nasa-gesdisc/es-publications-researchareas huggingface dataset:
Evaluation of MODIS-derived estimates of the albedo over the Atacama Desert using ground-based spectral measurements (2021)

Surface albedo is an important forcing parameter that drives the radiative energy budget as it determines the fraction of the downwelling solar irradiance that the surface reflects. Here we report on ground-based measurements of the spectral albedo (3502200 nm) carried out at 20 sites across a NorthSouth transect of approximately 1300 km in the Atacama Desert, from latitude 18 S to latitude 30 S. These spectral measurements were used to evaluate remote sensing estimates of the albedo derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). We found that the relative mean bias error (RMBE) of MODIS-derived estimates was within  5% of ground-based measurements in most of the Atacama Desert (1827 S). Although the correlation between MODIS-derived estimates and ground-based measurements remained relatively high (R= 0.94), RMBE values were slightly larger in the southernmost part of the desert (2730 S). Both MODIS-derived data and ground-based measurements show that the albedo at some bright spots in the Atacama Desert may be high enough (up to 0.25 in visible range) for considerably boosting the performance of bifacial photovoltaic technologies (612%).

Research areas: Sun-Earth Interactions, Validation
A simple new model for incoming solar radiation dependent only on screen-level relative humidity (2017)

Abstract Global incoming shortwave radiation (Rg) is the energy source for the majority of biogeochemical processes on Earth as well as for photovoltaic power production. Existing simple site-specific models to estimate Rg commonly use the daily range of air temperature as input variables. Here, the authors present a simple model for incoming shortwave radiation, requiring only screen-level relative humidity data (and site-specific astronomical information). The model was developed and parameterized using high-quality global radiation data covering a broad range of climate conditions. It was evaluated at independent sites, which were not involved in the process of model development and parameterization. The mean 1:1 slope was 1.02 with an average r2 of 0.98. Normalized root-mean-square error (NRMSE) averaged at 43%. Despite its simplicity, the new model clearly outperforms conventional approaches, and it comes close to more labor- and data-intensive alternative models.

Research areas: Sun-Earth Interactions, Validation
SORCE and TSIS‐1 SIM Comparison: Absolute Irradiance Scale Reconciliation (2022)

The Solar Radiation and Climate Experiment (SORCE) and Total and Spectral Irradiance Sensor (TSIS-1) conducted an intercomparison for the two Spectral Irradiance Monitors (SIM) spanning 704 days from 23 March 2018 to 25 February 2020 and permitted 554 time-matched pairs of observations. This comparison was conducted during the extremely quiescent Solar Cycle 24 minimum, so all observed differences and drifts between the two sensors are instrumental in nature. The TSIS-1 SIM benefitted from advanced calibration capabilities based on SI standards that were not available during the preflight calibration time period of SORCE. For this reason, a revision of the SORCE SIM absolute scale is appropriate. As expected, wavelength dependent differences in absolute agreement are a function of detector sensitivity and local changes in spectral slope. At the time of the comparison SORCE SIM has been on-orbit for 17 years while TSIS-1 observations commenced immediately after a 100-day outgassing and commissioning period. Peak-to-peak absolute scale differences are about 12% with a mean fractional difference of 0.7% ± 2.9%. The greatest scale differences occur at the change-over between the UV and visible photodiodes in the 310 nm region, and a systematic disagreement is present in the 850-1,600 nm range. A multiplicative scale correction factor has been developed to reconcile the TSIS-1 and SORCE difference with a wavelength dependent error on the mean typically less than 0.01% derived from every matched pair of observations.

