scholarly journals Global Analysis of Atmospheric Transmissivity Using Cloud Cover, Aridity and Flux Network Datasets

2021 ◽  
Vol 13 (9) ◽  
pp. 1716
Author(s):  
Ankur Srivastava ◽  
Jose F. Rodriguez ◽  
Patricia M. Saco ◽  
Nikul Kumari ◽  
Omer Yetemen
Keyword(s):  
Cloud Cover ◽  
Climatic Factors ◽  
Global Analysis ◽  
Empirical Relationship ◽  
Aridity Index ◽  
Global Scale ◽  
Empirical Models ◽  
Coefficient Of Determination ◽  
Crop Modeling ◽  
Atmospheric Transmissivity

Atmospheric transmissivity (τ) is a critical factor in climatology, which affects surface energy balance, measured at a limited number of meteorological stations worldwide. With the limited availability of meteorological datasets in remote areas across different climatic regions, estimation of τ is becoming a challenging task for adequate hydrological, climatic, and crop modeling studies. The availability of solar radiation data is comparatively less accessible on a global scale than the temperature and precipitation datasets, which makes it necessary to develop methods to estimate τ. Most of the previous studies provided region specific datasets of τ, which usually provide local assessments. Hence, there is a necessity to give the empirical models for τ estimation on a global scale that can be easily assessed. This study presents the analysis of the τ relationship with varying geographic features and climatic factors like latitude, aridity index, cloud cover, precipitation, temperature, diurnal temperature range, and elevation. In addition to these factors, the applicability of these relationships was evaluated for different climate types. Thus, empirical models have been proposed for each climate type to estimate τ by using the most effective factors such as cloud cover and aridity index. The cloud cover is an important yet often overlooked factor that can be used to determine the global atmospheric transmissivity. The empirical relationship and statistical indicator provided the best performance in equatorial climates as the coefficient of determination (r2) was 0.88 relatively higher than the warm temperate (r2 = 0.74) and arid regions (r2 = 0.46). According to the results, it is believed that the analysis presented in this work is applicable for estimating the τ in different ecosystems across the globe.

scholarly journals Structural equation modeling to shed light on the controversial role of climate on the spread of SARS-CoV-2

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alessia Spada ◽  
Francesco Antonio Tucci ◽  
Aldo Ummarino ◽  
Paolo Pio Ciavarella ◽  
Nicholas Calà ◽  
...  
Keyword(s):  
Structural Equation Modeling ◽  
Population Density ◽  
Structural Equation ◽  
Climatic Factors ◽  
Demographic Data ◽  
Factor Loading ◽  
Statistical Technique ◽  
Global Scale ◽  
Equation Modeling ◽  
Relevant Role

AbstractClimate seems to influence the spread of SARS-CoV-2, but the findings of the studies performed so far are conflicting. To overcome these issues, we performed a global scale study considering 134,871 virologic-climatic-demographic data (209 countries, first 16 weeks of the pandemic). To analyze the relation among COVID-19, population density, and climate, a theoretical path diagram was hypothesized and tested using structural equation modeling (SEM), a powerful statistical technique for the evaluation of causal assumptions. The results of the analysis showed that both climate and population density significantly influence the spread of COVID-19 (p < 0.001 and p < 0.01, respectively). Overall, climate outweighs population density (path coefficients: climate vs. incidence = 0.18, climate vs. prevalence = 0.11, population density vs. incidence = 0.04, population density vs. prevalence = 0.05). Among the climatic factors, irradiation plays the most relevant role, with a factor-loading of − 0.77, followed by temperature (− 0.56), humidity (0.52), precipitation (0.44), and pressure (0.073); for all p < 0.001. In conclusion, this study demonstrates that climatic factors significantly influence the spread of SARS-CoV-2. However, demographic factors, together with other determinants, can affect the transmission, and their influence may overcome the protective effect of climate, where favourable.

scholarly journals The role of climatic and terrain attributes in estimating baseflow recession in tropical catchments

2010 ◽  
Vol 14 (11) ◽  
pp. 2193-2205 ◽  
Author(s):  
J. L. Peña-Arancibia ◽  
A. I. J. M. van Dijk ◽  
M. Mulligan ◽  
L. A. Bruijnzeel
Keyword(s):  
Potential Evapotranspiration ◽  
Aridity Index ◽  
Global Scale ◽  
Tree Cover ◽  
Annual Rainfall ◽  
Ungauged Catchments ◽  
Ongoing Research ◽  
Daily Streamflow ◽  
Terrain Attributes ◽  
Streamflow Data

