Surface Insolation Research Articles

Impact of an unprecedented marine heatwave on extremely hot summer over Northern Japan in 2023

Possible local influence of an extreme marine heatwave is investigated on unprecedentedly hot summer around northern Japan in 2023. Sea-surface temperatures (SSTs) and subsurface ocean temperatures around northern Japan were also unprecedentedly high in the summer. This was especially the case off the east coast of Japan, where cool Oyashio water was replaced with much warmer water due to a striking poleward meander of the Kuroshio Extension persistent from the spring. Particularly amplified near-surface air temperature anomalies and even stronger warm anomalies in the subsurface ocean suggest that the marine heatwave acted to sustain the atmospheric heatwave. Anomalous upward of latent and sensible heat fluxes from the warmed sea surface are indicative of local oceanic impact. The warm SST anomalies reduced the lower-tropospheric stratification to maintain unfavourable condition for low-level cloud formation, which in turn led to increased surface insolation for further SST warming as positive feedback. The increased moisture in the warmed lower troposphere contributed to the enhanced surface downward longwave radiation. This enhanced greenhouse effect acted not only as positive feedback on the warm SST anomalies that increased evaporation but also as a contributor for the extreme warmth over northern Japan landmass.

Impacts of the Madden‐Julian Oscillation on Marginal Sea Heatwaves of the Southeastern Tropical Indian Ocean

AbstractMarginal seas of the southeastern tropical Indian Ocean (SETIO), including the South Java coasts and the Timor and Arafura Seas, are hotspots of large‐scale marine heatwaves (MHWs) in austral summer with notable impacts on local ecosystems. Yet, the prediction of these MHWs remains challenging. By analyzing 39 MHWs and 45 marine cold‐spells (MCSs) observed in the summers of 1982–2021, this study reveals a robust modulation effect of the Madden‐Julian Oscillation (MJO) on these events. The results show that 56% of MHWs and 51% of MCSs overlapped with MJO events, and their duration is systematically longer than others. Moreover, MHWs in phases 3–4 and MCSs in phases 6–7 of the real‐time multivariate MJO (RMM) index were nearly 2–3 times stronger in intensity than the others. The passage of MJOs drives prominent intraseasonal sea surface temperature (SST) variability in the SETIO through perturbing surface heat fluxes, which in turn modulates the occurrence of MHWs and MCSs. During RMM phases 1–2 (convective center over of the east of Africa or the central‐western Indian Ocean), the SETIO is controlled by a dry condition, with increased surface insolation and suppressed latent heat release. These anomalous fluxes drive a persistent SST increase, facilitating the emergence of strong and prolonged MHWs in the subsequent RMM phases 3–4. Further analysis suggests an 18% probability for MHWs in the SETIO 12 ± 10 days after Phase 1. Therefore, the MJO contributes to the predictability of MHWs/MCSs of the SETIO, with implications for predicting climate extremes and hazards.

Surface and Atmospheric Heating Responses to Spectrally Resolved Albedo of Frozen and Liquid Water Surfaces

AbstractMultiple Earth system models (ESMs) discretize surface albedo into two semi‐broadbands comprising the UV/visible and near‐infrared (NIR) wavelengths. Here, we use an offline single‐column radiative transfer model to investigate the radiative effects of spectrally resolving the surface albedo. We use the Snow, Ice, and Aerosol Radiative model, extended to simulate liquid water, to calculate snow, ice, and liquid water albedo. We flux‐weight the hyperspectral albedo into the coarser spectral bands used by the atmospheric shortwave radiative transfer model. We establish representative atmospheric profiles for the three surface types and compare their shortwave fluxes and atmospheric warming rates with the spectrally resolved albedo to those calculated with the semi‐broadband approximation. Spectrally resolved surface albedo over snow and ice reduces atmospheric warming by darkening the albedo of NIR bands, correcting the too‐strong surface absorption in visible bands, and too‐weak surface absorption in shortwave infrared bands caused by the semi‐broadband approximation. We explore the effects on surface and atmospheric warming rates of varying solar zenith angle, cloud cover, relative humidity, and snow grain/air bubble radii. The semi‐broadband albedo biases can exceed 10% and 2% for the surface and atmospheric net flux respectively, being particularly strong under conditions which alter the distributions of surface insolation (i.e., cloud cover or increased atmospheric water vapor). These results show that transmitting a higher resolution spectral radiation field between the atmosphere and surface reduces biases in surface absorption and atmospheric heating present in ESMs that currently use the semi‐broadband approximation.

