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DOE OSTI2020

Integrating environmental understanding into freshwater floatovoltaic deployment using an effects hierarchy and decision trees

Abstract In an era of looming land scarcity and environmental degradation, the development of low carbon energy systems without adverse impacts on land and land-based resources is a global challenge. ‘Floatovoltaic’ energy systems—comprising floating photovoltaic (PV) panels over water—are an appealing source of low carbon energy as they spare land for other uses and attain greater electricity outputs compared to land-based systems. However, to date little is understood of the impacts of floatovoltaics on the hosting water body. Anticipating changes to water body processes, properties and services owing to floatovoltaic deployment represents a critical knowledge gap that may result in poor societal choices and water body governance. Here, we developed a theoretically-derived hierarchical effects framework for the assessment of floatovoltaic impacts on freshwater water bodies, emphasising ecological interactions. We describe how the presence of floatovoltaic systems may dramatically alter the air-water interface, with subsequent implications for surface meteorology, air-water fluxes and physical, chemical and biological properties of the recipient water body. We apply knowledge from this framework to delineate three response typologies—‘ magnitude’ , those for which the direction and magnitude of effect can be predicted; ‘ direction’ , those for which only the direction of effect can be predicted; and ‘ uncertain’ , those for which the response cannot be predicted—characterised by the relative importance of levels in the effects hierarchy. Illustrative decision trees are developed for an example water body response within each typology, specifically, evaporative water loss, cyanobacterial biomass, and phosphorus release from bed sediments, and implications for ecosystem services, including climate regulation, are discussed. Finally, the potential to use the new understanding of likely ecosystem perturbations to direct floatovoltaic design innovations and identify future research priorities is outlined, showcasing how inter-sectoral collaboration and environmental science can inform and optimise this low carbon, land-sparing renewable energy for ecosystem gains.

Environmental Sciences & Ecology↗

NASA NTRS2000

Wavelet and Fractal Analysis of Remotely Sensed Surface Temperature with Applications to Estimation of Surface Sensible Heat Flux Density

Wavelet and fractal analyses have been used successfully to analyze one-dimensional data sets such as time series of financial, physical, and biological parameters. These techniques have been applied to two-dimensional problems in some instances, including the analysis of remote sensing imagery. In this respect, these techniques have not been widely used by the remote sensing community, and their overall capabilities as analytical tools for use on satellite and aircraft data sets is not well known. Wavelet and fractal analyses have the potential to provide fresh insight into the characterization of surface properties such as temperature and emissivity distributions, and surface processes such as the heat and water vapor exchange between the surface and the lower atmosphere. In particular, the variation of sensible heat flux density as a function of the change In scale of surface properties Is difficult to estimate, but - in general - wavelets and fractals have proved useful in determining the way a parameter varies with changes in scale. We present the results of a limited study on the relationship between spatial variations in surface temperature distribution and sensible heat flux distribution as determined by separate wavelet and fractal analyses. We analyzed aircraft imagery obtained in the thermal infrared (IR) bands from the multispectral TIMS and hyperspectral MASTER airborne sensors. The thermal IR data allows us to estimate the surface kinetic temperature distribution for a number of sites in the Midwestern and Southwestern United States (viz., San Pedro River Basin, Arizona; El Reno, Oklahoma; Jornada, New Mexico). The ground spatial resolution of the aircraft data varied from 5 to 15 meters. All sites were instrumented with meteorological and hydrological equipment including surface layer flux measuring stations such as Bowen Ratio systems and sonic anemometers. The ground and aircraft data sets provided the inputs for the wavelet and fractal analyses, and the validation of the results.

Schieldge, John↗

NASA NTRS1980

Mark 3 VLBI system: Tropospheric calibration subsystems

Tropospheric delay calibrations are implemented in the Mark 3 system with two subsystems. Estimates of the dry component of tropospheric delay are provided by accurate barometric data from a subsystem of surface meteorological sensors (SMS). An estimate of the wet component of tropospheric delay is provided by a water vapor radiometer (WVR). Both subsystems interface directly to the ASCII Transceiver bus of the Mark 3 system and are operated by the control computer. Seven WVR's under construction are designed to operate in proximity to a radio telescope and can be commanded to point along the line-of-sight to a radio source. They should provide a delay estimate that is accurate to the + or - 2 cm level.

