Influential Climatic Factors Research Articles

Response of Hydrothermal Conditions to the Saturation Values of Forest Aboveground Biomass Estimation by Remote Sensing in Yunnan Province, China

Identifying the key climate variables affecting optical saturation values (OSVs) in forest aboveground biomass (AGB) estimation using optical remote sensing is crucial for analyzing OSV changes. This can improve AGB estimation accuracy by addressing the uncertainties associated with optical saturation. In this study, Pinus yunnanensis forests and Landsat 8 OLI imagery from Yunnan were used as case studies to explain this issue. The spherical model was applied to determine the OSVs using specific spectral bands (Blue, Green, Red, Near-Infrared (NIR), and Short-Wave Infrared Band 2 (SWIR2)) derived from Landsat 8 OLI imagery. Canonical correlation analysis (CCA) uncovered the intricate relationships between climatic variables and OSV variations. The results reveal the following: (1) All Landsat 8 OLI spectral bands showed a negative correlation with the Pinus yunnanensis forest AGB, with OSVs ranging from 104.42 t/ha to 209.11 t/ha, peaking in the southwestern region and declining to the lowest levels in the southeastern region. (2) CCA effectively explained 93.2% of the OSV variations, identifying annual mean temperature (AMT) as the most influential climatic factor. Additionally, the mean temperature of the wettest quarter (MTQ) and annual precipitation (ANP) were significant secondary determinants, with higher OSV values observed in warmer, more humid areas. These findings offer important insights into climate-driven OSV variations, reducing uncertainty in forest AGB estimation and enhancing the precision of AGB estimations in future research.

Expanding the boundaries in the face of global warming: A lesson from genetic and ecological niche studies of Centaurium erythraea in Europe

Climate change affects plant species, especially those with restricted ecology and distribution. Centaurium erythraea is a flowering plant species in the Gentianaceae family, native to Europe, with its centre of diversity in the Mediterranean and western Asia. Of the 11 infraspecific taxa distinct from C. erythraea, only two are common in Europe: C. erythraea subsp. erythraea (widespread nominal subspecies) and C. erythraea subsp. majus (mainly distributed in the western Mediterranean region). Freshly collected samples of 36 plants from 11 localities across Lower Silesia (Central Europe) were utilised for taxonomic and genetic analysis. The barcode sequences of chloroplast DNA region matK were used for molecular analysis. Data deposited in GenBank was also used. Five haplotypes were identified among the analysed specimens. Species Distribution Modelling (SDM) techniques were applied to predict the current and future (short- and long-term projections) potential distribution of C. erythraea subsp. majus and to identify the most influential climatic factors. Despite the typical Mediterranean distribution, the presence of C. erythraea subsp. majus outside its natural range in SW Poland has been confirmed by morphological and genetic studies. The mean monthly precipitation of the wettest quarter and the mean daily temperatures of the warmest quarter were identified as the key climatic factors. Short-term scenarios suggest that C. erythraea subsp. majus will maintain most of its current suitable habitats and potentially expand into the lowlands of Central Europe. However, long-term projections indicate a potential reduction in its currently suitable areas, especially in the southern parts of its range, with a possible expansion into north-western Europe. The results of these studies provide clear evidence of the impact of ongoing climate change on species range changes. These findings suggest that climate change may create new opportunities for Mediterranean species to spread to new regions, using C. erythraea subsp. majus as an example.

Assessment of vegetation net primary productivity variation and influencing factors in the Beijing-Tianjin-Hebei region

