nasa-gesdisc/es-publications-researchareas huggingface dataset:
Measurements to determine the mixing state of black carbon emitted from the 2017–2018 California wildfires and urban Los Angeles (2020)

Abstract. The effects of atmospheric black carbon (BC) on climate and public health have been well established, but large uncertainties remain regarding the extent of the impacts of BC at different temporal and spatial scales. These uncertainties are largely due to the heterogeneous nature of BC in terms of its spatiotemporal distribution, mixing state, and coating composition. Here, we seek to further understand the size and mixing state of BC emitted from various sources and aged over different timescales using field measurements in the Los Angeles region. We measured refractory black carbon (rBC) with a single-particle soot photometer (SP2) on Catalina Island, California (70 km southwest of downtown Los Angeles) during three different time periods. During the first campaign (September 2017), westerly winds were dominant and measured air masses were representative of well-aged background over the Pacific Ocean. In the second and third campaigns (December 2017 and November 2018, respectively), atypical Santa Ana wind conditions allowed us to measure biomass burning rBC (BCbb) from air masses dominated by large biomass burning events in California and fossil fuel rBC (BCff) from the Los Angeles Basin. We observed that the emissions source type heavily influenced both the size distribution of the rBC cores and the rBC mixing state. BCbb had thicker coatings and larger core diameters than BBff. We observed a mean coating thickness (CTBC) of 4070 nm and a count mean diameter (CMD) of 120 nm for BCbb. For BCff, we observed a CTBC of 515 nm and a CMD of 100 nm. Our observations also provided evidence that aging led to an increased CTBC for both BCbb and BCff. Aging timescales < 1 d were insufficient to thickly coat freshly emitted BCff. However, CTBC for aged BCff within aged background plumes was 35 nm thicker than CTBC for fresh BCff. Likewise, we found that CTBC for aged BCbb was 18 nm thicker than CTBC for fresh BCbb. The results presented in this study highlight the wide variability in the BC mixing state and provide additional evidence that the emissions source type and aging influence rBC microphysical properties.

Research areas: Air Quality, Wildfires
Risk-Calibrated conventional-renewable generation mix using master-slave (2022)

This paper proposes a master-slave approach to quantify, combine and balance energy-risk and cost-risk involved in a generation portfolio with renewable and fuel-based technologies. Subjective preferences of the investor on risk, cost and emission are traded-off using pareto-optimization and quantified using multi-criteria decision-making techniques. Temporal variations in renewable energy production led to 'energy-risk' (kWh), characterized by energy-return-risk Efficient Frontier (EF). The uncertainty in the energy production cost of the fuel-based sources (FBS) results in 'cost-risk' ($/kWh), represented by cost-risk EF. These efficient frontiers are combined using the concepts of Sharpe ratio and tangency portfolio. The master portfolio (MP) gives a percentage share for the total renewable and total conventional generation. The slave portfolio (SP) assigns internal weights within the renewable (solar and wind) and within the fuel-based (coal, natural gas, and oil) generations. The best solution is selected from the pareto-front by calibrating the investor preferences using Analytic Hierarchy Process (AHP) and then verified using Elimination and Choice Translating Reality (ELECTRE). It is understood that a completely customizable multi-criteria portfolio selection can be achieved by incorporating subjective views of the investors, eliminating one-sided energy portfolios.

Research areas: Energy Production/Use
Impact of decomposition and kriging models on the solar irradiance downscaling accuracy in regions with complex topography (2020)

Many small island states are planning to invest heavily in solar photovoltaics in an attempt to curb their overreliance on fossil fuels for electricity generation. In order to efficiently exploit the abundant solar energy resource, these islands need reliable solar irradiance data. However, the orographic effects arising from their volcanic origins often result in strong variability and uncertainty in the solar resource. In this context, satellite-based models present an effective alternative to ground-based measurements. Different downscaling approaches have been applied that compensate for the large spatial resolution of satellite images and the terrain-related effects that they disregard. Nevertheless, the accuracy of these methods is influenced by the solar radiation decomposition model used. Moreover, the variogram model used in the kriging process to characterize the spatial dependence of the solar radiation has a significant effect on the results. In this study, we compare the performances of seven radiation decomposition models for the anisotropy analysis and seven variogram models for the spatial interpolation of the solar irradiance. A dense network of ground measurements at 43 stations is used to evaluate the accuracy of the different models. Results reveal that the Yao radiation model coupled with the Matern variogram provide the best results.