Resch, G. M.↗

NASA NTRS2024

Validation and Application of Satellite-Derived Sea Surface Temperature Gradients in the Bering Strait and Bering Sea

The Arctic is one of the most important regions in the world’s oceans for understanding the impacts of a changing climate. Yet, it is also difficult to measure because of extreme weather and ice conditions. In this work, we directly compare four datasets from the Group for High-Resolution Sea Surface Temperature (GHRSST) with a NASA Saildrone deployment along the Alaskan Coast and the Bering Sea and Bering Strait. The four datasets used are the Remote Sensing Systems Microwave Infrared Optimally Interpolated (MWIR) product, the Canadian Meteorological Center (CMC) product, the Daily Optimally Interpolated Product (DOISST), and the Operational Sea Surface Temperature and Ice Analysis (OSTIA) product. Spatial sea surface temperature (SST) gradients were derived for both the Saildrone deployment and GHRSST products, with the GHRSST products collocated with the Saildrone deployment. Overall, statistics indicate that the OSTIA product had a correlation of 0.79 and a root mean square difference of 0.11 °C/km when compared with Saildrone. CMC had the highest correlation of 0.81. Scatter plots indicate that OSTIA had the slope closest to one, thus best reproducing the magnitudes of the Saildrone gradients. Differences increased at latitudes > 65°N where sea ice would have a greater impact. A trend analysis was then performed on the gradient fields. Overall, positive trends in gradients occurred in areas along the coastal regions. A negative trend occurred at approximately 60°N. A major finding of this study is that future work needs to revolve around the impact of changing ice conditions on SST gradients. Another major finding is that a northward shift in the southern ice edge occurred after 2010 with a maxima at approximately 2019. This indicates that the shift of the southern ice edge is not gradual but has dramatically increased over the last decade. Future work needs to revolve around examining the possible causes for this northward shift.

Arctic↗

NASA NTRS2019

Soil Moisture Data Assimilation

Accurate knowledge of soil moisture at the continental scale is important for improving predictions of weather, agricultural productivity and natural hazards, but observations of soil moisture at such scales are limited to indirect measurements, either obtained through satellite remote sensing or from meteorological networks. Land surface models simulate soil moisture processes, using observation-based meteorological forcing data, and auxiliary information about soil, terrain and vegetation characteristics. Enhanced estimates of soil moisture and other land surface variables, along with their uncertainty, can be obtained by assimilating observations of soil moisture into land surface models. These assimilation results are of direct relevance for the initialization of hydro-meteorological ensemble forecasting systems. The success of the assimilation depends on the choice of the assimilation technique, the nature of the model and the assimilated observations, and, most importantly, the characterization of model and observation error. Systematic differences between satellite-based microwave observations or satellite-retrieved soil moisture and their simulated counterparts require special attention. Other challenges include inferring root-zone soil moisture information from observations that pertain to a shallow surface soil layer, propagating information to unobserved areas and downscaling of coarse information to finer-scale soil moisture estimates. This chapter summarizes state-of-the-art solutions to these issues with conceptual data assimilation examples, using techniques ranging from simplified optimal interpolation to spatial ensemble Kalman filtering. In addition, operational soil moisture assimilation systems are discussed that support numerical weather prediction at ECMWF and provide value-added soil moisture products for the NASA Soil Moisture Active Passive mission.

radar backscatter↗

DOE OSTI2025

Role of Forest Carbon Change in Shaping Future Land Use and Land Cover Change

Global change, particularly the changes in atmospheric CO 2 concentration, climatic variables, and nitrogen deposition, has been widely recognized and examined to have worldwide impacts on forest carbon. However, its influence on forest area required to meet the demand for timber and carbon storage and subsequent land use and land cover change (LULCC) is rarely studied. This study explores the role of global change-driven forest carbon change in shaping future global LULCC projections and investigates underlying drivers. We incorporated the global change impacts on forest carbon from the Canadian Land Surface Scheme Including Biogeochemical Cycles model simulations (driven by meteorological forcing projections from two Earth system models [ESMs]) into the Global Change Analysis Model, under three combinations of shared socioeconomic pathways and representative concentration pathways (SSP126, SSP370, and SSP585). Including forest carbon change decreases the projected expansion of managed forest and managed pasture, reduces the loss of unmanaged pastures and forests, and provides more cropland. The relative change in managed forest by 2100 is -4.0%, -21.7%, and -31.9%, under SSP126, SSP370, and SSP585, respectively, when forest carbon change is considered. CO 2 fertilization is the dominant driver, increasing forest vegetation and soil carbon by 37% and 4.1%, and leading to 78.6% of the total area with a change in land use types by 2100 under SSP585. In comparison, climate change reduces forest vegetation and soil carbon by -3.5% and -0.8%, influencing 23.9% of the total area with a change in land use types by 2100 under SSP585, while nitrogen deposition has minor impacts. Using meteorological forcing data from two ESMs leads to similar impacts of forest carbon change on LULCC in terms of sign and trend but different magnitudes. This study highlights the large impact of forest carbon change on shaping future LULCC dynamics and the critical role of CO 2 fertilization.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1990

