nasa-gesdisc/es-publications-researchareas huggingface dataset:
Optimised degradation correction for SCIAMACHY satellite solar measurements from 330 to 1600 nm by using the internal white light source (2020)

Abstract. SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) on-board the European Environmental Satellite (Envisat) provided spectrally resolved measurements in the wavelength range from 0.24 to 2.4 m by looking into the Earth's atmosphere using different viewing geometries (limb, nadir, solar, and lunar occultation). These observations were used to derive a multitude of parameters, in particular atmospheric trace gas amounts. In addition to radiance measurements solar spectral irradiances (SSIs) were measured on a daily basis. The instrument was operating for nearly a decade, from August 2002 to April 2012. Due to the harsh space environment, it suffered from continuous optical degradation. As part of recent radiometric calibration activities an optical (physical) model was introduced that describes the behaviour of the scanner unit of SCIAMACHY with time (Krijger et al., 2014). This model approach accounts for optical degradation by assuming contamination layers on optical surfaces in the scanner unit. The variation in layer thicknesses of the various optical components is determined from the combination of solar measurements from different monitoring light paths available for SCIAMACHY. In this paper, we present an optimisation of this degradation correction approach, which in particular improves the solar spectral data. An essential part of the modification is the use of measurements from SCIAMACHY's internal white light source (WLS) in combination with direct solar measurements. The WLS, as an independent light source, therefore, gives an opportunity to better separate instrument variations and natural solar variability. However, the WLS emission depends on its burning time and changes with time as well. To use these measurements in the optimised degradation correction, the change in the WLS emission in space needs to be characterised first. The changes in the WLS with accumulated burning time are in good agreement with detailed laboratory lamp studies by Sperling et al. (1996). Although the optimised degradation-corrected SCIAMACHY SSIs still show some instrumental issues when compared to SSI measurements from other instruments and model reconstructions, our study demonstrates the potential for the use of an internal WLS for degradation monitoring.

Research areas: Validation
Semi-analytical solar radiation pressure modeling for QZS-1 orbit-normal and yaw-steering attitude (2017)

Solar radiation pressure (SRP) is the dominant non-gravitational perturbation of global navigation satellite system (GNSS) satellites. In the absence of detailed surface models, empirical SRP models, such as the Empirical CODE Orbit Model (ECOM), are widely used in practice for GNSS orbit determination but may require an undue number of parameters to properly describe the actual motion. Building up on previous research for spacecraft in yaw-steering (YS) attitude, analytical expressions for the SRP acceleration in orbit-normal (ON) attitude are established based on a generic box-wing model, and related to the corresponding parameters of the ECOM. The results are used to obtain an a priori SRP model for the QZS-1 satellite of the Quasi Zenith Satellite System (QZSS), which achieves a modeling accuracy of about 1nm/s2 using as little as 6 parameters. To compensate remaining modeling deficiencies, we combine the analytical a priori model with a complementary set of five empirical parameters based on an ECOM-type formulation. QZS-1 orbits based on the resulting semi-analytical SRP model exhibit a better than 10cm RMS consistency with satellite laser ranging measurements for both YS and ON attitude modes, which marks a 24 times improvement over legacy orbit products without a priori model.

Research areas: Sun-Earth Interactions
How changes in worldwide operating conditions affect solar cell performance (2021)

In field operation, solar cells are exposed to constantly changing operating conditions. These changing conditions have an impact on energy yield. Present-day yield predictions mostly use linear correction coefficients derived from lab experiments. These corrections neglect interactions between meteorological parameters like temperature and humidity. In this study, we reverse this approach by analyzing simulated solar cell performance under varying conditions worldwide. We use meteorological data measured between 2006 and 2015 to establish trends in the development of meteorological conditions and solar cell performance. From these two trends, we obtain linear correlation coefficients. The obtained implied temperature coefficient, on average, has a value of 0.52  0.03%/K. This value is 15% higher than the tabulated temperature coefficient (0.45%/K) used in the simulation, demonstrating the impact of coinciding meteorological factors. Light absorption due to elevated humidity levels is likely the strongest contributor to the deviation. One application of these findings is a projection of how today's crystalline silicon solar panels would perform due to rising temperature at the end of the 21st century. Using the established implied temperature coefficient, we project performance reductions of between 0.7% and 2.5%, depending on the warming scenario. The effect is reduced in higher efficient, upcoming photovoltaic technologies, providing further motivation to develop and improve these solar cells.