Exploring the spatiotemporal variations of vegetation net primary productivity (NPP) and analyzing the relationships between NPP and its influencing factors are vital for ecological protection in the Beijing-Tianjin-Hebei (BTH) region. In this study, we employed the CASA model in conjunction with spatiotemporal analysis techniques to estimate and analyze the spatiotemporal variations of NPP in BTH and different ecological function sub-regions over the past two decades. Subsequently, we established three scenarios (actual, climate-driven and land cover-driven) to assess the influencing factors and quantify their relative contributions. The results indicated that the overall NPP in BTH exhibited a discernible upward trend from 2000 to 2020, with a growth rate of 3.83 gC·m−2a−1. Furthermore, all six sub-regions exhibited an increase. The Bashang Plateau Ecological Protection Zone (BP) exhibited the highest growth rate (5.03 gC·m−2a−1), while the Low Plains Ecological Restoration Zone (LP) exhibited the lowest (2.07 gC·m−2a−1). Geographically, the stability of NPP exhibited a spatial pattern of gradual increase from west to east. Climate and land cover changes collectively increased NPP by 0.04 TgC·a−1 and 0.07 TgC·a−1, respectively, in the BTH region. Climate factors were found to have the greatest influence on NPP variations, contributing 40.49% across the BTH region. This influence exhibited a decreasing trend from northwest to southeast, with precipitation identified as the most influential climatic factor compared to temperature and solar radiation. Land cover change has profound effects on ecosystems, which is an important factor on NPP. From 2000 to 2020, 15.45% area of the BTH region underwent land cover type change, resulting in a total increase in NPP of 1.33 TgC. The conversion of grass into forest brought about the 0.89 TgC increase in NPP, which is the largest of all change types. In the area where land cover had undergone change, the land cover factor has been found to be the dominant factor influencing variations in NPP, with an average contribution of 49.37%. In contrast, in the south-central area where there has been no change in land cover, the residual factor has been identified as the most influential factor influencing variations in NPP. Our study highlights the important role of land cover change in influencing NPP variations in BTH. It also offers a novel approach to elucidating the influences of diverse factors on NPP, which is crucial for the scientific assessment of vegetation productivity and carbon sequestration capacity.

Assessment of the relevance of features associated with corn crop yield prediction in Colombia, a country in the Neotropical zone

Obtaining highly accurate predictive models to precisely estimate corn crop yields is essential for making informed decisions in a sustainable agriculture environment. There are various approaches to achieve this goal, including models based on Fuzzy Logic, Association Rules, and Machine Learning. However, some of these models have limitations in terms of the accuracy of their predictions, attributable to the high complexity and non-linearity in the interactions between factors. While Machine Learning techniques alone can achieve high precision, the inclusion of multiple attributes can reduce it. This study focuses on identifying the most influential factors at the regional level through a comprehensive analysis of the relevance of features associated with corn crop yields in Colombia, a country in the Neotropical zone. To accomplish this, climatological time series and historical yield records are used through a methodology based on CRISP- DM, widely used in the field of data mining, involving a review of related work, data cleaning and transformation, relevance evaluation using the RReliefF algorithm, and verification of the performance of the most influential factors through prediction algorithms. The results obtained demonstrate that solar radiation, precipitation, vapor pressure, and maximum and minimum temperatures exert the greatest influence on corn crop yield prediction, with a relevance factor of 0.033, 0.032, 0.026, 0.022, and 0.021, respectively. In the validation of the performance of the selected factors, two predictive models were implemented. The first, based on Artificial Neural Networks, yielded a RMSE of 0.1216 with the subset of variables and 0.1403 with all available variables. In the second, Linear Regression was applied, resulting in an RMSE of 0.1417 with the subset of variables and 0.1424 with all available variables. These results highlight the importance of the selected features as the most influential climatic factors in defining highly accurate predictive models in the Neotropical zone.

Risk assessment of coral reef vulnerability to climate change and stressors in tropical islands: The case of Mauritius

Coral reefs play a critical role in the socio-economic development of oceanic islands, besides offering coastal protection against the destructive forces of the sea under storm conditions. A Multi-Criteria Decision Making-based geospatial model is used which combine highly influential climatic, ecological, and anthropogenic reef degradation factors in view of revealing regions of high coral reef vulnerabilities to inform ecosystems conservation and management. Further investigation of the coastal seawater temperature trend revealed a rise in sea surface temperature approximating 0.66 °C over the 2003–2020 period as compared to the 1985–2003 interval, with a decadal temperature rise of 0.16 °C reported to be higher than the global average. The bleaching threshold in the region is frequently exceeded during the postmillennial period, further reducing coral fitness. Finally, management strategies are proposed here, which include the adequate design of Marine Protected Area networks, and the implementation of policy strategies for fertilizer use, sustainable coastal development projects, and control of reef predator population. The insights in this paper are expected to be applicable in the reef management of other oceanic islands.

