Search Results (8)

Several studies proposed relationships linking irradiances in the photosynthetically active radiation (PAR) range and broadband irradiances. A previous study published in 2024 by the same authors proposes a linear model relating clear-sky indices in the PAR and broadband ranges that has been validated in clear and overcast conditions only. The present work extends this study for broken-cloud conditions by using ground-based measurements obtained from the Surface Radiation Budget Network in the U.S.A. mainland. As expected, the clear-sky indices are highly correlated and are linked by affine functions whose parameters depend on the fractional sky cover (FSC), the year, and the site. The previous linear model is also efficient in broken-cloud conditions, with the same level of accuracy as in overcast conditions. When this model is combined with a PAR clear-sky model, the result tends to overestimate the PAR as the FSC decreases, i.e., when fewer and fewer scattered clouds are present. The bias is equal to 1 W m⁻² in overcast conditions, up to 18 W m⁻² when the FSC is small, and 6 W m⁻² when all cloudy conditions are merged. The RMSEs are, respectively, 5, 24, and 15 W m⁻². The linear and the clear-sky models can be combined with estimates of the broadband irradiance from satellites to yield estimates of PAR. Full article

The cloud adjacency effect on surface reflectance retrievals for the region of the Russian Federation with coordinates 51–54${}^{\circ } \mathrm{N}$, 103–109${}^{\circ } \mathrm{E}$ including the southern part of Lake Baikal for the period of 1–23 July 2021 is assessed in this paper. The method is based on the computer program for statistical simulation of radiative transfer in the atmosphere with the stochastic cloud field including a deterministic gap of a given radius. The results of this program are then used in the interpolation formula. Masks of cloudless pixels, for which the cloud adjacency effect (CAE) changes the ground surface reflectance by more than 0.005, are constructed. The analysis of the resulting CAE radii shows that the average radius is 13.7 km for MODIS band 8, 11.2 km for band 3, 8.4 km for band 4, 7.2 km for band 1, and 7 km for band 2. For the considered MODIS images and bands, the pixels with strong CAE make up from 2.8 to 100% of the total number of cloudless pixels. The correlation coefficients between the initial data and the CAE radius suggest that the cloud optical depth, cloud cover index, and ground surface reflectance exert the major influence on the considered images. A simplified approximation equation for the CAE radius as a function of the cloud optical depth, cloud cover index, and surface reflectance is derived. The analysis of the approximation shows that for the considered images, the CAE radius decreases nearly linearly with wavelength for low reflective surfaces. However, for high reflective surfaces, its wavelength dependence is nonlinear. Full article

A method for estimating the cloud adjacency effect on the reflectance of ground surface areas reconstructed from passive satellite observations through gaps in cloud fields is proposed. The method allows one to estimate gaps of cloud fields in which the cloud adjacency effect can be considered small (the increment of the reflectance $\Delta r_{surf}\le$ 0.005). The algorithm is based on statistical simulation by the Monte Carlo method of radiation transfer in stochastic broken cloudiness with a deterministic cylindrical gap. An interpolation formula is obtained for the radius of the cloud adjacency effect that can be used for the reconstruction the ground surface reflectance in real time without calculations by the Monte Carlo method. Full article

With the spread of the use of renewable sources of energy, weather-dependent solar energy is also coming more and more to the fore. The quantity of generated electric power changes proportionally to the intensity of solar radiation. Thus, a cloudy day, for example, greatly reduces the amount of electricity produced from this energy source. In the countries of the European Union solar power plants are obligated to prepare power generation forecasts broken down to 15- or 60-min intervals. The interest of the regionally responsible transmission system operators is to be provided with forecasts with the least possible deviation from the actual figures. This paper examines the Visegrad countries’ intraday photovoltaic forecasts and their deviations from real power generation based on the photovoltaic power capacity monitored by the transmission system operators in each country. The novelty of this study lies in the fact that, in the context of monitored PV capacities in the Visegrad countries, it examines the regulation capacities needed for keeping the forecasts. After comparing the needs for positive and negative regulation, the author made deductions regarding storage possibilities complementing electrochemical regulation, based on the balance. The paper sought answers concerning the technologies required for the balancing of PV power plants in the examined countries. It was established that, as a result of photovoltaic power capacity regulation, among the four Visegrad countries, only the Hungarian transmission system operator has negative required power regulation, which could be utilized in power-to-gas plants. This power could be used to produce approximately 2.1 million Nm³ biomethane with a 98% methane content, which could be used to improve approximately 4 million Nm³ biogas of poor quality by enriching it (minimum 60% methane content), so that it can be utilized. The above process could enhance the viability of 4–6 low-methane agricultural biogas plants in Hungary. Full article

