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At least 37 records · Page 2

Soil Respiration Phenology Improves Modeled Phase of Terrestrial Net Ecosystem Exchange in Northern Hemisphere

In the northern hemisphere, terrestrial ecosystems transition from net sources of CO2 to the atmosphere in winter to net ecosystem carbon sinks during spring. The timing (or phase) of this transition, determined by the balance between ecosystem respiration (RECO) and primary production, is key to estimating the amplitude of the terrestrial carbon sink. We diagnose an apparent phase bias in the RECO and net ecosystem exchange (NEE) seasonal cycles estimated by the Terrestrial Carbon Flux (TCF) model framework and investigate its link to soil respiration mechanisms. Satellite observations of vegetation canopy conditions, surface meteorology, and soil moisture from the NASA SMAP Level 4 Soil Moisture product are used to model a daily carbon budget for a global network of eddy covariance flux towers. Proposed modifications to TCF include: the inhibition of foliar respiration in the light (the Kok effect); a seasonally varying litterfall phenology; an O2 diffusion limitation on heterotrophic respiration (RH); and a vertically resolved soil decomposition model. We find that RECO phase bias can result from bias in RECO magnitude and that mechanisms which reduce northern spring RECO, like substrate and O2 diffusion limitations, can mitigate the phase bias. A vertically resolved soil decomposition model mitigates this bias by temporally segmenting and lagging RH. Applying these model enhancements at Continuous Soil Respiration (COSORE) sites verifies their improvement of RECO and NEE skill compared to in situ observations (up to ∆RMSE = −0.76 g C m−2 d −1 35 ). Ultimately, these mechanisms can improve prior estimates of NEE for atmospheric inversion studies.

Soil respiration↗

The SMAP Level 4 Carbon PRODUCT for Monitoring Terrestrial Ecosystem-Atmosphere CO2 Exchange

The NASA Soil Moisture Active Passive (SMAP) mission Level 4 Carbon (L4_C) product provides model estimates of Net Ecosystem CO2 exchange (NEE) incorporating SMAP soil moisture information as a primary driver. The L4_C product provides NEE, computed as total respiration less gross photosynthesis, at a daily time step and approximate 14-day latency posted to a 9-km global grid summarized by plant functional type. The L4_C product includes component carbon fluxes, surface soil organic carbon stocks, underlying environmental constraints, and detailed uncertainty metrics. The L4_C model is driven by the SMAP Level 4 Soil Moisture (L4_SM) data assimilation product, with additional inputs from the Goddard Earth Observing System, Version 5 (GEOS-5) weather analysis and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. The L4_C data record extends from March 2015 to present with ongoing production. Initial comparisons against global CO2 eddy flux tower measurements, satellite Solar Induced Canopy Florescence (SIF) and other independent observation benchmarks show favorable L4_C performance and accuracy, capturing the dynamic biosphere response to recent weather anomalies and demonstrating the value of SMAP observations for monitoring of global terrestrial water and carbon cycle linkages.

SMAP↗

BOREAS TGB-3 Plant Species Composition Data over the NSA Fen

The BOReal Ecosystem-Atmosphere Study Trace Gas Biogeochemistry (BOREAS TGB-3) team collected several data sets that contributed to understanding the measured trace gas fluxes over sites in the Northern Study Area (NSA). This data set contains information about the composition of plant species that were within the collars used to measure Net Ecosystem Exchange of CO2 (NEE). The species composition was identified to understand the differences in NEE among the various plant communities in the NSA fen. The data were collected in July of 1994 and 1996. The data are contained in comma-delimited, ASCII files.

