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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

The Virginia Earth System Science Scholars (VESSS) Experience: Inspiring High School Students in Stem Through Mentorship and Collaborative Skills Development

Since 2016, the Virginia Earth System Science Scholars (VESSS) program offered by the Virginia Space Grant Consortium (VSGC) has provided an interactive science, technology, engineering, and mathematics learning experience for Virginia high school juniors and seniors. The VESSS program was created through a partnership with VSGC, NASA Langley Research Center (LaRC), and Hampton University to engage students in learning about Earth’s climate change and its global impacts. High school students from all areas of Virginia learn about Earth science and climate change in a 16 week online course focused on the Earth’s surface and interior, atmospheric composition, weather, water energy cycles, and climate variability. Students that complete the online course are invited to a no-cost seven-day residential summer academy at NASA LaRC where students are divided into teams based on four of the major spheres of study for Earth: atmosphere, biosphere, hydrosphere, and lithosphere. Each team is guided by a Master Teacher and teams of undergraduate student interns who were also previous VESSS scholars. Students interview for team positions and are given a role reflecting an actual satellite design team position such as project scientist, research scientist, budget analyst, launch and orbit analyst, contamination analyst, and education and public outreach specialist. The students spend a week mentored by NASA and industry scientists and engineers as they learn how to select science goals and objectives, select science instruments, balance a mission budget, determine the mission launch location and orbit, and communicate the importance of the mission to the public. Each team produces a mission proposal, and at the end of the week, each team presents their portion of the mission to a panel of experts, followed by a question and answer period. Through this week students learn teamwork, communication, time management, meeting management, and research skills. Project work is supplemented by team-building activities, NASA facility tours, and lectures by acclaimed guest speakers such as Dr. Christine Darden, a NASA “Hidden Figure.” Students have conveyed through course evaluations and testimonials not only the vast personal learning and growth they achieved, but also the new perspectives they gained on future STEM career fields and opportunities to explore.

Elaine Seasly↗
NASA NTRS2007

The Crew Earth Observations Experiment: Earth System Science from the ISS

This viewgraph presentation reviews the use of Astronaut Photography (AP) as taken from the International Space Station (ISS) in Earth System Science (ESS). Included are slides showing basic remote sensing theory, data characteristics of astronaut photography, astronaut training and operations, crew Earth observations group, targeting sites and acquisition, cataloging and database, analysis and applications for ESS, image analysis of particular interest urban areas, megafans, deltas, coral reefs. There are examples of the photographs and the analysis.

Stefanov, William L.↗
NASA NTRSDate not supplied

Publishing Variables Archived at GES DISC to Earth System Grid Federation (ESGF)

We present a straightforward and low-cost approach to publish variables archived at NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) to the Earth System Grid Federation (ESGF). An ESGF publication requires a single standard-name variable aggregated over time to facilitate data inter-comparison. It also contains significant metadata to enable searching in ESGF. We look up standard names on high demand in ESGF search history, and using OPeNDAP and NcML technologies we aggregate the corresponding variables available in the GES DISC archive with augmented metadata required by CMIP6 and obs4MIPs Data Specification version 2.1. At this writing 10 variables from a standard product of the Atmospheric Infrared Sounder along with the Tech Notes are published in ESGF by NASA Center for Climate Simulation (NCCS). Users can view, analyze, and subset remotely, and download these aggregated variables via links in any ESGF node after searching. We plan to work on and publish more variables and data from different NASA missions and experiments in our archive.

Fan Fang↗
NASA NTRS2004

The Hydrosphere State (Hydros) Satellite Mission: An Earth System Pathfinder for Global Mapping of Soil Moisture and Land Freeze/Thaw