Sea ice concentrations in the Canada Basin during 1988 - Comparisons with other years and evidence of multiple forcing mechanisms

Results from a study of special sensor microwave imager data and visible band DMSP-OLS imagery show a large area of reduced ice concentration in the Canada Basin during summer 1988. Drifting buoys, surface pressure fields, output from the Polar Ice Prediction System sea ice model, and other meteorological data used to examine processes responsible for development of the reduced ice concentrations are discussed. It is noted that, while ice divergence in the summer offers a partial explanation, the model indicates that there are other factors which play contributing roles. Among these factors are the anomalously warm atmospheric conditions, generally clear skies in June and July, extensive fracturing of the pack ice in spring and anomalous advection of oceanic heat. It is found that the second and third of these effects may occur in most years. It is concluded that, although the extent and magnitude of the concentration reductions during 1988 are unusual, these recurring factors tend to predispose the pack ice in the Canada Basin to decay.

Serreze, Mark C.↗

NASA NTRS2019

Assimilation of Satellite-Based Snow Cover and Freeze/Thaw Observations Over the High Mountain Asia

Toward qualifying hydrologic changes in the High Mountain Asia (HMA) region, this study explores the use of a hyper-resolution (1 km) land data assimilation (DA)framework developed within the NASA Land Information System using the Noah Multi-parameterization Land Surface Model (Noah-MP) forced by the meteorological boundary conditions from Modern-Era Retrospective analysis for Research and Applications, Version 2 data. Two different sets of DA experiments are conducted:(1) the assimilation of a satellite-derived snow cover map (MOD10A1) and (2) the assimilation of the NASA MEaSUREs landscape freeze/thaw product from 2007 to 2008. The performance of the snow cover assimilation is evaluated via comparisons with available remote sensing-based snow water equivalent product and ground-based snow depth measurements. For example, in the comparison against ground-based snow depth measurements, the majority of the stations (13 of 14) show slightly improved goodness-of-fit statistics as a result of the snow DA, but only four are statistically significant. In addition, comparisons to the satellite-based land surface temperature products (MOD11A1 and MYD11A1) show that freeze/thaw DA yields improvements (at certain grid cells) of up to 0.58 K in the root-mean-square error (RMSE) and 0.77K in the absolute bias (relative to model-only simulations). In the comparison against three ground-based soil temperature measurements along the Himalayas, the bias and the RMSE in the 0-10 cm soil temperature are reduced (on average) by 10 and 7%,respectively. The improvements in the top layer of soil estimates also propagate through the deeper soil layers, where the bias and the RMSE in the 10-40 cm soil temperature are reduced (on average) by 9 and 6%, respectively. However, no statistically significant skill differences are observed for the freeze/thaw DA system in the comparisons against ground-based surface temperature measurements at mid-to-low altitude. Therefore, the two proposed DA schemes show the potential of improving the predictability of snow mass, surface temperature, and soil temperature states across HMA, but more ground-based measurements are still required, especially at high-altitudes, in order to document a more statistically significant improvement as a result of the two DA schemes.

High Mountain Asia↗

NASA NTRS2010

Improving NOAA's NWLON Through Enhanced Data Inputs from NASA's Ocean Surface Topography

This report assesses the benefit of incorporating NASA's OSTM (Ocean Surface Topography Mission) altimeter data (C- and Ku-band) into NOAA's (National Oceanic and Atmospheric Administration) NWLON (National Water Level Observation Network) DSS (Decision Support System). This data will enhance the NWLON DSS by providing additional inforrnation because not all stations collect all meteorological parameters (sea-surface height, ocean tides, wave height, and wind speed over waves). OSTM will also provide data where NWLON stations are not present. OSTM will provide data on seasurface heights for determining sea-level rise and ocean circulation. Researchers and operational users currently use satellite altimeter data products with the GSFCOO NASA data model to obtain sea-surface height and ocean circulation inforrnation. Accurate and tirnely inforrnation concerning sea-level height, tide, and ocean currents is needed to irnprove coastal tidal predictions, tsunarni and storm surge warnings, and wetland restoration.