Research areas: Sun-Earth Interactions, Energy Production/Use
An optimized approach for mapping solar irradiance in a mid-low latitude region based on a site-adaptation technique using Himawari-8 satellite imageries (2022)

Solar technologies play an important role in the renewable electric energy budget, so accurate solar maps are a crucial point for finding a suitable place for solar panel installation. This study proposes a method for solar irradiance mapping in mid-low latitude regions, and the method's site-adaptation process is performed by optimizing the Heliosat method through the REST2 clear-sky model, cloud albedo selection, new clear-sky index, and linear subtraction for bias removal. A local station with two pyranometers provided ground measurements. Site-adapted model results were used to create a calibrated solar map by linear regression adaptation. This study also provides the evaluation and site-adaption of another irradiance dataset in the Asian region from the Japan Aerospace Exploration Agency (JAXA). Heliosat model results with optimal cloud albedo showed high accuracy of 4.78 W/m2 MBE and 63.11 W/m2 RMSE, which can be improved using the site-adaptation process to 0.71 W/m2 MBE and 57.42 W/m2 RMSE. The selection of an optimal cloud albedo improved the model by approximately 20%. The JAXA dataset obtained a large overestimation of 56.72 W/m2 MBE, thereby highlighting the importance of site adaptation. This research's findings pave a new way for the creation of accurate site-adapted solar maps and databases.

Research areas: Sun-Earth Interactions
Ray-tracing solar radiation pressure modeling for QZS-1 (2018)

Precise orbit determination requires accurate models for the orbital perturbations. Next to the well-known gravitational forces, the solar radiation pressure (SRP) is the main perturbation for navigation satellites. SRP results from the interaction between the photons of the Sun and the surfaces of the satellite. Hence, its modeling depends on proper knowledge of the geometry and optical properties of the satellite. Previous work showed that the use of an a priori box-wing model for the SRP significantly improves the estimated orbit products as well as orbit predictions compared to purely empirical models. However, the presently available box-wing models for the first satellite of the Japanese Quasi-Zenith Satellite System, QZS-1, do not consider an accurate geometry. Based on a computer-aided design model of the QZS-1 satellite, a ray-tracing simulation is performed to compute SRP accelerations in a more realistic manner. The resulting SRP model is validated through QZS-1 precise orbit determination over a two year data arc covering yaw-steering and orbit-normal attitude regimes. In yaw-steering mode, the ray-tracing model shows a better overall performance than a box-wing model and improves the standard deviation of QZS-1 satellite laser ranging residuals by a factor of three compared to orbits without a priori model. On the other hand, the ray-tracing SRP model does not account for thermal accelerations and thus performs worse than an adjusted box-wing model in orbit-normal mode.

Research areas: Sun-Earth Interactions
Annual and interannual complementarities of renewable energy sources in Colombia (2020)

The Colombian power sector is highly dependent on hydroelectricity, making it vulnerable to both annual dry seasons and the droughts brought by the El Nino-Southern Oscillation (ENSO). One efficient way to reduce such vulnerabilities is by introducing renewable energies that may complement the availability of hydroelectricity. This paper explores the degree of complementarity between solar and wind resources in Colombia and the country's hydropower sector, on both annual and interannual scales. Various correlation analyses are performed over four climatic variables: water inputs (runoff), precipitation, solar radiation, and wind speed, plus the Oceanic Nino Index (ONI), which helps to characterize ENSO events. The analysis is carried out over different geographic locations and seasons. The results indicate that solar and wind resources, particularly those in the Caribbean Coast and the central Andes regions, complement the hydropower sector during both the dry seasons of the annual climatological cycle and ENSO's warm and cold phases. Also, they show that complementarity varies, not just with the type of sources and location, but also with the seasons of the year and ENSO's stage of development. This paper provides an enhanced perspective on the behavior of renewables and offers an alternative viewpoint for designing the future expansion of power systems.

Research areas: Energy Production/Use
The economic value of photovoltaic performance loss mitigation in electricity spot markets (2022)

Photovoltaic (PV) performance is affected by reversible and irreversible losses. These can typically be mitigated through responsive and proactive operations and maintenance (O&M) activities. However, to generate profit, the cost of O&M must be lower than the value of the recovered electricity. This value depends both on the amount of recovered energy and on the electricity prices, which can vary significantly over time in spot markets. The present work investigates the impact of the electricity price variability on the PV profitability and on the related O&M activities in Italy, Portugal, and Spain. It is found that the PV revenues varied by 1.6  to 1.8  within the investigated countries in the last 5 years. Moreover, forecasts predict higher average prices in the current decade compared to the previous one. These will increase the future PV revenues by up to 60% by 2030 compared to their 20152020 mean values. These higher revenues will make more funds available for better maintenance and for higher quality components, potentially leading to even higher energy yield and profits. Linearly growing or constant price assumptions cannot fully reproduce these expected price trends. Furthermore, significant price fluctuations can lead to unexpected scenarios and alter the predictions.

