scholarly journals Improved estimation of global solar radiation over rugged terrains by the disaggregation of Satellite Applications Facility on Land Surface Analysis data (LSA SAF)

2020 ◽  
Vol 27 (4) ◽  
Author(s):  
Luca Fibbi ◽  
Fabio Maselli ◽  
Maurizio Pieri
Keyword(s):  
Solar Radiation ◽  
Surface Analysis ◽  
Land Surface ◽  
Analysis Data ◽  
Global Solar Radiation ◽  
Satellite Applications

scholarly journals 1-km-resolution land surface analysis over Japan: Impact of satellite-derived solar radiation

2015 ◽  
Vol 9 (1) ◽  
pp. 14-19 ◽  
Author(s):  
Shunji Kotsuki ◽  
Hideaki Takenaka ◽  
Kenji Tanaka ◽  
Atsushi Higuchi ◽  
Takemasa Miyoshi
Keyword(s):  
Solar Radiation ◽  
Surface Analysis ◽  
Land Surface

scholarly journals Meteosat SEVIRI Fire Radiative Power (FRP) products from the Land Surface Analysis Satellite Applications Facility (LSA SAF) – Part 1: Algorithms, product contents and analysis

2015 ◽  
Vol 15 (11) ◽  
pp. 15831-15907 ◽  
Author(s):  
M. J. Wooster ◽  
G. Roberts ◽  
P. H. Freeborn ◽  
W. Xu ◽  
Y. Govaerts ◽  
...  
Keyword(s):  
Surface Analysis ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Land Surface ◽  
Active Fire ◽  
Fire Activity ◽  
Radiative Power ◽  
Satellite Applications ◽  
The Impact ◽  
Fire Radiative Power

Abstract. Characterising changes in landscape scale fire activity at very high temporal resolution is best achieved using thermal observations of actively burning fires made from geostationary Earth observation (EO) satellites. Over the last decade or more, a series of research and/or operational "active fire" products have been developed from these types of geostationary observations, often with the aim of supporting the generation of data related to biomass burning fuel consumption and trace gas and aerosol emission fields. The Fire Radiative Power (FRP) products generated by the Land Surface Analysis Satellite Applications Facility (LSA SAF) from data collected by the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) are one such set of products, and are freely available in both near real-time and archived form. Every 15 min, the algorithms used to generate these products identify and map the location of new SEVIRI observations containing actively burning fires, and characterise their individual rates of radiative energy release (fire radiative power; FRP) that is believed proportional to rates of biomass consumption and smoke emission. The FRP-PIXEL product contains the highest spatial resolution FRP dataset, delivered for all of Europe, northern and southern Africa, and part of South America at a spatial resolution of 3 km (decreasing away from the west African sub-satellite point) at the full 15 min temporal resolution. The FRP-GRID product is an hourly summary of the FRP-PIXEL data, produced at a 5° grid cell size and including simple bias adjustments for meteorological cloud cover and for the regional underestimation of FRP caused, primarily, by the non-detection of low FRP fire pixels at SEVIRI's relatively coarse pixel size. Here we describe the enhanced geostationary Fire Thermal Anomaly (FTA) algorithm used to detect the SEVIRI active fire pixels, and detail methods used to deliver atmospherically corrected FRP information together with the per-pixel uncertainty metrics. Using scene simulations and analysis of real SEVIRI data, including from a period of Meteosat-8 "special operations", we describe some of the sensor and data pre-processing characteristics influencing fire detection and FRP uncertainty. We show that the FTA algorithm is able to discriminate actively burning fires covering down to 10−4 of a pixel, and is more sensitive to fire than algorithms used within many other widely exploited active fire products. We also find that artefacts arising from the digital filtering and geometric resampling strategies used to generate level 1.5 SEVIRI data can significantly increase FRP uncertainties in the SEVIRI active fire products, and recommend that the processing chains used for the forthcoming Meteosat Third Generation attempt to minimise the impact of these types of operations. Finally, we illustrate the information contained within the current Meteosat FRP-PIXEL and FRP-GRID products, providing example analyses for both individual fires and multi-year regional-scale fire activity. A companion paper (Roberts et al., 2015) provides a full product performance evaluation for both products, along with examples of their use for prescribing fire smoke emissions within atmospheric modelling components of the Copernicus Atmosphere Monitoring Service (CAMS).