Research areas: Sun-Earth Interactions, Validation
Inter-annual variability of wind and solar electricity generation and capacity values in Texas (2019)

As power systems shift towards increasing wind and solar electricity generation, inter-annual variability (IAV) of wind and solar resource and generation will pose increasing challenges to power system planning and operations. To help gauge these challenges to the power system, we quantify IAV of wind and solar resource and electricity generation across the Electric Reliability Council of Texas (ERCOT) power system, then assess the IAV of wind and solar electricity generation during peak-load hours (i.e. IAV of wind and solar capacity values) for the current ERCOT wind and solar generator fleet. To do so, we leverage the long timespan of four reanalysis datasets with the high resolution of grid integration datasets. We find the IAV (quantified as the coefficient of variation) of wind generation ranges from 2.3%-11% across ERCOT, while the IAV of solar generation ranges from 1.7%-5% across ERCOT. We also find significant seasonal and regional variability in the IAV of wind and solar generation, highlighting the importance of considering multiple temporal and spatial scales when planning and operating the power system. In addition, the IAV of the current wind and solar fleets' capacity values (defined as generation during peak-load hours) are larger than the IAV of the same fleets' capacity factors. IAV of annual generation and capacity values of wind and solar could impact operations and planning in several ways, e.g. through annual emissions, meeting emission reduction targets, and investment needs to maintain capacity adequacy.

Research areas: Sun-Earth Interactions, Energy Production/Use
Long-term impact of ionospheric scintillations on kinematic precise point positioning: seasonal and solar activity dependence over Indian low latitudes (2022)

The lengthiest GPS observations from a reference station during 20022018 and a colocated scintillation monitoring receiver during 20132018 at Hyderabad, India, are used to analyze the degradation in kinematic precise point positioning (KPPP) due to ionospheric irregularities. The GipsyX software is employed to estimate the KPPP of the reference station and the residuals for each coordinate are computed against the monthly mean values of the daytime observations. The results establish the long-term variability of the residuals of KPPP under the climatological and event-specific effect of the post-sunset equatorial plasma bubbles (EPBs). The extreme post-sunset fluctuations in the residuals during a few quiet and disturbed nights obtained from the 18 years of continuous observations are emphasized. The outstanding and persistent patterns in the residuals are majorly found during extended post-sunset hours with striking seasonal contrast. The large and rapid fluctuations in the residuals are found to exhibit long-term day-to-day, seasonal, and solar cycle variations, which correspond to the occurrence of the amplitude and phase scintillations. Thus, uniquely, the colocated observations of scintillations corroborate the impact of the simultaneously affected number of satellites (S4 index > 0.17) and indicate the possibility of cycle slips eventually affecting the KPPP solutions. The seasonal climatology of the scintillations is shown to translate over the 3-D position error, which modulates with change in the solar F10.7 cm flux. This study, thus probably for the first time, reports the long-term effect of solar cycle variability on the amplitude of perturbations in KPPP for the solar cycles 23 and 24.

Research areas: Sun-Earth Interactions
MODIS-derived global land products of shortwave radiation and diffuse and total photosynthetically active radiation at 5 km resolution from 2000 (2018)

Incident shortwave radiation (SW), photosynthetically active radiation (PAR), and diffuse PAR (PARdif) at the land surface drive a multitude of processes related to biosphere-atmosphere interactions and play a critical role in the Earth climate system. Previous global solar radiation products were spatially coarse (>50-km resolution) or temporally short (a few years), which hindered scaling-up ground based observations of the land surface processes into regional, continental, and global scales across multiple time scales. Here, we report Breathing Earth System Simulator (BESS) SW, PAR, and PARdif products over the global land surface at a 5km resolution with 4day intervals between 2000 and 2016. We combined an atmospheric radiative transfer model with an artificial neural network (ANN) to compute SW, PAR, and PARdif. A series of MODerate Resolution Imaging Spectroradiometer (MODIS) atmosphere and land products were used as inputs to run the ANN. We test the performance of the products using data from 158 (SW), 77 (PAR), and 22 (PARdif) stations collected in the Baseline Surface Radiation Network (BSRN) and flux tower networks, which covered a range of climatic zones from polar to tropical zones. BESS had strong linear relationships with in-situ SW data (R2=0.95, relative bias=2.3%), PAR (R2=0.94, relative bias=1.7%), and PARdif (R2=0.84, relative bias=0.2%). BESS captured the interannual variability of SW at both the site (a majority of long-term BSRN sites) and continental levels. Over the study period, global annual SW, PAR, and PARdif values did not show any dimming or brightening trends, although these trends appeared at regional levels, e.g. dimming in India. Mean annual SW over the global land surface was 184.8Wm2 (875ZJyr1, zetta=1021); 46% of SW was partitioned to PAR, which was further split into direct (59%) and diffuse (41%) components. The developed products will be useful in solar energy harvesting research and will improve water, carbon, and energy flux estimates of terrestrial ecosystems from local to the global scales.