Research areas: Energy Production/Use
A Cloudier Picture of Ice-Albedo Feedback in CMIP6 Models (2021)

Increased solar absorption is an important driver of Arctic Amplification, the interconnected set of processes and feedbacks by which Arctic temperatures respond more rapidly than global temperatures to climate forcing. The amount of sunlight absorbed in the Arctic is strongly modulated by seasonal ice and snow cover. Sea ice declines and shorter periods of seasonal snow cover in recent decades have increased solar absorption, amplifying local warming relative to the planet as a whole. However, this Arctic albedo feedback would be substantially larger in the absence of the ubiquitous cloud cover that exists throughout the region. Clouds have been observed to mask the effects of reduced surface albedo and slow the emergence of secular trends in net solar absorption. Applying analogous metrics to several models from the 6
              
                th
              
              Climate Model Intercomparison Project (CMIP6), we find that ambiguity in the influence of clouds on predicted Arctic solar absorption trends has increased relative to the previous generation of climate models despite better agreement with the observed albedo sensitivity to sea ice variations. Arctic albedo responses to sea ice loss are stronger in CMIP6 than in CMIP5 in all summer months. This agrees better with observations, but models still slightly underestimate albedo sensitivity to sea ice changes relative to observations. Never-the-less, nearly all CMIP6 models predict that the Arctic is now absorbing more solar radiation than at the start of the century, consistent with recent observations. In fact, many CMIP6 models simulate trends that are too strong relative to internal variability, and spread in predicted Arctic albedo changes has increased since CMIP5. This increased uncertainty can be traced to increased ambiguity in how clouds influence natural and forced variations in Arctic solar absorption. While nearly all CMIP5 models agreed with observations that clouds delay the emergence of forced trends, about half of CMIP6 models suggest that clouds accelerate their emergence from natural variability. Isolating atmospheric contributions to total Arctic reflection suggests that this diverging behavior may be linked to stronger Arctic cloud feedbacks in the latest generation of climate models.

Research areas: Sun-Earth Interactions
Evaluation the efficiency of a parametric model based on MODIS data for solar radiation estimation in comparison with some empirical models (2021)

In the present study, the output of several empirical models for estimating solar radiation and the output of a model based on data obtained from moderate resolution imaging spectroradiometer (MODIS) sensor (parametric model) are compared with ground observational station to introduce a suitable algorithm for estimating solar radiation in the studied stations. For this purpose, first the selected empirical models were calibrated according to the climatic conditions of the study area and then used to estimate solar radiation. To this aim, empirical models were evaluated based on suitably partitioned datasets. 75% of the total data were utilized for training phase and the remaining 25% data were used for testing phase and conducting statistical analysis. In the next step, the parametric model (SBDART) were tested and used for predicting the solar radiation data in target stations. The results indicated that the R2 value of models vary between 0.25 to 0.95, most of which are related to the Santa Barbara DISORT (discrete ordinates radiative transfer) atmospheric radiative transfer (SBDART) (R2=0.95) and calibrated Angstrom models (R2=0.89), respectively. The mean absolute percentage error of the SBDART model is significantly different from other models (MAPE=4.3%). After that, the lowest MAPE (mean absolute percentage error) is related to the Angstrom model (MAPE =5.98%). In addition, the parametric model is more efficient on cloudy days than on cloudless days so that the calculated RMSE (root mean square error) and MBE (mean bias error) indices are 9.07 W/m2.day and -0.72 W/m2.day for cloudy days, and 19.77 W/m2.day and 3.60 W/m2.day for cloudless days. In contrast, the empirical Angstrom-Prescott model had better results with observational data on cloudless days so that the indices were RMSE =43.60 W/m2.day and MBE =34.25 W/m2.day for cloudy days, and RMSE =29.56 W/m2.day and MBE= 6.19 MJ/m2.day for cloudless days.

Research areas: Sun-Earth Interactions
Changes in clear‐sky shortwave aerosol direct radiative effects since 2002 (2021)

A new method for determining clear sky shortwave aerosol direct radiative effects (ADRE) from the Clouds and the Earth's Radiant Energy System is used to examine changes in ADRE since 2002 alongside changes in aerosol optical depth (AOD) from the Moderate Resolution Spectroradiometer. At global scales, neither ADRE nor AOD show a significant trend. Over the northern hemisphere (NH), ADRE increases by 0.18 ± 0.17 Wm<SUP>−2</SUP> per decade (less reflection to space) but shows no significant change over the southern hemisphere. The increase in the NH is primarily due to emission reductions in China, the United States, and Europe. The COVID 19 shutdown shows no noticeable impact on either global ADRE or AOD, but there is a substantial influence over northeastern China in March 2020. In contrast, February 2020 anomalies in ADRE and AOD are within natural variability even though the impact of the shutdown on industry was more pronounced in February than March. The reason is because February 2020 was exceptionally hot and humid over China, which compensated for reduced emissions. After accounting for meteorology and normalizing by incident solar flux, February ADRE anomalies increase substantially, exceeding the climatological mean ADRE by 23%. February and March 2020 correspond to the only period in which adjusted anomalies exceed the 95% confidence interval for 2 consecutive months. Distinct water land differences over northeastern China are observed in ADRE but not in AOD. This is likely due to the influence of surface albedo on ADRE in the presence of absorbing aerosols.