Jovian Sodium Nebula and Io Plasma Torus S+ and Brightnesses 2017–2023: Insights Into Volcanic Versus Sublimation Supply

AbstractWe present first results derived from the largest collection of contemporaneously recorded Jovian sodium nebula and Io plasma torus in [S II] 6731 Å images assembled to date. The data were recorded by the Planetary Science Institute's Io Input/Output observatory and provide important context to Io geologic and atmospheric studies as well as the Juno mission and supporting observations. Enhancements in the observed emission are common, typically lasting 1–3 months, such that the average flux of material from Io is determined by the enhancements, not any quiescent state. The enhancements are not seen at periodicities associated with modulation in solar insolation of Io's surface, thus physical process(es) other than insolation‐driven sublimation must ultimately drive the bulk of Io's atmospheric escape. We suggest that geologic activity, likely involving volcanic plumes, drives escape.

Three Centuries of Snowpack Decline at an Alpine Pass Revealed by Cosmogenic Paleothermometry and Luminescence Photochronometry

AbstractThe spatial and temporal distribution of Alpine snow is a sensitive gauge of environmental change. While understanding past snow dynamics is essential for reconstructing past climate and forecasting future trends, reliable snowpack data prior to the instrumental record are scarce. We present a novel pairing of cosmogenic paleothermometry and luminescence photochronometry which constrain the temperature and insolation history of bedrock outcrops at the Gotthard Pass, Switzerland, over the last ∼15,000 years. By coupling these results with cosmogenic 14C‐10Be chronology and modern in situ rock thermometry, we infer a ∼70‐day reduction of snowpack at the topographic mid‐slope. Our data indicate stable environmental conditions throughout the Holocene, followed by a 6.6 ± 2.9°C increase of ground surface temperature, coeval with an order‐of‐magnitude or more increase in ground surface insolation. Bracketing the onset of these changes between 1504 and 1807 CE, our findings tie the snowpack decline with the onset of human industrialization.

India’s photovoltaic potential amidst air pollution and land constraints

India aims for ambitious solar energy goal to fulfill its climate commitment but there are limited studies on solar resource assessment considering both environmental and land availability constraints. The present work attempts to address this issue using satellite-derived air pollution, radiation, and land use data over the Indian region. Surface insolation over India has been decreasing at a rate of -0.29± 0.19 Wm-2 y-1 between 2001 and 2018. Solar resources over nearly 98%, 40%, and 39% of the Indian landmass are significantly impacted by aerosols, clouds, and both aerosols and clouds respectively. Only 29.3% of the Indian landmass is presently suitable for effective solar photovoltaic harnessing, but this is further declining by -0.21% annually, causing a presumptive loss of 50 GW solar potential, translating 75 TWh power generation. Lowering two decades of aerosol burden can make 8% additional landmass apt for photovoltaic use. Alleviating aerosol-induced dimming can fast-track India's solar energy expansion.

Сравнительная устойчивость биологических свойств почв разных типов Западного Кавказа к рубкам и пожарам

Soils and soil cover in the middle and low mountains of the Western Caucasus are significantly changed as a result of forest destruction. The causes of forest vegetation degradation can be logging, fires and windthrow. Initial soil alteration may be different: soil mixing and scalping during logging and skidding, pyrogenic impact, windthrow with plant roots, etc., as well as other factors. Further evolution of post-forest soils in the absence or weak erosion follows a similar scenario. The driving force is increased insolation of soil surface at elimination of closed tree crowns, which leads to changes in microclimate and regenerative successions. Changes in soil composition and properties persist for years and decades. The most dynamic and informative are biological parameters, which allow to quickly and effectively assess the ecological state of degraded soils. Generalization of long-term results obtained using an integral indicator of the biological state of soils allowed us to determine the comparative resistance of soils of different types and ecosystems to degradation (fires and logging). In the conditions of the Western Caucasus, biological activity of post-forest ecosystems and soils decreases in the series: Greyic Phaeozem Vertic > Cambisols Cromic ≥ Greyic Phaeozem Eutric ≥ Rendzik Leptosols > Cambisols Dystric. Keywords: ANTHROPOGENIC IMPACT, LOGGING, FIRES, BIOINDICATION, BIOLOGICAL ACTIVITY, ENZYME ACTIVITY