A method for determining rapid variations in atmospheric optical depth is proposed. The method is based upon computation of the ratio between close-time spectral measurements of solar direct flux. Use of the ratio avoids the need for absolute calibration of the instruments and minimizes the effects of changes in instrumental conditions (such as temperature or mechanical adjustments) and in air mass. The technique has been applied to some campaigns of measurement for sky conditions ranging from clear skies to scattered-to-broken cloudiness, performed at high frequency (~1Hz) with a system of three array spectrometers, capable of performing very rapid spectral acquisitions, in the 400 to 1700 nm band, thus covering the visible and extending to the near-infrared spectral ranges. Results demonstrate the capacity of this instrumentation and method to detect rapid variation of optical depth, as well as rapid changes in its spectral pattern. The optical depth variability depends on the particular state of the sky and is connected to particle condensation and evaporation processes and to the changes in water vapor content in the transition region between cloud-free and cloudy regions. Thus, the method is suitable for analyzing rapid processes involving particles, either aerosol or cloud droplets, and water vapor, in the cloud boundaries. Full article

FengYun-4A (FY-4A)’s Geostationary Interferometric Infrared Sounder (GIIRS) is the first hyperspectral infrared sounder on board a geostationary satellite, enabling the collection of infrared detection data with high temporal and spectral resolution. As clouds have complex spectral characteristics, and the retrieval of atmospheric profiles incorporating clouds is a significant problem, it is often necessary to undertake cloud detection before further processing procedures for cloud pixels when infrared hyperspectral data is entered into assimilation system. In this study, we proposed machine-learning-based cloud detection models using two kinds of GIIRS channel observation sets (689 channels and 38 channels) as features. Due to differences in surface cover and meteorological elements between land and sea, we chose logistic regression (lr) model for the land and extremely randomized tree (et) model for the sea respectively. Six hundred and eighty-nine channels models produced slightly higher performance (Heidke skill score (HSS) of 0.780 and false alarm rate (FAR) of 16.6% on land, HSS of 0.945 and FAR of 4.7% at sea) than 38 channels models (HSSof 0.741 and FAR of 17.7% on land, HSS of 0.912 and FAR of 7.1% at sea). By comparing visualized cloud detection results with the Himawari-8 Advanced Himawari Imager (AHI) cloud images, the proposed method has a good ability to identify clouds under circumstances such as typhoons, snow covered land, and bright broken clouds. In addition, compared with the collocated Advanced Geosynchronous Radiation Imager (AGRI)-GIIRS cloud detection method, the machine learning cloud detection method has a significant advantage in time cost. This method is not effective for the detection of partially cloudy GIIRS’s field of views, and there are limitations in the scope of spatial application. Full article

Availability of effective estimation of the power profiles of photovoltaic systems is essential for studying how to increase the share of intermittent renewable sources in the electricity mix of many countries. For this purpose, weather forecasts, together with historical data of the meteorological quantities, provide fundamental information. The weak point of the forecasts depends on variable sky conditions, when the clouds successively cover and uncover the solar disc. This causes remarkable positive and negative variations in the irradiance pattern measured at the photovoltaic (PV) site location. This paper starts from 1 to 3 days-ahead solar irradiance forecasts available during one year, with a few points for each day. These forecasts are interpolated to obtain more irradiance estimations per day. The estimated irradiance data are used to classify the sky conditions into clear, variable or cloudy. The results are compared with the outcomes of the same classification carried out with the irradiance measured in meteorological stations at two real PV sites. The occurrence of irradiance spikes in “broken cloud” conditions is identified and discussed. From the measured irradiance, the Alternating Current (AC) power injected into the grid at two PV sites is estimated by using a PV energy conversion model. The AC power errors resulting from the PV model with respect to on-site AC power measurements are shown and discussed. Full article

In this work a new gap-fill technique entitled projection transformation has been developed and used for filling missed parts of remotely sensed imagery. In general techniques for filling missed area of an image are broken down into three main categories: multi-source techniques that take the advantages of other data sources (e.g. using cloud free images to reconstruct the cloudy areas of other images); the second ones fabricate the gap areas using non-gapped parts of an image itself, this group of techniques are referred to as single-source gap-fill procedures; and third group contains methods that make up a combination of both mentioned techniques, therefore they are called hybrid gap-fill procedures. Here a new developed multi-source methodology called projection transformation for filling a simulated gapped area in the Landsat7/ETM+ imagery is introduced. The auxiliary imagery to filling the gaps is an earlier obtained L7/ETM+ imagery. Ability of the technique was evaluated from three points of view: statistical accuracy measuring, visual comparison, and post classification accuracy assessment. These evaluation indicators are compared to the results obtained from a commonly used technique by the USGS as Local Linear Histogram Matching (LLHM) [1]. Results show the superiority of our technique over LLHM in almost all aspects of accuracy. Full article