Bubier, Jill L.↗

Simulating Forest Dynamics of Lowland Rainforests in Eastern Madagascar

Ecological modeling and forecasting are essential tools for the understanding of complex vegetation dynamics. The parametric demands of some of these models are often lacking or scant for threatened ecosystems, particularly in diverse tropical ecosystems. One such ecosystem and also one of the world's biodiversity hotspots, Madagascar's lowland rainforests, have disappeared at an alarming rate. The processes that drive tree species growth and distribution remain as poorly understood as the species themselves. We investigated the application of the process-based individual-based FORMIND model to successfully simulate a Madagascar lowland rainforest using previously collected multi-year forest inventory plot data. We inspected the model's ability to characterize growth and species abundance distributions over the study site, and then validated the model with an independently collected forest-inventory dataset from another lowland rainforest in eastern Madagascar. Following a comparative analysis using inventory data from the two study sites, we found that FORMIND accurately captures the structure and biomass of the study forest, with r(squared) values of 0.976, 0.895, and 0.995 for 1:1 lines comparing observed and simulated values across all plant functional types for aboveground biomass (tonnes/ha), stem numbers, and basal area (m(squared)/ha), respectively. Further, in validation with a second study forest site, FORMIND also compared well, only slightly over-estimating shade-intermediate species as compared to the study site, and slightly under-representing shade-tolerant species in percentage of total aboveground biomass. As an important application of the FORMIND model, we measured the net ecosystem exchange (NEE, in tons of carbon per hectare per year) for 50 ha of simulated forest over a 1000-year run from bare ground. We found that NEE values ranged between 1 and -1 t Cha(exp -1)year(exp -1), consequently the study forest can be considered as a net neutral or a very slight carbon sink ecosystem, after the initial 130 years of growth. Our study found that FORMIND represents a valuable tool toward simulating forest dynamics in the immensely diverse Madagascar rainforests.

Forest Productivity↗

Reconciling Carbon-cycle Processes from Ecosystem to Global Scales

Understanding carbon (C) dynamics from ecosystem to global scales remains a challenge. Although expansion of global carbon dioxide (CO2) observatories makes it possible to estimate C-cycle processes from ecosystem to global scales, these estimates do not necessarily agree. At the continental US scale, only 5% of C fixed through photosynthesis remains as net ecosystem exchange (NEE), but ecosystem measurements indicate that only 2% of fixed C remains in grasslands, whereas as much as 30% remains in needleleaf forests. The wet and warm Southeast has the highest gross primary productivity and the relatively wet and cool Midwest has the highest NEE, indicating important spatial mismatches. Newly available satellite and atmospheric data can be combined in innovative ways to identify potential C loss pathways to reconcile these spatial mismatches. Independent datasets compiled from terrestrial and aquatic environments can now be combined to advance C-cycle science across the land–water interface.

carbon cycle↗

Development of Carbon Flux Model Using ABI Data Over the Conterminous US

The satellite-driven carbon flux estimation has been playing important role to estimate continental-scale carbon budget. One of the biggest recent advances in the satellite-driven carbon flux modeling is utilization of high-frequent geostationary satellites to estimate diurnal cycle in carbon fluxes. The satellite based carbon flux estimation used the polar orbiting satellite sensors (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)), which allow us to observe target regions only once during the day. The new generation of geostationary satellite sensors provide frequent observations, often less than every 10 minutes. Here, we use GOES Advanced Baseline Imager (ABI) data to estimate hourly NEE over the conterminous US. We used the Terrestrial Observation Prediction System (TOPS) model for estimating hourly NEE. TOPS is a diagnostic ecosystem process model that simulates the fluxes of carbon and water through vegetation in response to climate variability. For the climate input, we developed hourly climate data using the same algorithm with NASA Earth Exchange Gridded Daily Meteorology (NEX-GDM) datasets based on machine learning techniques. The hourly climate data includes precipitation, maximum temperature, minimum temperature, dew point temperature, and solar radiation were derived from the Geostationary observations. The spatial patterns of ecosystem parameters used in TOPS are optimized using satellite Solar Induced Fluorescence (SIF) data. The high frequency GPP estimations from geostationary satellite sensors make it comparable to the instantaneous SIF data than daily GPP. We also used Ameriflux data for optimization of model parameters and the validation of the output. The derived data addresses the diurnal dynamics of carbon cycling at large scales and should help in reducing the uncertainties in carbon budget studies.

geostationary satellite↗

Force-free electromagnetic pulses in a laboratory plasma

A short, intense current pulse is drawn from an electrode immersed in a magnetized afterglow plasma. The induced magnetic field B(r,t) assumes the shape of a helical double vortex which propagates along B(0) through the uniform plasma as a whistler mode. The observations support a prediction of force-free (J x B + neE = 0) electromagnetic fields and solitary waves. Energy and helicity are approximately conserved.

