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NASA NTRS2017

An Overview of the Design and Development of the Geostationary Operational Environmental Satellite R-Series (GOES-R) Space Segment

The first of the National Oceanic and Atmospheric Administration (NOAA) Geostationary Operational Environmental Satellite R-series (GOES-R) satellites was launched in November 2016. GOES-R has been developed by NOAA in partnership with the National Aeronautics and Space Administration (NASA). The satellite represents a quantum leap in the state of the art for geostationary weather satellites by providing data from a suite of six new instruments. All instruments were developed expressly for this mission, and include two Earth-observing instruments (the Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM)), two solar-viewing instruments (Solar Ultraviolet Imager (SUVI) and Extreme ultraviolet and X-ray Irradiance Sensors (EXIS)) and two in situ instruments (Space Environment In-Situ Suite (SEISS) and a magnetometer pair). In addition to hosting the instruments, GOES-R also accommodates several communication packages designed to collect and relay data for weather forecasting and emergency management. Accommodating the six instruments and four communication payloads imposed challenging and competing constraints on the satellite, including requirements for extremely stable earth and solar pointing, high-speed and nearly error-free instrument data transmission, and a very quiet electromagnetic background. To meet mission needs, GOES-R employed several technological innovations, including low-thrust rocket engines that allow instrument observations to continue during maneuvers, and the first civilian use of Global Positioning System-based orbit determination in geostationary orbit. This paper will provide a brief overview of the GOES-R satellite and its instruments as well as the developmental challenges involved in accommodating the instruments and communications payloads.

SUVI↗
NASA NTRS2017

An Overview of the Design and Development of the GOES R-Series Space Segment

The first of the National Oceanic and Atmospheric Administration (NOAA) Geostationary Operational Environmental Satellite R-series (GOES-R) satellites was launched in November 2016. GOES-R has been developed by NOAA in partnership with the National Aeronautics and Space Administration (NASA). The satellite represents a quantum leap in the state of the art for geostationary weather satellites by providing data from a suite of six new instruments. All instruments were developed expressly for this mission, and include two Earth-observing instruments (the Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM)), two solar-viewing instruments (Solar Ultraviolet Imager (SUVI) and Extreme ultraviolet and X-ray Irradiance Sensors (EXIS)) and two in situ instruments (Space Environment In-Situ Suite (SEISS) and a magnetometer pair). In addition to hosting the instruments, GOES-R also accommodates several communication packages designed to collect and relay data for weather forecasting and emergency management. Accommodating the six instruments and four communication payloads imposed challenging and competing constraints on the satellite, including requirements for extremely stable earth and solar pointing, high-speed and nearly error-free instrument data transmission, and a very quiet electromagnetic background. To meet mission needs, GOES-R employed several technological innovations, including low-thrust rocket engines that allow instrument observations to continue during maneuvers, and the first civilian use of Global Positioning System-based orbit determination in geostationary orbit. This paper will provide a brief overview of the GOES-R satellite and its instruments as well as the developmental challenges involved in accommodating the instruments and communications payloads.

GOES-16↗
DOE OSTI2023

Integration of a physics-based direct normal irradiance ($\mathrm{DNI}$) model to enhance the National Solar Radiation Database ($\mathrm{NSRDB}$)

