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NASA NTRS1982

A two-component rain model for the prediction of attenuation and diversity improvement

A new model was developed to predict attenuation statistics for a single Earth-satellite or terrestrial propagation path. The model was extended to provide predictions of the joint occurrences of specified or higher attenuation values on two closely spaced Earth-satellite paths. The joint statistics provide the information required to obtain diversity gain or diversity advantage estimates. The new model is meteorologically based. It was tested against available Earth-satellite beacon observations and terrestrial path measurements. The model employs the rain climate region descriptions of the Global rain model. The rms deviation between the predicted and observed attenuation values for the terrestrial path data was 35 percent, a result consistent with the expectations of the Global model when the rain rate distribution for the path is not used in the calculation. Within the United States the rms deviation between measurement and prediction was 36 percent but worldwide it was 79 percent.

Crane, R. K.↗

NASA NTRS2012

The Precise Orbit and the Challenge of Long Term Stability

The computation of a precise orbit reference is a fundamental component of the altimetric measurement. Since the dawn of the modern altimeter age, orbit accuracy has been determined by the quality of the GPS, SLR, and DORIS tracking systems, the fidelity of the measurement and force models, and the choice of parameterization for the orbit solutions, and whether a dynamic or a reduced-dynamic strategy is used to calculate the orbits. At the start of the TOPEX mission, the inaccuracies in the modeling of static gravity, dynamic ocean tides, and the nonconservative forces dominated the orbit error budget. Much of the error due to dynamic mismodeling can be compensated by reduced-dynamic tracking techniques depending on the measurement system strength. In the last decade, the launch of the GRACE mission has eliminated the static gravity field as a concern, and the background force models and the terrestrial reference frame have been systematically refined. GPS systems have realized many improvements, including better modeling of the forces on the GPS spacecraft, large increases in the ground tracking network, and improved modeling of the GPS measurements. DORIS systems have achieved improvements through the use of new antennae, more stable monumentation, and of satellite receivers that can track multiple beacons, and as well as through improved modeling of the nonconservative forces. Many of these improvements have been applied in the new reprocessed time series of orbits produced for the ERS satellites, Envisat, TOPEX/Poseidon and the Jason satellites, and as well as for the most recent Cryosat-2 and HY2A. We now face the challenge of maintaining a stable orbit reference for these altimetric satellites. Changes in the time-variable gravity field of the Earth and how these are modelled have been shown to affect the orbit evolution, and the calibration of the altimetric data with tide gauges. The accuracy of the reference frame realizations, and their projection into the future remains a source of error. Other sources of omission error include the geocenter for which no consensus model is as of yet applied. Although progress has been made in nonconservative force modeling through the use of detailed satellite-specific models, radiation pressure modeling, and atmospheric density modeling remain a potential source of orbit error. The longer term influence of variations in the solar and terrestrial radiation fields over annual and solar cycles remains principally untested. Also the long term variation in optical and thermal properties of the space vehicle surfaces would contribute to biases in the orbital frame if ignored. We review the status of altimetric precision orbit determination as exemplified by the recent computations undertaken by the different analysis centers for ERS, Envisat, TOPEX/Poseidon, Jason, Cryosat2 and HY2A, and we provide a perspective on the challenges for future missions such as the Jason-3, SENTINEL-3 and SWOT.

Lemoine, Frank G.↗

NASA NTRS1998

Detecting a Terrestrial Biosphere Sink for Carbon Dioxide: Interannual Ecosystem Modeling for the Mid-1980s

