Sensitivity of the surface temperature to changes in total solar irradiance calculated with the WRF model
Carolina Cipagauta
Corresponding author
Posgrado en Ciencias de la Tierra, Universidad Nacional Autónoma de México, Delegación Coyoacán, 04510, México D.F., México
Blanca Mendoza
Instituto de Geofísica, Universidad Nacional Autónoma de México, Delegación Coyoacán, 04510, México D.F., México
Jorge Zavala-Hidalgo
Centro de Ciencias de la Atmósfera, Universidad Nacional Autónoma de México, Delegación Coyoacán, 04510, México D.F., México
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On the map of Portugal (left), the Castelejo mine locates at the red rectangle (adapted from <a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleItalic">Ferreira, 1971</span></a>).</p>" ] ] ] "autores" => array:2 [ 0 => array:2 [ "autoresLista" => "Vitor Manuel Gomes de Oliveira, Luís Filipe Tavares Ribeiro" "autores" => array:2 [ 0 => array:2 [ "nombre" => "Vitor Manuel Gomes" "apellidos" => "de Oliveira" ] 1 => array:2 [ "nombre" => "Luís Filipe Tavares" "apellidos" => "Ribeiro" ] ] ] 1 => array:2 [ "autoresLista" => "María Catarina Rosalino da Silva" "autores" => array:1 [ 0 => array:2 [ "nombre" => "María Catarina Rosalino" "apellidos" => "da Silva" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0016716914714965?idApp=UINPBA00004N" "url" => "/00167169/0000005300000002/v2_201505081358/S0016716914714965/v2_201505081358/en/main.assets" ] "en" => array:17 [ "idiomaDefecto" => true "titulo" => "Sensitivity of the surface temperature to changes in total solar irradiance calculated with the WRF model" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "153" "paginaFinal" => "162" ] ] "autores" => array:3 [ 0 => array:4 [ "autoresLista" => "Carolina Cipagauta" "autores" => array:1 [ 0 => array:4 [ "nombre" => "Carolina" "apellidos" => "Cipagauta" "email" => array:1 [ 0 => "carocipa@gmail.com" ] "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] ] "afiliaciones" => array:1 [ 0 => array:2 [ "entidad" => "Posgrado en Ciencias de la Tierra, Universidad Nacional Autónoma de México, Delegación Coyoacán, 04510, México D.F., México" "identificador" => "aff0005" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "*" "correspondencia" => "Corresponding author:" ] ] ] 1 => array:3 [ "autoresLista" => "Blanca Mendoza" "autores" => array:1 [ 0 => array:2 [ "nombre" => "Blanca" "apellidos" => "Mendoza" ] ] "afiliaciones" => array:1 [ 0 => array:2 [ "entidad" => "Instituto de Geofísica, Universidad Nacional Autónoma de México, Delegación Coyoacán, 04510, México D.F., México" "identificador" => "aff0010" ] ] ] 2 => array:3 [ "autoresLista" => "Jorge Zavala-Hidalgo" "autores" => array:1 [ 0 => array:2 [ "nombre" => "Jorge" "apellidos" => "Zavala-Hidalgo" ] ] "afiliaciones" => array:1 [ 0 => array:2 [ "entidad" => "Centro de Ciencias de la Atmósfera, Universidad Nacional Autónoma de México, Delegación Coyoacán, 04510, México D.F., México" "identificador" => "aff0015" ] ] ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "f0035" "etiqueta" => "Figure 7" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr7.jpeg" "Alto" => 1022 "Ancho" => 1879 "Tamanyo" => 195044 ] ] "descripcion" => array:1 [ "en" => "<p id="sp0035" class="elsevierStyleSimplePara elsevierViewall">Daily temperature sensitivity in: a) The whole area of study. b) Zone A. c) Zone B. d) Zone C. e) Zone D. f) Zone E.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025"><a name="p154"></a>Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Before the spatial era, it was believed that the solar radiation reaching the top of the atmosphere was constant with an approximate value of<span class="elsevierStyleHsp" style=""></span>~1370W/m<span class="elsevierStyleSup">2</span>. Since 1978, the radiometers on board of satellites have shown that the solar radiation is not constant, as it presents an increase of<span class="elsevierStyleHsp" style=""></span>~0.1% between the minimum and the maximum of the 11-years solar activity cycle (Fröhlich, 2000). The Total Solar Irradiance (TSI) is the total electromagnetic power emitted by the Sun per unit area of cross section arriving at the mean Earth-Sun distance [<a class="elsevierStyleCrossRef" href="#bib0075">Tiwari and Ramesh, 2007</a>].</p><p id="par0010" class="elsevierStylePara elsevierViewall">The TSI variations can affect the Earth´s climate through their direct influence on the mean global temperature or in some other indirect ways (e.g. <a class="elsevierStyleCrossRef" href="#bib0030">Gray <span class="elsevierStyleItalic">et al</span>., 2010</a>). General Circulation Models (GCM) estimate that a 2% increase of the TSI could produce an increase of<span class="elsevierStyleHsp" style=""></span>~4°C in temperature. If we assume a linear scale, then 0.1% would produce a temperature increase of 0.2°C [<a class="elsevierStyleCrossRef" href="#bib0015">CGER, 1994</a>]. Comparing this temperature change with the temperature increase in the range of 1.5°C to 4.5°C estimated by the <a class="elsevierStyleCrossRef" href="#bib0040">IPCC [2007]</a>, we could conclude that the temperature changes due to the 11- year TSI cycle change is small.