The National Solar Radiation Database (NSRDB) is an extensively used dataset that furnishes satellite-retrieved solar resource data across the United States and an expanding list of other countries. Although the NSRDB uses a physical model to compute global horizontal irradiance (GHI), it currently employs an empirical approach based on surface observations to estimate cloudy-sky direct normal irradiance (DNI). Recently, a new physics-based approach, known as the Fast All-sky Radiation Model for Solar applications with DNI (FARMS-DNI), was developed to improve DNI forecasting. FARMS-DNI integrates direct and scattered solar radiances within the circumsolar region, resulting in improved day-ahead forecasting of DNI by incorporating it into the Weather Research and Forecasting model with Solar extensions (WRF-Solar). This study incorporates FARMS-DNI into the NSRDB algorithm to produce high-spatiotemporal-resolution DNI data from satellite data. The accuracy of the NSRDB based on FARMS-DNI is analyzed using surface observations from 19 sites situated within the National Oceanic and Atmospheric Administration (NOAA) Surface Radiation Budget (SURFRAD) and Solar Radiation (SOLRAD) networks, the University of Oregon (UO) network, the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) network, and at the National Renewable Energy Laboratory (NREL). The results demonstrate that FARMS-DNI reduces the significant overestimation of DNI in the conventional NSRDB at all surface sites, particularly in cloud overcast conditions classified using both satellite retrievals and surface observations. Consequently, this new model can effectively improve the overall accuracy of the NSRDB. The results also suggest that further improvement of DNI estimates at individual time steps, however, requires advanced satellite techniques and precise identification of clouds and retrieval of cloud properties.

14 SOLAR ENERGY↗
DOE OSTI2024

Clustering Interval Load with Weather to Create Scenarios of Behind-the-Meter Solar Penetration

Forecasting load at the feeder level has become increasingly challenging with the penetration of behind-the-meter solar, as this self-generation is only visible to the utility as aggregated net-load. This work proposes a methodology for creation of scenarios of solar penetration at the feeder level for use by forecasters to test the robustness of their algorithm to progressively higher penetrations of solar. The algorithm draws on publicly available observations of weather condition (e.g., rainy/cloudy/fair) for use as proxies to sky clearness. These observations are used to mask and weight the interval deviations of similar native usage profiles from which average interval usage is calculated and subsequently added to interval net generation to reconstruct interval total generation. This approach improves the estimate of annual energy generation by 23%; where the net generation signal currently reflects 52% of total annual gener- ation, now 75% is captured. This methodology for creation of forecast testing scenarios is data driven and extensible to service territories which lack information on irradiance measurements and geocoordinates.

solar, load↗
DOE OSTI2020

GET-Solar (Generation forecasting and parameter Estimation Tool for Solar) [SWR-20-115]

GET-Solar (Generation forecasting and parameter Estimation Tool for Solar) can be used to estimate behind the meter (BTM) solar generation from limited datasets. Using distributed sets of diverse solar sites, but with close spatial proximity, and/or limited historical PV generation information can be used to generate of solar profiles. This is useful for applications where partial solar generation data is available, and on-site irradiance data is not available. GET-Solar calculates PV technical data parameters and calculates output by modeling shading and cloud cover impacts. Clear sky irradiance profiles are used to calculate base generation profiles on which the local shading and cloud cover layers are added. In order to arrive at clear sky generation data, PV mounting information like panel tilt and and angle is needed. For cases where PV mounting information is missing, panel tilt and azimuth angle can be estimated using a non-linear optimization algorithm. GET-Solar can also be used for forecasting applications where historical PV data is available to estimate local shading at various solar positions. This overall framework can be used for estimation of solar parameters, and assisting in analyzing and modeling diverse sets of DER where solar generation is also present in utility meter data. GET-Solar has been developed in Python and uses the Pyomo optimization language.

Abraham, Sherin Ann↗
DOE OSTI2024

Improving the National Solar Radiation Database (NSRDB) Using a Physics-Based Direct Normal Irradiance (DNI) Model

The National Solar Radiation Database (NSRDB) is a widely used resource providing satellite-derived solar data across the United States and globally. While the NSRDB employs a physical model for computing global horizontal irradiance (GHI), its current method for estimating cloudy-sky direct normal irradiance (DNI) relies on surface observations and empirical models. Recently, a novel physics-based approach, the Fast All-Sky Radiation Model for Solar applications with DNI (FARMS-DNI), was developed to enhance the DNI forecasting. FARMS-DNI incorporates both direct and scattered solar radiation within the circumsolar region, resulting in improved day-ahead DNI predictions when integrated into the Weather Research and Forecasting model with Solar extensions (WRF-Solar). This study integrates FARMS-DNI into the NSRDB algorithm to generate high-resolution DNI data from satellite resources. Our findings reveal that FARMS-DNI effectively mitigates the substantial DNI overestimation present in the conventional NSRDB across surface sites, particularly in conditions categorized as cloudy overcast. Consequently, this innovative model substantially enhances the overall accuracy of the NSRDB.