Stenzel, R. L.↗

Application of remote sensing in regional scale estimates of vegetation carbon budgets: The Belfix project

A concept for coupling the remote sensing derived fraction of the absorbed photosynthetic active radiation (FAPAR) with a functional ecosystem model was developed. The study was named the Belfix procedure. The quantification of changes in carbon dynamics at the ecosystem level is a key issue in studies of global climatic change effects at the vegetation atmosphere interface. An operational procedure, for the determination of carbon fluxes at the regional scale (Belgian territory), is presented. The approach allows for the determination of the sink function of vegetation for carbon (dioxide). The phyto- and litter mass, photosynthetic assimilation, autotroph and heterotroph carbon fluxes and net ecosystem exchange (NEE) of carbon, were evaluated. The results suggest that a single solution can be obtained for ecosystem rates and states, applying an iterative procedure, based on minimizing the change in maximal seasonal green phytomass in function of yearly FAPAR temporal profiles. Total phytomass values obtained are in close range with those obtained by ground sampling.

Veroustraete, Frank↗

BOREAS TE-19 Ecosystem Carbon Balance Model

The BOREAS TE-19 team developed a model called the Spruce and Moss Model (SPAM) designed to simulate the daily carbon balance of a black spruce/moss boreal forest ecosystem. It is driven by daily weather conditions, and consists of four components: (1) soil climate, (2) tree photosynthesis and respiration, (3) moss photosynthesis and respiration, and (4) litter decomposition and associated heterotrophic respiration. The model simulates tree gross and net photosynthesis, wood respiration, live root respiration, moss gross and net photosynthesis, and heterotrophic respiration (decomposition of root litter, young needle and moss litter, and humus). These values can be combined to generate predictions of total site net ecosystem exchange of carbon (NEE), total soil dark respiration (live roots + heterotrophs + live moss), spruce and moss net productivity, and net carbon accumulation in the soil. To date, simulations have been of the BOREAS NSA-OBS and SSA-OBS tower sites, from 1968-95 (except 1990-93). The files include source code and sample input and output files in ASCII format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).

Hall, Forrest G.↗

Large-Aperture [O I] 6300 A Photometry of Comet Hale-Bopp: Implications for the Photochemistry of OH

Large-aperture photometric observations of comet Hale-Bopp (C/1995 O1) in the forbidden red line of neutral oxygen ([O I] 6300 angstroms) with the 150 mm dual-etalon Fabry-Perot spectrometer that comprises the Wisconsin H-alpha Mapper and a 50 mm dual-etalon Fabry-Perot spectrometer at the McMath-Pierce main telescope from 1997 late February to mid April yield a total metastable O((sup 1)D) production rate of (2.3-5.9) x 10(exp 30)/s. Applying the standard H2O and OH photodissociation branching ratios, we derive a water production rate, Q(H2O), of (2.6-6.1) x 10(exp 31)/s, which disagrees with Q(H2O = 1x10(exp 31)/s determined by independent H2O, OH, and H measurements. Furthermore, our own [O I] 6300 observations of the inner coma (< 30,000 km) using the 3.5 m Wisconsin-Indiana-Yale-NOAO telescope Hydra and Densepak multi-object spectrographs yield Q(H2O) = 1 x 10(exp 31)/s. Using our [O I] 6300 data, which cover spatial scales ranging from 2,000 to 1x10(exp 6) km, and a complementary set of wide-field ground-based OH images, we can constrain the sources of the apparent excess O((sup 1)D) emission to the outer coma, where photodissociation of OH is assumed to be the dominant O((sup 1)D) production mechanism. From production rates of other oxygen-bearing volatiles (e.g., CO and CO2), we can account for at most 30% of the observed excess O((sup 1)D) emission. Since even less O((sup 1)D) should be coming from other sources (e.g., electron excitation of neutral O and distributed nonnuclear sources of H2O), we hypothesize that the bulk of the excess O((sup 1)D) is likely coming from photodissociating OH. Using the experimental OH photo-dissociation cross section of Nee and Lee at Ly-alpha as a guide in modifying the theoretical OH cross sections of van Dishoeck and Dalgarno, we can account for approximately 60% of the observed O((sup 1)D) excess without requiring major modifications to the other OH branching ratios or the total OH photodissociation lifetime.