Abstract. The understanding of low flows in rivers is paramount more than ever as demand for water increases on a global scale. At the same time, limited streamflow data to investigate this phenomenon, particularly in the tropics, makes the provision of accurate estimations in ungauged areas an ongoing research need. This paper analysed the potential of climatic and terrain attributes of 167 tropical and sub-tropical unregulated catchments to predict baseflow recession rates. Daily streamflow data (m3 s–1) from the Global River Discharge Center (GRDC) and a linear reservoir model were used to obtain baseflow recession coefficients (kbf) for these catchments. Climatic attributes included annual and seasonal indicators of rainfall and potential evapotranspiration. Terrain attributes included indicators of catchment shape, morphology, land cover, soils and geology. Stepwise regression was used to identify the best predictors for baseflow recession coefficients. Mean annual rainfall (MAR) and aridity index (AI) were found to explain 49% of the spatial variation of kbf. The rest of climatic indices and the terrain indices average catchment slope (SLO) and tree cover were also good predictors, but co-correlated with MAR. Catchment elongation (CE), a measure of catchment shape, was also found to be statistically significant, although weakly correlated. An analysis of clusters of catchments of smaller size, showed that in these areas, presumably with some similarity of soils and geology due to proximity, residuals of the regression could be explained by SLO and CE. The approach used provides a potential alternative for kbf parameterisation in ungauged catchments.

Relatii temporale între parametrii climatici si cresterile anuale ale speciilor forestiere (studiu de caz)

2019 ◽  
Author(s):  
Maria Nedealcov ◽  
◽  
Ala Donica ◽  
Ion Agapi ◽  
Nicolae Grigoras ◽  
...  
Keyword(s):  
Climatic Factors ◽  
Growth Parameters ◽  
Ring Width ◽  
Aridity Index ◽  
Quercus Petraea ◽  
Distribution Area ◽  
Natural Distribution ◽  
Annual Ring Width ◽  
Republic Of Moldova ◽  
The Republic

The forests on the natural distribution area from the silvosteppe zone, under the influence of climate change will experience major changes in their structure and functioning. The analysis of growth parameters for Fraxinus excelsior, Quercus petraea, Q. robur in three experimental areas from center of the Republic of Moldova indicates that the radial growth processes are influenced by the same complex of climatic factors, which differ being dendroclimatic response intensity. It has been shown that between the annual tree growth and forest aridity index - FAI, there are close correlations: the higher FAI values indicate the lower annual growth of the trees, and vice versa, low FAI values identify good development conditions of the stands (higher increases in the annual ring width).

scholarly journals The impact of soil and climatic factors on forest growth

2016 ◽  
Vol 5 (1-2) ◽  
pp. 19-25
Author(s):  
Kitti Balog ◽  
András Szabó ◽  
János Rásó
Keyword(s):  
Plant Growth ◽  
Fine Particles ◽  
Black Locust ◽  
Climatic Factors ◽  
Calculated Data ◽  
Aridity Index ◽  
Vegetation Period ◽  
Forest Growth ◽  
Humus Layer ◽  
The Impact

This preliminary study reveals the relations between the forest growth (annual dendromass increment; ADMinc - as dependent variable) and some important soil factors, which have effect on plant growth, such as: groundwater level (GWL), groundwater composition (GWC), plant available water capacity (PAWC), depth of humus layer, texture (hyi) and pH of the soil, moreover the maximum concentration (MAX) of salt and CaCCb and the depth of its MAX in the soil profile. 17 plantations (Poplar, Common oak and Black locust) are included in the analysis investigated all over the Great Hungarian Plain. Correlation profile of the above parameters was created explaining that two abiotic parameters limit plant growth: if GWL is deeper than 5 m and if HCO3 concentration in groundwater is high (above 15 meq/L). Within the tested range (0.17 - 2.23 mS/cm for electrical conductivity (EC) and 0.5 /sand/ - 4.21 /clay loam/ for hyi), the higher magnitude of EC results in higher ADMinc and the higher hyi (higher proportion of fine soil particles) leads to higher ADMinc The positive relationship of ADMinc with EC suggests good nutrient supply of the soil, while the higher proportion of fine particles refers to better water management properties. Thickness of humus layer is an important soil factor: compared to shallow humus layer, deep one increases ADMinc exponentially. In case of Black locust, PAWC is the substantial factor for growing, unlike Poplar, whose growth depends on groundwater uptake (GWU). This phenomenon originates from the differences between the individual needs of the tree species and differences in root morphology. Merely 4 sampling plots were equipped with meteorological stations, thus the number of climatic parameter data were not enough for statistical analysis. So data for all 17 plots were collected from literature and a general, regionally calculated data were applied (mean rainfall in the vegetation period and aridity index). There was no significant correlation between climatic parameters and ADMinc Further studies and more field investigations are needed in order to clarify the results.

scholarly journals Global analysis reveals complex demographic responses of mammals to climate change

