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CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_FM1+FM3_Edition2)

The ERBE-like Monthly Geographical Averages (ES-4) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

CLEAR-SKY ALBEDO↗

DOE OSTI2022

Outage Cause Classification of Power Distribution Systems with Machine Learning and Real-World Data

Power distribution systems are geographically dispersed by nature. It may be affected by various factors, such as vegetation, weather, animal and human behaviors. Present response procedures to an outage event massively rely on expert experience and thus tend to be time-consuming. Automatic outage event detection and classification will help to reduce the responding and restoration time. However, this issue is less addressed with existing research done in this area. In this applied research, a set of waveform pre-processing techniques are first proposed to prepare the waveform data for being used as inputs to the classification algorithm. Further, a machine learning-based algorithm is proposed to classify the outage events according to their root causes, e.g. tree contact, animal contact, lightning, etc. Available data include three phase current & voltage waveforms and contextual information during the distribution system outages. The proposed machine learning algorithm takes the current and voltage waveforms as direct inputs in search of features that humans are unable to capture. Real data provided by a distribution company in the East Tennessee region is used to test the proposed pre-processing techniques and the classification algorithm.

Sun, Haoyuan↗

DOE OSTI2025

West Coast Offshore Wind Transmission Study

As a primary federal investigation of the utility of transmission to support offshore wind emergence in the Western Interconnect, the West Coast Offshore Wind Transmission study evaluates five distinct West Coast-wide transmission scenarios and trades the economic benefits and costs of six development pathways from 2035 to 2050. In this time, 33 GW of OSW generation and supporting transmission are explored within the context of 350 additional GW of generation to support 100% clean electricity. Geospatial analysis informed plausible transmission topologies and cost estimates. All pathways to intraregional or interregional coordination transmission builds showed more than $\$$14 billion in present value cost savings, with a maximum of $\$$25 billion of savings in the interregional case. These savings are primarily driven by fuel costs and increased availability of power flows enabled by new transmission networks. Key considerations of clean, dispatchable generation options, geographic disaggregation of costs, system reliability reinforcements, resilience, and community values are also presented and discussed.

17 WIND ENERGY↗

NASA NTRS1993

The 3-D Moons: The Voyager stereo atlas of the outer solar system

Comprehension and analysis of geologic features on any planet is enhanced manyfold by a clear perception between albedo and topography. On many of the icy satellites significant albedo contrasts due to mixtures of dark rocky and bright icy materials can be associated with topographic features. Subtle topographic features can be masked by albedo variation and under high solar illumination albedo and topography can be difficult to separate. To this end we are compiling an atlas of stereo image pairs of the outer solar system based on Voyager imaging for the investigation of various geologic problems and for general use. For the icy satellites, general perceptions of topography are usually gleaned from shape-from-shading information in the images processed by the human brain (i.e. visual inspection). With few exceptions, actual topography has been measured on a spot-by-spot basis using shadow heights or photoclinometry, or along limb profiles (where geographic context may be unavailable). Shadow heights are limited to regions within approximately 10 deg of the terminator and images with resolution better than approximately 1 km/pixel. Photoclinometric scans can be used more widely but are subject to a variety of errors, primarily uncertain assumptions of uniform scene albedo or poorly understood photometry. Stereoscopic analysis, where available, has the potential for greatly expanding topographic perception.