Operational hydrology in highly steep areas: evaluation of tin-based toolchain

2020 ◽  
Author(s):  
Olga Silantyeva ◽  
John F. Burkhart ◽  
Bikas C. Bhattarai ◽  
Ola Skavhaug ◽  
Sigbjørn Helset
Keyword(s):  
Solar Radiation ◽  
Land Surface ◽  
Analysis Data ◽  
Hydrologic Modelling ◽  
Cold Environments ◽  
Direct Benefits ◽  
Inclined Surfaces ◽  
Terrain Representation ◽  
High Flexibility ◽  
University Of Oslo

<div> <div> <div> <p>Triangular Irregular Network (TIN) is known to be an efficient way to represent surface topography (Marsh et al. 2018). However, little attention has been given to assess direct benefits of the TIN-based terrain representation in operational hydrology. We connect Shyft-hydrology, a part of Shyft open-source project dedicated to distributed hydrologic modelling in operational environments, with Rasputin software intended for conversion of digital elevation models into simplified triangular meshes. Shyft is known for its high flexibility: the framework lets researcher test different functioning hypothesis with very little programming effort. We implemented new routine in Shyft-hydrology, which allows translation of solar radiation onto inclined surfaces based on (Allen et al. 2006). Thus, Shyft and Rasputin is a unique toolchain to study impact of hillslope variations in solar radiation onto snowmelt, evapotranspiration and discharge simulation.</p> <p>We conducted several experiments on subcatchments of Narayani river located in Central Nepal. This area is known to be very steep, with meteorological stations, located mainly in the low-land. The re-analysis data for the area is coarse and prone to different kind of issues (Bhattarai et al 2020). The outcomes are promising: tin-based solution outperfoms regular grid, when running with Shyft-hydrology model most used in the operations. The new model with translated radiation also works well, giving us no decrease in performance of discharge simulations, but some more insights in snow modelling. We clearly see, what we expect from observations: sunny slopes melt earlier while shady ones keep snow for longer periods.</p> <div> <div> <div> <p>Acknowledgments. This project contributes to LATICE (Land Atmosphere Interaction in Cold Environments) initiative at the University of Oslo.</p> <p>References</p> <p>Marsh, C. B., Spiteri, R. J., Pomeroy, J. W., and Wheater, H. S.: Multi-objective unstructured triangular mesh generation for use in hydro- logical and land surface models, Computers and Geo- sciences, 119, 4967, 2018.</p> <p>Richard G. Allen, Ricardo Trezza, and Masahiro Tasumi. Analytical integrated functions for daily solar radiation on slopes. Agricultural and Forest Meteorology, 139:5573, 2006.</p> <p>Bhattarai, B. C., Burkhart, J. F., Tallaksen, L. M., Xu, C.-Y., and Matt, F. N.: Evaluation of forcing datasets for hydropower inflow simulation in Nepal, Accepted for publication. Hydrology research, 2020</p> </div> </div> </div> </div> </div> </div>

scholarly journals Global Solar Radiation Forecasting using Artificial Neural Network and Support Vector Machine

2021 ◽  
Vol 2129 (1) ◽  
pp. 012079
Author(s):  
Emmanuel Philibus ◽  
Roselina Sallehuddin ◽  
Yusliza Yussof ◽  
Lizawati Mi Yusuf
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Support Vector Machine ◽  
Solar Radiation ◽  
Land Surface ◽  
Statistical Tests ◽  
Global Solar Radiation ◽  
Support Vector ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

Abstract Global solar radiation (GSoR) forecasting involves predicting future energy from the sun based on past and present data. Literature reveals that not all meteorological stations record solar radiation, some equipments are faulty, and are not available in every location due to high cost. Hence, the need to predict and forecast using predictors such as land surface temperature (LST). Satellite data when were used to complement ground-based stations have been yielding good results. Different artificial intelligence (AI) methods such as Support Vector Machine (SVM) and Artificial Neural Network (ANN) present different forecasting performances. Motivated by existing literature-related contradictions on the performance superiority of ANN and SVM in GSoR forecasting, the two techniques were compared based on several statistical tests. Experimental results show that ANN outperformed SVM by 2.9864% accuracy, making it superior in the forecast of GSoR.

scholarly journals Uwarunkowania cyrkulacyjne ilości całkowitego promieniowania słonecznego docierającego do powierzchni ziemi w Polsce w latach 1986–2015 = Atmospheric circulation determinants of the amount of global solar radiation reaching the land surface in Poland in the years 1986–2015