There is considerable uncertainty as to whether interannual variability in climate and terrestrial ecosystem production is sufficient to explain observed variation in atmospheric carbon content over the past 20-30 years. In this paper, we investigated the response of net CO2 exchange in terrestrial ecosystems to interannual climate variability (1983 to 1988) using global satellite observations as drivers for the NASA-CASA (Carnegie-Ames-Stanford Approach) simulation model. This computer model of net ecosystem production (NEP) is calibrated for interannual simulations driven by monthly satellite vegetation index data (NDVI) from the NOAA Advanced Very High Resolution Radiometer (AVHRR) at 1 degree spatial resolution. Major results from NASA-CASA simulations suggest that from 1985 to 1988, the northern middle-latitude zone (between 30 and 60 degrees N) was the principal region driving progressive annual increases in global net primary production (NPP; i.e., the terrestrial biosphere sink for carbon). The average annual increase in NPP over this predominantly northern forest zone was on the order of +0.4 Pg (10 (exp 15) g) C per year. This increase resulted mainly from notable expansion of the growing season for plant carbon fixation toward the zonal latitude extremes, a pattern uniquely demonstrated in our regional visualization results. A net biosphere source flux of CO2 in 1983-1984, coinciding with an El Nino event, was followed by a major recovery of global NEP in 1985 which lasted through 1987 as a net carbon sink of between 0.4 and 2.6 Avg C per year. Analysis of model controls on NPP and soil heterotrophic CO2 fluxes (Rh) suggests that regional warming in northern forests can enhance ecosystem production significantly. In seasonally dry tropical zones, periodic drought and temperature drying effects may carry over with at least a two-year lag time to adversely impact ecosystem production. These yearly patterns in our model-predicted NEP are consistent in magnitude with the estimated exchange of CO2 by the terrestrial biosphere with the atmosphere, as determined by previous isotopic (delta (sup 13 C) convolution analysis. Ecosystem simulation results can help further target locations where net carbon sink fluxes have occurred in the past or may be verified in subsequent field studies.

Potter, Christopher S.↗

NASA NTRS1996

The effect of Birkeland currents on magnetic field topology

A technique was developed for the inclusion of large scale magnetospheric current systems in magnetic field models. The region 1 and 2 Birkeland current systems are included in the source surface model of the terrestrial magnetosphere. The region 1 and 2 Birkeland currents are placed in the model using a series of field aligned, infinitely thin wire segments. The normal component of the magnetic field from these currents is calculated on the surface of the magnetopause and shielded using image current carrying wires placed outside of the magnetosphere. It is found that the inclusion of the Birkeland currents in the model results in a northward magnetic field in the near-midnight tail, leading to the closure of previously open flux in the tail, and a southward magnetic field in the flanks. A sunward shift in the separatrix is observed.

Peroomian, Vahe↗

NASA NTRS2016

Soil Moisture Active Passive Mission L4_C Data Product Assessment (Version 2 Validated Release)

The SMAP satellite was successfully launched January 31st 2015, and began acquiring Earth observation data following in-orbit sensor calibration. Global data products derived from the SMAP L-band microwave measurements include Level 1 calibrated and geolocated radiometric brightness temperatures, Level 23 surface soil moisture and freezethaw geophysical retrievals mapped to a fixed Earth grid, and model enhanced Level 4 data products for surface to root zone soil moisture and terrestrial carbon (CO2) fluxes. The post-launch SMAP mission CalVal Phase had two primary 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. This report provides analysis and assessment of the SMAP Level 4 Carbon (L4_C) product pertaining to the validated release. The L4_C validated product release effectively replaces an earlier L4_C beta-product release (Kimball et al. 2015). The validated release described in this report incorporates a longer data record and benefits from algorithm and CalVal refinements acquired during the SMAP post-launch CalVal intensive period. The SMAP L4_C algorithms utilize 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 net ecosystem CO2 exchange (NEE) and component carbon fluxes for 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 freeze/thaw (FT) controls on GPP and respiration (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 FT 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. There are no L1 science requirements for the L4_C product; however self-imposed requirements have been established focusing on NEE as the primary product field for validation, and on demonstrating L4_C accuracy and success in meeting product science requirements (Jackson et al. 2012). The other L4_C product fields also have strong utility for carbon science applications; however, analysis of these other fields is considered secondary relative to primary validation activities focusing on NEE. The L4_C targeted accuracy requirements are to meet or exceed a mean unbiased accuracy (ubRMSE) for NEE of 1.6 g C/sq m/d or 30 g C/sq m/yr, emphasizing northern (45N) boreal and arctic ecosystems; this is similar to the estimated accuracy level of in situ tower eddy covariance measurement-based observations (Baldocchi 2008).