</p><p id="par0015" class="elsevierStylePara elsevierViewall">The stratospheric changes induced by the solar activity can influence the troposphere and the climate. Simulations using GCM suggest that solar UV changes modify the stratospheric ozone content and the temperature, affecting its latitudinal gradient. This modifies the stratospheric winds altering the tropospheric stability and impacting in several tropospheric dynamic processes including the intensity of the Hadley cell in low and subtropical latitudes and the low extra-tropical pressure systems. Although some GCM climatic simulations estimate a decrease of mean global temperature of 0.46°C for a 0.25% TSI reduction, some surface regions could cool and others could heat more than 1°C as a result of the advective changes produced by the differential heating of land and oceans [<a class="elsevierStyleCrossRef" href="#bib0035">Haigh <span class="elsevierStyleItalic">et al</span>., 2005</a>; <a class="elsevierStyleCrossRef" href="#bib0055">Meehl <span class="elsevierStyleItalic">et al</span>., 2008</a>; <a class="elsevierStyleCrossRef" href="#bib0005">Barriopedro <span class="elsevierStyleItalic">et al</span>., 2008</a>; <a class="elsevierStyleCrossRef" href="#bib0050">Lee <span class="elsevierStyleItalic">et al</span>., 2008</a>].</p><p id="par0020" class="elsevierStylePara elsevierViewall">The aim of this paper is to estimate the sensitivity of the surface terrestrial temperature to changes in the TSI using the Weather Research and Forecasting Model (WFR). Although the WRF model can estimate other variables (<a class="elsevierStyleCrossRef" href="#bib0010">Cipagauta <span class="elsevierStyleItalic">et al</span>., 2013</a>), we choose the temperature as it is the most widely used climatic variable. We applied the model under several conditions: We use a regional model to observe the impact on México, although the boundary conditions constrain the behavior of the region, it allows us to use a higher resolution. The WRF model is applied only to the atmosphere, the sea surface temperature is prescribed. Finally, due to the computational cost required for each experiment the model was only ran for a single year.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0030">The Weather Research and Forecasting Model (WRF)</span><p id="par0025" class="elsevierStylePara elsevierViewall">The WRF model is a next-generation mesoscale non-hydrostatic numerical weather prediction system designed to serve both operational forecasting and atmospheric research needs. Several institutions support the WRF project in order to achieve a better understanding of atmospheric processes and improved weather prediction [<a class="elsevierStyleCrossRef" href="#bib0065">Skamarock <span class="elsevierStyleItalic">et al</span>., 2008</a>]. In this study we used the WRF version 3.1.1 with the Advanced Research WRF (ARW) core. In all the simulations we applied Mercator projection and the schemes described in <a class="elsevierStyleCrossRef" href="#bib0065">Skamarock <span class="elsevierStyleItalic">et al</span>. [2008]</a> as follows:<ul class="elsevierStyleList" id="lis0005"><li class="elsevierStyleListItem" id="lsti0005"><span class="elsevierStyleLabel">•</span><p id="par0030" class="elsevierStylePara elsevierViewall">WRF Single-Moment 3-class for microphysics in a simple and efficient scheme that considers ice, snow and the Graupel processes, which are adequate for real mesoscale simulations.</p></li><li class="elsevierStyleListItem" id="lsti0010"><span class="elsevierStyleLabel">•</span><p id="par0035" class="elsevierStylePara elsevierViewall">The Kain-Fritsch scheme for cumulus parameterization.</p></li><li class="elsevierStyleListItem" id="lsti0015"><span class="elsevierStyleLabel">•</span><p id="par0040" class="elsevierStylePara elsevierViewall">The Yonsei University (YSU) scheme for the planetary boundary layer.</p></li><li class="elsevierStyleListItem" id="lsti0020"><span class="elsevierStyleLabel">•</span><p id="par0045" class="elsevierStylePara elsevierViewall">The Rapid Radiative Transfer Model (RRTM) for the long-wave radiation.</p></li><li class="elsevierStyleListItem" id="lsti0025"><span class="elsevierStyleLabel">•</span><p id="par0050" class="elsevierStylePara elsevierViewall">The Dudhia scheme for the short-wave radiation.</p></li></ul></p></span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Sensitivity of the surface temperature</span><p id="par0055" class="elsevierStylePara elsevierViewall">Four numerical simulations were run to investigate the impact of TSI on surface temperature. A fifth experiment was introduced to compare temperature sensitivity to changes in TSI and initial boundary conditions. We aim to estimate the variability of the temperature in each case. The simulation that corresponds to the base year represents the typical conditions of the region of interest. To study the sensitivity of the WRF model surface temperature due to TSI variations, we used non-dimensional parameters that estimate the surface temperature change as responses to radiation variations.