scholarly journals Quantification of the Direct Solar Impact on Some Components of the Hydro-Climatic System

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 691
Author(s):  
Constantin Mares ◽  
Ileana Mares ◽  
Venera Dobrica ◽  
Crisan Demetrescu
Keyword(s):  
Solar Activity ◽  
Time Domain ◽  
Climate Models ◽  
External Factors ◽  
Solar Flux ◽  
Climatic Variables ◽  
Climate Variables ◽  
Complete Chain ◽  
Climatic System ◽  
A Chain

This study addresses the causal links between external factors and the main hydro-climatic variables by using a chain of methods to unravel the complexity of the direct sun–climate link. There is a gap in the literature on the description of a complete chain in addressing the structures of direct causal links of solar activity on terrestrial variables. This is why the present study uses the extensive facilities of the application of information theory in view of recent advances in different fields. Additionally, by other methods (e.g., neural networks) we first tested the existent non-linear links of solar–terrestrial influences on the hydro-climate system. The results related to the solar impact on terrestrial phenomena are promising, which is discriminant in the space-time domain. The implications prove robust for determining the causal measure of climate variables under direct solar impact, which makes it easier to consider solar activity in climate models by appropriate parametrizations. This study found that hydro-climatic variables are sensitive to solar impact only for certain frequencies (periods) and have a coherence with the Solar Flux only for some lags of the Solar Flux (in advance).

scholarly journals Quantification of the Direct Solar Impact on Some Components of the Hydroclimatic System

2021 ◽  
Author(s):  
Mares Constantin ◽  
Mares Ileana ◽  
Dobrica Venera ◽  
Demetrescu Crisan
Keyword(s):  
Neural Networks ◽  
Information Theory ◽  
Solar Activity ◽  
Time Domain ◽  
Climate Models ◽  
External Factors ◽  
Solar Flux ◽  
Climatic Variables ◽  
Climate Variables ◽  
Complete Chain

This study addresses the causal links between external factors and the main hydro-climatic variables. There is a gap in the literature on the description of a complete chain in addressing the structures of direct causal links of solar activity on the terrestrial variables. This is why, the present study uses the extensive facilities of the application of information theory in view of recent advances in different fields. Also, by other methods (e.g. neural networks) first are tested the existence non-linear links of solar-terrestrial influences on hydro-climate system. The results are promising related to the solar impact on terrestrial phenomena which is discriminant in space-time domain. The implications prove robust for determining the causal measure of climate variables under direct solar impact which makes it easier to consider solar activity in climate models, by appropriate parametrizations. This study found that hydro-climatic variables are sensitive to solar impact only for certain frequencies (periods) and these have a coherence with the Solar-Flux only for some lags of the Solar-Flux (in advance).

scholarly journals Sensitivity of the MnI 539.47 nm spectral line to solar activity

2004 ◽  
pp. 47-52 ◽  
Author(s):  
Sanja Danilovic ◽  
Istvan Vince
Keyword(s):  
Solar Activity ◽  
Spectral Line ◽  
Equivalent Width ◽  
Astronomical Observatory ◽  
Solar Flux ◽  
Full Width ◽  
Half Maximum ◽  
Relative Variation ◽  
Ccd Observations ◽  
Central Depth

CCD observations of the MnI 539.47 nm spectral line in the solar flux made at the Astronomical Observatory in Belgrade between 1994 and 2003 have been reduced and certain line parameters, viz. the equivalent width, full width at half maximum and central depth have been derived. The variation of these parameters with the solar activity has been evaluated. The relative variation of the equivalent width from minimum to maximum of solar activity was found to be 1.4%, while the variation of the central depth is 2.3%. The full width at half maximum remains practically constant.

scholarly journals Validation of RegCM regional and HadGEM global climate models using mean and extreme climatic variables

Időjárás ◽  
2019 ◽  
Vol 123 (4) ◽  
pp. 409-433
Author(s):  
Ildikó Pieczka ◽  
Judit Bartholy ◽  
Rita Pongrácz ◽  
Karolina Szabóné André
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Climatic Variables

scholarly journals Impact Analysis of Univariate and Multivariate Bias Correction on Rice Irrigation Water Needs in Jiangxi Province, China

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 381
Author(s):  
Wido Hanggoro ◽  
Jing Yuanshu ◽  
Leila Cudemus ◽  
Jing Zhihao
Keyword(s):  
Irrigation Water ◽  
Bias Correction ◽  
Climate Models ◽  
Regional Climate ◽  
Jiangxi Province ◽  
Observation Data ◽  
Climate Variables ◽  
Calibration Period ◽  
Significant Difference ◽  
Rice Irrigation