Summer drought exposure, stand structure, and soil properties jointly control the growth of European beech along a steep precipitation gradient in northern Germany.

Increasing exposure to climate warming-related drought and heat threatens forest vitality in many regions on earth, with the trees' vulnerability likely depending on local climatic aridity, recent climate trends, edaphic conditions, and the drought acclimatization and adaptation of populations. Studies exploring tree species' vulnerability to climate change often have a local focus or model the species' entire distribution range, which hampers the separation of climatic and edaphic drivers of drought and heat vulnerability. We compared recent radial growth trends and the sensitivity of growth to drought and heat in central populations of a widespread and naturally dominant tree species in Europe, European beech (Fagus sylvatica), at 30 forest sites across a steep precipitation gradient (500-850 mmyear-1 ) of short length to assess the species' adaptive potential. Size-standardized basal area increment remained more constant during the period of accelerated warming since the early 1980s in populations with >360 mm growing season precipitation (April-September), while growth trends were negative at sites with <360 mm. Climatic drought in June appeared as the most influential climatic factor affecting radial growth, with a stronger effect at drier sites. A decadal decrease in the climatic water balance of the summer was identified as the most important factor leading to growth decline, which is amplified by higher stem densities. Inter-annual growth variability has increased since the early 1980s, and variability is generally higher at drier and sandier sites. Similarly, within-population growth synchrony is higher at sandier sites and has increased with a decrease in the June climatic water balance. Our results caution against predicting the drought vulnerability of trees solely from climate projections, as soil properties emerged as an important modulating factor. We conclude that beech is facing recent growth decline at drier sites in the centre of its distribution range, driven by climate change-related climate aridification.

Assembly dynamics of East Asian subtropical evergreen broadleaved forests: New insights from the dominant Fagaceae trees.

The dominant species of a biome can be regarded as its genuine indicator. Evergreen broadleaved forests (EBLFs) in subtropical East Asia harbor high levels of species biodiversity and endemism and are vital to regional carbon storage and cycling. However, the historical assembly of this unique biome is still controversial. Fagaceae is the most essential family in East Asian subtropical EBLFs and its dominant species are vital for the existence of this biome. Here, we used the dominant Fagaceae species to shed light on the dynamic process of East Asian subtropical EBLFs over time. Our results indicate high precipitation in summer and low temperature in winter are the most influential climatic factors for the distribution of East Asian subtropical EBLFs. Modern East Asian subtropical EBLFs did not begin to appear until 23 Ma, subsequently experienced a long-lasting development in the Miocene and markedly deteriorated at about 4 Ma, driven jointly by orogenesis and paleoclimate. We also document that there is a lag time between when one clade invaded the region and when its members become dominant species within the region. This study may improve our ability to predict and mitigate the threats to biodiversity of East Asian subtropical EBLFs and points to a new path for future studies involving multidisciplinary methods to explore the assembly of regional biomes.

One million years of diversity shifts in amphibians and reptiles in a Mediterranean landscape: resilience rules the Quaternary

AbstractIn contrast with the well documented strain on extant amphibian and reptile populations today, the Quaternary fossil record of these groups is very conservative showing few changes over long periods of time. In order to establish the non‐human‐induced effect of climate change on herpetofaunal diversity, we collected data from Pleistocene sites in the Sierra de Atapuerca complex (Burgos, Spain), which records the last few million years of changes. Diversity was measured in terms of richness and evenness indices and its relationship to the climatic parameters was analysed with OLS regression models. The highest diversity (richness and evenness; 1‐D) occurred in periods considered to be analogues of the current interglacial, whereas minimum diversity values were reached during periods when conditions were harsher (cooler or glacial stage). In all cases, the diversity values were always restored subsequently, pointing to great resilience. Temperature proves to be the most influential climatic factor. Accordingly, amphibians and reptiles have been able to overcome previous climatic changes successfully. In contrast, the effects of anthropization have generated an uncommon loss of diversity, the like of which has not been seen in the last few million years. The data presented here demonstrate that the current amphibian loss seems to be driven by anthropogenic influence, with climate a factor of a secondary importance.