<a name="p155"></a></p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Description of Non-dimensional parameters technique</span><p id="par0060" class="elsevierStylePara elsevierViewall">To relate TSI and temperature, we applied the radiative balance equation, widely used in atmospheric models. This relation is basically the Stephan-Boltzman expression for the black body radiation</p><p id="par0065" class="elsevierStylePara elsevierViewall"><elsevierMultimedia ident="eq0005"></elsevierMultimedia></p><p id="par0070" class="elsevierStylePara elsevierViewall">where <span class="elsevierStyleItalic">α</span> the planetary albedo, <span class="elsevierStyleItalic">S</span> the solar radiation, <span class="elsevierStyleItalic">σ</span> is the Stephan-Boltzman constant, and <span class="elsevierStyleItalic">T</span> is the mean effective planetary temperature.</p><p id="par0075" class="elsevierStylePara elsevierViewall">From <a class="elsevierStyleCrossRef" href="#eq0005">equation (1)</a>, we calculated a non-dimensional parameter defined as</p><p id="par0080" class="elsevierStylePara elsevierViewall"><elsevierMultimedia ident="eq0010"></elsevierMultimedia></p><p id="par0085" class="elsevierStylePara elsevierViewall">where <span class="elsevierStyleItalic">k</span><span class="elsevierStyleInf">1</span> is a constant to be selected and <span class="elsevierStyleItalic">T</span> is the mean effective temperature. This parameter is a measure of the sensitivity of the corresponding variable [<a class="elsevierStyleCrossRef" href="#bib0070">Szirtes, 2006</a>].</p><p id="par0090" class="elsevierStylePara elsevierViewall">In <a class="elsevierStyleCrossRef" href="#eq0010">equation (2)</a> the partial derivative is estimated by keeping as constants the other variables that could depend on <span class="elsevierStyleItalic">T</span>, and <span class="elsevierStyleItalic">k</span><span class="elsevierStyleInf">1</span> is choose in such a way that <span class="elsevierStyleItalic">β</span><span class="elsevierStyleInf"><span class="elsevierStyleItalic">T</span></span> is non-dimensional. Using <a class="elsevierStyleCrossRef" href="#eq0005">equation (1)</a> we find the partial derivative in <a class="elsevierStyleCrossRef" href="#eq0010">(2)</a>, then we choose <span class="elsevierStyleItalic">k</span><span class="elsevierStyleInf">1</span> as the inverse value of the partial derivative evaluated in a reference condition of radiation and temperature. Then the sensitivity parameter associated to temperature becomes:</p><p id="par0095" class="elsevierStylePara elsevierViewall"><elsevierMultimedia ident="eq0015"></elsevierMultimedia></p><p id="par0100" class="elsevierStylePara elsevierViewall">where <span class="elsevierStyleItalic">T</span> is the model temperature for the radiative condition of our interest, <span class="elsevierStyleItalic">T</span><span class="elsevierStyleInf">0</span> is the temperature of the base radiation. <span class="elsevierStyleItalic">T</span> and <span class="elsevierStyleItalic">T</span><span class="elsevierStyleInf">0</span> can be daily or monthly averages, obtained from the model for different zones as well as over the full region of study, depending on the spatial and temporal behavior that we choose to examine</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Simulation configuration</span><p id="par0105" class="elsevierStylePara elsevierViewall">We choose a base year: September 1st of 1983 to August 31st of 1984. In this year the Sun was in the descending phase of its activity cycle showing intermediate activity, as it is approximately half way between the maximum and the minimum of solar activity. The simulation grid (see <a class="elsevierStyleCrossRef" href="#f0005">Figure 1</a>) consists of a single domain centered over the North Atlantic Ocean between 0-100°W and 5-60°N, with a resolution of 30<span class="elsevierStyleHsp" style=""></span>km, the region includes portions of Eastern North America, Western Europe and Northwest Africa. The initial and boundary conditions were taken from the NCEP/NCAR reanalysis project (<a class="elsevierStyleCrossRef" href="#bib0045">Kalnay <span class="elsevierStyleItalic">et al</span>., 1996</a>). We focus the analysis on five zones of the domain, where the surface temperature <a name="p156"></a>variations appear more noticeable. One exception was zone C, which was chosen due to the locations particular interest in this study.