Research areas: Sun-Earth Interactions
Operation and Maintenance Decision Support System for Photovoltaic Systems (2022)

Operation and maintenance (O&M) and monitoring strategies are important for safeguarding optimum photovoltaic (PV) performance while also minimizing downtimes due to faults. An O&M decision support system (DSS) was developed in this work for providing recommendations of actionable decisions to resolve fault and performance loss events. The proposed DSS operates entirely on raw field measurements and incorporates technical asset and financial management features. Historical measurements from a large-scale PV system installed in Greece were used for the benchmarking procedure. The results demonstrated the financial benefits of performing mitigation actions in case of near zero power production incidents. Stochastic simulations that consider component malfunctions and failures exhibited a net economic gain of approximately 4.17 /kW/year when performing O&M actions. For an electricity price of 59.98 /MWh, a minimum of 8.4% energy loss per year is required for offsetting the annualized O&M cost value of 7.45 /kW/year calculated by the SunSpec/National Renewable Energy Laboratory (NREL) PV O&M Cost Model.

Research areas: Validation
Reduction in 317–780 nm radiance reflected from the sunlit Earth during the eclipse of 21 August 2017 (2018)

Abstract. Ten wavelength channels of calibrated radiance image data from the sunlit Earth are obtained every 65 min during Northern Hemisphere summer from the EPIC (Earth Polychromatic Imaging Camera) instrument on the DSCOVR (Deep Space Climate Observatory) satellite located near the EarthSun Lagrange 1 point (L1), about 1.5 million km from the Earth. The L1 location permitted seven observations of the Moon's shadow on the Earth for about 3 h during the 21 August 2017 eclipse. Two of the observations were timed to coincide with totality over Casper, Wyoming, and Columbia, Missouri. Since the solar irradiances within five channels (i=388, 443, 551, 680, and 780 nm) are not strongly absorbed in the atmosphere, they can be used for characterizing the eclipse reduction in reflected radiances for the Earth's sunlit face containing the eclipse shadow. Five channels (i=317.5, 325, 340, 688, and 764 nm) that are partially absorbed in the atmosphere give consistent reductions compared to the non-absorbed channels. This indicates that cloud reflectivities dominate the 317.5780 nm radiances reflected back to space from the sunlit Earth's disk with a significant contribution from Rayleigh scattering for the shorter wavelengths. An estimated reduction of 10 % was obtained for spectrally integrated radiance (387 to 781 nm) reflected from the sunlit Earth towards L1 for two sets of observations on 21 August 2017, while the shadow was in the vicinity of Casper, Wyoming (42.8666 N, 106.3131 W; centered on 17:44:50 UTC), and Columbia, Missouri (38.9517 N, 92.3341 W; centered on 18:14:50 UTC). In contrast, when non-eclipse days (20 and 23 August) are compared for each wavelength channel, the change in reflected light is much smaller (less than 1 % for 443 nm compared to 9 % (Casper) and 8 % (Columbia) during the eclipse). Also measured was the ratio REN(i) of reflected radiance on adjacent non-eclipse days divided by radiances centered in the eclipse totality region with the same geometry for all 10 wavelength channels. The measured REN(443 nm) was smaller for Columbia (169) than for Casper (935), because Columbia had more cloud cover than Casper. REN(i) forms a useful test of a 3-D radiative transfer models for an eclipse in the presence of optically thin clouds. Specific values measured at Casper with thin clouds are REN(340 nm) = 475, REN(388 nm) = 3500, REN(443 nm) = 935, REN(551 nm) = 5455, REN(680 nm) = 220, and REN(780 nm) = 395. Some of the variability is caused by changing cloud amounts within the moving region of totality during the 2.7 min needed to measure all 10 wavelength channels.