Morgenthaler, Jeffrey P.↗

X-Ray Testing Constellation-X Optics at MSFC's 100-m Facility

In addition to the 530-m-long X-Ray Calibration Facility (XRCF), NASA's Marshall Space Flight Center (MSFC) operates a 104-m-long (source-to-detector) X-ray-test facility. Originally developed and still occasionally used for stray-light testing of visible-fight optical systems, the so-called "Stray-Light Facility" now serves primarily as a convenient and inexpensive facility for performance evaluation and calibration of X-ray optics and detectors. The facility can accommodate X-ray optics up to about 1-m diameter and 12-m focal length. Currently available electron-impact sources at the facility span the approximate energy range 0.2 to 100 keV, thus supporting testing of soft- and hard-X-ray optics and detectors. Available MSFC detectors are a front-illuminated CCD (charge-coupled device) and a scanning CZT (cadmium--zinc--telluride) detector, with low-energy cut-offs of about 0.8 and 3 keV, respectively. In order to test developmental optics for the Constellation-X Project, led by NASA's Goddard Space Flight Center (GSFC), MSFC undertook several enhancements to the facility. Foremost among these was development and fabrication of a five-degree-of-freedom (5-DoF) optics mount and control system, which translates and tilts the user-provided mirror assembly suspended from its interface plate. Initial Constellation-X tests characterize the performance of the Optical Alignment Pathfinder Two (OAP2) for the large Spectroscopy X-ray Telescope (SXT) and of demonstration mirror assemblies for the Hard X-ray Telescope (HXT). With the Centroid Detector Assembly (CDA), used for precision alignment of the Chandra (nee AXAF) mirrors, the Constellation-X SXT Team optically aligned the individual mirrors of the OAPZ at GSFC. The team then developed set-up and alignment procedures, including transfer of the alignment from the optical alignment facility at GSFC to the X-ray test facility at MSFC, using a reference flat and fiducials. The OAPZ incorporates additional ancillary features --- fixed aperture mask and movable sub-aperture mask --- to facilitate X-ray characterization of the optics. Although the OAPZ was designed to- have low sensitivity to temperature offsets and gradients, analyses showed the necessity of active temperature control for the X-ray performance testing. Thus, the Smithsonian Astrophysical Observatory (SAO) implemented a thermal control and monitoring system, designed to hold the OAP2 close to its assembly.

O'Dell, Stephen↗

Effects of mechanical stress or abscisic acid on growth, water status and leaf abscisic acid content of eggplant seedlings

Container-grown eggplant (Solanum melongena L. var esculentum Nees. 'Burpee's Black Beauty') seedlings were conditioned with brief, periodic mechanical stress or abscisic acid (ABA) in a greenhouse prior to outdoor exposure. Mechanical stress consisted of seismic (shaking) or thigmic (stem flexing) treatment. Exogenous ABA (10(-3) or 10(-4)M) was applied as a soil drench 3 days prior to outdoor transfer. During conditioning, only thigmic stress reduced stem elongation and only 10(-3) M ABA reduced relative growth rate (RGR). Both conditioning treatments increased leaf specific chlorophyll content, but mechanical stress did not affect leaf ABA content. Outdoor exposure of unconditioned eggplant seedlings decreased RGR and leaf-specific chlorophyll content, but tended to increase leaf ABA content relative to that of plants maintained in the greenhouse. Conditioning did not affect RGR of plants subsequently transferred outdoors, but did reduce stem growth. Seismic stress applied in the greenhouse reduced dry weight gain by plants subsequently transferred outdoors. Mechanical stress treatments increased leaf water potential by 18-25% relative to that of untreated plants.

NASA Discipline Plant Biology↗

UV-B radiation and photosynthetic irradiance acclimate eggplant for outdoor exposure

Treatment of greenhouse-grown eggplant (Solanum melongena L. var. esculentum Nees. 'Burpee's Black Beauty') seedlings with supplemental photosynthetically active radiation from cool-white fluorescent lamps increased growth of plants subsequently transferred outdoors relative to growth of plants that received no supplemental radiation or were shaded to 45% of solar irradiation in the greenhouse before transfer outdoors. Eggplant seedlings transferred outdoors were placed under plastic tarps either to provide relative protection from solar ultraviolet-B (UV-B) radiation (280-315 nm) using Mylar film or to allow exposure to UV-B using cellulose acetate. Protection of seedlings from UV-B radiation resulted in greater leaf expansion than for UV-B-exposed seedlings, but no change in leaf or shoot dry weight occurred after 9 days of treatment. Specific leaf weight increased in response to UV-B exposure outdoors. Exposure of eggplant to UV-B radiation from fluorescent sunlamps in the greenhouse also decreased leaf expansion and leaf and shoot dry weight gain after 5 days of treatment. However, there were no differences in leaf or shoot dry weight relative to control plants after 12 days of UV-B treatment, indicating that UV-B treated plants had acclimated to the treatment and actually had caught up with non-UV-B-irradiated plants in terms of growth.

