys" model outputs reported in Mekonnen et al. (2021) to examine the importance of heat transfer from precipitation on permafrost degradation. The study highlighted the importance of mechanistically representing this process in earth system models (ESMs) and demonstrated that precipitation is as important an environmental control on permafrost degradation as surface air temperature. Included are (1) the modeled spatially averaged annual active layer depth (ALD) and daily maximum soil temperature across the North Slope of Alaska from 1980 to 2100, and (2) 25 km resolution modeled ALD for averaged for two time intervals, 2006 - 2010 and 2096 - 2100. The results are provided for two "ecosys" simulations: S1 with precipitation heat transfer and S2 without precipitation heat transfer across the North Slope of Alaska. These data are available in a NetCDF and csv data formats. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2021

Investigations on the Anthropogenic Reversal of the Natural Ozone Gradient Between Northern and Southern Midlatitudes

Our quantitative understanding of natural tropospheric ozone concentrations is limited by the paucity of reliable measurements before the 1980s. We utilize the existing measurements to compare the long-term ozone changes that occurred within the marine boundary layer at northern and southern midlatitudes. Since 1950 ozone concentrations have increased by a factor of 2.1 ± 0.2 in the Northern Hemisphere (NH) and are presently larger than in the Southern Hemisphere (SH), where only a much smaller increase has occurred. These changes are attributed to increased ozone production driven by anthropogenic emissions of photochemical ozone precursors that increased with industrial development. The greater ozone concentrations and increases in the NH are consistent with the predominant location of anthropogenic emission sources in that hemisphere. The available measurements indicate that this interhemispheric gradient was much smaller and was likely reversed in the pre-industrial troposphere with higher concentrations in the SH. Six Earth system model (ESM) simulations indicate similar total NH increases (1.9 with a standard deviation of 0.3), but they occurred more slowly over a longer time period, and the ESMs do not find higher pre-industrial ozone in the SH. Several uncertainties in the ESMs may cause these model–measurement disagreements: the assumed natural nitrogen oxide emissions may be too large, the relatively greater fraction of ozone injected by stratosphere–troposphere exchange to the NH may be overestimated, ozone surface deposition to ocean and land surfaces may not be accurately simulated, and model treatment of emissions of biogenic hydrocarbons and their photochemistry may not be adequate.

natural tropospheric ozone concentrations↗

DOE OSTI2021

Simulation of radon-222 with the GEOS-Chem global model: Emissions, seasonality, and convective transport

Radon-222 (222Rn) is a short-lived radioactive gas naturally emitted from land surface, and has long been used to assess convective transport in atmospheric models. In this study, we simulate 222Rn using the GEOS-Chem chemical transport model with aims to improve our understanding of 222Rn emissions and surface concentration seasonality, and to characterize convective transport associated with two Goddard Earth Observing System (GEOS) meteorological products, MERRA and GEOS-FP. We evaluate four available 222Rn emission scenarios by comparing model results with surface observations at 51 global surface sites. The default emission scenario in GEOS-Chem yields a moderate agreement with global surface observations (< 70% data within a factor of 2) and a large underestimate of wintertime surface 222Rn concentrations at Northern Hemisphere mid- and high-latitudes due to an oversimplified formulation of 222Rn emission fluxes (1 atom cm-2 s-1 over land with a reduction by a factor of 3 under freezing conditions). We compose a new global 222Rn emission scenario based on Zhang et al. (2011) and show its potential to improve simulated surface 222Rn concentrations and seasonality. The regional components of this emission scenario include spatially and temporally varying emission fluxes derived from previous measurements of soil radium content and soil exhalation models, which are key factors to 222Rn emission flux rates. However, large model underestimates of surface 222Rn concentrations still exist in Asia, suggesting unusually high regional 222Rn emissions. We propose a conservative up-scaling factor of 1.2 for 222Rn emission fluxes in China, as also constrained by the observed deposition fluxes of 210Pb (decay daughter of 222Rn). With this modification, the model shows better agreement with the observations in Europe and North America (>80% data within a factor of 2), and reasonable agreement in Asia (close to 70%). Further constraints on 222Rn emissions would require additional observations of surface 222Rn concentrations and emission fluxes in central U.S., Canada, Africa, and Asia. We also compare and assess convective transport in model simulations driven by MERRA and GEOS-FP using observed 222Rn vertical profiles during northern mid-latitude summertime and from two short-term airborne campaigns. While the simulations with both GEOS products are able to capture the observed vertical gradient of 222Rn concentrations in the lower troposphere (0-4 km), neither correctly represents the level of convective detrainment, resulting in biases in the middle and upper troposphere. Compared to GEOS-FP, MERRA leads to stronger convective transport of 222Rn, which is partially compensated by its weaker large-scale vertical advection, resulting in similar global vertical distributions of 222Rn concentrations between the two simulations.