The Hydrosphere State Mission (Hydros) is a pathfinder mission in the National Aeronautics and Space Administration (NASA) Earth System Science Pathfinder Program (ESSP). The objective of the mission is to provide exploratory global measurements of the earth's soil moisture at 10-km resolution with two- to three-days revisit and land-surface freeze/thaw conditions at 3-km resolution with one- to two-days revisit. The mission builds on the heritage of ground-based and airborne passive and active low-frequency microwave measurements that have demonstrated and validated the effectiveness of the measurements and associated algorithms for estimating the amount and phase (frozen or thawed) of surface soil moisture. The mission data will enable advances in weather and climate prediction and in mapping processes that link the water, energy, and carbon cycles. The Hydros instrument is a combined radar and radiometer system operating at 1.26 GHz (with VV, HH, and HV polarizations) and 1.41 GHz (with H, V, and U polarizations), respectively. The radar and the radiometer share the aperture of a 6-m antenna with a look-angle of 39 with respect to nadir. The lightweight deployable mesh antenna is rotated at 14.6 rpm to provide a constant look-angle scan across a swath width of 1000 km. The wide swath provides global coverage that meet the revisit requirements. The radiometer measurements allow retrieval of soil moisture in diverse (nonforested) landscapes with a resolution of 40 km. The radar measurements allow the retrieval of soil moisture at relatively high resolution (3 km). The mission includes combined radar/radiometer data products that will use the synergy of the two sensors to deliver enhanced-quality 10-km resolution soil moisture estimates. In this paper, the science requirements and their traceability to the instrument design are outlined. A review of the underlying measurement physics and key instrument performance parameters are also presented.

Entekhabi, D.↗
NASA NTRSDate not supplied

Artificial Intelligence for Future Earth Science Information Systems and Earth System Digital Twins

NASA's Advanced Information Systems Technology (AIST) Program is one of several Technology programs managed by the Earth Science Technology Office (ESTO) in the Earth Science Division (ESD). The AIST Program focuses on advanced information systems and novel computer science technologies that will be needed by NASA Earth Science in the next 5 to 10 years. The three main thrusts of the AIST Program deal with Novel Observing Strategies (NOS), Analytic Collaborative Frameworks (ACF) and Earth System Digital Twins (ESDT). This presentation summarizes the AIST Program with a special focus on the Artificial Intelligence (AI) and Machine Learning (ML) technologies included in its funded projects.

Earth Science Remote Sensing; Information Systems↗
NASA NTRS2011

Towards a Standard for Provenance and Context for Preservation of Data for Earth System Science

Long-term data sets with data from many missions are needed to study trends and validate model results that are typical in Earth System Science research. Data and derived products originate from multiple missions (spaceborne, airborne and/or in situ) and from multiple organizations. During the missions as well as well past their termination, it is essential to preserve the data and products to support future studies. Key aspects of preservation are: preserving bits and ensuring data are uncorrupted, preserving understandability with appropriate documentation, and preserving reproducibility of science with appropriate documentation and other artifacts. Computer technology provides adequate standards to ensure that, with proper engineering, bits are preserved as hardware evolves. However, to ensure understandability and reproducibility, it is essential to plan ahead to preserve all the relevant data and information. There are currently no standards to identify the content that needs to be preserved, leading to non-uniformity in content and users not being sure of whether preserved content is comprehensive. Each project, program or agency can specify the items to be preserved as a part of its data management requirements. However, broader community consensus that cuts across organizational or national boundaries would be needed to ensure comprehensiveness, uniformity and long-term utility of archived data. The Federation of Earth Science Information Partners (ESIP), a diverse network of scientists, data stewards and technology developers, has a forum for ESIP members to collaborate on data preservation issues. During early 2011, members discussed the importance of developing a Provenance and Context Content Standard (PCCS) and developed an initial list of content items. This list is based on the outcome of a NASA and NOAA meeting held in 1998 under the auspices of the USGCRP, documentation requirements from NOAA and our experience with some of the NASA Earth science missions. The items are categorized into the following 8 high level categories: Preflight/Pre-Operations, Products (Data), Product Documentation, Mission Calibration, Product Software, Algorithm Input, Validation, Software Tools.

Ramaprian, Hampapuram K.↗
NASA NTRS2017

Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records

Knowledge of the distribution, extent, duration and timing of snowmelt is critical for characterizing the Earth's climate system and its changes. As a result, snow cover is one of the Global Climate Observing System (GCOS) essential climate variables (ECVs). Consistent, long-term datasets of snow cover are needed to study interannual variability and snow climatology. The NASA snow-cover datasets generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft and the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) are NASA Earth System Data Records (ESDR). The objective of the snow-cover detection algorithms is to optimize the accuracy of mapping snow-cover extent (SCE) and to minimize snow-cover detection errors of omission and commission using automated, globally applied algorithms to produce SCE data products. Advancements in snow-cover mapping have been made with each of the four major reprocessings of the MODIS data record, which extends from 2000 to the present. MODIS Collection 6 (C6) and VIIRS Collection 1 (C1) represent the state-of-the-art global snow cover mapping algorithms and products for NASA Earth science. There were many revisions made in the C6 algorithms which improved snow-cover detection accuracy and information content of the data products. These improvements have also been incorporated into the NASA VIIRS snow cover algorithms for C1. Both information content and usability were improved by including the Normalized Snow Difference Index (NDSI) and a quality assurance (QA) data array of algorithm processing flags in the data product, along with the SCE map.The increased data content allows flexibility in using the datasets for specific regions and end-user applications.Though there are important differences between the MODIS and VIIRS instruments (e.g., the VIIRS 375m native resolution compared to MODIS 500 m), the snow detection algorithms and data products are designed to be as similar as possible so that the 16C year MODIS ESDR of global SCE can be extended into the future with the S-NPP VIIRS snow products and with products from future Joint Polar Satellite System (JPSS) platforms.These NASA datasets are archived and accessible through the NASA Distributed Active Archive Center at the National Snow and Ice Data Center in Boulder, Colorado.