Regional climate models (RCMs) provide an improved representation of climate information as compared to global climate models (GCMs). However, in climate-agricultural impact studies, accurate and interdependent local-scale climate variables are preferable, but both RCMs and GCMs are still subjected to bias. This study compares univariate bias correction (UBC) and multivariate bias correction (MBC) method to simulate rice irrigation water needs (IWNs) in Jiangxi Province, China. This research uses the daily output of Hadley Centre Global Environmental Model version 3 regional climate model (HadGEM3-RA) forced with ERAINT (ECMWF ERA Interim) data and 13 Jiangxi ground-based observations, and the observation data are reference data with 1989–2005 defined as a calibration period and 2006–2007 as a validation period. The result shows that UBC and MBC methods favorably bias-corrected all climate variables during the calibration period, but still no significant difference is noted between the two methods. However, the UBC ignores the relationship between climate variables, while MBC preserves the climate variables’ interdependence which affect subsequent analyses. In rice IWNs simulation analysis, MBC has better skill at correcting bias compare to UBC in ETo (evapotranspiration) and Peff (effective rainfall) components. Nonetheless, both methods have a low ability to correct extreme values bias. Overall, both techniques successfully reduce bias, even though they are still less effective for precipitation compared to maximum and minimum temperature, relative humidity and windspeed.

scholarly journals Simulation of a Complete Chain of QCA Cells with Realistic Potentials

VLSI Design ◽  
2001 ◽  
Vol 13 (1-4) ◽  
pp. 149-153
Author(s):  
M. Girlanda ◽  
M. Macucci
Keyword(s):  
Numerical Simulation ◽  
Bias Voltage ◽  
Polarization State ◽  
Applied Bias ◽  
Applied Bias Voltage ◽  
Voltage Unbalance ◽  
Complete Chain ◽  
A Chain ◽  
Realistic Potentials

We present a numerical simulation of the operation of a chain of 3 Quantum Cellular Automanton (QCA) cells, with the inclusion of a realistic procedure to enforce, with an externally applied bias voltage unbalance, the polarization of the first cell. The polarization state is shown to propagate correctly, as long as the bias unbalance applied to the electrodes of the first cell is not so large as to directly perturb nearby cells. The addition of dummy cells is needed to balance the asymmetries existing at the ends of a chain: this is an indication of further difficulties, that may become relevant if fabrication of more complex arrays is attempted.

scholarly journals Lower-thermosphere response to solar activity: an empirical-mode-decomposition analysis of GOCE 2009–2012 data

2020 ◽  
Vol 38 (3) ◽  
pp. 789-800
Author(s):  
Alberto Bigazzi ◽  
Carlo Cauli ◽  
Francesco Berrilli
Keyword(s):  
Solar Activity ◽  
Solar Cycle ◽  
Empirical Mode Decomposition ◽  
Dynamic Range ◽  
Extreme Ultraviolet ◽  
Lower Thermosphere ◽  
European Space Agency ◽  
Solar Flux ◽  
Specific Response ◽  
Mode Decomposition

Abstract. Forecasting the thermosphere (the atmosphere's uppermost layer, from about 90 to 800 km altitude) is crucial to space-related applications, from space mission design to re-entry operations, space surveillance and more. Thermospheric dynamics is directly linked to the solar dynamics through the solar UV (ultraviolet) input, which is highly variable, and through the solar wind and plasma fluxes impacting Earth's magnetosphere. The solar input is non-periodic and non-stationary, with long-term modulations from the solar rotation and the solar cycle and impulsive components, due to magnetic storms. Proxies of the solar input exist and may be used to forecast the thermosphere, such as the F10.7 radio flux and the Mg II EUV (extreme-ultraviolet) flux. They relate to physical processes of the solar atmosphere. Other indices, such as the Ap geomagnetic index, connect with Earth's geomagnetic environment. We analyse the proxies' time series comparing them with in situ density data from the ESA (European Space Agency) GOCE (Gravity Field and Steady-State Ocean Circulation Explorer) gravity mission, operational from March 2009 to November 2013, therefore covering the full rising phase of solar cycle 24, exposing the entire dynamic range of the solar input. We use empirical mode decomposition (EMD), an analysis technique appropriate to non-periodic, multi-scale signals. Data are taken at an altitude of 260 km, exceptionally low for a low-Earth-orbit (LEO) satellite, where density variations are the single most important perturbation to satellite dynamics. We show that the synthesized signal from optimally selected combinations of proxy basis functions, notably Mg II for the solar flux and Ap for the plasma component, shows a very good agreement with thermospheric data obtained by GOCE, during periods of low and medium solar activity. In periods of maximum solar activity, density enhancements are also well represented. The Mg II index proves to be, in general, a better proxy than the F10.7 index for modelling the solar flux because of its specific response to the UV spectrum, whose variations have the largest impact over thermospheric density.

scholarly journals Predicting suitability of regions for Zika outbreaks with zero-inflated models trained using climate data

