Search

Aims: We characterize the solar rotational modulations of spectral solar irradiance (SSI) and compare them with the corresponding changes of total solar irradiance (TSI). Solar rotational modulations of TSI and SSI at wavelengths between 120 and 1600 nm are identified over one hundred Carrington rotational cycles during 2003–2013. Methods: The SORCE (Solar Radiation and Climate Experiment) and TIMED (Thermosphere Ionosphere Mesosphere Energetics and Dynamics)/SEE (Solar EUV Experiment) measured and SATIRE-S modeled solar irradiances are analyzed using the EEMD (Ensemble Empirical Mode Decomposition) method to determine the phase and amplitude of 27-day solar rotational variation in TSI and SSI. Results: The mode decomposition clearly identifies 27-day solar rotational variations in SSI between 120 and 1600 nm, and there is a robust wavelength dependence in the phase of the rotational mode relative to that of TSI. The rotational modes of visible (VIS) and near infrared (NIR) are in phase with the mode of TSI, but the phase of the rotational mode of ultraviolet (UV) exhibits differences from that of TSI. While it is questionable that the VIS to NIR portion of the solar spectrum has yet been observed with sufficient accuracy and precision to determine the 11-year solar cycle variations, the temporal variations over one hundred cycles of 27-day solar rotation, independent of the two solar cycles in which they are embedded, show distinct solar rotational modulations at each wavelength.

Simulations of climate over the Last Millennium (850–1850 CE) have been incorporated into the third phase of the Paleoclimate Modelling Intercomparison Project (PMIP3). The drivers of climate over this period are chiefly orbital, solar, volcanic, changes in land use/land cover and some variation in greenhouse gas levels. While some of these effects can be easily defined, the reconstructions of solar, volcanic and land use-related forcing are more uncertain. We describe here the approach taken in defining the scenarios used in PMIP3, document the forcing reconstructions and discuss likely implications.

Warming of the global climate is usually correlated with atmospheric carbon dioxide (CO2) concentration. The sensitivity of global surface temperature to rising CO2 concentration was evaluated over the period 1853 to present. Publicly available datasets were used including temperature anomalies, CO2 concentration, global sea level, oceanic oscillations, solar activity, and magnetic field declination. A specific, statistically significant contribution to global warming of the CO2 atmospheric concentration could not be extracted from the available dataset. While comparing the calculation results from a simple radiative forcing and feedback model with the observed global warming, the CO2 contribution is estimated to be less than 25 to 30% of the total, while other causes contribute for the rest. Thus, the “Equilibrium Climate Sensitivity” is estimated to be at 0.53°C (0.42 to 0.73)., Le réchauffement climatique est habituellement mis en corrélation avec la concentration atmosphérique en dioxyde de carbone (CO2). La sensibilité de la température superficielle globale à la concentration en CO2 a été évaluée sur la période de 1853 à nos jours. Des séries de données accessibles au public on été utilisées incluant les anomalies de température, la concentration en CO2, le niveau global des mers, les oscillations océaniques, l'activité solaire, et la déclinaison du champ magnétique. Aucune contribution statistiquement significative au réchauffement global n'a pu être attribuée à la seule concentration atmosphérique en CO2. En comparant le réchauffement observé avec le résultat du calcul d'un modèle simple de forçage radiatif avec rétroaction, la contribution du CO2 est estimée à moins de 25 à 30% du tout, alors que d'autres causes contribuent au reste. Ainsi la "Equilibrium Climate Sensitivity" est estimée à 0.53°C (0.42 à 0.73).

International audience; The accurate determination of the solar photospheric radius has been an important problem in astronomy for many centuries. From the measurements made by the PICARD spacecraft during the transit of Venus in 2012, we obtained a solar radius of 696,156 ±145 kilometres. This value is consistent with recent measurements carried out atmosphere. This observation leads us to propose a change of the canonical value obtained by Arthur Auwers in 1891. An accurate value for total solar irradiance (TSI) is crucial for the Sun-Earth connection, and represents another solar astrophysical fundamental parameter. Based on measurements collected from different space instruments over the past 35 years, the absolute value of the TSI, representative of a quiet Sun, has gradually decreased from 1,371W.m−2 in 1978 to around 1,362W.m−2 in 2013, mainly due to the radiometers calibration differences. Based on the PICARD data and in agreement with Total Irradiance Monitor measurements, we predicted the TSI input at the top of the Earth's atmosphere at a distance of one astronomical unit (149,597,870kilometres) from the Sun to be 1,362±2.4W.m−2, which may be proposed as a reference value. To conclude, from the measurements made by the PICARD spacecraft, we obtained a solar photospheric equator-to-pole radius difference value of 5.9 ±0.5 kilometres. This value is consistent with measurements made by different space instruments, and can be given as a reference value.