</p><elsevierMultimedia ident="f0005"></elsevierMultimedia><p id="par0110" class="elsevierStylePara elsevierViewall">The intent of this study was to analyze temperature sensitivity to TSI variations using WRF model. Four simulations were run, each one with a fixed TSI value that vary among the simulations according to <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>. The first simulation corresponds to the control experiment or base year, with a fixed TSI value similar to the one measured for the year 1983, which was a year half with a value between the maximum and the minimum of the 11-years solar cycle phase (<a href="http://www.pmodwrc.ch/php?topic=tsi/composite/SolarConstant">http://www.pmodwrc.ch/php?topic=tsi/composite/SolarConstant</a>). The measurements since the satellite era (1978) indicate that the TSI increase between the minimum and the maximum of the 11-years solar activity cycle<span class="elsevierStyleHsp" style=""></span>~0.1%, this is mainly due to an interplay between superficial magnetic dark features such as sunspots and bright features such as faculae and network elements (<a class="elsevierStyleCrossRef" href="#bib0020">Fröhlich, 2006</a>). A higher solar activity year (HR) with a TSI increased by 0.05% corresponds to the second simulation. A year of lower solar activity (LR) with a TSI reduced by 0.05% corresponds to the third simulation. The fourth simulation was run with an estimate of the TSI for the next two solar activity cycles (<a class="elsevierStyleCrossRef" href="#bib0060">Mendoza <span class="elsevierStyleItalic">et al</span>., 2010</a>). This estimate indicates a period of lower solar activity and therefore lower solar irradiance. We named this numerical experiment as the future minimum radiation (FMR). Finally we performed a fifth simulation, using the control (base year) experiment but introducing the atmospheric conditions of the 2nd of September, 1983 as the initial conditions. We run this last simulation in order to compare the effects due to the TSI changes against the effects due to a variation of initial conditions.</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0115" class="elsevierStylePara elsevierViewall">We performed two different analyses with the surface temperature model results using monthly and daily averages. In the first analysis we calculated the monthly average differences between the HR, LR and FMR and the base year, those are D_HR for HR-Base, D_LR for LR-Base and finally D_FMR for FMR-Base, respectively. In the same way we indicate as D_IC the monthly average differences between the year with the changed initial conditions and the base year, that is D_IC<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>IC-Base. The second analysis is based on the calculation of the non-dimensional sensitivity parameter. We averaged the daily and monthly surface temperature means over the region of study. This average is used to calculate the sensitivity parameter through <a class="elsevierStyleCrossRef" href="#eq0015">Equation (3)</a>, we take T_0 as the base year temperature over the whole domain and T is the model temperature over the whole domain.</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Results</span><p id="par0120" class="elsevierStylePara elsevierViewall">The monthly mean surface temperature differences (D_HR, D_LR, D_FMR and D_IC), from September 1983 to August 1984, for each simulation are shown in <a class="elsevierStyleCrossRef" href="#f0010">figures 2</a>, <a class="elsevierStyleCrossRef" href="#f0015">3</a> and <a class="elsevierStyleCrossRef" href="#f0020">4</a>. Larger changes occur in latitudes higher than 30°N. The changes are observed on the Eastern US and Canada and Northwest Africa. In low latitudes (5°- 10°N) the differences are smaller compared to those observed at higher latitudes. Larger positive differences occur in November and June on the Eastern US and Canada and negative differences, also in November, occur on Northwest Africa.</p><elsevierMultimedia ident="f0010"></elsevierMultimedia><elsevierMultimedia ident="f0015"></elsevierMultimedia><elsevierMultimedia ident="f0020"></elsevierMultimedia><p id="par0125" class="elsevierStylePara elsevierViewall">In these plots, variations of surface temperature are noticeable for each case during the year of study. However, the variations observed for D_HR, D_LR and D_FMR are of the same magnitude as those corresponding to variations in the initial conditions D_IC. Then to determine if the model is more sensitive either to TSI changes or to changes in the initial conditions, we use the technique of dimensionless parameters.</p><p id="par0130" class="elsevierStylePara elsevierViewall">In <a class="elsevierStyleCrossRef" href="#f0010">Figures 2</a>-<a class="elsevierStyleCrossRef" href="#f0020">4</a> we also see variations in some continental zones in low latitudes. Those changes are usually smaller than in higher latitudes. When we calculate the monthly surface temperature averaged over the full area of study (see <a class="elsevierStyleCrossRef" href="#f0025">Figure 5a</a>), i.e. the simulation grid, the five simulations do not show meaningful differences; i.e. the base, HR, LR and FMR have the same monthly mean temperature over the full grid. This can be due to the fact that the zones where there are large differences are small compared to the zones where the differences are smaller. If we compute the monthly average for each one of the five zones (A, B, C, D and E) we found larger monthly differences. For instance in zones A, C, D and E there is a difference of <a name="p157"></a>at least 1°C in November and June, while in January and March the differences are smaller (see figs. 5b, 5d, 5e and 5f).