Zhang, Bo↗

NASA NTRS1993

Application of the target decomposition theorem to a polarimetric random media model

With advances in polarimetric radar measurements of land surfaces, the need for understanding the underlying scattering mechanisms and dominant target features has become the focus of many studies. In particular, the maximum use of the polarimetric information to identify and/or separate parameters related to the surface features such as vegetation thickness, structure, water content, and soil surface characteristics will enhance the possibility of using polarimetric radars for monitoring the earth's surface from space. In this paper, Cloude's decomposition theorem is applied to a polarimetric random media model to simulate the radar measurements of vegetated canopies. The vegetated canopies are modeled as a three layer discrete random medium with leaves and branches in the first layer, tree trunks in the second layer, and a half space of homogeneous ground with rough interface as the bottom layer. The distorted born approximation (DBA) has been used to compute full Mueller matrix of the canopy, using canonical dielectric objects such as thin discs and cylinders as leaves, branches, and trunks, respectively. The Mueller matrix and the derived covariance matrix contain information on the second order statistics of radar signals at various polarizations from the canopy. To decompose the covariance matrix to its constituent targets, the eigenvalues and eigenvectors of the covariance matrix are computed in terms of the physical parameters of the canopy. In addition, each eigenvector explicitly shows the scattering mechanisms such as odd and even reflections in the canopy. Cloude's decomposition theorem is applied using the Pauli spin matrices as a basis and an expression for the degree of disorder or the entropy for the vegetated surface is found. Then, the physical parameters estimated from in situ measurements are used in the random media to obtain realistic covariance matrices. As a result, the sensitivity of the eigenvalue spectrums and the coefficients resulting from the target decomposition theorem to the physical parameters of the canopy are examined and the possible use of Cloude's theorem to estimate vegetation and soil parameters is discussed.

Saatchi, Sasan S.↗

DOE OSTI2024

An extensible perturbed parameter ensemble for the Community Atmosphere Model version 6

This paper documents the methodology and preliminary results from a perturbed parameter ensemble (PPE) technique, where multiple parameters are varied simultaneously and the parameter values are determined with Latin hypercube sampling. This is done with the Community Atmosphere Model version 6 (CAM6), the atmospheric component of the Community Earth System Model version 2 (CESM2). We apply the PPE method to CESM2–CAM6 to understand climate sensitivity to atmospheric physics parameters. The initial simulations vary 45 parameters in the microphysics, convection, turbulence and aerosol schemes with 263 ensemble members. These atmospheric parameters are typically the most uncertain in many climate models. Control simulations and targeted simulations to understand climate forcing due to aerosols and fast climate feedbacks are analyzed. The use of various emulators is explored in the multi-dimensional space mapping input parameters to output metrics. Parameter impacts on various model outputs, such as radiation, cloud and aerosol properties, are evaluated. Machine learning is also used to probe optimal parameter values against observations. Our findings show that PPE is a valuable tool for climate uncertainty analysis. Furthermore, by varying many parameters simultaneously, we find that many different combinations of parameter values can produce results consistent with observations, and thus careful analysis of tuning is important. The CESM2–CAM6 PPE is publicly available and extensible to other configurations to address questions of other model processes in the atmosphere and other model components (e.g., coupling to the land surface).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1991

Comparison of ground and satellite based measurements of the fraction of photosynthetically active radiation intercepted by tall-grass prairie