Cal/Val↗

NASA NTRS2007

Not So Rare Earth? New Developments in Understanding the Origin of the Earth and Moon

A widely accepted model for the origin of the Earth and Moon has been a somewhat specific giant impact scenario involving an impactor to proto-Earth mass ratio of 3:7, occurring 50-60 Ma after T(sub 0), when the Earth was only half accreted, with the majority of Earth's water then accreted after the main stage of growth, perhaps from comets. There have been many changes to this specific scenario, due to advances in isotopic and trace element geochemistry, more detailed, improved, and realistic giant impact and terrestrial planet accretion modeling, and consideration of terrestrial water sources other than high D/H comets. The current scenario is that the Earth accreted faster and differentiated quickly, the Moon-forming impact could have been mid to late in the accretion process, and water may have been present during accretion. These new developments have broadened the range of conditions required to make an Earth-Moon system, and suggests there may be many new fruitful avenues of research. There are also some classic and unresolved problems such as the significance of the identical O isotopic composition of the Earth and Moon, the depletion of volatiles on the lunar mantle relative to Earth's, the relative contribution of the impactor and proto-Earth to the Moon's mass, and the timing of Earth's possible atmospheric loss relative to the giant impact.

Righter, Kevin↗

DOE OSTI2020

Modeling biological nitrogen fixation in global natural terrestrial ecosystems

Biological nitrogen fixation plays an important role in the global nitrogen cycle. However, the fixation rate has been usually measured or estimated at a particular observational site. To quantify the fixation amount at the global scale, process-based models are needed. This study develops a biological nitrogen fixation model to quantitatively estimate the nitrogen fixation rate by plants in a natural environment. The revised nitrogen module better simulates the nitrogen cycle in comparison with our previous model that has not considered the fixation effects. The new model estimates that tropical forests have the highest fixation rate among all ecosystem types, which decreases from the Equator to the polar region. The estimated nitrogen fixation in global terrestrial ecosystems is 61.5 Tg N yr-1 with a range of 19.8–107.9 Tg N yr-1 in the 1990s. Our estimates are relatively low compared to some early estimates using empirical approaches but comparable to more recent estimates that involve more detailed processes in their modeling. Furthermore, the contribution of nitrogen made by biological nitrogen fixation depends on ecosystem type and climatic conditions. This study highlights that there are relatively large effects of biological nitrogen fixation on ecosystem nitrogen cycling. and the large uncertainty of the estimation calls for more comprehensive understanding of biological nitrogen fixation. More direct observational data for different ecosystems are in need to improve future quantification of fixation and its impacts.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2008

TPF-C Performance Modeling

This slide presentation reviews the performance modeling of the Terrestrial Planet Finder Coronagraph (TPF-C). Included is a chart of the Error Budget Models, definitions of the static and dynamic terms, a chart showing the aberration sensitivity at 2 lambda/D, charts showing the thermal performance models and analysis, surface requirements, high-level requirements, and calculations for the beam walk model.Also included is a description of the control systems, and a flow for the iterative design and analysis cycle.

terrestrial planet finder↗

NASA NTRS2019

Maximum Carbon Uptake Rate Dominates the Interannual Variability of Global Net Ecosystem Exchange

Terrestrial ecosystems contribute most of the interannual variability (IAV) in atmospheric carbon dioxide (CO2) concentrations, but processes driving the IAV of net ecosystem CO2 exchange (NEE) remain elusive. For a predictive understanding of the global C cycle, it is imperative to identify indicators associated with ecological processes that determine the IAV of NEE. Here, we decompose the annual NEE of global terrestrial ecosystems into their phenological and physiological components, namely maximum carbon uptake (MCU) and release (MCR), the carbon uptake period (CUP), and two parameters, α and β, that describe the ratio between actual versus hypothetical maximum C sink and source, respectively. Using long‐term observed NEE from 66 eddy covariance sites and global products derived from FLUXNET observations, we found that the IAV of NEE is determined predominately by MCU at the global scale, which explains 48% of the IAV of NEE on average while α, CUP, β, and MCR explain 14%, 25%, 2%, and 8%, respectively. These patterns differ in water‐limited ecosystems versus temperature‐ and radiation‐limited ecosystems; 31% of the IAV of NEE is determined by the IAV of CUP in water‐limited ecosystems, and 60% of the IAV of NEE is determined by the IAV of MCU in temperature‐ and radiation‐limited ecosystems. The Lund‐Potsdam‐Jena (LPJ) model and the Multi‐scale Synthesis and Terrestrial Model Inter‐comparison Project (MsTMIP) models underestimate the contribution of MCU to the IAV of NEE by about 18% on average, and overestimate the contribution of CUP by about 25%. This study provides a new perspective on the proximate causes of the IAV of NEE, which suggest that capturing the variability of MCU is critical for modeling the IAV of NEE across most of the global land surface.