2020 ◽  
Vol 92 (3) ◽  
pp. 341-359
Author(s):  
Kinga Kulesza
Keyword(s):  
Spatial Distribution ◽  
Solar Radiation ◽  
Atmospheric Circulation ◽  
Land Surface ◽  
Radiant Energy ◽  
Global Solar Radiation ◽  
Circulation Type ◽  
Air Masses ◽  
Anticyclonic Circulation ◽  
Circulation Types

Solar radiation is a key element of the Earth’s climate system and one of the most important variables in the energy balance of the active surface. The inflow of radiant energy to the Earth’s surface depends on the movement (circulation) of the atmosphere and on the associated changes in the amount of aerosols contained in the atmosphere as well as on cloudiness changes (which reduce the inflow of radiation to the Earth’s surface through reflection, dispersion and absorption processes). In that context, the work detailed in this paper had as its main aim a determination of the influence of atmospheric circulation on the amount of global solar radiation reaching the land surface in Poland. The research was based on source material from 1986–2015, originating from meteorological reanalyses and satellite products. Global solar radiation was analysed based on data from CM SAF satellite products, while atmospheric circulation types were designated with the use of modified version of the Lityński’s classification. Mean daily sums of radiation during individual circulation types, during A, 0, C macrotypes and on days with advection from particular directions were presented. Also the spatial distribution of radiation over the area of Poland during individual circulation types was shown. In the analyses special attention was paid to days with extremely large sums of solar radiation (above the 0.95 percentile). The largest daily sums of solar radiation are connected with anticyclonic circulation types, and the smallest ones – with cyclonic types. The largest mean daily sum of solar radiation occurs during south-western anticyclonic circulation, which is related to the significantly expanded Azores High. The smallest daily sums of solar radiation occur during cyclonic types, with advection of air masses from the north and east – in spring during NWC type, in autumn during EC type, in summer and winter during NEC type. The spatial distribution of solar radiation daily sums over the territory of Poland also depends on the circulation type. For most of the year, the circulation types with the northern and eastern components (N-NE-E) are associated with the reduction of the amount of solar radiation from north to south, while the inflow of air masses from the S-SW-W directions favours the reduction of radiation from south to north. Extremely large sums of solar radiation occur most probably during anticyclonic types with advection of air masses from SW, S and SE, and during the advectionless circulation 0A (conditional probability 0.13, 0.13, 0.11 and 0.10 respectively). The paper also demonstrates that the circulation type (i.e. prevailing pressure system) has a greater influence on daily sums of global solar radiation over Poland than the direction of air masses advection. The research results show that atmospheric circulation plays a significant role in determining the amount of solar radiation reaching the land surface in Poland.

scholarly journals Detrended Multiple Cross-Correlation Coefficient applied to solar radiation, air temperature and relative humidity

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Andrea de Almeida Brito ◽  
Heráclio Alves de Araújo ◽  
Gilney Figueira Zebende
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Solar Energy ◽  
Correlation Coefficient ◽  
Air Temperature ◽  
Cross Correlation ◽  
Global Solar Radiation ◽  
Meteorological Variables ◽  
Hourly Data ◽  
Cross Correlations

AbstractDue to the importance of generating energy sustainably, with the Sun being a large solar power plant for the Earth, we study the cross-correlations between the main meteorological variables (global solar radiation, air temperature, and relative air humidity) from a global cross-correlation perspective to efficiently capture solar energy. This is done initially between pairs of these variables, with the Detrended Cross-Correlation Coefficient, ρDCCA, and subsequently with the recently developed Multiple Detrended Cross-Correlation Coefficient, $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}$$DMCx2. We use the hourly data from three meteorological stations of the Brazilian Institute of Meteorology located in the state of Bahia (Brazil). Initially, with the original data, we set up a color map for each variable to show the time dynamics. After, ρDCCA was calculated, thus obtaining a positive value between the global solar radiation and air temperature, and a negative value between the global solar radiation and air relative humidity, for all time scales. Finally, for the first time, was applied $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}$$DMCx2 to analyze cross-correlations between three meteorological variables at the same time. On taking the global radiation as the dependent variable, and assuming that $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}={\bf{1}}$$DMCx2=1 (which varies from 0 to 1) is the ideal value for the capture of solar energy, our analysis finds some patterns (differences) involving these meteorological stations with a high intensity of annual solar radiation.

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