Schenk, P.↗

NASA NTRS2014

Software Suite to Support In-Flight Characterization of Remote Sensing Systems

A characterization software suite was developed to facilitate NASA's in-flight characterization of commercial remote sensing systems. Characterization of aerial and satellite systems requires knowledge of ground characteristics, or ground truth. This information is typically obtained with instruments taking measurements prior to or during a remote sensing system overpass. Acquired ground-truth data, which can consist of hundreds of measurements with different data formats, must be processed before it can be used in the characterization. Accurate in-flight characterization of remote sensing systems relies on multiple field data acquisitions that are efficiently processed, with minimal error. To address the need for timely, reproducible ground-truth data, a characterization software suite was developed to automate the data processing methods. The characterization software suite is engineering code, requiring some prior knowledge and expertise to run. The suite consists of component scripts for each of the three main in-flight characterization types: radiometric, geometric, and spatial. The component scripts for the radiometric characterization operate primarily by reading the raw data acquired by the field instruments, combining it with other applicable information, and then reducing it to a format that is appropriate for input into MODTRAN (MODerate resolution atmospheric TRANsmission), an Air Force Research Laboratory-developed radiative transport code used to predict at-sensor measurements. The geometric scripts operate by comparing identified target locations from the remote sensing image to known target locations, producing circular error statistics defined by the Federal Geographic Data Committee Standards. The spatial scripts analyze a target edge within the image, and produce estimates of Relative Edge Response and the value of the Modulation Transfer Function at the Nyquist frequency. The software suite enables rapid, efficient, automated processing of ground truth data, which has been used to provide reproducible characterizations on a number of commercial remote sensing systems. Overall, this characterization software suite improves the reliability of ground-truth data processing techniques that are required for remote sensing system in-flight characterizations.

Stanley, Thomas↗

DOE OSTI2025

A Near-Real-Time Model for Predicting Electricity Disruptions in Texas During Winter Storms

There has been an increase in extreme weather events, posing a threat to power grid systems, potentially influenced by factors such as population growth, changes in ecosystems, land cover, and land use in the service area, as well as the growth of certain vegetation types. This research seeks to develop a predictive model to mitigate potential damages caused by future winter storms. This research utilizes the Light Gradient Boosting Machine (LightGBM), incorporating the number of power outages experienced at the county level, geographic details, weather information, and lagged outage and lagged weather data. The developed models were broadly divided into two groups, with six models in each group - one group without optimization and another with optimization, totaling 12 trained models. For model optimization, Bayesian optimization was employed using Root Mean Squared Error (RMSE) as the objective function. In results, when comparing Group 2 (the optimized group) with Group 1 (the non-optimized group), it was found that optimization did not always lead to a reduction in RMSE and Mean Absolute Error (MAE). However, in terms of Mean Directional Accuracy (MDA), while all results in Group 1 were below the baseline accuracy of 0.33, all results in Group 2 exceeded 0.33, with some cases showing an increase of more than three times the baseline. The results indicated that, in the optimized model group, Population and Pressure were the most influential factors when using current weather data and geographical information. When using lagged data, lagged recorded outages and lagged Pressure emerged as the most significant factors. Among the 12 developed models, the L-1-2-O model showed the lowest RMSE and MAE, as well as the highest accuracy, with values of 390.62 households and 168.13 households, respectively. To normalize the RMSE and MAE values, each metric was divided by the average number of households among the counties in Texas. For the L-1-2-O model, the scaled RMSE was 0.88% and the scaled MAE was 0.38%. In terms of MDA, which indicates the accuracy of the prediction direction, the L-1-O model achieved the highest score of 0.41. Although this study focused on Texas, which suffered the greatest impact from the winter storms in 2021, with additional validation, the methodology used in this research could be applied to other regions.

Lee, Jangjae [Texas A & M Univ., College Station, ↗

DOE OSTI2020

Distributed Resources for the Earth System Grid Federation (ESGF) Advanced Management (DREAM). Final Report

Distributed Resources for the Earth System Grid Federation (ESGF) Advanced Management (DREAM) is a proposed system that will enable data from an infinite number of diverse sources to be organized and accessed from anywhere using any handheld or other computer device. The approach offers a powerful roadmap for the creation and integration of a unified knowledge base of an entire ecosystem, including its many geophysical, geographical, social, political, agricultural, energy, transportation, and cyber aspects. The resulting aggregation of data has the potential to generate an informational universe of unprecedented size that has never before been possible due to the prohibitive costs, managerial complexity, and technical barriers associated with ever-changing exponential-growth data flows. We envision that DREAM will accelerate discovery by enabling climate researchers, among other types of researchers, to manage, analyze, and visualize data from earth-scale measurements and simulations. DREAM’s success will be built on proven components that leverage existing services and resources. A key building block for DREAM will be the ESGF, chaired by Dean N. Williams. Expanding on the existing ESGF, the project will ensure that the access, storage, movement, and analysis of the large quantities of data that are processed and produced by diverse science projects can be dynamically distributed with proper resource management. Much of the Office of Science data is currently generated by multiple stand-alone facilities. DREAM can collect data accumulated from these facilities and incorporate it into a fully integrated network accessible from anywhere in the world. The result is a completely new paradigm shift for data management, analysis, and visualization enabling researchers to: Manage their calculations, data, tools, and research results; Ensure that all data are sharable, reproducible and (re)usable—accompanied by appropriate metadata describing its provenance, syntax, and semantics at creation; Advance application performance by selectively adapting APIs and services in response to scientific requirements and architectural complexities; and Provide scalable interactive resource management—navigate data and metadata at multiple levels, provide architecture-aware data integration, analysis and visualization tools. We will engage closely with DOE, NASA, and NOAA science groups working at the leading edge of computing. These engagements—in domains such as biology, climate, and hydrology—will allow us to advance disciplinary science goals and inform our development of technologies that can accelerate discovery across DOE more broadly. We will advertise and promote our technologies via dedicated workshops, tutorials, and sessions at conferences, stand-alone events with broad inter-disciplinary invitation, and engagements with leadership facilities.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1997