Improvement of Korea Meteorological Administration Solar Energy Resources Map Using Fine-Scale Terrain Data

Real-time solar energy resources mapping is crucial for the development and management of solar power facilities. This study analyzes the effects of the digital elevation model (DEM) resolution on the accuracy of the surface insolation (insolation hereafter) calculated by the Korea Meteorological Administration solar energy mapping system, KMAP-Solar, using two DEMs of different resolutions, 1.5 km and 100 m. It is found that KMAP-Solar yields smaller land-mean insolation with the fine-scale DEM than the coarse-scale DEM. The fine-scale DEM reduces biases by as much as 32 Wm− 2 for all observation sites, especially those in complex terrain and that the insolation error reduction is correlated with the difference in sky view factor (SVF) between the coarse- and fine-scale DEM. Both the coarse- and fine-scale DEMs generate the insolation-elevation and insolation-SVF relationship which is characterized by positive (negative) correlation between the insolation and the terrain altitude (SVF). However, the coarse-scale DEM substantially underestimates these relationships compared to the fine-scale DEM, mainly because the coarse-scale DEM underrepresents large terrain slopes and/or small SVFs, most seriously in high-altitude regions. The fine-scale DEM generates a more realistic insolation distribution than the coarse-scale DEM by incorporating a wider range of key terrain parameters involved in determining insolation. Improvements of insolation calculations in KMAP-Solar using a fine-scale DEM, especially in the areas of complex terrain, is of a practical value for Korea because the operational solar resources map from KMAP-Solar supports solar energy research, solar power plant installations, and real-time prediction and management of solar power within the power grid.

Projected patterns of climate change impact on photovoltaic energy potential: A case study of Iraq

Ambitious plans for the decarbonization of the global energy system necessitate the scaling up of renewable energy exploitation. This could render the energy supply system more susceptible to the effects of climate change as most renewables are climate-dependent by nature. Therefore, understanding the consequences of climate change on renewable energy systems at a regional level plays an important role in the financial management, process optimization, and energy yield assessment of these systems. In this work, the key objective is to examine the projected impacts of surface insolation and temperature fluctuations on the future photovoltaic (PV) energy potentials in Iraq. Projections are quantified across two climate scenarios, RCP4.5 and RCP8.5, which represent the intermediate and worst-case scenarios in which insolation will rise by 4.5 and 8.5 W/m2 by the beginning of the next century. The results show that the average temperature across the country is anticipated to rise by 1.5 °C and 2.4 °C under RCP4.5 and RCP8.5, respectively. The results also show that the change in solar PV potential relative to current climatic conditions, would be −0.3 to 8.1% under RCP4.5 while it is −5.1 to 6.3% under RCP8.5 by the beginning of the next century. The highest potentials are predicted in the western parts, and the greatest drops are in the southeastern parts. Temporal stability of PV potentials also appears to be little affected by future climatic scenarios, with some southern parts even indicating a little positive rise. So, even though climate change is expected to cause small drops in PV output in some areas, it is unlikely to pose a danger under RCP4.5 to PV productivity in Iraq.