Earth System Data Record↗
NASA NTRS2012

Earth System Modeling and Field Experiments in the Arctic-Boreal Zone - Report from a NASA Workshop

Early climate modeling studies predicted that the Arctic Ocean and surrounding circumpolar land masses would heat up earlier and faster than other parts of the planet as a result of greenhouse gas-induced climate change, augmented by the sea-ice albedo feedback effect. These predictions have been largely borne out by observations over the last thirty years. However, despite constant improvement, global climate models have greater difficulty in reproducing the current climate in the Arctic than elsewhere and the scatter between projections from different climate models is much larger in the Arctic than for other regions. Biogeochemical cycle (BGC) models indicate that the warming in the Arctic-Boreal Zone (ABZ) could lead to widespread thawing of the permafrost, along with massive releases of CO2 and CH4, and large-scale changes in the vegetation cover in the ABZ. However, the uncertainties associated with these BGC model predictions are even larger than those associated with the physical climate system models used to describe climate change. These deficiencies in climate and BGC models reflect, at least in part, an incomplete understanding of the Arctic climate system and can be related to inadequate observational data or analyses of existing data. A workshop was held at NASA/GSFC, May 22-24 2012, to assess the predictive capability of the models, prioritize the critical science questions; and make recommendations regarding new field experiments needed to improve model subcomponents. This presentation will summarize the findings and recommendations of the workshop, including the need for aircraft and flux tower measurements and extension of existing in-situ measurements to improve process modeling of both the physical climate and biogeochemical cycle systems. Studies should be directly linked to remote sensing investigations with a view to scaling up the improved process models to the Earth System Model scale. Data assimilation and observing system simulation studies should be used to guide the deployment pattern and schedule for inversion studies as well. Synthesis and integration of previously funded Arctic-Boreal projects (e.g., ABLE, BOREAS, ICESCAPE, ICEBRIDGE, ARCTAS) should also be undertaken. Such an effort would include the integration of multiple remotely sensed products from the EOS satellites and other resources.

Sellers, Piers↗
NASA NTRS2022

Modeling Demographic-Driven Vegetation Dynamics and Ecosystem Biogeochemical Cycling in NASA GISS’s Earth System Model (ModelE-BiomeE v.1.0)

We developed a demographic vegetation model, BiomeE, to improve the modeling of vegetation dynamics and ecosystem biogeochemical cycles in the NASA Goddard Institute of Space Studies' ModelE Earth system model. This model includes the processes of plant growth, mortality, reproduction, vegetation structural dynamics, and soil carbon and nitrogen storage and transformations. The model combines the plant physiological processes of ModelE's original vegetation model, Ent, with the plant demographic and ecosystem nitrogen processes that have been represented in the Geophysical Fluid Dynamics Laboratory's LM3-PPA. We used nine plant functional types to represent global natural vegetation functional diversity, including trees, shrubs, and grasses, and a new phenology model to simulate vegetation seasonal changes with temperature and precipitation fluctuations. Competition for light and soil resources is individual based, which makes the modeling of transient compositional dynamics and vegetation succession possible. Overall, the BiomeE model simulates, with fidelity comparable to other models, the dynamics of vegetation and soil biogeochemistry, including leaf area index, vegetation structure (e.g., height, tree density, size distribution, and crown organization), and ecosystem carbon and nitrogen storage and fluxes. This model allows ModelE to simulate transient and long-term biogeophysical and biogeochemical feedbacks between the climate system and land ecosystems. Furthermore, BiomeE also allows for the eco-evolutionary modeling of community assemblage in response to past and future climate changes with its individual-based competition and demographic processes.