Moisture source variations for summer rainfall in different intensity classes over Huaihe River Valley, China

Rainfall is one of the most influential climatic factors on regional development and environment, and changes in rainfall intensity are of specific concern. In the Huaihe River Valley (HRV), heavy rainfall is a primary trigger of floods. However, the difference in the origin of moisture contributed to heavy rainfall and light rainfall is rarely studied and not entirely understood. This study analyzes the rainfall moisture sources in association with different categories of rainfall intensity over the HRV during 1980–2018 using the Water Accounting Model with ERA-Interim reanalysis and precipitation observations from China Meteorological Administration. The results show that the moisture for the HRV summer rainfall is mainly from terrestrial subregion (40%), the Indian Ocean (27%), the Pacific Ocean (25%), and the local HRV (8%). In addition, moisture sources differ substantially between light and heavy rainfall. Specifically, the local HRV contributes more moisture to light rainfall (12%) compared to heavy rainfall (4%), whereas the Indian Ocean contributes more to heavy rainfall (33%) than to light rainfall (20%). The grids located in the southern source region make higher contribution ratio in heavy rainfall than in light rainfall. These results suggest that moisture from distant oceanic areas, especially the Indian Ocean, plays a crucial role in intense summer rainfall, whereas moisture from the land sources covering local grids plays a dominant role in light rainfall in the HRV.

Impacts of Rainfall Variability on Potato Productivity in Haramaya District, Eastern Hararge Zone, Ethiopia

Rainfall variability is one of the most influential climatic factors that determine crop productivity. This study was conducted to analyze rainfall variability and its impact on potato productivity for the period of 2000-2019, and to assess farmer’s perception on impacts of climate variability and evaluate their adaptation measures for potato productivity in Haramaya District. Primary data were obtained from randomly selected farmers through questionnaire, key informants interview and field observation. Secondary data on rainfall and potato production were collected from Ethiopia Meteorological agency and Haramaya District Agriculture Office. Purposive sampling was used to select 362 farmers in the district. Proportionate sampling was used to select the sample of farmers in each of the three kebeles (Tiniqe, Tuji Gabisa and Kuro). The data collected were analyzed using Statistical software SPSS. Annual rainfall and potato yield showed decreasing trend from 2000 to 2019. Annual rainfall trends variability was significant and ranged from -25.25 in 2009 to +48.99 in 2007. Annual Potato yield trends variability was also significant and ranged from -33.14 in 2000 to +60.89 in 2007. Rainfall variations, crop diseases, pests, and high cost of inputs have been the major challenges facing potato production in the study area. Forty three percent (43%) of the respondents agreed that rainfall variation was the main cause of decreased potato yields 24% crop diseases and pests and 15% high cost of inputs 10% inadequate improved seed and 8% soil erosions. From the findings Pearson’s r=0.668 showed that there was significant impact of rainfall variability trend on potato yields. From the findings, the study recommended that soil and water management practices such as mulching, digging of trenches, water harvesting, crop diversification and use of irrigation during the dry spell as adaptation measures should be applied to cope with rainfall variation.

Climatic responses of Pinus brutia along the Black Sea coast of Crimea and the Caucasus

Pinus brutia var. pityusa (Steven) Silba (Calabrian pine) is considered a vulnerable species because of reductions in its population sizes linked to habitat decline in recent decades. Global warming alongside the collateral modification of precipitation regimes may markedly affect the distribution ranges of this species.In this dendroecological study, we identified the most influential climatic factors affecting the radial growth of P. brutia on the northern and eastern coasts of the Black Sea among the northern refugia of this species. Chronologies from five sites located on the Crimea Peninsula and the Caucasian coast and exposed to varying climatic conditions were used in this analysis. The study of environmental factors controlling the growth of P. brutia trees in the coastal populations of Crimea and the Caucasus revealed that within the longitudinal transect, which encompasses a specific range of climatic conditions, correlations between climate and the growth of P. brutia under analogous orographic conditions are similar.Aridisation of the dry Crimean climate in 1981–2012 led to an increase in the tree growth response. In the same period, populations of P. brutia trees growing in the subtropical climate of the Black Sea coast exhibited a weakened growth response to the point of disappearance. The northern populations of P. brutia, which are at the climatic limit of the species’ distribution, are exposed to a high risk of increasing climate aridisation. Our findings could provide useful information for further research on the effects of climate change on Black Sea coastal forest ecosystems.