Research areas: Sun-Earth Interactions
Comparative Reliability Assessment of Hybrid Si/SiC and Conventional Si (2022)

Energy harnessing from renewable energy sources has become more flexible with power electronic technologies. Recent advancements in power electronic technologies achieve converter efficiency higher than 98%. Today, reliable power electronic devices are needed to design a PV-based energy converter (inverter) to reduce the risk of failure and maintenance costs during operation. Wide-bandgap SiC devices are becoming more common in power electronic converters. These devices are designed to reduce switching loss and improve the efficiency of the system. Nevertheless, the cost of SiC devices is a major concern. Hence, to improve the reliability of the PV inverter while considering the economic aspects, this paper develops a highly reliable PV inverter with a hybrid Si/SiC power module that consists of a Si-IGBT with a SiC anti-parallel diode. A test case of a 3 kW PV inverter is considered for reliability analysis. The loading of the PV inverter is done under uncertain environmental conditions by considering the yearly Mission Profile (MP) data related to Ambient Temperature (AT) and Solar Irradiance (SI) at the India and Denmark locations. The effectiveness of the proposed hybrid Si/SiC power module is tested by comparing it with a conventional IGBT power module. The results showcase the marked improvement in PV inverter reliability with the proposed hybrid power module.

Research areas: Energy Production/Use, Sun-Earth Interactions
Influence of temporal resolution on the performance of global ionospheric maps (2021)

Global ionosphere maps (GIM) computed from dual-frequency GNSS measurements have been widely used for monitoring ionosphere as well as providing ionospheric corrections in Space Geodesy since 1998. This work focuses on a comprehensive study of the influence of time resolution on GIM performance. One and a half solar cycle of the IGS GIM with higher time resolution and accuracy (the UPC-IonSAT Quarter-of-an-hour time resolution Rapid GIM, AKA uqrg) has been taken as baseline to downsample them to all possible sub-daily temporal resolutions. The performance of the resulting GIMs has been assessed by directly comparing with external vertical total electron content (VTEC) measurements from Jason altimeters over oceanic regions. In order to perform a complete assessment and analysis of involved GIMs, the influence of geographical position and solar and geomagnetic activities was also taken into account during more than one solar cycle. In addition, to have a clear view at the smaller time resolutions, a more accurate assessment, the dSTEC test based on external GNSS measurements not used in the GIM generation was also done during two solstice and two equinox days in 2015 over continental regions. The assessment shows that discrepancy among GIMs with different time resolutions becomes more apparent at low latitudes and also at high solar-geomagnetic activity. The results also suggest that the accuracy for GIMs with time resolution smaller or equal to 60 min is consistent during the period from 2002 to 2019 and is more accurate than other GIMs with lower temporal resolution. Accordingly, high time resolution (including 15, 30, 45 and 60 min) is recommended for the application of GIMs with the highest accuracy.

Research areas: Validation
Estimating surface solar irradiance from geostationary Himawari-8 over Australia: A physics-based method with calibration (2021)