Biogeochemical cycles↗
NASA NTRS2022

Climate Change Penalty and Benefit on Surface Ozone: A Global Perspective Based on CMIP6 Earth System Models

This work presents an analysis of the effect of climate change on surface ozone discussing the related penalties and benefits around the globe from the global modelling perspective based on simulations with five CMIP6 (Coupled Model Intercomparison Project Phase 6) Earth System Models. As part of AerChemMIP (Aerosol Chemistry Model Intercomparison Project) all models conducted simulation experiments considering future climate (ssp370SST) and present-day climate (ssp370pdSST) under the same future emissions trajectory (SSP3-7.0). A multi-model global average climate change benefit on surface ozone of −0.96 ± 0.07 ppbv °C−1 is calculated which is mainly linked to the dominating role of enhanced ozone destruction with higher water vapour abundances under a warmer climate. Over regions remote from pollution sources, there is a robust decline in mean surface ozone concentration on an annual basis as well as for boreal winter and summer varying spatially from −0.2 to −2 ppbv °C−1, with strongest decline over tropical oceanic regions. The implication is that over regions remote from pollution sources (except over the Arctic) there is a consistent climate change benefit for baseline ozone due to global warming. However, ozone increases over regions close to anthropogenic pollution sources or close to enhanced natural biogenic volatile organic compounds emission sources with a rate ranging regionally from 0.2 to 2 ppbv C−1, implying a regional surface ozone penalty due to global warming. Overall, the future climate change enhances the efficiency of precursor emissions to generate surface ozone in polluted regions and thus the magnitude of this effect depends on the regional emission changes considered in this study within the SSP3_7.0 scenario. The comparison of the climate change impact effect on surface ozone versus the combined effect of climate and emission changes indicates the dominant role of precursor emission changes in projecting surface ozone concentrations under future climate change scenarios.

surface ozone↗
NASA NTRS2021

Reduced Complexity Model Intercomparison Project Phase 2: Synthesizing Earth System Knowledge for Probabilistic Climate Projections

Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state-of-the-art knowledge in an internally self-consistent modelling framework are the increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and the structural rigidity of ESMs mean that the full range of uncertainties across multiple domains are difficult to capture with ESMs alone. The tools of choice are instead more computationally efficient reduced complexity models (RCMs), which are structurally flexible and can span the response dynamics across a range of domain-specific models and ESM experiments. Here we present Phase 2 of the Reduced Complexity Model Intercomparison Project (RCMIP Phase 2), the first comprehensive intercomparison of RCMs that are probabilistically calibrated with key benchmark ranges from specialized research communities. Unsurprisingly, but crucially, we find that models which have been constrained to reflect the key benchmarks better reflect the key benchmarks. Under the low-emissions SSP1-1.9 scenario, across the RCMs, median peak warming projections range from 1.3 to 1.7°C (relative to 1850-1900, using an observationally-based historical warming estimate of 0.8°C between 1850-1900 and 1995-2014). Further developing methodologies to constrain these projection uncertainties seems paramount given the international community's goal to contain warming to below 1.5°C above pre-industrial in the long-term. Our findings suggest that users of RCMs should carefully evaluate their RCM, specifically its skill against key benchmarks and consider the need to include projections benchmarks either from ESM results or other assessments to reduce divergence in future projections.

Climate↗
NASA NTRS1992

Modeling Earth system changes of the past

This review outlines some of the challenging problems to be faced in understanding the causes and mechanisms of large climatic changes and gives examples of initial studies of these problems with climate models. The review covers climatic changes in three main periods of earth history: (1) the past several centuries; (2) the past several glacial-interglacial cycles; and (3) the past several million years. The review will concentrate on studies of climate but, where possible, will mention broader aspects of the earth system.

Kutzbach, John E.↗
NASA NTRS1993

Earth system dynamics: The interrelation of atmospheric, ocean and solid earth dynamics

The research work performed during the time period 16 Oct. 1992 through 31 Dec. 1993 is summarized. The overall research activity, including a list of the major findings of the EOS IDS research to date, is described, the publications and presentations are listed, and a budget request for the subsequent year is attached. Specifically, the report covers: EOS panel activities; major findings of research; team member contributions; new research directions; EOS restructuring effect; changes in requirements; plans for using existing data; collaborations with other EOS and non-EOS investigations; EOS instrument team interaction; instrument development verification and validation; interaction with EOSDIS and DAAC's; team coordination; overall management; summary of response to site review questions and comments; science computing facility; and additional new research activities.