High-resolution regional climate modeling of warm-season precipitation over the Tibetan Plateau: Impact of grid spacing and convective parameterization

The Tibetan Plateau (TP) features high elevation and complex terrain, which together shape the region's unique precipitation with high spatial heterogeneity and strong diurnal variations. Due to low spatial resolution, deficient convective parameterization (CP) and uncertainties in other physical assumptions, global climate models and traditional regional models tend to produce excessive precipitation with an earlier diurnal timing. In this work, two sets of numerical experiments with 4- and 10-km grid spacing, respectively, were performed using the Weather Research and Forecasting model to simulate the seasonal precipitation for an average warm season (April–September 2017) over the TP. Results showed that the 4-km experiment with microphysics only (i.e., without CP) reproduced the precipitation amount, frequency, intensity and diurnal cycle reasonably well on regional and local scales, as well as the nocturnal propagating convection at the lee side. The 10-km experiments with scale-aware CP schemes significantly overestimated the precipitation amount and frequency, underestimated the intensity, and failed to capture the diurnal propagation signature. The 10-km experiment with microphysics only had the poorest skill in representing the spatial distribution of precipitation. The scale-aware CP schemes on the 4-km grid caused a too-frequent occurrence of light precipitation even though their overall contribution to the total precipitation amount was rather small, and thus had little benefit to the model performance. A common deficiency in all experiments was excessive afternoon precipitation across the high elevation of the central Himalaya possibly due to the excessive surface insolation, but the satellite-based data may not accurately capture the afternoon precipitation. This research highlights the value of the 4-km model (the so-called convection-permitting model) and the limited benefit of the tested convective parameterizations over the TP.

Warming Trend and Cloud Responses over the Indochina Peninsula during Monsoon Transition

An exacerbated precipitation–temperature relationship can lead to compound extremes. The role of clouds in such a relationship is relatively uncertain. Here, we investigate the cloud–precipitation–temperature relationships over the Indochina Peninsula during the summer monsoon transition. The negative correlation between cloudiness/precipitation and surface maximum temperature is valid on seasonal and interannual timescales. The near-surface temperature exhibits interdecadal variability and a long-term warming trend. The warming trend has accelerated in the past two decades. In the anomalous warm years, the remarkably strong western Pacific subtropical high inhibits the development of clouds, especially the middle and high cloud-top regimes, leading to the suppression of deep convection and precipitation. There are more optically thin (moderate to thick) clouds with smaller (larger) effective radii in the high cloud-top regime for the warm (cold) years. The dominance of shallow cumulus is a distinct feature in the warm years. The daytime heating of enhanced surface insolation due to decreased cloudiness is worsened by the dry condition of the precipitation deficit. The water vapor warming effect can prevent an efficient drop in nighttime temperature, thereby exacerbating the warm condition under the warming trend. The cloud–precipitation–temperature relationships coupling with the monsoon development can be used to diagnose the regional scale cloud–climate interactions in climate models.

The Influence of Intraseasonal Oscillations on Humid Heat in the Persian Gulf and South Asia

Abstract Humans’ essential ability to combat heat stress through sweat-based evaporative cooling is modulated by ambient air temperature and humidity, making humid heat a critical factor for human health. In this study, we relate the occurrence of extreme humid heat in two focus regions to two related modes of intraseasonal climate variability: the Madden–Julian oscillation (MJO) and the boreal summer intraseasonal oscillation (BSISO). In the Persian Gulf and South Asia during the May–June and July–August seasons, wet-bulb temperatures of 28°C are found to be almost twice as likely during certain oscillation phases than in others. Variations in moisture are found, to varying degrees, to be an important ingredient in anomalously high wet-bulb temperatures in all three areas studied, influenced by distinct local circulation anomalies. In the Persian Gulf, weakening of climatological winds associated with the intraseasonal oscillation’s propagating center of convection allows for anomalous onshore advection of humid air. Anomalously high wet-bulb temperatures in the northwestern region of South Asia are closely aligned with positive specific humidity anomalies associated with the convectively active phase of the oscillation. On the southeastern coast of India, high wet-bulb temperatures are associated with convectively inactive phases of the intraseasonal oscillation, suggesting that they may be driven by increased surface insolation and reduced evaporative cooling during monsoon breaks. Our results aid in building a foundation for subseasonal predictions of extreme humid heat in regions where it is highly impactful. Significance Statement Understanding when and why extreme humid heat occurs is essential for informing public health efforts protecting against heat stress. This analysis works to improve our understanding of humid heat variability in two at-risk regions, the Persian Gulf and South Asia. By exploring how subseasonal oscillations affect daily extreme events, this analysis helps bridge the prediction gap between weather and climate. We find that extreme humid heat is more than twice as likely during specific phases of these oscillations than in others. Extremes depend to different extents upon combinations of above-average temperature and humidity. This new knowledge of the regional drivers of humid heat variability is important to better prepare for the increasingly widespread health and socioeconomic impacts of heat stress.