Remote Sensing of Surficial Process Responses to Extreme Meteorological Events

Changes in the frequency and magnitude of extreme meteorological events are associated with changing environmental means. Such events are important in human affairs, and can also be investigated by orbital remote sensing. During the course of this project, we applied ERS-1, ERS-2, Radarsat, and an airborne sensor (AIRSAR-TOPSAR) to measure flood extents, flood water surface profiles, and flood depths. We established a World Wide Web site (the Dartmouth Flood Observatory) for publishing remote sensing-based maps of contemporary floods worldwide; this is also an online "active archive" that presently constitutes the only global compilation of extreme flood events. We prepared an article for EOS concerning SAR imaging of the Mississippi Valley flood; an article for the International Journal of Remote Sensing on measurement of a river flood wave using ERS-2, began work on an article (since completed and published) on the Flood Observatory for a Geoscience Information Society Proceedings volume, and presented lectures at several Geol. Soc. of America Natl. Meetings, an Assoc. of Amer. Geographers Natl. Meeting, and a Binghamton Geomorphology Symposium (all on SAR remote sensing of the Mississippi Valley flood). We expanded in-house modeling capabilities by installing the latest version of the Army Corps of Engineers RMA two-dimensional hydraulics software and BYU Engineering Graphics Lab's Surface Water Modeling System (finite elements based pre- and post-processors for RMA work) and also added watershed modeling software. We are presently comparing the results of the 2-d flow models with SAR image data. The grant also supported several important upgrades of pc-based remote sensing infrastructure at Dartmouth. During work on this grant, we collaborated with several workers at the U.S. Army Corps of Engineers, Remote Sensing/GIS laboratory (for flood inundation mapping and modeling; particularly of the Illinois River using the AIRSAR/TOPSAR/ERS-2 combined data), with Dr. Karen Prestegaard at the University of Maryland (geomorphological responses to the extreme 1993 flood along the Raccoon drainage in central Iowa), and with Mr Tim Scrom of the Albany National Weather Service River Forecast Center (initial planning for the use of Radarsat and ERS-2 for flood warning). The work thus initiated with this proposal is continuing.

Brakenridge, G. Robert↗

NASA NTRS2006

Central America Regional Climate Change Program: Tools for Your Use

USAID/E-CAM and EGAT's Global Climate Change Team, in partnership with EPA, NASA, Oak Ridge National Lab, and the Central American Commission for Environment and Development (CCAD), have had a significant impact on the region's ability to monitor, mitigate, and adapt to environmental threats. Environmental decision-making tools and data are posted on a website (SERVIR: http://servir.nsstc.nasa.pov/home.html)that provides satellite and geographic data and maps to anybody with an Internet connection. The SERVIR program has been identified as the model for the Global Earth Observation System of Systems (GEOSS) - a major international effort to develop a 21st century system for environmental management and disaster response. In coordination with the USAID/EPA program, NASA has developed a GIs tool that enables countries to examine their forest cover and document changes on an annual basis. This information is used in calculating carbon emissions as part of greenhouse gas inventories, but also serves a valuable monitoring function. In addition, USAID/E-CAM and EGAT's Global Climate Change Team in collaboration with EPA are helping countries meet their obligations as signatories to the United Nations Framework Convention on Climate Change (UNFCCC). EPA is assisting Central American governments to improve the quality of their greenhouse gas emission inventories reported to the UNFCCC through the development of tools and improvements in data quality. New EPA tools developed include software to automatically calculate greenhouse gas emissions for the agricultural and forestry sector inventories, determine key sources of greenhouse gas emissions, and document institutional arrangements. Several of these tools are state of the art and are comparable to tools currently used in the U.S.