Surface Solar Irradiance (SSI) is required for solar energy planning and adoption, and is a fundamental parameter in modelling weather, climate, ecosystem and agricultural activities. Herein a time series based radiative transfer model was developed to simultaneously retrieve properties of clouds, aerosols and surface albedo, which were in turn used to calculate the components of SSI: i.e., global, direct and diffuse irradiance. The calculated results were calibrated across the Australian continent against in-situ measurements to account for minor factors (e.g., water vapor) not considered by the physics-based method. Detailed validation of the SSI components was performed against three years of in-situ measurements at 11 sites across Australia, at a range of time scales (i.e., instantaneous, hourly, daily and monthly) and under both all-sky and cloudy-sky conditions. The main advantage of the present method is the reliable separation of the direct and diffuse components with consistently low biases (~4 W/m2) at all four time scales, while still maintaining relatively low RMSE (root-mean-square-error) and MAE (mean-absolute-error). Once calibration has been performed the model does not require any ancillary data when implemented operationally: that is the model only requires geostationary satellite data. This model may be implemented across the globe using widely available next generation geostationary satellite data with a handful of ground-data for calibration.

Research areas: Sun-Earth Interactions
Earth as an Exoplanet. I. Time Variable Thermal Emission Using Spatially Resolved Moderate Imaging Spectroradiometer Data (2020)

Among the more than 4000 exoplanets known today, some terrestrial planets have been detected in the so-called habitable zone of their host stars and their number is expected to increase in the near future, energizing a drive to understand and interpret the eagerly awaited wealth of data to identify signs of life beyond our solar system. So far, Earth remains the best and only example of a habitable (and inhabited) world. Although, it seems extremely unlikely that any other exoplanets will be true Earth twins, it is important to explore and understand the full range of spectral signatures and variability of Earth in order to inform the design of future instruments and missions, and understand their diagnostic power as well as potential limitations. In this work we use Earth observation data collected by the MODIS instrument aboard the Aqua satellite. The complete data set comprises 15 years of thermal emission observations in the 3.66-14.40 μm range for five different locations on Earth (Amazon Rainforest, Antarctica, Arctic, Indian Ocean, and the Sahara Desert). We then determine flux levels and variations as a function of wavelength and surface type (i.e., climate zone and surface thermal properties) and investigate whether periodic signals indicating Earth&amp;'s tilted rotation axis can be detected. Our findings suggest that (1) viewing geometry plays an important role when thermal emission data is analyzed as Earth&amp;'s spectrum varies by a factor of three and more depending on the dominant surface type underneath; (2) typically strong absorption bands from CO<SUB>2</SUB> (15 μm) and O<SUB>3</SUB> (9.65 μm) are significantly less pronounced and partially absent in data from the polar regions implying that estimating correct abundance levels for these molecules might be challenging in these cases; and (3) the time-resolved thermal emission spectrum encodes information about seasons/planetary obliquity, but the significance depends on the viewing geometry and spectral band considered.

Research areas: Validation
Prediction of time series for several hours of surface solar irradiance using one-granule cloud property data from satellite observations (2019)

Satellite observation is one of the most useful methods for monitoring the power generated by photovoltaic systems. We propose a method for predicting time series of the surface solar irradiance (SSI) from one-granule cloud properties data obtained by satellite observation. This method has two parts. One is prediction of time series features from cloud properties, which is based on a previous study. The other is prediction of a time series from time series features, which is developed in this work. Seven time series features are used: mean, standard deviation, skewness, kurtosis, linear regression coefficient, autocorrelation coefficient with lag-1, and sample entropy. The prediction skill is characterized in two ways: by the distance between the predicted and observed time series (metric D), and by the similarity of the spectrum between the two time series (metric S). Verifying the time series prediction method from time series features shows that the mean and linear regression coefficient are the first and second most influential factors for metric D, and standard deviation and autocorrelation coefficient with lag-1 are those for metric S. The prediction skill of the prediction method for the time series features from cloud properties is also verified, indicating that predictors for the mean, standard deviation lag-1 autocorrelation coefficient, and sample entropy have sufficient prediction skill, measured by the standardized root mean square error. Finally, the two methods are integrated to construct the prediction system using four time series features. The overall skill of the prediction system for the time series is evaluated. The proposed system provides information about the strength of the SSI time series and its variation for several hours over the satellite observation area.