Productivity of Jute Influenced by Some Major Climatic Variables in South -Western Coastal Region of Bangladesh

Due to be in disaster prone geographic area because of climate change, Bangladesh is one of the vulnerable largest deltas in the world. Agriculture is the main influential factor for Bangladesh economy. Jute and various vendible of jute are good sources of earning foreign currency of Bangladesh. But in the last decades it seems that our Agricultural sector especially coastal belt has been affected drastically by climate change. It is to scientifically assess the vulnerability of the golden fibre of Bangladesh; Jute production due to the unfavourable climatic variables fluctuation in South Western coastal belt, a original field research has been done considering the influential climatic factors of temperature, rainfall, humidity, sun shine hours and sea level pressure of last 30 years (1981-2011) and their impacts on the production of Jute. During the producing season of Jute, it has been increased the maximum and average temperature. And it was about unchanged pattern of sea-level pressure of here but the most important factor for production rainfall has been increased by 53, 12 and 142 mm in Khulna, Satkhira, Bagerhat respectively. The production proclivity of the jute shows most of the time as increasing except in Khulna in 2009 it was affected by demolishing natural disaster; AILA, so the production was drastically felled down in 2009.

Phenological pattern reproductive of Attalea speciosa Mart ex Spreng. in pasture area in the central region of Rondônia.

The objective of this work was to evaluate the phenology of the babassu (Attalea speciosa Mart ex Spreng.), aiming to subsidize information for non - timber management of the species in pasture area. For 48 months, the phenological patterns of babassu were studied, relating them to meteorological variables such as monthly average temperature, monthly total precipitation, relative humidity of the medium air and photoperiod. A total of 130 adult palm trees from natural regeneration were monitored in a pasture in the municipality of Ji-Paraná, RO, from January 2012 to December 2015. The data were analyzed by means of the activity indexes, the relation of the phenophases and meteorological variables by means of Pearson correlation. The population synchrony index was also evaluated. During the study, the population of Attalea speciosa showed flowering asynchronously in the population. In the process of formation and maturation of the fruits of the babassu, it was possible to observe that the time of total development of the fruits was in average 254 days. In young infructescence, the most influential climatic factors were temperature and photoperiod. In the green infructescence, climatic factors such as precipitation, relative humidity and photoperiod influenced negatively. The presence of mature infructescence occurred throughout the year, with the highest intensities in the month of November, and its activity related to the increase in temperature and duration of days. Phenological monitoring of babassu allowed to identify the intensity and predictability of reproductive events, thus enabling information to be provided to the plans for the sustainable exploitation of the species in pasture in the municipality of Ji-Paraná.

Spatiotemporal variability of sunshine duration and influential climatic factors in mainland China during 1959–2017

AbstractSunshine duration (SD) is a key index with which to quantitatively measure the intensity and duration of solar radiation. The exploration of spatiotemporal characteristics and potential influential factors for SD could help us better understand solar radiation variability. In this study, we first explore the spatiotemporal variability of SD across mainland China during 1959–2017, then identify the predominant influential climatic factors and detect their relative influence of temporal dynamic on SD, and finally discuss the relative influential rates of climatic factors and detect the dominating climatic factor on a spatial scale. The results show that: Firstly, the annual and seasonal SD gradually decreased from the northwest to southeast across mainland China; a significant decreasing trend (p &lt; .05) was detected for annual SD at a rate of −2.7 h⋅a–1, a turning point significantly occurred in 1986 (p &lt; .05) in the year SD series, and oscillation periods of 2.4–3.8 years existed in mainland China and most sub‐regions. Secondly, the significant (p &lt; .05) decrease of wind speed (Win), increase of precipitation (Pre), and increase of vapour pressure (Vp) were responsible for the decreasing trend of SD with relative influential rates of 39.9, 30.6, and 29.5%, respectively. Thirdly, temporally, the relative influential rate of each climatic variable changed over time; spatially, Win dominated most areas of mainland China (55.9%) during 1959–2017, followed by Pre (24.9%) and Vp (19.2%).