Tapley, Byron D.↗
NASA NTRS2002

Orbital Noise in the Earth System is a Common Cause of Climate and Greenhouse-Gas Fluctuation

The mismatch between fossil isotopic data and climate models known as the cool-tropic paradox implies that either the data are flawed or we understand very little about the climate models of greenhouse warming. Here we question the validity of the climate models on the scientific background of orbital noise in the Earth system. Our study shows that the insolation pulsation induced by orbital noise is the common cause of climate change and atmospheric concentrations of carbon dioxide and methane. In addition, we find that the intensity of the insolation pulses is dependent on the latitude of the Earth. Thus, orbital noise is the key to understanding the troubling paradox in climate models.

Liu, H. S.↗
NASA NTRS2018

The Tropospheric Emission Spectrometer: From Discovery Mission to Earth System Sounding

The Tropospheric Emission Spectrometer (TES) was launched aboard the Aura spacecraft in 2004 and decommissioned in February 2018. Over more than a decade of observations, TES has shown the potential of high-resolution Fourier Transform Spectrometer (FTS) measurements to alter our understanding of atmospheric composition and its relationship to the Earth System. We survey some of the major contributions TES has made to understanding air quality, chemistry-climate interactions, atmospheric hydrology, and carbon cycle science. We then show how innovations in retrieval methods pioneered by the TES team are now being applied to multi-spectral, multi-instrument records, establishing a new paradigm for composition measurements into the future.

Bowman, Kevin W.↗
NASA NTRS2017

Reduced ENSO Variability at the LGM Revealed by an Isotope-Enabled Earth System Model

Studying the El Nino Southern Oscillation (ENSO) in the past can help us better understand its dynamics and improve its future projections. However, both paleoclimate reconstructions and model simulations of ENSO strength at the Last Glacial Maximum (LGM; 21 ka B.P.) have led to contradicting results. Here we perform model simulations using the recently developed water isotope-enabled Community Earth System Model (iCESM). For the first time, model-simulated oxygen isotopes are directly compared with those from ENSO reconstructions using the individual foraminifera analysis (IFA). We find that the LGM ENSO is most likely weaker comparing with the preindustrial. The iCESM suggests that total variance of the IFA records may only reflect changes in the annual cycle instead of ENSO variability as previously assumed. Furthermore, the interpretation of subsurface IFA records can be substantially complicated by the habitat depth of thermocline-dwelling foraminifera and their vertical migration with a temporally varying thermocline.

El Niño–Southern Oscillation;isotope-enabled si↗
NASA NTRSDate not supplied

Regional Impacts of Ice Sheet Surface Representation Improvements in an Earth System Model

Ice sheet surface conditions and their subsequent impact on surface mass balance play an important role in ice sheet dynamics and ice sheet interaction with the overlying atmosphere and surrounding ocean. The NASA Global Modeling and Assimilation Office’s (GMAO) Goddard Earth Observing System (GEOS) ecosystem of models and reanalyses model ice sheet and glacier surface mass balance with a moderately complex snow and ice module, including prognostic surface albedo evolution, fractional snow cover, and snowpack hydrology and meltwater retention. With this configuration, Greenland near surface air temperatures and ice sheet melt are well represented in MERRA-2, GMAO’s current atmospheric reanalysis; however, the similarity to observations in some regions is due, in part, to compensating biases in surface energy budget. Recent improvements to GEOS’ cloud microphysics and longwave radiation parameterizations reduced biases in surface net longwave radiation and exacerbated surface net shortwave radiation biases, effectively increasing near surface temperatures and melting, particularly during the summer months. Here, we demonstrate the Earth system response to an improved representation of the ice sheet surface focused on minimizing the surface energy biases and increasing spatial and temporal representativeness. New changes to the surface albedo parameterization, including the introduction of a prognostic aerosol darkening scheme, help mitigate shortwave biases, while modifications to surface roughness characteristics improve near surface sensible heat fluxes. Focusing on the Arctic and Greenland, we examine the combined impact on these changes on regional weather conditions and ice sheet surface mass balance using a high resolution atmospheric only experiment, and we use a coupled model configuration to assess the impact on oceanic conditions and subseasonal-to-seasonal prediction. Overall, these improvements increase modeled ice sheet surface realism and provide a strong basis for more accurate ice sheet mass balance in GMAO’s future reanalyses and forecasting systems.

Lauren C Andrews↗