2019 ◽  
Author(s):  
Maria Paniw ◽  
Tamora James ◽  
C. Ruth Archer ◽  
Gesa Römer ◽  
Sam Levin ◽  
...  
Keyword(s):  
Climate Change ◽  
Climatic Factors ◽  
Global Analysis ◽  
Demographic Data ◽  
Mammal Species ◽  
Full Spectrum ◽  
Terrestrial Mammals ◽  
Demographic Rates ◽  
Global Understanding ◽  
Demographic Responses

ABSTRACTApproximately 25 % of mammals are threatened globally with extinction, a risk that is amplified under climate change1. Persistence under climate change is determined by the combined effects of climatic factors on multiple demographic rates (survival, development, reproduction), and hence, on population dynamics2. Thus, to quantify which species and places on Earth are most vulnerable to climate-driven extinction, a global understanding of how demographic rates respond to climate is needed3. We synthesise information on such responses in terrestrial mammals, where extensive demographic data are available4. Given the importance of assessing the full spectrum of responses, we focus on studies that quantitatively link climate to multiple demographic rates. We identify 106 such studies, corresponding to 86 mammal species. We reveal a strong mismatch between the locations of demographic studies and the regions and taxa currently recognised as most vulnerable to climate change5,6. Moreover, we show that the effects of climate change on mammals will operate via complex demographic mechanisms: a vast majority of mammal populations display projected increases in some demographic rates but declines in others. Assessments of population viability under climate change therefore need to account for multiple demographic responses. We advocate to prioritise coordinated actions to assess mammal demography holistically for effective conservation worldwide.

scholarly journals Is there a trend in cirrus cloud cover due to aircraft traffic?

2005 ◽  
Vol 5 (8) ◽  
pp. 2155-2162 ◽  
Author(s):  
F. Stordal ◽  
G. Myhre ◽  
E. J. G. Stordal ◽  
W. B. Rossow ◽  
D. S. Lee ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Cloud Cover ◽  
Reasonable Agreement ◽  
Global Scale ◽  
Cirrus Cloud ◽  
Positive Trend ◽  
Spatially Correlated ◽  
Upper Limit ◽  
Main Emphasis ◽  
The Mean

Abstract. Trends in cirrus cloud cover have been estimated based on 16 years of data from ISCCP (International Satellite Cloud Climatology Project). The results have been spatially correlated with aircraft density data to determine the changes in cirrus cloud cover due to aircraft traffic. The correlations are only moderate, as many other factors have also contributed to changes in cirrus. Still we regard the results to be indicative of an impact of aircraft on cirrus amount. The main emphasis of our study is on the area covered by the METEOSAT satellite to avoid trends in the ISCCP data resulting from changing satellite viewing geometry. In Europe, which is within the METEOSAT region, we find indications of a trend of about 1-2% cloud cover per decade due to aircraft, in reasonable agreement with previous studies. The positive trend in cirrus in areas of high aircraft traffic contrasts with a general negative trend in cirrus. Extrapolation in time to cover the entire period of aircraft operations and in space to cover the global scale yields a mean estimate of 0.03 Wm-2 (lower limit 0.01, upper limit 0.08 Wm-2) for the radiative forcing due to aircraft induced cirrus. The mean is close to the value given by IPCC (1999) as an upper limit.

Predicting the ground vibration induced by mine blasting using imperialist competitive algorithm

2018 ◽  
Vol 35 (4) ◽  
pp. 1774-1787 ◽  
Author(s):  
Katayoun Behzadafshar ◽  
Fahimeh Mohebbi ◽  
Mehran Soltani Tehrani ◽  
Mahdi Hasanipanah ◽  
Omid Tabrizi
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Ground Vibration ◽  
Imperialist Competitive Algorithm ◽  
Empirical Models ◽  
Coefficient Of Determination ◽  
Content Type ◽  
Competitive Algorithm ◽  
Spacing Ratio ◽  
Artificial Neural

PurposeThe purpose of this paper is to propose three imperialist competitive algorithm (ICA)-based models for predicting the blast-induced ground vibrations in Shur River dam region, Iran.Design/methodology/approachFor this aim, 76 data sets were used to establish the ICA-linear, ICA-power and ICA-quadratic models. For comparison aims, artificial neural network and empirical models were also developed. Burden to spacing ratio, distance between shot points and installed seismograph, stemming, powder factor and max charge per delay were used as the models’ input, and the peak particle velocity (PPV) parameter was used as the models’ output.FindingsAfter modeling, the various statistical evaluation criteria such as coefficient of determination (R2) were applied to choose the most precise model in predicting the PPV. The results indicate the ICA-based models proposed in the present study were more acceptable and reliable than the artificial neural network and empirical models. Moreover, ICA linear model with theR2 of 0.939 was the most precise model for predicting the PPV in the present study.Originality/valueIn the present paper, the authors have proposed three novel prediction methods based on ICA to predict the PPV. In the next step, we compared the performance of the proposed ICA-based models with the artificial neural network and empirical models. The results indicated that the ICA-based models proposed in the present paper were superior in terms of high accuracy and have the capacity to generalize.