Fu, Zheng↗

NASA NTRS2015

Assimilation of GRACE Terrestrial Water Storage Observations into a Land Surface Model for the Assessment of Regional Flood Potential

We evaluate performance of the Catchment Land Surface Model (CLSM) under flood conditions after the assimilation of observations of the terrestrial water storage anomaly (TWSA) from NASA's Gravity Recovery and Climate Experiment (GRACE). Assimilation offers three key benefits for the viability of GRACE observations to operational applications: (1) near-real time analysis; (2) a downscaling of GRACE's coarse spatial resolution; and (3) state disaggregation of the vertically-integrated TWSA. We select the 2011 flood event in the Missouri river basin as a case study, and find that assimilation generally made the model wetter in the months preceding flood. We compare model outputs with observations from 14 USGS groundwater wells to assess improvements after assimilation. Finally, we examine disaggregated water storage information to improve the mechanistic understanding of event generation. Validation establishes that assimilation improved the model skill substantially, increasing regional groundwater anomaly correlation from 0.58 to 0.86. For the 2011 flood event in the Missouri river basin, results show that groundwater and snow water equivalent were contributors to pre-event flood potential, providing spatially-distributed early warning information.

flood↗

DOE OSTI2024

Integrating Tide‐Driven Wetland Soil Redox and Biogeochemical Interactions Into a Land Surface Model

Abstract Redox processes, aqueous and solid‐phase chemistry, and pH dynamics are key drivers of subsurface biogeochemical cycling and methanogenesis in terrestrial and wetland ecosystems but are typically not included in terrestrial carbon cycle models. These omissions may introduce errors when simulating systems where redox interactions and pH fluctuations are important, such as wetlands where saturation of soils can produce anoxic conditions and coastal systems where sulfate inputs from seawater can influence biogeochemistry. Integrating cycling of redox‐sensitive elements could therefore allow models to better represent key elements of carbon cycling and greenhouse gas production. We describe a model framework that couples the Energy Exascale Earth System Model (E3SM) Land Model (ELM) with PFLOTRAN biogeochemistry, allowing geochemical processes and redox interactions to be integrated with land surface model simulations. We implemented a reaction network including aerobic decomposition, fermentation, sulfate reduction, sulfide oxidation, methanogenesis, and methanotrophy as well as pH dynamics along with iron oxide and iron sulfide mineral precipitation and dissolution. We simulated biogeochemical cycling in tidal wetlands subject to either saltwater or freshwater inputs driven by tidal hydrological dynamics. In simulations with saltwater tidal inputs, sulfate reduction led to accumulation of sulfide, higher dissolved inorganic carbon concentrations, lower dissolved organic carbon concentrations, and lower methane emissions than simulations with freshwater tidal inputs. Model simulations compared well with measured porewater concentrations and surface gas emissions from coastal wetlands in the Northeastern United States. These results demonstrate how simulating geochemical reaction networks can improve land surface model simulations of subsurface biogeochemistry and carbon cycling.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1993