Time series analysis of temperatures and insolation of the Earth's surface at Kara-Dag using satellite observation

This article discusses the results of a numerical analysis of the time series of the surface temperature, air temperature at a height of 2 m, as well as the total insolation falling to the earth at the Kara-Dag point over the past 38 years. Statistical analysis of observations and continuous time-frequency wavelet analysis are performed. Models of seasonal fluctuations in three time series of observations are compared. Coherent fluctuations were established between variations in total insolation data and data variations: of length of the day (LOD) (the period of variations is 11.8 years, the square of the coherence modulus is 0.85); of solar activity (the period of variations is 10.5 years, the squared modulus of coherence is 0.8; and the period of variations is 3.6 years, the squared modulus of coherence is 0.85); of global temperature indices (the period of variations is 2.3 years, the squared modulus of coherence is 0.7; and the period of variations is 3.5 years, the squared modulus of coherence is 0.9), respectively. The time evolution of observations in order to detect signs of chaotic oscillations is discussed.

Brown Carbon Fuel and Emission Source Attributions to Global Snow Darkening Effect

AbstractSnow and ice albedo reduction due to deposition of absorbing particles (snow darkening effect [SDE]) warms the Earth system and is largely attributed to black carbon (BC) and dust. Absorbing organic aerosol (BrC) also contributes to SDE but has received less attention due to uncertainty and challenges in model representation. This work incorporates the SDE of absorbing organic aerosol (BrC) from biomass burning and biofuel sources into the Snow Ice and Aerosol Radiative (SNICAR) model within a variant of the Community Earth System Model. Additionally, 12 different emission regions of BrC and BC from biomass burning and biofuel sources are tagged to quantify the relative contribution to global and regional SDE. BrC global SDE (0.021–0.056 Wm−2 over land area and 0.0061–0.016 Wm−2 over global area) is larger than other model estimates, corresponding to 37%–98% of the SDE from BC. When compared to observations, BrC simulations have a range in median bias (−2.5% to +21%), with better agreement in the simulations that include BrC photochemical bleaching. The largest relative contributions to global BrC SDE are traced to Northern Asia (23%–31%), Southeast Asia (16%–21%), and South Africa (13%–17%). Transport from Southeast Asia contributes nearly half of the regional BrC SDE in Antarctica (0.084–0.3 Wm−2), which is the largest regional input to global BrC SDE. Lower latitude BrC SDE is correlated with snowmelt, in‐snow BrC concentrations, and snow cover fraction, while polar BrC SDE is correlated with surface insolation and snowmelt. This indicates the importance of in‐snow processes and snow feedbacks on modeled BrC SDE.

ANALYSIS OF TEMPERATURE REGIME OF LAND SURFACE FOR BYSTRYTSIA RIVER BASIN AND THE INFLUENCE OF TERRAIN ATTRIBUTES USING LANDSAT 8 DATA