Guest, DeNeice C.↗

DOE OSTI2022

Meteorological Influences on Anthropogenic PM 2.5 in Future Climates: Species Level Analysis in the Community Earth System Model v2

Abstract Biomass and fossil fuel burning impact air quality by injecting fine particulate matter (PM 2.5 ) and its precursors into the atmosphere, which poses serious threats to human health. However, the surface concentration of PM 2.5 depends not only on the magnitude of emissions, but also secondary production, transport, and removal. For example, in response to greenhouse gas driven warming, meteorological conditions that govern aerosol removal, primarily through rainfall and wet deposition, could shift in pattern, frequency, and intensity. This climate change driven process can impact air quality even without changes in aerosol emissions. In this experiment, we conduct new simulations by fixing aerosol emissions at present‐day levels in the Community Earth System Model Version 2, but increasing greenhouse gases through the 21st century. In our results, the changes in patterns and intensity of PM 2.5 are found to be associated with precipitation (via aerosol removal), temperature (via secondary organic aerosol (SOA) formation), and moisture and clouds (via sulfate production). A decrease in wet day frequency (∼1.2% global mean) contributes to increases in the surface concentrations of black carbon, primary organic matter, and sulfate in many regions. This is offset in some regions by an upward vertical shift in the level where SOA forms, which contributes to higher column burden but lower surface concentration. These results highlight a need, using a variety of modeling tools, to continually reassess aerosol emissions regulations in response to anticipated climate changes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Site G - Surface Meteorological Station / Reviewed Data

This dataset contains meteorological data both from the ground and tether termination near the balloon on tethered balloon system at AWAKEN site G. The met data include time stamp, wind speed, temperature, relative humidity, and pressure.

17 WIND ENERGY↗

DOE OSTI2025

Site A1 - Surface Meteorological Station / Reviewed Data

This dataset contains meteorological data both from the ground and tether termination near the balloon on tethered balloon system at AWAKEN site A1. The met data include time stamp, wind speed, temperature, relative humidity, and pressure.

17 WIND ENERGY↗

NASA NTRS2023

Towards an Indian Land Data Assimilation System (ILDAS): A Coupled Hydrologic-Hydraulic System for Water Balance Assessments

Effective management of water resources requires reliable estimates of land surface states and fluxes, including water balance components. But most land surface models run in uncoupled mode and do not produce river discharge at catchment scales to be useful for water resources management applications. Such integrated systems are also rare over India where hydrometeorological extremes have wreaked havoc on the economy and people. So, an Indian Land Data Assimilation System (ILDAS) with a coupled land surface and a hydrodynamic model has been developed and driven by multiple meteorological forcings (0.1°, daily) to estimate land surface states, channel discharge, and floodplain inundation. ILDAS benefits from an integrated framework as well as the largest suite of observation records collected over India and has been used to produce a reanalysis product for 1981–2021 using four forcing datasets, namely, Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), ECMWF’s ERA-5, and Indian Meteorological Department (IMD) gridded precipitation. We assessed the uncertainty and bias in these precipitation datasets and validated all major components of the terrestrial water balance, i.e., surface runoff, soil moisture, terrestrial water storage anomalies, evapotranspiration, and streamflow, against a combination of satellite and in situ observation datasets. Our assessment shows that ILDAS can represent the hydrological processes reasonably well over the Indian landmass with IMD precipitation showing the best relative performance. Evaluation against ESA-CCI soil moisture shows that MERRA-2 based estimates outperform the others, whereas ERA-5 performs best in simulating evapotranspiration when evaluated against MODIS ET. Evaluations against observed records show that CHIRPS-based estimates have the highest performance in reconstructing surface runoff and streamflow. Once operational, this system will be useful for supporting transboundary water management decision making in the region.

Indian Land Data Assimilation System (ILDAS)↗

NASA NTRS1990

A system for recording physical properties of clouds

Characterization of the physical properties of clouds is an important objective of the FIRE Project intensive field operations (IFO) planned for 1990 thru 1992. Physical properties observed from satellites will be directly compared to ground based observations during this period. The technical information is provided which is required to record local cloud parameters such as type of clouds, direction of travel, layering, and cloud fraction data. Such information should be very useful in analyzing other cloud and meteorological data. A system of the type described was deployed as part of the First Global Surface Radiation Budget Experiment in April 1989.