The fraction, of photosynthetically active radiation intercepted by vegetation, F(sub ipar) is an important parameter for modeling the interactions between the land-surface and atmosphere and for estimating vegetation biomass productivity. This study was; therefore, an integral part of FIFE. The specific purpose of this experiment was to find out how well definitive measurements of F(sub ipar) on the ground relate to near-ground and satellite based spectral reflectance measurements. Concurrent measurements of F(sub ipar) and ground, helicopter, and satellite based reflectance measurements were taken at thirteen tall-grass prairie sites within the FIFE experimental area. The sites were subjected to various combinations of burning and grazing managements. The ground and helicopter based reflectance measurements were taken on the same day or few days from the time of the overpass of LANDSAT and SPOT satellites. Ground-based reflectance measurements and sun photometer readings taken at the times of the satellite overpasses were used to correct for atmospheric attenuation. Hand-held radiometer spectral indices were strongly correlated with helicopter and satellite based values (r=0.94 for helicopter, 0.93 for LANDSAT Thematic Mapper, and 0.86 for SPOT). However, the ground, helicopter, and satellite based normalized difference spectral vegetation indices showed low sensitivity to changes in F(sub ipar). Reflectance measurements were only moderately well correlated with measurements of F(sub ipar) (r=0.82 for hand-held radiometer, 0.84 for helicopter measurements, and 0.75 for the LANDSAT Thematic Mapper and SPOT). Improved spectral indices which can compensate for site differences are needed in order to monitor F(sub ipar) more reliably.

Demetriades-Shah, T. H.↗

NASA NTRS1992

Comparison of ground and satellite based measurements of the fraction of photosynthetically active radiation intercepted by tall-grass prairie

The fraction of photosynthetically active radiation intercepted by vegetation, F(sub ipar) is an important parameter for modeling the interactions between the land-surface and atmosphere and for estimating vegetation biomass productivity. This study was, therefore, an integral part of FIFE. The specific purpose of this experiment was to find out how well definitive measurements of F(sub ipar) on the ground relate to near-ground and satellite based spectral reflectance measurements. Concurrent measurements of F(sub ipar) and ground, helicopter, and satellite based reflectance measurements were taken at thirteen tall-grass prairie sites within the FIFE experimental area. The sites were subjected to various combinations of burning and grazing managements. The ground and helicopter based reflectance measurements were taken on the same day or few days from the time of the overpass of LANDSAT and SPOT satellites. Ground-based reflectance measurements and sun photometer readings taken at the times of the satellite overpasses were used to correct for atmospheric attenuation. Hand-held radiometer spectral indices were strongly correlated with helicopter and satellite based values (r = 0.94 for helicopter, 0.93 for LANDSAT Thematic Mapper, and 0.86 for SPOT). However, the ground, helicopter, and satellite based normalized difference spectral vegetation indices showed low sensitivity to changes in F(sub ipar). Reflectance measurements were only moderately well correlated with measurements of F(sub ipar) (r = 0.82 for hand-held radiometer, 0.84 for helicopter measurements, and 0.75 for the LANDSAT Thematic Mapper and SPOT). Improved spectral indices which can compensate for site differences are needed in order to monitor F(sub ipar) more reliably.

Demetriades-Shah, T. H.↗

NASA NTRS1992

A comparative analysis of two land surface heterogeneity representations

Two contrasting representations of land surface variability used in general circulation models (GCMs) are compared through an analysis of their corresponding surface energy balance equations. In one representation (the 'mixture' approach), different vegetation types are assumed to be homogeneously mixed over a grid square, so that the GCM atmosphere sees near-surface conditions pertaining to the mixture only. In the second representation (the 'mosaic' approach), different vegetation types are viewed as separate 'tiles' of a grid-square 'mosaic', and each tile interacts with the atmosphere independently. The mosaic approach is computationally simpler and in many ways more flexible than the mixture approach. Analytical solutions to the linearized energy balance equations and numerical solutions to the nonlinear equations both demonstrate that the mixture strategy, when applied to two coexisting vegetation types that differ only in canopy transpiration resistance, promotes both total turbulent flux and latent heat flux relative to the mosaic strategy. The effective differences between the strategies, however, are small over a wide range of conditions. In particular, the strategies are effectively equivalent when the transpiration resistances of the different vegetation types are of the same order of magnitude.

Koster, Randal D.↗