Terrain morphology is a powerful factor influencing climate characteristics, which manifests itself at various scale levels. At the detailed scale, this effect is mainly due to the redistribution of solar radiation on surfaces and slopes of different slope and aspect, which causes their unequal heating, and local redistribution of air masses. Spatial distribution of land surface temperatures can be effectively studied using remote sensing data in far-infrared range, which can be recalculated into temperature values. The values of the land surface temperature in the Bystrytsia river basin were calculated with far-infrared channels of Landsat spatial images for three time slices: October 5, 2013, February 13, 2015, August 10, 2016. The statistical analysis has been carried out on the impact of terrain morphometric parameters and land surface type and characteristics on its temperature. To determine the relative influence of each specific factor, the method of hierarchical partitioning has been implemented with the hier.part package of R software environment. Significant seasonal differentiation of the influence of individual factors on temperature was revealed. During all the seasons of the year, absolute height appeared as the most significant factor among those analyzed. The influence of absolute height on temperature distribution was the strongest in autumn, somewhat weaker in winter and the weakest in summer. Artificial surfaces, dry grass and soil were heated more strongly despite their lower albedo due to smaller heat consumption by evaporation, whereas vegetation surface and wet soils were less heated. On the other hand, the influence of relative surface insolation, being differentiated by terrain elements appeared to be relatively weaker, which can be explained by the calculation method used (insolation has been calculated for the moment the images were taken, whereas surface heating takes some time). The influence of the level of surface moisture also appeared to be significant. Key words: land surface temperature, Landsat, Bystrytsia, morphometric parameters, hierarchical partitioning.

Analysing the day/night seasonal and annual changes and trends in land surface temperature and surface urban heat island intensity (SUHII) for Indian cities

• Day/night seasonal and annual changes and trends (2001- 2018) in land surface temperature and surface urban heat island intensity (SUHII) for Indian cities (Lucknow, Kolkata and Pune). • Nighttime LST is a better indicator to study the urban heating effect due to its sensitivity towards urbanization. • Positive trends in mean annual daytime (0.003 to 0.059 °C/year) and nighttime (0.030 to 0.078 °C/year) LST are observed in all cities, except in Pune where urban cooling occurs during daytime. • Nighttime SUHII is positive for all cities with mean annual SUHII ranging from 1.34 to 2.07 °C. Understanding the patterns and possible causes of urban heat islands (UHI) effect due to urbanisation-induced anthropogenic activities is an important area in urban climatic research. Few studies on long-term thermal behaviour of Indian cities are available in the literature. Towards this, the present study investigates the day/night seasonal and annual changes and trends in land surface temperature (LST) and surface urban heat island intensity (SUHII) during the last two decades for three Indian cities (Lucknow, Kolkata and Pune) with distinct urban, physiographic and climatic setting. Moderate Resolution Imaging Spectroradiometer (MODIS) LST data products acquired during daytime and nighttime from 2001 to 2018 are processed and analysed for this purpose. MODIS-based aerosol optical depth (AOD) and normalised difference vegetation index (NDVI) products are used to understand the plausible reasons of change in LST and SUHII patterns. The urban (contiguous built-up) and non-urban (surrounding rural) areas are delineated by applying city clustering algorithm on MODIS Land Cover datasets of 500 m spatial resolution. Mann-Kendall and Seasonal-Kendall tests along with Theil-Sen estimator are used for trend analysis. The findings show that the diurnal temperature range (DTR) has decreased from 2001 to 2018 due to higher increase in nighttime LST as compared to daytime. Nighttime LST is a better indicator to study the urban heating effect due to its sensitivity towards urbanisation. Positive trends in mean annual daytime (0.003 to 0.059 °C/year) and nighttime (0.030 to 0.078 °C/year) LST are observed in all cities, except in Pune where urban cooling occurs during daytime. Increase in aerosol loading (with consequent decrease in air temperature and surface insolation) and vegetative cover over time are attributed as the primary reasons of urban cooling effect in Pune during daytime. Seasonal analysis indicate high warming rates during monsoon and summer seasons, particularly during nighttime (0.062 to 0.1 °C/year). Nighttime SUHII is positive for all cities with mean annual SUHII ranging from 1.34 to 2.07 °C. Statistically significant ( p <0.01) increasing trends are observed in mean annual SUHII (0.009 °C/year to 0.022 °C/year) for Kolkata and Pune. Decreasing trend in SUHII is observed over Lucknow due to higher rate of increase in LST in non-urban area as compared to urban area. The study highlights that geographical, physiographic and climatic setting along with anthropogenic processes in urban and its surrounding non-urban areas are critical towards understanding the causative factors in exacerbating the phenomenon of urban heating.