Impacts of climate variability and landscape pattern change on evapotranspiration in a grassland landscape mosaic

AbstractEvapotranspiration (ET), a key component of the hydrological cycle, affects the transport of water and energy in the soil–vegetation–atmosphere system. Thus, quantifying the driving forces of ET dynamics is important to ensure rational water resource utilization. Based on meteorological and satellite data, spatiotemporal dynamics of ET were detected using the Surface Energy Balance System (SEBS) model, and effects of climate variability and landscape pattern change on ET dynamics in an arid to semiarid landscape mosaic during the growing season (April‐October) from 2001 to 2015 in Xilingol League, China were evaluated. The results indicated that (a) a significant increase (P &lt; .05) in ET was found in the north‐eastern Xilingol League, and a significant decrease (P &lt; .05) in ET was confined to the southwest and (b) climate variability had significant effects on ET dynamics. All climatic factors showed a positive correlation relationship with ET dynamics, and mean temperature (Ta) was the most influential climatic factor on ET dynamics followed by relative humidity (Rh), wind speed (Ws), and precipitation (Pr), respectively. The influence of landscape pattern change on ET dynamics was mainly reflected in the increase of the normalized difference vegetation index (NDVI) promoting ET dynamics. Several other landscape pattern metrics also had important impacts on ET dynamics, which were mainly reflected in the positive effect of the aggregation index (AI) on ET dynamics and the negative effects of the largest patch index (LPI), edge density (ED), and percentage of landscape (PLAND) on ET dynamics. To promote effective water resource utilization, landscape managers should continue to moderately implement vegetation restoration projects such as the Grain for Green Project, orient with conversion of low‐quality cropland into grassland, and conserve large areas of grassland. Appropriate management measures for forests and cropland scattered in the landscape mosaic, based on local climate and soil properties, as well as socioeconomic goals, are also required.

Regional Pungency Degree in China and Its Correlation with Typical Climate Factors.

Chili is an indispensable condiment in Chinese dishes. Due to regional environmental and cultural differences, there are certain differences in the regional food spicy degree. This study analyzed the pungency degree of dishes in 21 regions of China and created a pungency degree map using experiments and statistics. Seven typical climatic factors were selected, such as temperature and humidity, to analyze the most influential climatic factor on pungency degree through multiple regression methods. This study sampled 300 dishes of 12 cities in three typical provinces (Sichuan, Hubei, and Zhejiang) and found out the SHU (pungency degree in Scoville Heat Units) of dishes to supplement the study. The results suggest that Guizhou cuisine is the most pungent, where the proportion of dishes with chili is more than 50%. In the pungency degree map of the 21 Chinese regions, southwest China has cuisine that is strongly pungent, and the next pungent cuisine area includes the middle reaches of the Yangtze River, Shanxi, and Ningxia. The cold area in northeast China, including Qinghai and Beijing, is the area of intermediate pungent cuisine. Central and eastern parts of China belong to the light pungent cuisine area. The field sampling of 12 cities also confirmed that the pungency degree of regions is Sichuan > Hubei > Zhejiang. The multiple regression analysis results suggest that the most influential climatic factor is the average sunshine duration which has negative correlation with pungency degree. PRACTICAL APPLICATION: Environment correlative dietology is an emerging and important discipline in China. This research has helped us to enrich our data on chili dishes and expand our geo-environmental food database. In terms of the flavor of the dishes, objective data were used instead of the former subjective comments for quantitative analysis. Since ancient times, there has been a traditional saying of spicy dehumidification and perspiration. This study uses mathematical statistical analysis methods to innovatively analyze the correlation between regional chili taste and geographical environment climate. These are all conducive to the establishment of scientific and healthy food flavor models.