2019 ◽  
Author(s):  
Samantha Roth ◽  
Miranda Teboh-Ewungkem ◽  
Ming Li
Keyword(s):  
Statistical Models ◽  
Birth Defect ◽  
Climate Changes ◽  
Geographic Range ◽  
Future Climate ◽  
Climatic Variables ◽  
Human Populations ◽  
Climate Projections ◽  
Climate Variables ◽  
Climate Suitability

AbstractIn recent years, Zika spread through the Americas. This virus has been linked to Guillain-Barré syndrome, which can lead to paralysis, and microcephaly, a severe birth defect. Zika is primarily transmitted by Aedes (Ae.) aegypti, a mosquito whose geographic range has expanded and is anticipated to continue shifting as the climate changes.We used statistical models to predict regional suitability for autochthonous Zika transmission using climatic variables. By suitability for Zika, we mean the potential for an outbreak to occur based on the climate’s habitability for Ae. aegypti. We trained zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) regression models to predict Zika outbreak suitability using 20 subsets of climate variables for 102 regions. Variable subsets were selected for the final models based on importance to Ae. aegypti survival and their performance in aiding prediction of Zika-suitable regions. We determined the two best models to both be ZINB models. The best model’s regressors were winter mean temperature, yearly minimum temperature, and population, and the second-best model’s regressors were winter mean temperature and population.These two models were then run on bias-corrected climate projections to predict future climate suitability for Zika, and they generated reasonable predictions. The predictions find that most of the sampled regions are expected to become more suitable for Zika outbreaks. The regions with the greatest risk have increasingly mild winters and high human populations. These predictions are based on the most extreme scenario for climate change, which we are currently on track for.Author Summary:In recent years, Zika spread through the Americas. This virus has been linked to Guillain-Barré syndrome, which can lead to paralysis, and microcephaly, a severe birth defect. Zika is primarily transmitted by Aedes (Ae.) aegypti, a mosquito whose geographic range has expanded and is anticipated to continue shifting as the climate changes. We used statistical models to predict regional suitability for locally-acquired Zika cases using climatic variables. By suitability for Zika, we mean the potential for an outbreak to occur based on the climate’s habitability for Ae. aegypti. We trained statistical models to predict Zika outbreak suitability using 20 subsets of climate variables for 102 regions. Variable subsets were selected for the final two models based on importance to Ae. aegypti survival and their performance in aiding prediction of Zika-suitable regions. These two models were then run on climate projections to predict future climate suitability for Zika, and they generated reasonable predictions. The predictions find that most of the sampled regions are expected to become more suitable for Zika outbreaks. The regions with the greatest risk have high human populations and increasingly mild winters.

scholarly journals Reference crop evapotranspiration database in Spain (1961–2014)

2019 ◽  
Vol 11 (4) ◽  
pp. 1917-1930 ◽  
Author(s):  
Miquel Tomas-Burguera ◽  
Sergio M. Vicente-Serrano ◽  
Santiago Beguería ◽  
Fergus Reig ◽  
Borja Latorre
Keyword(s):  
Climate Models ◽  
Severity Index ◽  
Important Variable ◽  
Drought Indices ◽  
Drought Severity ◽  
Climate Variables ◽  
Evaporative Demand ◽  
Research Areas ◽  
Climate Studies ◽  
Reference Crop

Abstract. Obtaining climate grids describing distinct variables is important for developing better climate studies. These grids are also useful products for other researchers and end users. The atmospheric evaporative demand (AED) may be measured in terms of the reference evapotranspiration (ETo), a key variable for understanding water and energy terrestrial balances and an important variable in climatology, hydrology and agronomy. Despite its importance, the calculation of ETo is not commonly undertaken, mainly because datasets consisting of a high number of climate variables are required and some of the required variables are not commonly available. To address this problem, a strategy based on the spatial interpolation of climate variables prior to the calculation of ETo using FAO-56 Penman–Monteith equation was followed to obtain an ETo database for continental Spain and the Balearic Islands, covering the 1961–2014 period at a spatial resolution of 1.1 km and at a weekly temporal resolution. In this database, values for the radiative and aerodynamic components as well as the estimated uncertainty related to ETo were also provided. This database is available for download in the Network Common Data Form (netCDF) at https://doi.org/10.20350/digitalCSIC/8615 (Tomas-Burguera et al., 2019). A map visualization tool (http://speto.csic.es, last access: 10 December 2019) is available to help users download the data corresponding to one specific point in comma-separated values (csv) format. A relevant number of research areas could take advantage of this database. For example, (i) studies of the Budyko curve, which relates rainfall data to the evapotranspiration and AED at the watershed scale, (ii) calculations of drought indices using AED data, such as the Standardized Precipitation–Evapotranspiration Index (SPEI) or Palmer Drought Severity Index (PDSI), (iii) agroclimatic studies related to irrigation requirements, (iv) validation of climate models' water and energy balance, and (v) studies of the impacts of climate change in terms of the AED.

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