Evaluation of atmosphere clearness and cloudiness parameters in the southern regions of Ukraine using statistical analysis

Introduction. This paper deals with the specific aspects of insolation of the terrestrial surface in the southern regions of Ukraine, namely the clearness index and diffuse fraction of the atmosphere. The study was based on satellite data of the average daily insolation and total cloudiness in the nodes of the two-degree grid for the domain with coordinates 48°-45° N and 29°-39° E for the period of 1981-2020. The purpose of article. The purpose was to develop statistic models of horizontal surface insolation for various locations of study domain. Main focus was put on special characteristics in conditions of fixed cloudiness. Satellite data for the summer season had been used to evaluate the maximum solar energy potential of Ukraine. Methods. Application statistical analysis and means of cartographic data layout were used in the paper. Results. It was found that with the highest (more than 50%) frequency the total cloud cover can be characterized by the atmosphere clarity corresponding to a clear sky condition. The significance of irradiation of the terrestrial surface with diffuse solar radiation has been observed, with the share of such radiation in the global irradiation (diffuse ratio) being closely inversely related to the clearness index (correlation about -0.97). In turn, both diffuse ratio and clearness index are statistically dependent on the sky clarity, that allowed deriving analytical functions - diffuse ratio and clearness index - of the sky clarity, which appeared to be S- and Z-shaped curves, respectively. Dispersion of the clearness index ( ) and the diffuse fraction ( ) values and the strength of their statistical relationship significantly depend on the sky clarity. The empirical distribution of the two-dimensional random variable ( ; ) well meets the Gaussian distribution, and the obtained dispersion ellipses allowed calculating the confidence intervals of the two-dimensional random variable (clearness index: diffuse fraction) for a given confidence level. The spatial distribution of the clearness index and diffuse fraction of the atmosphere in the southern regions of Ukraine revealed a significant dependence of these indices on the latitude and the type of underlying surface. At the end of the summer a seasonal effect has been observed in the spatial distribution of the clearness index and diffuse fraction, which can be explained by the specific seasonal features of atmospheric circulation, caused by the spreading out of the eastern ridge of the Azores anticyclone and the general situation with blocking developments in the Atlantic-European sector of the Northern Hemisphere. The scientific novelty. Correlation and regression models of special insolation characteristics in conditions of various cloudiness that are represented in this paper are new to Ukraine. Analysis of two-dimensional random value spread (clearness index: cloudiness index) allowed to assess probabilities of integral solar radiation flows. The obtained analytical membership functions for monthly average values of clearness and cloudiness indices depending on the level of sky clarity proved to be applicable for determining respective indices for daily time scale. Practical significance. The obtained results are important for comprehensive assessment of the solar / photovoltaic resources of southern regions of Ukraine. Specifically, analytical dependences have practical values for the purpose of forecasting direct and diffuse solar radiation in various time scales based on publically available global records of solar radiation.

The Impact of Variable Horizon Shade on the Growing Season Energy Budget of a Subalpine Headwater Wetland

Surface energy budgets are important to the ecohydrology of complex terrain, where land surfaces cycle in and out of shadows creating distinct microclimates. Shading in such environments can help regulate downstream flow over the course of a growing season, but our knowledge on how shadows impact the energy budget and consequently ecohydrology in montane ecosystems is very limited. We investigated the influence of horizon shade on the surface energy fluxes of a subalpine headwater wetland in the Canadian Rocky Mountains during the growing season. During the study, surface insolation decreased by 60% (32% due to evolving horizon shade and 28% from seasonality). The influence of shade on the energy budget varied between two distinct periods: (1) Stable Shade, when horizon shade was constant and reduced sunlight by 2 h per day; and (2) Dynamic Shade, when shade increased and reduced sunlight by 0.18 h more each day, equivalent to a 13% reduction in incoming shortwave radiation and 16% in net radiation. Latent heat flux, the dominant energy flux at our site, varied temporally because of changes in incoming radiation, atmospheric demand, soil moisture and shade. Horizon shade controlled soil moisture at our site by prolonging snowmelt and reducing evapotranspiration in the late growing season, resulting in increased water storage capacity compared to other mountain wetlands. With the mounting risk of climate-change-driven severe spring flooding and late season droughts downstream of mountain headwaters, shaded subalpine wetlands provide important ecohydrological and mitigation services that are worthy of further study and mapping. This will help us better understand and protect mountain and prairie water resources.