Xie, Yu↗
DOE OSTI2024

Improving the National Solar Radiation Database (NSRDB) Using a Physics-Based Direct Normal Irradiance (DNI) Model: Preprint

The National Solar Radiation Database (NSRDB) is a widely used resource providing satellite-derived solar data across the United States and globally. While the NSRDB employs a physical model for computing global horizontal irradiance (GHI), its current method for estimating cloudy-sky direct normal irradiance (DNI) relies on surface observations and empirical models. Recently, a novel physics-based approach, the Fast All-Sky Radiation Model for Solar applications with DNI (FARMS-DNI), was developed to enhance the DNI forecasting. FARMS-DNI incorporates both direct and scattered solar radiation within the circumsolar region, resulting in improved day-ahead DNI predictions when integrated into the Weather Research and Forecasting model with Solar extensions (WRF-Solar). This study integrates FARMS-DNI into the NSRDB algorithm to generate high-resolution DNI data from satellite resources. Our findings reveal that FARMS-DNI effectively mitigates the substantial DNI overestimation present in the conventional NSRDB across surface sites, particularly in conditions categorized as cloudy overcast. Consequently, this innovative model substantially enhances the overall accuracy of the NSRDB.

DNI↗
DOE OSTI2021

Improving the prediction of DNI with physics-based representation of all-sky circumsolar radiation

Direct normal irradiance (DNI) is often interpreted differently in ground measurements and forecasts using numerical weather prediction (NWP) models, leading to substantial bias in DNI forecasting especially under cloudy-sky conditions. To mitigate the bias, we use the Fast All-sky Radiation Model for Solar applications with DNI (FARMS-DNI) to conduct physics-based simulations of solar radiation in the circumsolar region. The DNI is quantified using the sum of the radiation along the sun direction and the scattered radiation within the circumsolar region. FARMS-DNI is coupled with the Weather Research and Forecasting model with solar extensions (WRF-Solar) to predict day-ahead DNI in 9-km pixels over an extended domain covering the contiguous United States. The DNI forecasts for the entire year of 2018 are validated using surface-based observations at the Atmospheric Radiation Measurement (ARM) and Surface Radiation Budget Network (SURFRAD) sites and a satellite-based solar radiation product developed by the procedure of the National Solar Radiation Data Base (NSRDB). The results show that the WRF-Solar coupled with the conventional Beer-Bouguer-Lambert law underestimes the overall DNI forecasts by 30%-60%, which is a joint effect of the uncertainties in computing the circumsolar radiation and forecasting cloud properties. This bias is significantly reduced by using FARMS-DNI.

14 SOLAR ENERGY↗
NASA NTRS2006

Supporting Energy-Related Societal Applications Using NASA's Satellite and Modeling Data

Improvements to NASA Surface Meteorology and Solar Energy (SSE) web site are now being made through the Prediction of Worldwide Energy Resource (POWER) project under NASA Science Mission Directorate Applied Science Energy Management Program. The purpose of this project is to tailor NASA Science Mission results for energy sector applications and decision support systems. The current status of SSE and research towards upgrading estimates of total, direct and diffuse solar irradiance from NASA satellite measurements and analysis are discussed. Part of this work involves collaborating with partners such as the National Renewable Energy Laboratory (NREL) and the Natural Resources Canada (NRCan). Energy Management and POWER plans including historic, near-term and forecast datasets are also overviewed.