Irwin, Dan↗

NASA NTRS2014

Characteristics of Extreme Auroral Charging Events

The highest level spacecraft charging observed in low Earth orbit (LEO) occurs when spacecraft are exposed to energetic auroral electrons. Since auroral charging has been identified as a mechanism responsible for on-orbit anomalies and even possible satellite failures it is important to consider extreme auroral charging events as design and test environments for spacecraft to be used in high inclination LEO orbits. This paper will report on studies of extreme auroral charging events using data from the SSJ/4 and SSJ/5 precipitating electron and ion sensors on the Defense Meteorology Satellite Program (DMSP) satellites. Early studies of DMSP charging to negative potentials ≥100 V focused on statistics of the electron environment responsible for charging. Later statistical studies of auroral charging have generally focused on solar cycle dependence of charging behavior and magnitude of the maximum potential and duration of the charging events. We extend these studies to focus on more detailed investigations of extreme charging event characteristics that are required to evaluate potential threats to spacecraft systems. A collection of example auroral charging events is assembled from the DMSP data set using the criteria that "extreme auroral charging" is defined as periods with spacecraft negative potentials ≥400 V. Specific characteristics to be treated include (but are not limited to) maximum and mean potentials, time history of spacecraft potentials through the events, total charging duration and the time potentials exceed voltage thresholds, frame charging/discharging rates, and information on geographic and geomagnetic latitudes at which the events are observed. Finally, we will comment on the implications of these studies for potential auroral charging risks to the International Space Station.

Minow, Joseph I.↗

DOE OSTI2021

Selecting and Implementing Resilience Metrics in Existing Energy Sector Models [Slides]

Resilience is a topic receiving much attention in relation to energy systems, with particular attention being paid to the supply of electricity. As a result of the growing interest in energy sector resilience, research communities have proposed a plethora of candidate resilience indicators and metrics, most of which remain immature at different scales and segments within the energy system. A necessary focus of the research community lies in implementing, testing, and validating resilience metrics and analysis approaches in energy sector models, which will be invaluable for informing resilience planning and investment decisions. Recognizing these challenges that need to be addressed, we explore how to effectively integrate resilience considerations into energy sector models and tools. The overarching goal of the effort was to evaluate the data needs, methodologies, and outcomes - including consequences and/or changes in investment or operational decisions due to avoided consequences - based on resilience analysis in a range of existing tools. In particular, we selected five models originally built at NREL to explore non-resilience energy research questions to implement and exercise resilience metrics and analysis approaches. To demonstrate the importance of perspective, we selected models that represent different segments of the energy sector, geographic scales, and modeling approaches. A second important aspect of our effort was the development of generalized power interruption scenarios. These scenarios were intended to help establish a framework for simulating the effects of real-world threats in terms of their impacts on system components and, in turn, power interruption.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Adapting Existing Energy Models for Resilience Analysis

Resilience is a topic receiving much attention in relation to energy systems, with particular attention being paid to the supply of electricity. As a result of the growing interest in energy sector resilience, research communities have proposed a plethora of candidate resilience indicators and metrics, most of which remain immature at different scales and segments within the energy system. A necessary focus of the research community lies in implementing, testing, and validating resilience metrics and analysis approaches in energy sector models, which will be invaluable for informing resilience planning and investment decisions. Recognizing these challenges that need to be addressed, we explore how to effectively integrate resilience considerations into energy sector models and tools. The overarching goal of the effort was to evaluate the data needs, methodologies, and outcomes—including consequences and/or changes in investment or operational decisions due to avoided consequences—based on resilience analysis in a range of existing tools. In particular, we selected five models originally built at NREL to explore non-resilience energy research questions to implement and exercise resilience metrics and analysis approaches. To demonstrate the importance of perspective, we selected models that represent different segments of the energy sector, geographic scales, and modeling approaches. A second important aspect of our effort was the development of generalized power interruption scenarios. These scenarios were intended to help establish a framework for simulating the effects of real-world threats in terms of their impacts on system components and, in turn, power interruption.

ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1980

A survey of light-scattering techniques used in the remote monitoring of atmospheric aerosols

A critical survey of the literature on the use of light-scattering mechanisms in the remote monitoring of atmospheric aerosols, their geographical and spatial distribution, and temporal variations was undertaken to aid in the choice of future operational systems, both ground based and air or space borne. An evaluation, mainly qualitative and subjective, of various techniques and systems is carried out. No single system is found to be adequate for operational purposes. A combination of earth surface and space-borne systems based mainly on passive techniques involving solar radiation with active (lidar) systems to provide auxiliary or backup information is tentatively recommended.

Deirmendjian, D.↗

NASA NTRS2018

Global Relationships Among Traditional Reflectance Vegetation Indices (NDVI and NDII), Evapotranspiration (ET), and Soil Moisture Variability on Weekly Time Scales

Monitoring the effects of water availability on vegetation globally using satellites is important for applications such as drought early warning, precision agriculture, and food security as well as for more broadly understanding relationships between water and carbon cycles. In this global study, we examine how quickly several satellite-based indicators, assumed to have relationships with water availability, respond, on timescales of days to weeks, in comparison with variations in root-zone soil moisture (RZM) that extends to about 1 m depth. The satellite indicators considered are the normalized difference vegetation and infrared indices (NDVI and NDII, respectively) derived from reflectances obtained with moderately wide (20–40 nm) spectral bands in the visible and near-infrared (NIR) and evapotranspiration (ET) estimated from thermal infrared observations and normalized by a reference ET. NDVI is primarily sensitive to chlorophyll contributions and vegetation structure while NDII may contain additional information on water content in leaves and canopy. ET includes both the loss of root zone soil water through transpiration (modulated by stomatal conductance) as well as evaporation from bare soil. We find that variations of these satellite-based drought indicators on time scales of days to weeks have significant correlations with those of RZM in the same water-limited geographical locations that are dominated by grasslands, shrublands, and savannas whose root systems are generally contained within the 1 m RZM layer. Normalized ET interannual variations show generally a faster response to water deficits and enhancements as compared with those of NDVI and NDII, particularly in sparsely vegetated regions.

Joanna Joiner↗

NASA NTRS2002

Stratospheric Analysis and Forecasting in the Northern Winter of 1999/2000: The NASA DAO's GEOS-3 System

An evaluation is presented of the performance in the northern winter 1999/2000 of the GEOS-3 troposphere-stratosphere data assimilation system (DAS). The impacts of the two main input data types are assessed: upper-air soundings (sondes) provide wind and temperature information and satellite-based (Tiros Operational Vertical Sounders: TOVS) give estimates of the thermal structure. It is shown that in the low stratosphere (300-70hPa) the analyses are generally slightly warmer than the sonde data, but colder than the TOVS data; this relationship reverses between 70 and 10 hPa. There are geographical biases, related to the spatial and temporal coverage of the observation types and to the statistical weights assigned to them in the DAS. Forecasts show a tendency to reduce zonal asymmetries in the atmospheric flow and to suppress stratospheric temperature minima. In the DAS, the analysis increments compensate for this, but it leads to important biases in the multi-day forecasts. The analysis increments are as large as the diabatic forcing in the lower polar stratosphere, indicating a substantial model bias. The results provide important insights into the roles of different data types and the circulation model in producing accurate analyses for studies of polar chemistry and physical processes.