Research areas: Sun-Earth Interactions
Variability and trends in surface solar spectral ultraviolet irradiance in Italy: on the influence of geopotential height and lower-stratospheric ozone (2021)

Abstract. The short- and long-term variability of the surface spectral solar ultraviolet (UV) irradiance is investigated across Italy using high-quality ground-based measurements from three locations: Aosta (45.7 N, 7.4 E, 570 m a.s.l.), Rome (41.9 N, 12.5 E, 15 75 m a.s.l.), and Lampedusa (35.5 N, 12.6 E, 50 m a.s.l.). The three sites are characterized by different environmental conditions and represent almost the full latitudinal extent of the Italian territory. Data of two periods were analysed: 20062020 (all sites) and 19962020 (Rome only). The main objective of this study is to quantify the effect of the geopotential height (GPH) at 250 hPa on total ozone, and spectral irradiance at 307.5 and 324 nm. We first show that monthly anomalies in GPH, total ozone, and spectral irradiances are correlated amongst the three sites, suggesting that Italy is often affected by the same synoptical weather systems. We further find statistically significant anticorrelations between GPH and monthly anomalies in total ozone for all stations and months. Conversely, we identify positive correlations between GPH and monthly anomalies in spectral irradiance at 307.5 nm for most months. The influence of GPH on short-term variability also hold for long-term trends. For example, long-term changes in total ozone over the period 20062020 were associated with changes in GPH for all stations. This suggests that observed negative trends in total ozone were mainly driven by changes in lower-stratospheric ozone as upper-stratospheric ozone was increasing over this period. For several months of the year, positive trends in UV irradiance were observed, and we found that these trends were predominantly caused by changes in clouds and/or aerosols instead of total ozone. For the longer period of 19962020, a statistically significant annualized decrease in total ozone of  0.1 % per year was identified for Rome and could subsequently be attributed to decreasing lower-stratospheric ozone. While positive trends in spectral irradiance at 307.5 nm were observed for several months of this extended period, the negative trend in total ozone did not lead to a positive trend in the spectral irradiance at 307.5 nm in the deseasonalized data. Our study provides evidence that dynamical processes taking place in the troposphere lead to significant variability in total ozone and surface solar UV irradiance.

Research areas: Public Health, Sun-Earth Interactions
Quantification of Effects of Errors in the Cloud Properties on the Representation of the Surface Downward Shortwave Flux Based on MERRA-2 in Japan (2022)

Abstract The evaluation of the representation of the surface downward shortwave flux (DSF) from atmospheric reanalysis data products is required to obtain reliable information for the resource assessment of surface solar energy. The representation of the DSF from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), reanalysis data product was evaluated using surface solar radiation from ground-based observations in Japan. The cloud fraction (CFR) and cloud optical thickness (COT) from Moderate Resolution Imaging Spectroradiometer (MODIS) were also used as references. The CFR from MERRA-2 tends to be smaller than that from MODIS, and the correlation between the difference in the CFR and that in the DSF is negative. The correlation between the difference in the COT and that in the DSF is weakly negative. To quantify the effects of the difference in the CFR and COT to that of the DSF, a regression model based on an artificial neural network architecture that emulates the process of the DSF in MERRA-2 was constructed. Numerical experiments using the emulator quantify contributions of each of the differences in the CFR and COT and joint contributions of the two variables. In addition, a cluster analysis was performed to clarify the differences in the seasonal changes in the monthly mean bias error (MBE) in the DSF among ground observation stations, and three clusters were identified. Contributions of the differences in the CFR and COT to the seasonal change in the monthly MBE were also clarified using the results of the numerical experiments.