Impact of Some Climatic Variables on the Yields of Boro Rice in Bangladesh

Bangladesh is primarily an Agriculture based country and its economy largely depends on the agriculture. Weather and climate are key determinants of the productivity of crops grown in an agrarian country like Bangladesh. Boro rice constitutes a large share in the domestic food grain of the country. Sometimes its production affected by some climatic factors. Therefore, the objective of this research was to determine the likely climatic factors for Boro rice production in Bangladesh. In this study we employed traditional OLS method and recent Bootstrap technique to identify the influential climatic factors on Boro rice production. Our study revealed that the considered variables rainfalls (RAIN), maximum temperature (MAX), minimum temperature (MIN) and wind speed (WIND) have significant effect on Boro rice production both by OLS and Bootstrap method. Bootstrap method exhibits lower standard errors in comparison to the OLS method indicating that this estimate could be useful in Boro rice production of Bangladesh. The messages from this study could be useful for the policy makers of the country.

EXOGENOUS DRIVERS Of SURfACE URBAN HEAT ISLANDS IN NORTHERN wEST SIBERIA

Urban temperature anomalies, frequently referred to as the urban heat islands (UHIs), are of the most distinct and influential climatic factors with significant impact on urban life and environment. However, UHIs in high latitudes are still studied only fragmentary. There is a knowledge gap related to the urban temperature distinction with respect to local temperature anomalies of natural surface types. This study extends upon our recent high latitude regional-scale climatic survey in 28 cities in the Northern West Siberia (NWS) region. Based on MODIS land surface temperature (LST) products covering 15 years between 2001 and 2015, it was revealed that all 28 cities have significant surface urban heat islands (SUHIs). The strong statistical dependence (r = 0.73) on endogenous factors such as city size and the population was found. It was suggested that exogenous factors such as the background LC types could be significant as well. This study presents the analysis of the exogenous factors shaping the apparent SUHI intensities. The major contribution to the SUHI was revealed for water, sparse vegetation, grassland, and shrubland. There are no clear dependence between the partial SUHI intensity and the area fraction occupied by the given LC type. The mechanisms and pathways of the SUHI maintenance cannot be inferred solely from the remote sensing data. Further understanding requires numerical experiments with turbulence-resolving models.

A regional hybrid GOA-SVM model based on similar day approach for short-term load forecasting in Assam, India

In today's restructuring electricity market, short-term load forecasting (STLF) is an essential tool for the electricity utilities to predict future scenario and act towards a profitable policy. The electric load demand is highly influenced by the thermal inertia due to the climatic factors. These influential climatic factors are different in different regions. Therefore, it is necessary to have a region specific STLF model for load forecasting under regional climatic conditions. This paper proposes a regional hybrid STLF model utilizing SVM with a new technique, called grasshopper optimization algorithm (GOA), to evaluate its suitable parameters. This study is carried out in Assam, a state of India and proposed GOA-SVM model is targeted for forecasting the load under local climatic conditions. The proposed model uses the similar day approach (SDA) to satisfy the regional climatic requirements. The results of the proposed model show better accuracy comparing to results generated with classical STLF model of incorporating temperature universally as the only climatic factor. To further affirm the efficacy of the proposed model, same inputs are delivered in two alternative hybrid models, namely GA-SVM (GA with SVM) and PSO-SVM (PSO with SVM). The results indicate that the proposed model outperforms the other hybrid models.

Impact of Some Climatic Variables on the Yields of Boro Rice in Bangladesh

Bangladesh is primarily an Agriculture based country and its economy largely depends on theagriculture. Weather and climate are key determinants of the productivity of crops grown inan agrarian country like Bangladesh. Boro rice constitutes a large share in the domestic foodgrain of the country. Sometimes its production affected by some climatic factors. Therefore,the objective of this research was to determine the likely climatic factors for Boro riceproduction in Bangladesh. In this study we employed traditional OLS method and recentBootstrap technique to identify the influential climatic factors on Boro rice production. Ourstudy revealed that the considered variables rainfalls (RAIN), maximum temperature (MAX),minimum temperature (MIN) and wind speed (WIND) have significant effect on Boro riceproduction both by OLS and Bootstrap method. Bootstrap method exhibits lower standarderrors in comparison to the OLS method indicating that this estimate could be useful in Bororice production of Bangladesh. The messages from this study could be useful for the policymakers of the country.