NASA Program Space Biology↗

Regional Carbon Dioxide and Water Vapor Exchange Over Heterogeneous Terrain

In spite of setbacks due to forest fires, eviction after a change of landowners and unanticipated need to upgrade and replace much of the instrumentation, substantial progress has been made during the past three years, resulting in major new findings. Although most of the results are in manuscript form, three papers have been published and a fourth was recently submitted. The data has been subjected to extensive quality control. Extra attention has been devoted to the influence of tilt rotation and flux-calculation method, particularly with respect to nocturnal fluxes. Previous/standard methods for calculating nocturnal fluxes with moderate and strong stability are inadequate and lead to large random fluxes errors for individual records, due partly to inadvertent inclusion of mesoscale motions that strongly contaminant the estimation of fluxes by weak turbulence. Such large errors are serious for process studies requiring carbon dioxide fluxes for individual records, but are substantially reduced when averaging fluxes over longer periods as in calculation of annual NEE budgets. We have employed a superior method for estimating fluxes in stable conditions with a variable averaging width . Mesoscale fluxes are generally unimportant except for events and are generally not systematic or predictable. Mesoscale or regional models of our region are not able to reproduce important aspects of the diurnally varying wind field

Mahrt, Larry J.↗

Prospects for Chlorophyll Fluorescence Remote Sensing from the Orbiting Carbon Observatory-2

The Orbiting Carbon Observatory-2 (OCO-2), scheduled to launch in July 2014, is a NASA mission designed to measure atmospheric CO2. Its main purpose is to allow inversions of net flux estimates of CO2 on regional to continental scales using the total column CO2 retrieved using high-resolution spectra in the 0.76, 1.6, and 2.0 nm ranges. Recently, it was shown that solar-induced chlorophyll fluorescence (SIF), a proxy for gross primary production (GPP, carbon uptake through photosynthesis), can be accurately retrieved from space using high spectral resolution radiances in the 750 nm range from the Japanese GOSAT and European GOME-2 instruments. Here, we use real OCO-2 thermal vacuum test data as well as a full repeat cycle (16 days) of simulated OCO-2 spectra under realistic conditions to evaluate the potential of OCO-2 for retrievals of chlorophyll fluorescence and also its dependence on clouds and aerosols. We find that the single-measurement precision is 0.3-0.5 Wm(exp -2)sr(exp -1) nm(exp -1) (15-25% of typical peak values), better than current measurements from space but still difficult to interpret on a single-sounding basis. The most significant advancement will come from smaller ground-pixel sizes and increased measurement frequency, with a 100-fold increase compared to GOSAT (and about 8 times higher than GOME-2). This will largely decrease the need for coarse spatial and temporal averaging in data analysis and pave the way to accurate local studies.We also find that the lack of full global mapping from the OCO-2 only incurs small representativeness errors on regional averages. Eventually, the combination of net ecosystem exchange (NEE) derived from CO2 source/sink inversions and SIF as proxy for GPP from the same satellite will provide a more process-based understanding of the global carbon cycle.

vegetation agriculture satellite↗

Impacts of Light Use Efficiency and fPAR Parameterization on Gross Primary Production Modeling