Research areas: Sun-Earth Interactions
A Machine Learning Technique for Spatial Interpolation of Solar (2021)

This study applies statistical methods to interpolate missing values in a data set of radiative energy fluxes at the surface of Earth. We apply Random Forest (RF) and seven other conventional spatial interpolation models to a global Surface Solar Radiation (SSR) data set. We apply three categories of predictors: climatic, spatial, and time series variables. Although the first category is the most common in research, our study shows that it is actually the last two categories that are best suited to predict the response. In fact, the best spatial variable is almost 40 times more important than the best climatic variable in predicting SSR. Furthermore, the 10 fold cross validation shows that the RF has a Mean Absolute Error (MAE) of 10.2 Wm<SUP>−2</SUP> and a standard deviation of 1.5 Wm<SUP>−2</SUP>. On the other hand, the average MAE of the conventional interpolation methods is 21.3 Wm<SUP>−2</SUP>, which is more than twice as large as the RF method, in addition to an average standard deviation of 6.4 Wm<SUP>−2</SUP>, which is more than four times larger than the RF standard deviation. This highlights the benefits of using machine learning in environmental research.

Research areas: Validation
Effects of soiling on photovoltaic (PV) modules in the Atacama Desert (2018)

Soiling by dry deposition affects the power output of photovoltaic (PV) modules, especially under dry and arid conditions that favor natural atmospheric aerosols (wind-blown dust). In this paper, we report on measurements of the soiling effect on the energy yield of grid-connected crystalline silicon PV modules deployed in five cities across a north-south transect of approximately 1300 km in the Atacama Desert ranging from latitude 18S to latitude 30S. Energy losses were assessed by comparing side-by-side outputs of four co-planar PV modules. Two of the PV modules of the array were kept clean as a control, while we allowed the other two to naturally accumulate soiling for 12 months (from January 2017 to January 2018). We found that the combination of high deposition rates and infrequent rainfalls led to annual energy losses that peaked at 39% in the northern coastal part of the desert. In contrast, annual energy losses of 3% or less were measured at relatively high-altitude sites and also at locations in the southern part of the desert. For comparison, soiling-induced annual energy losses of about 7% were measured in Santiago, Chile (33S), a major city with higher rainfall frequency but where urban pollution plays a significant role.

Research areas: Sun-Earth Interactions, Energy Production/Use, Environmental Impacts
Newly collected data across Alaska reveal remarkable biases in solar radiation products (2021)

AbstractData on surface solar radiation are scarce in highlatitude regions, and few studies have evaluated the performance of reanalysis products in estimating solar radiation in those regions. Here, an extensive solar radiation dataset is compiled from 98 stations across Alaska to evaluate 11 different surface solar radiation products (seven reanalysis and four observationderived). No product can capture all aspects of the groundbased observations, and there is ample room for improvement; root mean square errors (RMSEs) of daily, monthly, and annual average comparisons of the products against observations are 3865, 1939, and 1117 Wm2, respectively. ERA5, MERRA2, and ERAInterim performed the best in Alaska. Daily records from all products show large RMSEs of 60108 Wm2 during MayJuly, equivalent to 3055% of the observed solar radiation during this season. The sparseness of Alaskan observations, cloud cover, and algorithm issues may be potential sources of bias.

Research areas: Validation, Sun-Earth Interactions
Radiative forcing under mixed aerosol conditions (2011)