Pawson, Steven↗

NASA NTRS2005

Comparison of TRMM Ground Validation and Satellite Rain Intensity Estimates

The Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) Program began in the late 1980's and has provided a wealth of data and resources for validating TRMM satellite estimates. The TRMM GV program's main operational task is to provide rainfall products for four sites: Darwin, Australia (DARW); Houston, Texas (HSTN); Kwajalein, Republic of the Marshall Islands (KWAJ); and, Melbourne, Florida (MELB). A comparison between TRMM Ground Validation (Version 5) and Satellite (Version 6) rain intensity estimates is presented. The full suite of Version 6 satellite data is currently being generated by the TRMM Science Data and Information System (TSDIS) and should be completed some time near the end of 2005. The gridded satellite product (3G68) will be compared to GV Level II rain-intensity and -type maps (2A53 and 2A54, respectively). The 3G68 product represents a 0.5 deg x 0.5 deg data grid providing estimates of rain intensities from the TRMM Precipitation Radar (PR), Microwave Imager (TMI) and Combined (COM) algorithms. The comparisons will be sub-setted according to geographical type (land, coast and ocean). A bias statistic will be presented that provides quantification of the relative differences between the various estimators. Previous comparisons of an interim satellite product (Version 6a) showed that all of the estimates (GV and satellite) are converging, with some expected discrepancies. The convergence of the GV and satellite estimates bodes well for expectations for the proposed Global Precipitation Measurement (GPM) program and this study and others are being leveraged towards planning GV goals for GPM.

Wolff, David B.↗

NASA NTRS2000

Ocean Data from MODIS at the NASA Goddard DAAC

Terra satellite carrying the Moderate Resolution Imaging Spectroradiometer (MODIS) was successfully launched on December 18, 1999. Some of the 36 different wavelengths that MODIS samples have never before been measured from space. New ocean data products, which have not been derived on a global scale before, are made available for research to the scientific community. For example, MODIS uses a new split window in the four-micron region for the better measurement of Sea Surface Temperature (SST), and provides the unprecedented ability (683 nm band) to measure chlorophyll fluorescence. At full ocean production, more than a thousand different ocean products in three major categories (ocean color, sea surface temperature, and ocean primary production) are archived at the NASA Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC) at the rate of approx. 230GB/day. The challenge is to distribute such large volumes of data to the ocean community. It is achieved through a combination of public and restricted EOS Data Gateways, the GES DAAC Search and Order WWW interface, and an FTP site that contains samples of MODIS data. A new Search and Order WWW interface at http://acdisx.gsfc.nasa.gov/data/ developed at the GES DAAC is based on a hierarchical organization of data, will always return non-zero results. It has a very convenient geographical representation of five-minute data granule coverage for each day MODIS Data Support Team (MDST) continues the tradition of quality support at the GES DAAC for the ocean color data from the Coastal Zone Color Scanner (CZCS) and the Sea Viewing Wide Field-of-View Sensor (SeaWiFS) by providing expert assistance to users in accessing data products, information on visualization tools, documentation for data products and formats (Hierarchical Data Format-Earth Observing System (HDF-EOS)), information on the scientific content of products and metadata. Visit the MDST website at http://daac.gsfc.nasa.gov/CAMPAIGN DOCS/MODIS/index.html

Leptoukh, Gregory G.↗

DOE OSTI2021

Potential ecological impacts of climate intervention by reflecting sunlight to cool Earth

As the effects of anthropogenic climate change become more severe, several approaches for deliberate climate intervention to reduce or stabilize Earth’s surface temperature have been proposed. Solar radiation modification (SRM) is one potential approach to partially counteract anthropogenic warming by reflecting a small proportion of the incoming solar radiation to increase Earth’s albedo. While climate science research has focused on the predicted climate effects of SRM, almost no studies have investigated the impacts that SRM would have on ecological systems. The impacts and risks posed by SRM would vary by implementation scenario, anthropogenic climate effects, geographic region, and by ecosystem, community, population, and organism. Complex interactions among Earth’s climate system and living systems would further affect SRM impacts and risks. We focus here on stratospheric aerosol intervention (SAI), a well-studied and relatively feasible SRM scheme that is likely to have a large impact on Earth’s surface temperature. We outline current gaps in knowledge about both helpful and harmful predicted effects of SAI on ecological systems. Desired ecological outcomes might also inform development of future SAI implementation scenarios. In addition to filling these knowledge gaps, increased collaboration between ecologists and climate scientists would identify a common set of SAI research goals and improve the communication about potential SAI impacts and risks with the public. Without this collaboration, forecasts of SAI impacts will overlook potential effects on biodiversity and ecosystem services for humanity.

54 ENVIRONMENTAL SCIENCES↗