</p><elsevierMultimedia ident="f0025"></elsevierMultimedia><p id="par0135" class="elsevierStylePara elsevierViewall">To quantify these differences the daily and monthly temperature sensitivity of the WRF model to changes in TSI using Equation (5) was computed. To calculate the daily sensitivity (<a class="elsevierStyleCrossRef" href="#f0030">Figure 6</a>) over the area of study (<a class="elsevierStyleCrossRef" href="#f0025">Figure 5a</a>) and the five zones (<a class="elsevierStyleCrossRef" href="#f0025">Figures 5b</a> to <a class="elsevierStyleCrossRef" href="#f0025">5f</a>), we use T_0 as the base year daily average temperature of the area, and T as the daily average temperature in the area for the different TSI values. Also, the monthly temperature sensitivity over the area of study (<a class="elsevierStyleCrossRef" href="#f0035">Figure 7a</a>) and the five zones (<a class="elsevierStyleCrossRef" href="#f0035">Figures 7b</a> to <a class="elsevierStyleCrossRef" href="#f0035">7F</a>) was computed; here T_0 is the base year monthly average temperature and T is the monthly average temperature in the area for the different TSI values. In <a class="elsevierStyleCrossRef" href="#f0030">Figures 6</a> and <a class="elsevierStyleCrossRef" href="#f0035">7</a>, the curves for the various numerical experiments are different. Although the variations are small we notice that the temperature was more sensitive in November and June as we also notice in <a class="elsevierStyleCrossRef" href="#f0010">Figures 2</a> to <a class="elsevierStyleCrossRef" href="#f0020">4</a>. The average sensitivity of the temperature for each of the simulations is shown in Table 2. <a class="elsevierStyleCrossRef" href="#f0030">Figures 6</a> and <a class="elsevierStyleCrossRef" href="#f0035">7</a> show that the sensitivity is positive for the various TSI, but it is negative for changes of initial conditions during November and June.</p><elsevierMultimedia ident="f0030"></elsevierMultimedia><elsevierMultimedia ident="f0035"></elsevierMultimedia><p id="par0140" class="elsevierStylePara elsevierViewall">Finally, to complement the analysis made for the temperature, although is not the main purpose of this article to do a comprehensive analysis of all the variables that are available from the numerical simulations, we present results of: latent heat, sensible heat, surface pressure, and precipitation. <a class="elsevierStyleCrossRef" href="#f0040">Figure 8</a> shows the monthly average differences between the HR, LR and FMR and the base year, those are D_HR for HR-Base, D_LR for LR-Base and finally D_FMR for FMR-Base, respectively of the variables mentioned above (<a class="elsevierStyleCrossRef" href="#bib0010">Cipagauta <span class="elsevierStyleItalic">et al</span>., 2013</a>). Since our temperature analysis reveals that the month of November 1983, has larger differences with respect to the base year, we restrict the presentation of the results of the additional variables to this month. These results show that changes in the TSI modify <a name="p158"></a>the temperature as well as other variables. <a class="elsevierStyleCrossRef" href="#f0040">Figure 8</a> shows that the largest changes in these variables also occur at higher latitudes. Changes of latent heat, sensible heat, and surface pressure occur mainly in the ocean rather than in the continents.</p><elsevierMultimedia ident="f0040"></elsevierMultimedia></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Conclusions</span><p id="par0145" class="elsevierStylePara elsevierViewall">Based on predictions of GCM and the supposition of linearity, it was expected that an increase (decrease) in TSI would cause an increase (decrease) in surface temperature. However, <a class="elsevierStyleCrossRef" href="#f0010">Figures 2</a> to <a class="elsevierStyleCrossRef" href="#f0020">4</a> show that this is not the case, for instance, in November and June for the three different values of TSI the temperature in Northeast EU and Canada increases, but the temperature change is larger for the FMR, while in Northwest Africa for the three scenarios of TSI there is a decrease in temperature, being larger during the FMR. Some studies using GCM suggest that some regions of the Earth´s surface could cool and others could heat by least 1°C as a results of changes caused by the differential heating of the land and ocean [<a class="elsevierStyleCrossRef" href="#bib0035">Haigh <span class="elsevierStyleItalic">et al</span>., 2005</a>; <a class="elsevierStyleCrossRef" href="#bib0055">Meehl <span class="elsevierStyleItalic">et al</span>., 2008</a>; <a class="elsevierStyleCrossRef" href="#bib0005">Barriopedro <span class="elsevierStyleItalic">et al</span>., 2008</a>; <a class="elsevierStyleCrossRef" href="#bib0050">Lee <span class="elsevierStyleItalic">et al</span>.,2008</a>]. Our results seem to support this suggestion.