Research areas: Atmospheric/Ocean Indicators, Sun-Earth Interactions
Surface irradiance estimations on watercourses with remote sensing data (2018)

The vegetation in the riparian zone of a watercourse influences the water state with multiple factors, first via direct substance discharge and secondly via shadow casting on the water surface. Shadowing directly regulates the solar radiant energy arriving at the water surface. Solar radiation input to aquatic environments is the most important abiotic factor for aquatic flora and fauna habitat development. Thus, to adequately asses the ecological state of water courses it is necessary to quantify the solar surface irradiance E (W/m<SUP>2</SUP>) arriving on the water surface. When estimating the solar surface irradiance the complex coherence between incoming solar radiation, atmospheric influences, and spatial-temporal geometries need to be investigated. This work established a work flow to compute the solar surface irradiance for water bodies using different remote sensing data. The work flow was tested on regional level for a section of the river Freiberger Mulde, Saxony, for the year 2016. Product of the calculations is a map visualising the annual sum of the solar surface irradiance (kWh/m<SUP>2</SUP>) arriving on the Freiberger Mulde water surface and the surrounding terrain. Based on these information bio-hydrological issues can be further examinated.

Research areas: Sun-Earth Interactions
Validation of SAGE III/ISS Solar Occultation Ozone Products With Correlative Satellite and GroundBased Measurements (2020)

The Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) was launched on 19 February 2017 and began routine operation in June 2017. The first 2 years of SAGE III/ISS (v5.1) solar occultation ozone data were evaluated by using correlative satellite and ground-based measurements. Among the three (MES, AO3, and MLR) SAGE III/ISS retrieved solar ozone products, AO3 ozone shows the smallest bias and best precision, with mean biases less than 5% for altitudes ~15-55 km in the midlatitudes and ~20-55 km in the tropics. In the lower stratosphere and upper troposphere, AO3 ozone shows high biases that increase with decreasing altitudes and reach ~10% near the tropopause. Preliminary studies indicate that those high biases primarily result from the contributions of the oxygen dimer (O<SUB>4</SUB>) not being appropriately removed within the ozone channel. The precision of AO3 ozone is estimated to be ~3% for altitudes between 20 and 40 km. It degrades to ~10-15% in the lower mesosphere (~55 km) and ~20-30% near the tropopause. There could be an altitude registration error of ~100 m in the SAGE III/ISS auxiliary temperature and pressure profiles. This, however, does not affect retrieved ozone profiles in native number density on geometric altitude coordinates. In the upper stratosphere and lower mesosphere (~40-55 km), the SAGE III/ISS (and SAGE II) retrieved ozone values show sunrise/sunset differences of ~5-8%, which are almost twice as large as what was observed by other satellites or model predictions. This feature needs further study.

Research areas: Validation
An improved ocean surface albedo computational scheme: Structure and Performance (2021)

Ocean surface albedo (OSA) is an important factor for the transfer of radiation in the coupled atmosphere-ocean system. By resolving the spectral variations of the reflective properties for incident direct and diffuse solar radiation, we develop an OSA computational scheme to study the impact of ocean biogeochemistry on the air-sea boundary condition of solar radiative transfer in the atmosphere. The new scheme is implemented for the General Circulation Model applications of the shortwave rapid radiative transfer model RRTMG_SW, a radiative transfer model used extensively in regional and global models. We show that a number of OSA schemes lead to underestimated results in comparison with in-situ measurements obtained at a site 25 km east of Virginia Beach. The scheme developed in this study considers multiple influential factors and is robust in terms of the mean absolute percentage error (MAPE) and the root mean square error in comparison with in-situ measurements. Furthermore, the new simulations are highly consistent with the Clouds and the Earth's Radiant Energy System (CERES) OSA distribution on a global scale. However, the theoretical results show slight differences compared with the CERES OSA under all sky conditions and overestimate the OSA in the subpolar Southern Ocean under clear sky conditions. The assumption of a uniform phase function, which neglects the spatial variability of the optical properties of oceanic particles, is largely responsible for the primary source of uncertainties in an OSA scheme.

Research areas: Sun-Earth Interactions