Stackhouse, Paul W., Jr.↗
DOE OSTI2023

Clear-Sky Probability for the 2023 Annular Solar Eclipse and the 2024 Total Solar Eclipse Using the NREL National Solar Radiation Database

The National Renewable Energy Laboratory (NREL) and collaborators have created a clear-sky probability analysis to help guide viewers to the 2023 annular solar eclipse and the 2024 total solar eclipse. Using cloud and solar data from the NREL National Solar Radiation Database (NSRDB), the analysis provides cloudless-sky probabilities specific to the date, time, and location of each eclipse with a 4-km resolution. Though not intended to be an eclipse weather forecast, the detailed maps can help guide eclipse enthusiasts to likely optimal viewing locations. Additionally, high-resolution data are presented for the centerline of the path of each eclipse, representing the likelihood for cloudless skies and atmospheric clarity. The NSRDB provides industry, academia, and other stakeholders with high-resolution solar irradiance data to support feasibility analyses for photovoltaic and concentrating solar power generation projects.

14 SOLAR ENERGY↗
NASA NTRS2007

Solar Cycle #24 and the Solar Dynamo

We focus on two solar aspects related to flight dynamics. These are the solar dynamo and long-term solar activity predictions. The nature of the solar dynamo is central to solar activity predictions, and these predictions are important for orbital planning of satellites in low earth orbit (LEO). The reason is that the solar ultraviolet (UV) and extreme ultraviolet (EUV) spectral irradiances inflate the upper atmospheric layers of the Earth, forming the thermosphere and exosphere through which these satellites orbit. Concerning the dynamo, we discuss some recent novel approaches towards its understanding. For solar predictions we concentrate on a solar precursor method, in which the Sun s polar field plays a major role in forecasting the next cycle s activity based upon the Babcock- Leighton dynamo. With a current low value for the Sun s polar field, this method predicts that solar cycle #24 will be one of the lowest in recent times, with smoothed F10.7 radio flux values peaking near 130+ 30 (2 4, in the 2013 timeframe. One may have to consider solar activity as far back as the early 20th century to find a cycle of comparable magnitude. Concomitant effects of low solar activity upon satellites in LEO will need to be considered, such as enhancements in orbital debris. Support for our prediction of a low solar cycle #24 is borne out by the lack of new cycle sunspots at least through the first half of 2007. Usually at the present epoch in the solar cycle (-7+ years after the last solar maximum), for a normal size following cycle, new cycle sunspots would be seen. The lack of their appearance at this time is only consistent with a low cycle #24. Polar field observations of a weak magnitude are consistent with unusual structures seen in the Sun s corona. Polar coronal holes are the hallmarks of the Sun s open field structures. At present, it appears that the polar coronal holes are relatively weak, and there have been many equatorial coronal holes. This appears consistent with a weakening polar field, but coronal hole data must be scrutinized carefully as observing techniques have changed. We also discuss new solar dynamo ideas, and the SODA (Solar Dynamo Amplitude) index, which provides the user with the ability to track the Sun s hidden, dynamo magnetic fields throughout the various stages of the Sun s cycle. Our solar dynamo ideas are a modernization and rejuvenation of the Babcock-Leighton original idea of a shallow solar dynamo, using modem observations that appear to support their shallow dynamo viewpoint. We are in awe of being able to see an object the size of the Sun undergoing as dramatic a change as our model provides in a few short years. The Sun, however, has undergone changes as rapid as this before! The weather on the Sun is at least as fickle as the weather on the Earth.