</p><p id="par0150" class="elsevierStylePara elsevierViewall">However, temperature variations observed in the numerical experiment IC, are similar to those that occurred in experiments in which the TSI was varied, in the sense that the changes are observed in the same zones and of the same order of magnitude. However, the calculated model sensitivity shows that the sign corresponding to the TSI variations is opposite to the sign of the change in initial conditions (<a class="elsevierStyleCrossRef" href="#f0030">Figure 6a</a>, <a class="elsevierStyleCrossRef" href="#f0035">7a</a>). This would suggest that in this model the temperature changes observed due to different conditions of TSI are different from variations in the IC. Although we have only one IC experiment, this gives an idea of the order of magnitude expected for the differences that can be found for a small change in the initial conditions.<a name="p159"></a><a name="p160"></a><a name="p161"></a></p><p id="par0155" class="elsevierStylePara elsevierViewall">Therefore, we conclude that changes in TSI produce changes similar to those of a disturbance in the initial conditions, but do not lead to significant changes in the conditions of the average temperature. Probably significant temperature variations will be produced if larger TSI changes occurred. To have more conclusive results concerning the sensitivity of the model to TSI variations leading to effects on weather, it will be desirable to couple the WRF model with an ocean model in order to allow the ocean heat content change under different TSI conditions. Our results are relevant for climate change experiments using the technique of downscaling [<a class="elsevierStyleCrossRef" href="#bib0025">Giorgi <span class="elsevierStyleItalic">et al</span>, 2009</a>] because it highlights the importance of using coupled ocean-atmosphere models to get a better temperature setting.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres498001" "titulo" => "Resumen" "secciones" => array:1 [ 0 => array:1 [ "identificador" => "abst0005" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec519548" "titulo" => "Palabras clave" ] 2 => array:3 [ "identificador" => "xres498002" "titulo" => "Abstract" "secciones" => array:1 [ 0 => array:1 [ "identificador" => "abst0010" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec519549" "titulo" => "Key words" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:2 [ "identificador" => "sec0010" "titulo" => "The Weather Research and Forecasting Model (WRF)" ] 6 => array:2 [ "identificador" => "sec0015" "titulo" => "Sensitivity of the surface temperature" ] 7 => array:2 [ "identificador" => "sec0020" "titulo" => "Description of Non-dimensional parameters technique" ] 8 => array:2 [ "identificador" => "sec0025" "titulo" => "Simulation configuration" ] 9 => array:2 [ "identificador" => "sec0030" "titulo" => "Results" ] 10 => array:2 [ "identificador" => "sec0035" "titulo" => "Conclusions" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2013-01-14" "fechaAceptado" => "2013-09-03" "PalabrasClave" => array:2 [ "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec519548" "palabras" => array:5 [ 0 => "WRF" 1 => "sensibilidad de la temperature" 2 => "radiación solar total" 3 => "Atlántico Norte" 4 => "técnica de parámetros adimensionales" ] ] ] "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Key words" "identificador" => "xpalclavsec519549" "palabras" => array:5 [ 0 => "WRF model" 1 => "sensivity temperature" 2 => "total solar irradiance" 3 => "North Atlantic" 4 => "non-dimensional parameters technique" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "es" => array:2 [ "titulo" => "Resumen" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">En este trabajo se estima la sensibilidad de la temperatura del modelo WRF a cambios en la Radiación Solar Total (RST). Las simulaciones se realizaron para una región centrada en el Atlántico norte, incluyendo partes del Este de Norteamérica, Oeste de Europa y Noroeste de África. Para esto, se realizaron 4 simulaciones iguales, donde el único parámetro que se modificó fue la RST. Adicionalmente, se realizó una quinta simulación donde se cambiaron las condiciones iniciales atmosféricas, para comparar el efecto del cambio de la RST sobre la temperatura con el de un cambio en el día de inicio de la integración. Se compararon promedios mensuales de temperatura para cada simulación obteniéndose que tanto los cambios en las condiciones iniciales como los de la RST tienen un impacto medible en la temperatura de la región de estudio. Se presenta también una estimación de la sensibilidad del modelo usando parámetros adimensionales. Con estos experimentos numéricos encontramos algunos rasgos que permitirían distinguir entre los efectos de cambios de la RST y en las condiciones iniciales sobre la temperatura. Sin embargo, los cambios debidos al RST son de la misma magnitud que los cambios debidos a las variaciones en las condiciones iniciales. Se observa también que, en promedio y sobre toda la malla, la temperatura promedio no sufre cambios significativos ni ante cambios de la RST ni ante los de las condiciones iniciales.