Aspects of modelling the tectonics of large volcanoes on the terrestrial planets

Analytic solutions for the responses of planetary lithospheres to volcanic loads have been used to model faulting and infer elastic plate thicknesses. Predictions of the distribution of faulting around volcanic loads, based on the application of Anderson's criteria for faulting to the results of the models, do not agree well with observations. Such models do not give the stress state in the load itself, but only suggest a state of horizontal compressive stress there. Further, these models have considered only the effect of an instantaneously emplaced load. They do not address the time evolution of stresses, nor do they consider the effect of a load which grows. A finite element approach allows us to assign elements to the load itself, and thus permits calculation of the stress state and stress history within the edifice. The effects of episodic load growth can also be treated. When these effects are included, models give much better agreement with observations. We use the finite element code TECTON to construct axisymmetric models of volcanoes resting on an elastic lithospheric plate overlying a viscoelastic asthenosphere. We have implemented time-dependent material properties in order to simulate incremental volcano growth. The viscoelastic layer was taken to extend to a sufficient depth so that a rigid lower boundary has no significant influence on the results. The code first calculates elastic deformations and stresses and then determines the time-dependent viscous deformations and stresses. Time in the model scales as the Maxwell time tau(m) in the asthenosphere. We consider a volcano 25 km in height and 200 km in radius on an elastic lithosphere 40 km thick (parameters approximately appropriate to Ascraeus Mons). The volcano consists of three load increments applied at intervals of 1000 tau(m). Contours of maximum deviatoric stress in the fully-grown edifice at the conclusion of flexure (t = 3000 tau(m)) are shown.

Mcgovern, Patrick J.↗

NASA NTRS1993

Aspects of modelling the tectonics of large volcanoes on the terrestrial planets

Analytic solutions for the response of planetary lithospheres to volcanic loads have been used to model faulting and infer elastic plate thicknesses. Predictions of the distribution of faulting around volcanic loads, based on the application of Anderson's criteria for faulting to the results of the models, do not agree well with observations. Such models do not give the stress state and stress history within the edifice. The effects of episodic load growth can also be treated. When these effects are included, models give much better agreement with observations.

Mcgovern, Patrick J.↗

DOE OSTI2025

Investigating the Global Biogeophysical Impact of Area and Mass Based Wood Harvest in a Vegetation Demography Model

Wood harvesting alters land surface properties and energy redistribution, but there is a lack of studies estimating these changes on a global scale. We coupled a vegetation demographic model, the Functionally Assembled Terrestrial Ecosystem Simulator, with the E3SM land model to perform offline model simulation to investigate the land biogeophysical responses, including canopy coverage, leaf area index, albedo, surface roughness length, and energy fluxes, to historical wood harvest on the global scale. In this study, we found 50% less harvested carbon (C) when choosing the area-based harvest rate as driving data that has not been spatially harmonized, compared to reharmonized mass-based harvesting. By considering the uncertainty from reconstruction of historical wood harvest time series and the choice of wood harvest approach in the model, continuous wood harvest (1850–2015) results in 5%–10% of canopy coverage loss, contributing 0.5%–1% increase of albedo over disturbed land, which is much stronger than a non-demographic land surface model. Changes in energy flux from the wood harvest are negligible (<1%), but the responses of land surface properties vary (up to 30%) due to differences in model structure between the single canopy, sun-shade leaf model and vegetation demographic model.

Shu, Shijie [Lawrence Berkeley National Laboratory↗

NASA NTRSDate not supplied

Isolating the Impacts of Soil Moisture Initialization on Land Carbon Fluxes at the Sub-Seasonal to Seasonal Scale

Soil moisture, through its impact on transpiration, plays a significant role in controlling the productivity of terrestrial vegetation. Initial soil moisture conditions in a seasonal forecast may therefore affect the forecast of land carbon uptake. Here we investigate the relative impacts of soil moisture initialization and carbon reservoir initialization on forecasts of land carbon fluxes at the sub-seasonal to seasonal (S2S) scale. The bias-corrected, retrospective meteorology of NASA Global Modeling and Assimilation Office (GMAO)’s S2S ensemble forecast was used to force the stand-alone Catchment-CN model and thereby estimate terrestrial carbon responses out to nine lead months. Our results show that soil moisture initialization is a major contributor (approximately 44%) to the high global carbon uptake forecast skill seen during the first three lead months. The carbon reservoir initialization explains roughly another half of the monthly carbon forecast skill during this period and becomes relatively more important at longer leads (while the overall forecast skill decreases after the 3 lead month), suggesting a slower but longer-lasting influence of carbon reservoir initialization on carbon fluxes. Our results highlight the significance of a good soil moisture initialization for improved forecasts of carbon fluxes at leads of several months, further support for the usefulness of assimilating the satellite based soil moisture information into terrestrial biosphere models and of a short term carbon forecast to understand current events with often a lag in the availability of flux estimates.