Pesnell, W. Dean↗
NASA NTRS2007

Solar Cycle #24 and the Solar Dynamo

We focus on two solar aspects related to flight dynamics. These are the solar dynamo and long-term solar activity predictions. The nature of the solar dynamo is central to solar activity predictions, and these predictions are important for orbital planning of satellites in low earth orbit (LEO). The reason is that the solar ultraviolet (UV) and extreme ultraviolet (EUV) spectral irradiances inflate the upper atmospheric layers of the Earth, forming the thermosphere and exosphere through which these satellites orbit. Concerning the dynamo, we discuss some recent novel approaches towards its understanding. For solar predictions we concentrate on a solar precursor method, in which the Sun's polar field plays a major role in forecasting the next cycle s activity based upon the Babcock-Leighton dynamo. With a current low value for the Sun s polar field, this method predicts that solar cycle #24 will be one of the lowest in recent times, with smoothed F10.7 radio flux values peaking near 130 plus or minus 30 (2 sigma), in the 2013 timeframe. One may have to consider solar activity as far back as the early 20th century to find a cycle of comparable magnitude. Concomitant effects of low solar activity upon satellites in LEO will need to be considered, such as enhancements in orbital debris. Support for our prediction of a low solar cycle #24 is borne out by the lack of new cycle sunspots at least through the first half of 2007. Usually at the present epoch in the solar cycle (approx. 7+ years after the last solar maximum), for a normal size following cycle, new cycle sunspots would be seen. The lack of their appearance at this time is only consistent with a low cycle #24. Polar field observations of a weak magnitude are consistent with unusual structures seen in the Sun s corona. Polar coronal holes are the hallmarks of the Sun's open field structures. At present, it appears that the polar coronal holes are relatively weak, and there have been many equatorial coronal holes. This appears consistent with a weakening polar field, but coronal hole data must be scrutinized carefully as observing techniques have changed. We also discuss new solar dynamo ideas, and the SODA (SOlar Dynamo Amplitude) index, which provides the user with the ability to track the Sun's hidden, dynamo magnetic fields throughout the various stages of the Sun's cycle. Our solar dynamo ideas are a modernization and rejuvenation of the Babcock-Leighton original idea of a shallow solar dynamo, using modern observations that appear to support their shallow dynamo viewpoint. We are in awe of being able to see an object the size of the Sun undergoing as dramatic a change as our model provides in a few short years. The Sun, however, has undergone changes as rapid as this before! The weather on the Sun is at least as fickle as the weather on the Earth.

Schatten, Kenneth↗
NASA NTRS2004

Long-Term Total Solar Irradiance (TSI) Variability Trends: 1984-2004

The incoming total solar irradiance (TSI), typically referred to as the solar constant, is being studied to identify long-term TSI changes, which may trigger global climate changes. The TSI is normalized to the mean earth-sun distance. Studies of spacecraft TSI data sets confirmed the existence of 0.1 %, long-term TSI variability component with a period of 10 years. The component varied directly with solar magnetic activity associated with recent 10-year sunspot cycles. The 0.1 % TSI variability component is clearly present in the spacecraft data sets from the 1984-2004, Earth Radiation Budget Experiment (ERBE) active cavity radiometer (ACR) solar monitor; 1978-1993, Nimbus-7 HF; 1980-1989, Solar Maximum Mission [SMM] ACRIM; 1991-2004, Upper Atmosphere Research Satellite (UARS) ACRIM; 1996-2003, Solar and Heliospheric Observatory (SOHO)/VIRGO, Space Science (ATLAS), 2000-2004, ACRIMSAT; and 2003-2004 SOlar Radiation and Climate Experiment (SORCE) active cavity radiometer (ACR) missions. From October 1984, through March 2004, the ERBS/ERBE solar monitor was used to produce the longest continuous data set of total solar irradiance (TSI) variability measurements. The solar monitor is located on Shuttle Atmospheric Laboratory for Applications and the NASA Earth Radiation Budget Satellite (ERBS). Maximum TSI values occurred during the 1989-1991, and 1998-2002, time frames; while minimum [quiet sun] TSI levels occurred during 1986 and 1996. Recent ERBS measurements indicate that the TSI is decreasing to forecasted, minimum levels by 2006. Using the discontinuous non-operational Nimbus-7, SMM ACRIM, and UARS ACRIM mission TSI data sets, Wilson and Mordvinor (2003) suggested the existence of an additional long-term TSI variability component, 0.05 %, with a period longer than a decade. Analyses of the ERBS/ERBE data set do not support the Wilson and Mordvinor analyses approach because it used the Nimbus-7 data set which exhibited a significant ACR response shift of 0.7 Wm-2

Lee, Robert Benjamin, III↗
NASA NTRS2001

Overview of ACE-Asia Spring 2001 Investigations on Aerosol Radiative Effects and Related Aerosol Properties