Vertical distributions and columnar properties of the aerosols during different seasons over Kattankulathur (12.82oN, 80.04oE): A semi-urban tropical coastal station

Seasonal characteristics of the aerosols over Kattankulathur (12.83° N, 80.04° E) is studied using Micro Pulse Lidar observations during 2016–2018 and Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observation, Moderate Resolution Imaging Spectroradiometer and Ozone Monitoring Instrument datasets during 2006–2018. The vertical distribution of the aerosols is characterized as the steep decrease with altitude nearly exponentially up to 2–3 km during the northeast (NE) monsoon and winter seasons mainly dominated by clear marine and polluted continental aerosols. While it gradually decreases with altitude up to 4–5 km during pre-monsoon and southwest monsoon (SW) seasons mainly dominated by dust aerosols. The mean aerosol loadings near the surface are ~0.38 km−1 during NE monsoon and winter, ~0.30 km−1 pre-monsoon, and 0.22 km−1 during SW monsoon seasons. Such difference in the seasonal distribution of aerosol loading is mainly attributed to the difference in surface insolation, convection, long-range transport, and the atmospheric boundary layer (ABL) structure and dynamics. The ABL contributes 61%, 46%, 38%, and 63% of the overall aerosol optical depth (AOD) during the winter, pre-monsoon, SW monsoon, and NE monsoon seasons, respectively. The AOD shows a substantial seasonal variation with two local maxima during May and October and minima during January and July. The maximum and minimum AOD is found to be ~0.59 ± 0.16 and 0.4 ± 0.05, respectively. The Angstrom exponent (AE) (fine mode fraction (FMF)) shows a marked seasonal variation with a maximum value of 0.84 (0.60), indicating the dominance of finer particles during winter and minimum value of 0.54 (0.27), indicating dominance coarse particles during SW monsoon. The AE and UV aerosol index values suggest that Kattankulathur is mainly characterized by large-sized absorbing aerosols (30%) such as dust mixture and sea salt particles. Small-sized non-absorbing aerosols such as biogenic aerosols are rarely (<1%) observed.

Оптимизация методом роя частиц структуры автономного энергетического комплекса с использованием солнечной энергии

The aim of the study involved the development of a methodology for optimising the structure of an autonomous energy complex consisting of photovoltaic panels, accumulator batteries and a diesel generator, as well as its implementation in a software and computer complex. In order to optimise the structure of the complex, a particle swarm method was used that does not require the exact gradient of the optimisation function to be known. In terms of an optimisation function, the cost price of the electricity generated by the energy complex was chosen. During the optimisation process, changes in the consumer load demand, local actinometric and meteorological conditions, as well as technical characteristics of photovoltaic panels and batteries were taken into account. Additionally, a choice of three following options for installing photovoltaic panels relative to the horizon is provided: horizontally; inclined to the horizon; inclined to the horizon on a rotary uniaxial base with a vertical rotation axis using a sun tracking system (selecting an angle of inclination equal to the latitude). For Kyzyl-Khaya village in the Republic of Tyva, currently supplied from a diesel power station, the average monthly values of horizontal surface insolation are calculated with the total installed capacity of the power generating elements for an autonomous energy complex optimised by the particle swarm method equal to 450.1 kW and having a battery capacity of 22.2 kA×h. The developed technique for optimising the structure of the energy complex is implemented in the MATLAB software environment. Following optimisation by the proposed methodology, the structure of an autonomous energy complex with an inclined arrangement of photovoltaic panels, the cost of electricity generated by it amounted to 26.978 roubles/kW h with a capital cost of 16956.853 thousand roubles. This optimised structure of the complex provides for changing the power supply schedule from 18 to 24 hours a day and additional possible reduction in diesel fuel consumption by 70% compared to the same setup having an 18-hour power supply schedule from a diesel power plant.