</p></span>" ] "en" => array:2 [ "titulo" => "Abstract" "resumen" => "<span id="abst0010" class="elsevierStyleSection elsevierViewall"><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">The temperature sensitivity of the WRF model to changes in Total Solar Irradiance (TSI). The simulations were performed for a region centered over the North Atlantic Ocean, including portions of Eastern North America, Western Europe and Northwest Africa. Four simulations were run with different TSI values. Also, a fifth simulation was performed in which we varied the initial atmospheric conditions, in order to compare the effect on the temperature of both, changes in the TSI and initial atmospheric conditions. Comparing temperature monthly averages we found that changes in TSI and in the initial conditions have a measurable impact on temperature in the region of study. The sensitivity of the model using non-dimensional parameters was also estimated. The numerical experiments show some features that might allow to distinguish between the effects on the temperature due to changes in TSI from those caused by initial conditions. However, TSI changes are of the same order of magnitude than those of disturbances in the initial conditions. We also found that the mean monthly values of temperature over the full grid, did not present significant variations due to changes of either initial conditions or TSI.</p></span>" ] ] "multimedia" => array:12 [ 0 => array:7 [ "identificador" => "f0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1033 "Ancho" => 1143 "Tamanyo" => 127716 ] ] "descripcion" => array:1 [ "en" => "<p id="sp0005" class="elsevierStyleSimplePara elsevierViewall">Domain used in the numerical simulations. We divided the domain in five zones, the corresponding coordinates appear in the center of the squares.</p>" ] ] 1 => array:7 [ "identificador" => "f0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1349 "Ancho" => 1878 "Tamanyo" => 550614 ] ] "descripcion" => array:1 [ "en" => "<p id="sp0010" class="elsevierStyleSimplePara elsevierViewall">Average monthly surface temperature differences (ºC) for September, October, November and December, 1983. The first column shows D_HR, the second D_LR, the third D_FMR and the fourth D_CI.</p>" ] ] 2 => array:7 [ "identificador" => "f0015" "etiqueta" => "Figure 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 1350 "Ancho" => 1879 "Tamanyo" => 527184 ] ] "descripcion" => array:1 [ "en" => "<p id="sp0015" class="elsevierStyleSimplePara elsevierViewall">Average monthly surface temperature differences (ºC) for January, February, March and April, 1984. The first column shows D_HR, the second D_LR, the third D_FMR and the fourth D_CI.</p>" ] ] 3 => array:7 [ "identificador" => "f0020" "etiqueta" => "Figure 4" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr4.jpeg" "Alto" => 1351 "Ancho" => 1879 "Tamanyo" => 535989 ] ] "descripcion" => array:1 [ "en" => "<p id="sp0020" class="elsevierStyleSimplePara elsevierViewall">Average monthly surface temperature differences (ºC) for May, June, July and August 1984. The first column shows D_HR, the second D_LR, the third D_FMR and the fourth D_CI.</p>" ] ] 4 => array:7 [ "identificador" => "f0025" "etiqueta" => "Figure 5" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr5.jpeg" "Alto" => 1214 "Ancho" => 1165 "Tamanyo" => 147485 ] ] "descripcion" => array:1 [ "en" => "<p id="sp0025" class="elsevierStyleSimplePara elsevierViewall">Monthly average temperature (ºC) for five simulations in: a) The whole area of study. b) Zone A. c) Zone B. d) Zone C. e) Zone D. f) Zone E.</p>" ] ] 5 => array:7 [ "identificador" => "f0030" "etiqueta" => "Figure 6" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr6.jpeg" "Alto" => 1019 "Ancho" => 1882 "Tamanyo" => 221351 ] ] "descripcion" => array:1 [ "en" => "<p id="sp0030" class="elsevierStyleSimplePara elsevierViewall">Monthly temperature sensitivity in: a) The whole area of study. b) Zone A. c) Zone B. d) Zone C. e) Zone D. f) Zone E.</p>" ] ] 6 => array:7 [ "identificador" => "f0035" "etiqueta" => "Figure 7" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr7.jpeg" "Alto" => 1022 "Ancho" => 1879 "Tamanyo" => 195044 ] ] "descripcion" => array:1 [ "en" => "<p id="sp0035" class="elsevierStyleSimplePara elsevierViewall">Daily temperature sensitivity in: a) The whole area of study. b) Zone A. c) Zone B. d) Zone C. e) Zone D. f) Zone E.</p>" ] ] 7 => array:7 [ "identificador" => "f0040" "etiqueta" => "Figure 8" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr8.jpeg" "Alto" => 1850 "Ancho" => 1859 "Tamanyo" => 772642 ] ] "descripcion" => array:1 [ "en" => "<p id="sp0040" class="elsevierStyleSimplePara elsevierViewall">Average monthly differences a) Sensible Heat. b) Latent Heat. c) Surface Pressure. d) Precipitation, for November, 1983. The first column shows D_HR, the second D_LR, the third D_FMR.</p>" ] ] 8 => array:7 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">Experiment \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black">TSI (<span class="elsevierStyleItalic">W/m</span><span class="elsevierStyleSup">3</span>) \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " align="center" valign="top">Base \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">1366.2 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="center" valign="top">HR \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">1366.8 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="center" valign="top">LR \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">1365.5 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="center" valign="top">FMR \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">1364.9 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="center" valign="top">CI \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">1366.2 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab795068.