A primary, ACE-Asia objective was to quantify the interactions between aerosols and radiation in the Asia-Pacific region. Toward this end, radiometric and related aerosol measurements were made from ocean, land, air and space platforms. Models that predict aerosol fields guided the measurements and are helping integrate and interpret results. Companion overview's survey these measurement and modeling components. Here we illustrate how these components were combined to determine aerosol radiative. impacts and their relation to aerosol properties. Because clouds can obscure or change aerosol direct radiative effects, aircraft and ship sorties to measure these effects depended on predicting and finding cloud-free areas and times with interesting aerosols present. Pre-experiment satellite cloud climatologies, pre-flight aerosol and cloud forecasts, and in-flight guidance from satellite imagery all helped achieve this. Assessments of aerosol regional radiative impacts benefit from the spatiotemporal coverage of satellites, provided satellite-retrieved aerosol properties are accurate. Therefore, ACE-Asia included satellite retrieval tests, as part of many comparisons to judge the consistency (closure) among, diverse measurements. Early results include: (1) Solar spectrally resolved and broadband irradiances and optical depth measurements from the C-130 aircraft and at Kosan, Korea yielded aerosol radiative forcing efficiencies, permitting comparisons between efficiencies of ACE-Asia and INDOEX aerosols, and between dust and "pollution" aerosols. Detailed results will be presented in separate papers. (2) Based on measurements of wavelength dependent aerosol optical depth (AOD) and single scattering albedo the estimated 24-h a average aerosol radiative forcing efficiency at the surface for photosynthetically active radiation (400 - 700 nm) in Yulin, China is approx. 30 W sq m per AOD(500 nm). (3) The R/V Brown cruise from Honolulu to Sea of Japan sampled an aerosol optical depth gradient, with AOD(500 nm) extremes from 0.1 to 1.1. On the Pacific transit from Honolulu to Hachijo AOD(500 nm) averaged 0.2, including increases to 0.4 after several storms, suggesting the strong impact of wind-generated seasalt. The AOD maximum, found in the Sea of Japan, was influenced by dust and anthropogenic sources. (4) In Beijing, single scattering albedo retrieved from AERONET sun-sky radiometry yielded midvisible SSA=0.88 with strong wavelength dependence, suggesting a significant black carbon component. SSA retrieved during dust episodes was approx. 0.90 and variable but wavelength neutral reflecting the presence of urban haze with the dust. Downwind at Anmyon Island SSA was considerably higher, approx. 0.94, but wavelength neutral for dust episodes and spectrally dependent during non dust periods. (5) Satellite retrievals show major aerosol features moving from Asia over the Pacific; however, determining seasonal-average aerosol effects is hampered by sampling frequency and large-scale cloud systems that obscure key parts of aerosol patterns. Preliminary calculations using, satellite-retrieved AOD fields and initial ACE-Asia aerosol properties (including sulfates, soot, and dust) yield clear-sky aerosol radiative effects in the seasonal-average ACE-Asia plume exceeding those of manmade greenhouse gases. Quantifying all-sky direct aerosol radiative effects is complicated by the need to define the height of absorbing aerosols with respect to cloud decks.

Russell, Philip B.↗
NASA NTRSDate not supplied

Global Solar Activity Data Portal for Studying 3D Dynamics and Activity of the Sun

The main problems with understanding and predicting solar activity are tightly linked to limitations in describing the global evolution of the Sun from the deep interior to the corona. Because of the complexity of interactions in a wide range of dynamical, turbulent, and spatial scales and dramatic changes in thermodynamic and magnetic field conditions, only physics-based models can provide essential background to generate reliable solar activity forecasts. However, performing accurate model calibration and estimating uncertainties is often challenging due to the unavailability of a long time series of observations. To mitigate these limitations, we have developed the Global Solar Activity (GSA) Data Portal, which enables convenient access to a variety of modern and historical data. The portal supports a dynamic visualization for 1D time series (such as the sunspot number and solar irradiance) and quick-look visualization for 2D datasets (e.g., synoptic magnetograms, the solar internal rotation, and flows). The GSA portal includes a search engine that enables data retrieval from user-specified data sources and time intervals. In this presentation, we will discuss the current and upcoming capabilities of the data portal and its potential applications for space weather studies.