Research areas: Sun-Earth Interactions
Tailoring Meridional and Seasonal Radiative Forcing by Sulfate Aerosol Solar Geoengineering (2018)

We study the possibility of designing solar radiation management schemes to achieve a desired meridional radiative forcing (RF) profile using a two-dimensional chemistry-transport-aerosol model. Varying SO<SUB>2</SUB> or H<SUB>2</SUB>SO<SUB>4</SUB> injection latitude, altitude, and season, we compute RF response functions for a broad range of possible injection schemes, finding that linear combinations of these injection cases can roughly achieve RF profiles that have been proposed to accomplish various climate objectives. Globally averaged RF normalized by the sulfur injection rate (the radiative efficacy) is largest for injections at high altitudes, near the equator, and using emission of H<SUB>2</SUB>SO<SUB>4</SUB> vapor into an aircraft wake to produce accumulation-mode particles. There is a trade-off between radiative efficacy and control as temporal and spatial control is best achieved with injections at lower altitudes and higher latitudes. These results may inform studies using more realistic models that couple aerosol microphysics, chemistry, and stratospheric dynamics.

Research areas: Sun-Earth Interactions
Assessment of Floating Solar Photovoltaic (FSPV) Potential in India (2020)

This study deals with an assessment of the potential of utility-scale floating solar photovoltaic (FSPV) plants in India. Global Solar Atlas (GSA) and Global Reservoir and Dam (GRanD) databases are used for examining water bodies such as man-made reservoirs used for hydroelectricity generation, irrigation, drinking water purposes, and few lakes in India. Considering 10% coverage of water surface area by FSPV systems, a gross potential estimate of 124.6 GWp is arrived at. Further screening by fixing technological and other criteria limits the potential to 111.9 GWp.

Research areas: Energy Production/Use, Sun-Earth Interactions
Prediction of the day-ahead clear-sky downwelling surface solar irradiances using the REST2 model and WRF-CHIMERE simulations over the Arabian Peninsula (2018)

The forecasting of the downwelling surface solar irradiances is required by the operators of solar powered plants to predict the power output of the plant. The purpose of this study is to use aerosol optical depth and columnar water vapor forecasts by the chemistry transport model CHIMERE, coupled with the Weather Research and Forecast (WRF) model, as inputs in the REST2 model to predict the day-ahead clear-sky global horizontal, direct normal and diffuse horizontal irradiances at hourly steps. A dataset of quality-assured and cloud-screened surface solar irradiance measurements collected from 44 sites scattered throughout Saudi Arabia was used to validate the predicted surface solar irradiances. The validation for the day-ahead forecasting of the clear-sky global horizontal irradiance for the data of all 44 stations combined exhibits a bias (relative to the mean reference value) of 0%, a relative root mean square error of 4% and a correlation coefficient of 0.993. Respectively, the clear-sky direct normal irradiance exhibits values of 0%, 15% and 0.769, while the clear-sky diffuse horizontal irradiance values are 0%, 35% and 0.542. The errors in the inputs are also investigated. The results are satisfactory and pave the way to the inclusion of the attenuation due to clouds with the final aim of predicting the surface solar irradiance under all-sky conditions.

Research areas: Sun-Earth Interactions
Effects of absorbing aerosols on the determination of the surface solar radiation (2003)

Coincident and collocated measurements of solar radiation from the Scanner for Radiation Budget (ScaRaB) on Meteor-3 and from towers in a boreal forest region during the Boreal Ecosystems and Atmosphere Study (BOREAS) period are used to evaluate an algorithm of [1993a] which was developed to derive the net surface solar radiation flux from satellite measurements. The analysis shows that after correcting for mismatching between the footprints of the tower measurements and the satellite pixels, there is a substantial bias that is due to the presence of absorbing aerosols. Application of the aerosol correction term of [1995] reduces the mean bias to about 5 W m<SUP>-2</SUP>. Cloud radiation forcing ratio R has been used in many studies to address the issue of a cloud absorption anomaly. Three methods, each with a different approach to the consideration of the effect on radiative fluxes by absorbing aerosols, are used to calculate R. Methods that account inadequately for aerosol effects when applied to the coincident and collocated tower and satellite measurements give large values of R (1.28-1.42) under conditions of heavy aerosol loading, which could be interpreted as an indication of a cloud absorption anomaly. However, application of the method that accounts best for aerosol effects gives values of R within the range 1.08∼1.18 and so does not support the idea of anomalous cloud absorption.

Research areas: Sun-Earth Interactions