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">TSI values used in the four WRF simulations.</p>" ] ] 9 => array:6 [ "identificador" => "eq0005" "etiqueta" => "(1)" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "(1-α)S=4σT¯4" "Fichero" => "si1.jpeg" "Tamanyo" => 996 "Alto" => 17 "Ancho" => 116 ] ] 10 => array:6 [ "identificador" => "eq0010" "etiqueta" => "(2)" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "βT=1-k1∂T∂S" "Fichero" => "si2.jpeg" "Tamanyo" => 998 "Alto" => 21 "Ancho" => 107 ] ] 11 => array:6 [ "identificador" => "eq0015" "etiqueta" => "(3)" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "βT=1-(T0T)3" "Fichero" => "si3.jpeg" "Tamanyo" => 984 "Alto" => 25 "Ancho" => 94 ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:15 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "Barriopedro et al., 2008" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Solar modulation of northern hemisphere winter blocking" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:3 [ 0 => "D. 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| Year/Month | Html | Total | |
|---|---|---|---|
| 2024 November | 1 | 0 | 1 |
| 2024 October | 14 | 1 | 15 |
| 2024 September | 9 | 2 | 11 |
| 2024 August | 12 | 7 | 19 |
| 2024 July | 21 | 3 | 24 |
| 2024 June | 19 | 1 | 20 |
| 2024 May | 18 | 2 | 20 |
| 2024 April | 15 | 4 | 19 |
| 2024 March | 17 | 1 | 18 |
| 2024 February | 22 | 6 | 28 |
| 2024 January | 23 | 3 | 26 |
| 2023 December | 24 | 11 | 35 |
| 2023 November | 33 | 8 | 41 |
| 2023 October | 43 | 12 | 55 |
| 2023 September | 11 | 3 | 14 |
| 2023 August | 17 | 4 | 21 |
| 2023 July | 21 | 5 | 26 |
| 2023 June | 12 | 1 | 13 |
| 2023 May | 29 | 2 | 31 |
| 2023 April | 15 | 2 | 17 |
| 2023 March | 14 | 5 | 19 |
| 2023 February | 15 | 4 | 19 |
| 2023 January | 13 | 12 | 25 |
| 2022 December | 14 | 10 | 24 |
| 2022 November | 13 | 8 | 21 |
| 2022 October | 8 | 6 | 14 |
| 2022 September | 7 | 13 | 20 |
| 2022 August | 13 | 13 | 26 |
| 2022 July | 20 | 6 | 26 |
| 2022 June | 18 | 7 | 25 |
| 2022 May | 24 | 12 | 36 |
| 2022 April | 12 | 6 | 18 |
| 2022 March | 17 | 8 | 25 |
| 2022 February | 10 | 6 | 16 |
| 2022 January | 24 | 7 | 31 |
| 2021 December | 13 | 5 | 18 |
| 2021 November | 13 | 13 | 26 |
| 2021 October | 16 | 15 | 31 |
| 2021 September | 9 | 11 | 20 |
| 2021 August | 19 | 19 | 38 |
| 2021 July | 23 | 6 | 29 |
| 2021 June | 18 | 9 | 27 |
| 2021 May | 20 | 8 | 28 |
| 2021 April | 100 | 14 | 114 |
| 2021 March | 15 | 8 | 23 |
| 2021 February | 14 | 8 | 22 |
| 2021 January | 19 | 20 | 39 |
| 2020 December | 11 | 3 | 14 |
| 2020 November | 34 | 12 | 46 |
| 2020 October | 19 | 4 | 23 |
| 2020 September | 13 | 6 | 19 |
| 2020 August | 16 | 8 | 24 |
| 2020 July | 10 | 1 | 11 |
| 2020 June | 23 | 4 | 27 |
| 2020 May | 17 | 4 | 21 |
| 2020 April | 16 | 2 | 18 |
| 2020 March | 17 | 5 | 22 |
| 2020 February | 16 | 3 | 19 |
| 2020 January | 22 | 2 | 24 |
| 2019 December | 19 | 1 | 20 |
| 2019 November | 19 | 4 | 23 |
| 2019 October | 15 | 3 | 18 |
| 2019 September | 19 | 3 | 22 |
| 2019 August | 6 | 3 | 9 |
| 2019 July | 13 | 4 | 17 |
| 2019 June | 22 | 2 | 24 |
| 2019 May | 53 | 2 | 55 |
| 2019 April | 22 | 13 | 35 |
| 2019 March | 3 | 3 | 6 |
| 2019 February | 6 | 7 | 13 |
| 2019 January | 5 | 6 | 11 |
| 2018 December | 2 | 0 | 2 |
| 2018 November | 1 | 2 | 3 |
| 2018 October | 2 | 4 | 6 |
| 2018 September | 7 | 2 | 9 |
| 2018 August | 2 | 1 | 3 |
| 2018 July | 0 | 1 | 1 |
| 2018 June | 3 | 0 | 3 |
| 2018 May | 4 | 6 | 10 |
| 2018 April | 5 | 0 | 5 |
| 2018 March | 1 | 0 | 1 |
| 2018 February | 7 | 4 | 11 |
| 2018 January | 2 | 4 | 6 |
| 2017 December | 2 | 0 | 2 |
| 2017 November | 9 | 5 | 14 |
| 2017 October | 10 | 3 | 13 |
| 2017 September | 4 | 8 | 12 |
| 2017 August | 4 | 1 | 5 |
| 2017 July | 7 | 0 | 7 |
| 2017 June | 12 | 0 | 12 |
| 2017 May | 7 | 3 | 10 |
| 2017 April | 4 | 15 | 19 |
| 2017 March | 2 | 93 | 95 |
| 2017 February | 4 | 4 | 8 |
| 2017 January | 7 | 0 | 7 |
| 2016 December | 11 | 2 | 13 |
| 2016 November | 14 | 4 | 18 |
| 2016 October | 11 | 6 | 17 |
| 2016 September | 17 | 2 | 19 |
| 2016 August | 8 | 1 | 9 |
| 2016 July | 10 | 0 | 10 |
| 2016 June | 14 | 8 | 22 |
| 2016 May | 7 | 14 | 21 |
| 2016 April | 7 | 3 | 10 |
| 2016 March | 4 | 2 | 6 |
| 2016 February | 3 | 7 | 10 |
| 2016 January | 4 | 5 | 9 |
| 2015 December | 3 | 2 | 5 |
| 2015 November | 6 | 4 | 10 |
| 2015 October | 14 | 4 | 18 |
| 2015 September | 13 | 4 | 17 |
| 2015 August | 3 | 3 | 6 |
| 2015 July | 7 | 4 | 11 |
| 2015 June | 2 | 0 | 2 |
| 2015 May | 2 | 2 | 4 |
| 2015 April | 3 | 5 | 8 |
| 2015 March | 3 | 0 | 3 |
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