SMD↗
DOE OSTI2026

High-Resolution WRF-Based Downscaling of Earth System Model Projections for Energy Applications across CONUS

Evaluating energy resources under future scenarios requires meteorological information that adequately resolves regional-scale variability and is suitable for regional energy system studies. Although Earth system model (ESM) outputs provide essential large-scale context, their coarse resolution and inherent biases limit direct use in energy system applications. This work presents a high-resolution dynamical downscaling framework using the Weather Research and Forecasting (WRF) model to generate energy-relevant regional fields for future scenarios over the contiguous United States (CONUS). The framework first identifies an optimal WRF configuration through sensitivity experiments, then evaluates raw and bias-corrected ESM initial and boundary conditions, with soil moisture and soil temperature bias correction implemented as an integral component of the bias-corrected ESM atmospheric forcing prior to WRF dynamical downscaling to improve land-atmosphere interactions. Simulations performed at 4-km resolution show that uncorrected ESM forcing leads to systematically dry and cold soil states, which propagate into elevated near-surface air temperature and solar irradiance biases, particularly during summer for the period 2000-2014. Incorporating bias-corrected atmospheric forcing together with soil state bias correction substantially reduces these errors and improves the representation of surface energy processes in WRF simulations. The results highlight the importance of bias-aware initialization strategies in high-resolution dynamical downscaling for future energy system analysis and planning.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Outdoor performance of a tandem InGaP/Si photovoltaic luminescent solar concentrator

Here, we report the design, fabrication and outdoor characterization of a tandem luminescent solar concentrator/Si multi-junction photovoltaic module. Our tandem LSC/Si device consists of an InGaP LSC functioning as a top cell and a passivated contact Si bottom cell. The LSC comprises of an InGaP microcell array coupled to a polymer waveguide, loaded with CdSe/CdS core-shell quantum dot luminophores. The light trapping efficiency of the LSC waveguide is enhanced by encapsulation with photoluminescence trapping mirrors consisting of dielectric multilayer thin films. We demonstrate the performance of the LSC/Si device through a series of outdoor tests under various irradiance conditions conducted at the National Renewable Energy Laboratory. We report the first outdoor testing data of an LSC/Si tandem module, displaying maintained performance across varied diffusivity conditions for the LSC component. Finally, we model the tandem module performance using a ray optic simulation-based multiphysics model and forecast a pathway for high efficiency tandem LSC/Si module performance.

14 SOLAR ENERGY↗
NASA NTRS2007

Solutions Network Formulation Report. Aerosol Polarimetry Sensor Measurements of Diffuse-to-Global Irradiance Ratio for Improved Forecasting of Plant Productivity and Health

Studies have shown that vegetation is directly sensitive to changes in the diffuse-to-global irradiance ratio and that increased percentage of diffuse irradiation can accelerate photosynthesis. Therefore, measurements of diffuse versus global irradiance could be useful for monitoring crop productivity and overall vegetative health as they relate to the total amount of particulates in the air that result from natural disasters or anthropogenic (manmade) causes. While the components of solar irradiance are measured by satellite and surface sensors and calculated with atmospheric models, disagreement exists between the results, creating a need for more accurate and comprehensive retrievals of atmospheric aerosol parameters. Two satellite sensors--APS and VIIRS--show promise for retrieving aerosol properties at an unprecedented level of accuracy. APS is expected to be launched in December 2008. The planned launch date for VIIRS onboard NPP is September 2009. Identified partners include the USDA s ARS, North Carolina State University, Purdue Climate Change Research Center, and the Cooperative Institute for Research in the Atmosphere at Colorado State University. Although at present no formal DSSs (decision support systems) require accurate values of diffuse-to-global irradiance, this parameter is sufficiently important that models are being developed that will incorporate these measurements. This candidate solution is aligned with the Agricultural Efficiency and Air Quality National Applications.

Knowlton, Kelly↗