Land carbon↗

NASA NTRS2008

Assimilation of GRACE Terrestrial Water Storage Data into a Land Surface Model

The NASA Gravity Recovery and Climate Experiment (GRACE) system of satellites provides observations of large-scale, monthly terrestrial water storage (TWS) changes. In. this presentation we describe a land data assimilation system that ingests GRACE observations and show that the assimilation improves estimates of water storage and fluxes, as evaluated against independent measurements. The ensemble-based land data assimilation system uses a Kalman smoother approach along with the NASA Catchment Land Surface Model (CLSM). We assimilated GRACE-derived TWS anomalies for each of the four major sub-basins of the Mississippi into the Catchment Land Surface Model (CLSM). Compared with the open-loop (no assimilation) CLSM simulation, assimilation estimates of groundwater variability exhibited enhanced skill with respect to measured groundwater. Assimilation also significantly increased the correlation between simulated TWS and gauged river flow for all four sub-basins and for the Mississippi River basin itself. In addition, model performance was evaluated for watersheds smaller than the scale of GRACE observations, in the majority of cases, GRACE assimilation led to increased correlation between TWS estimates and gauged river flow, indicating that data assimilation has considerable potential to downscale GRACE data for hydrological applications. We will also describe how the output from the GRACE land data assimilation system is now being prepared for use in the North American Drought Monitor.

Reichle, Rolf H.↗

NASA NTRS1987

The Martian dust cycle: A proposed model

Despite more than a decade of study of martian dust storms, many of their characteristics and associated processes remain enigmatic, including the mechanisms for dust raising, modes of settling, and the nature of dust deposits. However, observations of Mars dust, considerations of terrestrial analogs, theoretical models, and laboratory simulations permit the formulation of a Martian Dust Cycle Model, which consists of three main processes: (1) suspension threshold, (2) transportation, and (3) deposition; two associated processes are also included: (4) dust removal and (5) the addition of new dust to the cycle. Although definitions vary, dust includes particles less than 4 to approx. 60 microns in diameter, which by terrestrial usage includes silt, loess, clay, and aerosolic dust particles. The dust cycle model is explained.

Greeley, Ronald↗

DOE OSTI2026

Integrating Maximum Entropy Production Theory and Machine Learning to Improve Global Evapotranspiration Modeling

Accurate estimation of terrestrial evapotranspiration (ET) is vital for understanding global water and energy cycles. However, current global ET estimations are not well constrained. This study introduces an integrated framework combining the Maximum Entropy Production (MEP) theory with Random Forest (RF) model to improve global ET estimation. Specifically, in contrast to direct ET estimation by the RF model, the integrated framework (MEP‐RF) trains to predict error of MEP‐simulated ET. MEP‐RF outperforms RF in spatiotemporal extrapolation. Attribution analysis with in situ observations reveals that the inputs of MEP are the most critical variables for the ET process, including net radiation, vegetated area, soil moisture, and surface temperature. We further drive MEP‐RF with global reanalysis and satellite data sets of these four inputs, yielding a global mean terrestrial ET of 548 mm/year, with 77% attributed to transpiration. The global ET increased at a rate of 0.85 mm/year per year during 2003–2021, primarily due to vegetation greening rather than rising temperature, while decreasing soil moisture led to decreasing regional ET. The integrated framework provides a novel approach for the estimation of global ET without the need for hard‐to‐obtain and thus uncertain inputs, such as wind speed, surface roughness, aerodynamic and canopy stomatal resistance. Therefore, MEP‐RF offers an independent method on existing global ET products. It represents a promising physically based approach that can be incorporated into Earth System Models to enhance water and energy cycle simulations.

54 ENVIRONMENTAL SCIENCES↗