scholarly journals Evolution of Coronal and Interplanetary Magnetic Fields

1980 ◽  
Vol 91 ◽  
pp. 1-20
Author(s):  
Randolph H. Levine
Keyword(s):  
Magnetic Field ◽  
Solar Magnetic Field ◽  
Empirical Relation ◽  
Coronal Magnetic Field ◽  
Global Scale ◽  
Empirical Models ◽  
Quarter Century ◽  
New Era ◽  
Interplanetary Magnetic Fields ◽  
The Magnetic Field

Numerous studies have provided the detailed information necessary for a substantive synthesis of the empirical relation between the magnetic field of the sun and the structure of the interplanetary field. We will point out the latest techniques and studies of the global solar magnetic field and its relation to the interplanetary field. The potential to overcome most of the limitations of present methods of analysis exists in techniques of modelling the coronal magnetic field using observed solar data. Such empirical models are, in principle, capable of establishing the connection between a given heliospheric point and its magnetically-connected photospheric point, as well as the physical basis for the connection. We thus find ourselves at a plateau, looking back over a quarter century of empirical synthesis while anticipating a new era of detailed physical investigation on a global scale.

scholarly journals Positive biodiversity–productivity relationships in forests: climate matters

2018 ◽  
Vol 14 (4) ◽  
pp. 20170747 ◽  
Author(s):  
H. Jactel ◽  
E. S. Gritti ◽  
L. Drössler ◽  
D. I. Forrester ◽  
W. L. Mason ◽  
...  
Keyword(s):  
Climate Change ◽  
Carbon Sequestration ◽  
Tree Species ◽  
Climatic Factors ◽  
Meta Analysis ◽  
Global Scale ◽  
Tree Age ◽  
Drought Severity ◽  
Natural Forests ◽  
Mixed Species

While it is widely acknowledged that forest biodiversity contributes to climate change mitigation through improved carbon sequestration, conversely how climate affects tree species diversity–forest productivity relationships is still poorly understood. We combined the results of long-term experiments where forest mixtures and corresponding monocultures were compared on the same site to estimate the yield of mixed-species stands at a global scale, and its response to climatic factors. We found positive mixture effects on productivity using a meta-analysis of 126 case studies established at 60 sites spread across five continents. Overall, the productivity of mixed-species forests was 15% greater than the average of their component monocultures, and not statistically lower than the productivity of the best component monoculture. Productivity gains in mixed-species stands were not affected by tree age or stand species composition but significantly increased with local precipitation. The results should guide better use of tree species combinations in managed forests and suggest that increased drought severity under climate change might reduce the atmospheric carbon sequestration capacity of natural forests.

Impacts and responses to sea-level rise: a global analysis of the SRES scenarios over the twenty-first century

2006 ◽  
Vol 364 (1841) ◽  
pp. 1073-1095 ◽  
Author(s):  
Robert J Nicholls ◽  
Richard S.J Tol
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Global Analysis ◽  
Cost Benefit ◽  
Atmospheric Temperature ◽  
Global Scale ◽  
First Century ◽  
Twenty First Century ◽  
Sres Scenarios ◽  
The Impact

Taking the Special Report on Emission Scenarios (SRES) climate and socio-economic scenarios (A1FI, A2, B1 and B2 ‘future worlds’), the potential impacts of sea-level rise through the twenty-first century are explored using complementary impact and economic analysis methods at the global scale. These methods have never been explored together previously. In all scenarios, the exposure and hence the impact potential due to increased flooding by sea-level rise increases significantly compared to the base year (1990). While mitigation reduces impacts, due to the lagged response of sea-level rise to atmospheric temperature rise, impacts cannot be avoided during the twenty-first century by this response alone. Cost–benefit analyses suggest that widespread protection will be an economically rational response to land loss due to sea-level rise in the four SRES futures that are considered. The most vulnerable future worlds to sea-level rise appear to be the A2 and B2 scenarios, which primarily reflects differences in the socio-economic situation (coastal population, Gross Domestic Product (GDP) and GDP/capita), rather than the magnitude of sea-level rise. Small islands and deltaic settings stand out as being more vulnerable as shown in many earlier analyses. Collectively, these results suggest that human societies will have more choice in how they respond to sea-level rise than is often assumed. However, this conclusion needs to be tempered by recognition that we still do not understand these choices and significant impacts remain possible. Future worlds which experience larger rises in sea-level than considered here (above 35 cm), more extreme events, a reactive rather than proactive approach to adaptation, and where GDP growth is slower or more unequal than in the SRES futures remain a concern. There is considerable scope for further research to better understand these diverse issues.

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