Purgold, G. C.↗

NASA NTRSDate not supplied

Surface meteorology and Solar Energy

The Release 5.1 Surface meteorology and Solar Energy (SSE) data contains parameters formulated for assessing and designing renewable energy systems. Parameters fall under 11 categories including: Solar cooking, solar thermal applications, solar geometry, tilted solar panels, energy storage systems, surplus product storage systems, cloud information, temperature, wind, other meteorological factors, and supporting information. This latest release contains new parameters based on recommendations by the renewable energy industry and it is more accurate than previous releases. On-line plotting capabilities allow quick evaluation of potential renewable energy projects for any region of the world. The SSE data set is formulated from NASA satellite- and reanalysis-derived insolation and meteorological data for the 10-year period July 1983 through June 1993. Results are provided for 1 degree latitude by 1 degree longitude grid cells over the globe. Average daily and monthly measurements for 1195 World Radiation Data Centre ground sites are also available. [Mission Objectives] The SSE project contains insolation and meteorology data intended to aid in the development of renewable energy systems. Collaboration between SSE and technology industries such as the Hybrid Optimization Model for Electric Renewables ( HOMER ) may aid in designing electric power systems that employ some combination of wind turbines, photovoltaic panels, or diesel generators to produce electricity. [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=1993-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180].

Stackhouse, Paul W.↗

NASA NTRS2006

A Conceptual Titan Orbiter Mission Using Advanced Radioisotope Power Systems

This study details a conceptual follow-on Titan orbiter mission that would provide full global topographic coverage. surface imaging, and meteorological characterization of the atmosphere over a nominal 5-year science mission duration. The baseline power requirement is approx.1 kWe at EOM and is driven by a high power radar instrument that would provide 3-dimensional measurements of atmospheric clouds, precipitation, and surface topography. While this power level is moderately higher than that of the Cassini spacecraft. higher efficiency advanced RPSs could potentially reduce the plutonium usage to less than 1/3rd of that used on the Cassini spacecraft. The Titan Orbiter mission is assumed to launch in 2015. It would utilize advanced RPSs to provide all on-board power.

radioisotope power systems (RPS)↗

NASA NTRS1994

SeaWiFS technical report series. Volume 19: Case studies for SeaWiFS calibration and validation, part 2

This document provides brief reports, or case studies, on a number of investigations and data set development activities sponsored by the Calibration and Validation Team (CVT) within the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Project. Chapter 1 is a comparison with the atmospheric correction of Coastal Zone Color Scanner (CZCS) data using two independent radiative transfer formulations. Chapter 2 is a study on lunar reflectance at the SeaWiFS wavelengths which was useful in establishing the SeaWiFS lunar gain. Chapter 3 reports the results of the first ground-based solar calibration of the SeaWiFS instrument. The experiment was repeated in the fall of 1993 after the instrument was modified to reduce stray light; the results from the second experiment will be provided in the next case studies volume. Chapter 4 is a laboratory experiment using trap detectors which may be useful tools in the calibration round-robin program. Chapter 5 is the original data format evaluation study conducted in 1992 which outlines the technical criteria used in considering three candidate formats, the hierarchical data format (HDF), the common data format (CDF), and the network CDF (netCDF). Chapter 6 summarizes the meteorological data sets accumulated during the first three years of CZCS operation which are being used for initial testing of the operational SeaWiFS algorithms and systems and would be used during a second global processing of the CZCS data set. Chapter 7 describes how near-real time surface meteorological and total ozone data required for the atmospheric correction algorithm will be retrieved and processed. Finally, Chapter 8 is a comparison of surface wind products from various operational meteorological centers and field observations. Surface winds are used in the atmospheric correction scheme to estimate glint and foam radiances.

Hooker, Stanford B.↗

NASA NTRS2008

Surface Meteorology and Solar Energy (SSE) Data Release 5.1

The Surface meteorology and Solar Energy (SSE) data set contains over 200 parameters formulated for assessing and designing renewable energy systems.The SSE data set is formulated from NASA satellite- and reanalysis-derived insolation and meteorological data for the 10-year period July 1983 through June 1993. Results are provided for 1 degree latitude by 1 degree longitude grid cells over the globe. Average daily and monthly measurements for 1195 World Radiation Data Centre ground sites are also available. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=1993-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree].

Arctic heating↗