This study examines the impact of parameterization of two variables, light use efficiency (LUE) and the fraction of absorbed photosynthetically active radiation (fPAR or fAPAR), on gross primary production(GPP) modeling. Carbon sequestration by terrestrial plants is a key factor to a comprehensive under-standing of the carbon budget at global scale. In this context, accurate measurements and estimates of GPP will allow us to achieve improved carbon monitoring and to quantitatively assess impacts from cli-mate changes and human activities. Spaceborne remote sensing observations can provide a variety of land surface parameterizations for modeling photosynthetic activities at various spatial and temporal scales. This study utilizes a simple GPP model based on LUE concept and different land surface parameterizations to evaluate the model and monitor GPP. Two maize-soybean rotation fields in Nebraska, USA and the Bartlett Experimental Forest in New Hampshire, USA were selected for study. Tower-based eddy-covariance carbon exchange and PAR measurements were collected from the FLUXNET Synthesis Dataset. For the model parameterization, we utilized different values of LUE and the fPAR derived from various algorithms. We adapted the approach and parameters from the MODIS MOD17 Biome Properties Look-Up Table (BPLUT) to derive LUE. We also used a site-specific analytic approach with tower-based Net Ecosystem Exchange (NEE) and PAR to estimate maximum potential LUE (LUEmax) to derive LUE. For the fPAR parameter, the MODIS MOD15A2 fPAR product was used. We also utilized fAPAR chl, a parameter accounting for the fAPAR linked to the chlorophyll-containing canopy fraction. fAPAR chl was obtained by inversion of a radiative transfer model, which used the MODIS-based reflectances in bands 1-7 produced by Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. fAPAR chl exhibited seasonal dynamics more similar with the flux tower based GPP than MOD15A2 fPAR, especially in the spring and fall at the agricultural sites. When using the MODIS MOD17-based parameters to estimate LUE, fAPAR chl generated better agreements with GPP (r2= 0.79-0.91) than MOD15A2 fPAR (r2= 0.57-0.84).However, underestimations of GPP were also observed, especially for the crop fields. When applying the site-specific LUE max value to estimate in situ LUE, the magnitude of estimated GPP was closer to in situ GPP; this method produced a slight overestimation for the MOD15A2 fPAR at the Bartlett forest. This study highlights the importance of accurate land surface parameterizations to achieve reliable carbon monitoring capabilities from remote sensing information.

grossprimary↗

Technical Report Series on Global Modeling and Data Assimilation: Soil Moisture Active Passive (SMAP) Project Calibration and Validation for the L4_C Beta-Release Data Product - Volume 42

During the post-launch Cal/Val Phase of SMAP there are two objectives for each science product team: 1) calibrate, verify, and improve the performance of the science algorithms, and 2) validate accuracies of the science data products as specified in the L1 science requirements according to the Cal/Val timeline. This report provides analysis and assessment of the SMAP Level 4 Carbon (L4_C) product specifically for the beta release. The beta-release version of the SMAP L4_C algorithms utilizes a terrestrial carbon flux model informed by SMAP soil moisture inputs along with optical remote sensing (e.g. MODIS) vegetation indices and other ancillary biophysical data to estimate global daily NEE and component carbon fluxes, particularly vegetation gross primary production (GPP) and ecosystem respiration (Reco). Other L4_C product elements include surface (<10 cm depth) soil organic carbon (SOC) stocks and associated environmental constraints to these processes, including soil moisture and landscape FT controls on GPP and Reco (Kimball et al. 2012). The L4_C product encapsulates SMAP carbon cycle science objectives by: 1) providing a direct link between terrestrial carbon fluxes and underlying freeze/thaw and soil moisture constraints to these processes, 2) documenting primary connections between terrestrial water, energy and carbon cycles, and 3) improving understanding of terrestrial carbon sink activity in northern ecosystems.

Cal/Val↗

Assimilation of Remotely Sensed Leaf Area Index into the Noah-MP Land Surface Model: Impacts on Water and Carbon Fluxes and States over the Continental U.S.

Accurate representation of vegetation states is required for the modeling of terrestrial water-energy-carbon exchanges and the characterization of the impacts of natural and anthropogenic vegetation changes on the land surface. This study presents a comprehensive evaluation of the impact of assimilating remote sensing-based Leaf Area Index (LAI) retrievals over the Continental U.S. in the Noah-MP land surface model, during a time period of 2000 to 2017. The results demonstrate that the assimilation has a beneficial impact on the simulation of key water budget terms such as soil moisture, evapotranspiration, snow depth, terrestrial water storage and streamflow, when compared with a large suite of reference datasets. In addition, the assimilation of LAI is also found to improve the carbon fluxes of Gross Primary Production (GPP) and Net Ecosystem Exchange (NEE). Most prominent improvements in the water and carbon variables are observed over the agricultural areas of the U.S., where assimilation improves the representation of vegetation seasonality impacted by cropping schedules. The systematic, added improvements from assimilation in a configuration that employs high quality boundary conditions highlight the significant utility of LAI data assimilation in capturing the impacts of vegetation changes.

anthropogenic vegetation↗