The mixture of mineral dust with biomass burning or urban-industrial aerosols presents significant differences in optical properties when compared to those of the individual constituents, leading to different impacts on solar radiation levels. This effect is assessed by estimating the direct radiative forcing (ΔF) of these aerosols from solar flux models using the radiative parameters derived from the Aerosol Robotic Network (AERONET). These data reveal that, in oceanic and vegetative covers (surface albedo (SA) &lt; 0.30), the aerosol effect at the top of atmosphere (TOA) is always cooling the Earth-atmosphere system, regardless of the aerosol type. The obtained average values of ΔF range between -27 ± 15 Wm<SUP>-2</SUP> (aerosol optical depth (AOD) at 0.55 μm, 0.3 ± 0.3) for mineral dust mixed with urban-industrial aerosols, registered in the East Asia region, and -34 ± 18 Wm<SUP>-2</SUP> (AOD = 0.8 ± 0.4) for the mixture of the mineral dust and biomass burning particles, observed in the Central Africa region. In the intermediate SA range (0.30-0.50) the TOA radiative effect depends on the aerosol absorption properties. Thus, aerosols with single scattering albedo at 0.55 μm lower than ∼0.88 lead to a warming of the system, with ΔF of 10 ± 11 Wm<SUP>-2</SUP> for the mixture of mineral dust and biomass burning. Cases with SA &gt; 0.30 are not present in East Asia region. At the bottom of atmosphere (BOA) the maximum ΔF values are associated with the highest AOD levels obtained for the mixture of mineral dust and biomass burning aerosols (-130 ± 44 Wm<SUP>-2</SUP> with AOD = 0.8 ± 0.4 for SA &lt; 0.30).

Research areas: Sun-Earth Interactions, Environmental Impacts
Mapping potential surface contributions to reflected solar radiation (2022)

Abstract
            Modifying Earths albedo is one of the strategies considered to reduce its energy imbalance and slow global warming by reflecting solar energy. Atmospheric contributions to reflected solar radiation through stratospheric aerosols or cloud brightening have received considerable attention; however, the efficacy of surface interventions is less understood. We address this gap by estimating the potential for surface contributions to reflected solar radiation at approximately 30 km resolution using a simple radiative transfer model. Long-term average annual-mean incoming and outgoing top-of-atmosphere and surface solar fluxes are input to determine atmospheric shortwave optical properties (i.e., transmittance, absorptance, and reflectance), which can be used with surface albedo to estimate surface-reflected outgoing solar radiation. A comparison of reanalysis- and satellite-based input datasets shows good agreement. The results indicate global annual-mean surface-reflected outgoing solar radiation potential of 109 Wm-2, nearly a factor of five larger than the actual value, and local areas where it could be increased above 200 Wm-2 with surface albedo enhancement. Regions with particularly strong potential include Andean South America, the Middle East, southwestern North America, southwestern Africa, Australia, and the sub-equatorial tropical oceans. Future research could extend the methods to account for seasonal variations and the potential to mitigate extreme heat events in particular.

Research areas: Sun-Earth Interactions
On the influence of impact effect modelling for global asteroid impact risk distribution (2016)

The collision of an asteroid with Earth can potentially have significant consequences for the human population. The European and United States space agencies (ESA and NASA) maintain asteroid hazard lists that contain all known asteroids with a non-zero chance of colliding with the Earth in the future. Some software tools exist that are, either, capable of calculating the impact points of those asteroids, or that can estimate the impact effects of a given impact incident. However, no single tool is available that combines both aspects and enables a comprehensive risk analysis. The question is, thus, whether tools that can calculate impact location may be used to obtain a qualitative understanding of the asteroid impact risk distribution. To answer this question, two impact risk distributions that control for impact effect modelling were generated and compared. The Asteroid Risk Mitigation Optimisation and Research (ARMOR) tool, in conjunction with the freely available software OrbFit, was used to project the impact probabilities of listed asteroids with a minimum diameter of 30m onto the surface of the Earth representing a random sample (15% of all objects) of the hazard list. The resulting 261 impact corridors were visualised on a global map. Furthermore, the impact corridors were combined with Earth population data to estimate the simplified risk (without impact effects) and advanced risk (with impact effects) associated with the direct asteroid impacts that each nation faces from present to 2100 based on this sample. The relationship between risk and population size was examined for the 40 most populous countries and it was apparent that population size is a good proxy for relative risk. The advanced and simplified risk distributions were compared and the alteration of the results based on the introduction of physical impact effects was discussed. Population remained a valid proxy for relative impact risk, but the inclusion of impact effects resulted in significantly different risks, especially when considered at the national level. Therefore, consideration of physical impact effects is essential in estimating the risk to specific nations of the asteroid threat.

Research areas: Validation