Aims. The existing records of total solar irradiance (TSI) since 1978 differ not only in absolute values, but also show different trends. For the study of TSI variability these records need to be combined and three composites have been devised; however, the results depend on the choice of the records and the way they are combined. A new composite should be based on all existing records with an individual qualification. It is proposed to use a time-dependent uncertainty for weighting of the individual records. Methods. The determination of the time-dependent deviation of the TSI records is performed by comparison with the square root of the sunspot number (SSN). However, this correlation is only valid for timescales of the order of a year or more because TSI and SSN react quite differently to solar activity changes on shorter timescales. Hence the results concern only periods longer than the one-year-low-pass filter used in the analysis. Results. Besides the main objective to determine an investigator-independent uncertainty, the comparison of TSI with √SSN turns out to be a powerful tool for the study of the TSI long-term changes. The correlation of √SSN with TSI replicates very well the TSI minima, especially the very low value of the recent minimum. The results of the uncertainty determination confirm not only the need for adequate corrections for degradation, but also show that a rather detailed analysis is needed. The daily average of all TSI values available on that day, weighted with the correspondingly determined uncertainty, is used to construct a “new” composite, which, overall, compares well with the Physikalisch-Meteorologisches Observatorium Davos (PMOD) composite. Finally, the TSI − √SSN comparison proves to be an important diagnostic tool not only for estimating uncertainties of observations, but also for a better understanding of the long-term variability of TSI.

The penetration and acceptance of Renewable Energy Sources has already taken place in our lives. Solar Energy is the feedstock for various applications of Renewable Energy Systems (RES), thus, the knowledge of the intensity of the incident solar irradiance is essential for monitoring the performance of such systems. The only unpredictable factor in defining the solar irradiance and the performance of the systems is clouds. So far, various researchers proposed several models for the estimation of solar irradiance in correlation to cloud coverage and cloud type. The present work describes the development of a simple method for cloud detection and computation of short-term cloud motion using a Nikon D3100 camera with a 18–55 mm VR lens, positioned on a tripod in Limassol, Cyprus. The method used for distinguishing clouds from the sky is the “Red-Blue threshold”. Additionally, the results of the cloud distinction are used to calculate the future position of clouds. The developed methodology will provide a useful tool for researchers that want to focus on the effect of small local clouds on the energy production of their solar RES. The maximum error in our model was 12% for the prediction of the cloud location eight time steps in advance with only two cloud images processed.

A recent study has suggested a link between the surface level diurnal temperature range (DTR) and variations in the cosmic ray (CR) flux. As the DTR is an effective proxy for cloud cover, this result supports the notion that widespread cloud changes may be induced by the CR flux. If confirmed, this would have significant implications for our understanding of natural climate forcings. Here, we perform a detailed investigation of the relationships between DTR and solar activity (total solar irradiance and the CR flux) from more than 60 years of NCEP/NCAR reanalysis data and observations from meteorological station data. We find no statistically significant evidence to suggest that the DTR is connected to either long- term solar periodicities (11 or 1.68-year) or short-term (daily timescale) fluctuations in solar activity, and we attribute previous reports on the contrary to an incorrect estimation of the statistical significance of the data. If a CR–DTR relationship exists, based on the estimated noise in DTR composites during Forbush decrease (FD) events, the DTR response would need to be larger than 0.03°C per 1% increase in the CR flux to be reliably detected. Compared with a much smaller rough estimate of −0.005°C per 1% increase in the CR flux expected if previous claims that FD events cause reductions in the cloud cover are valid, we conclude it is not possible to detect a solar related responses in station-based or reanalysis- based DTR data sets related to a hypothesized CR– cloud link, as potential signals would be drowned in noise.

Although over long (centennial) timescales solar variability may be one of the most important natural causes of climate change, the extent to which solar activity may influence Earth's climate over shorter time periods is still poorly understood. It has been proposed that a solar-atmosphere link may influence climate variability. If such a link is operating, it is likely via one (or a combination) of the following three factors: total solar irradiance (TSI), ultraviolet (UV) spectral irradiance, or cosmic rays (CR). We present an analysis of the largest short-term TSI variations recorded by Active Cavity Radiometer Irradiance Monitor (ACRIM measurements), using an epoch-superposition (composite) approach, and test a possible link between TSI and several key atmospheric parameters. The statistical significance of these parameters is evaluated using Monte Carlo simulation techniques. Additionally, the relevance of our results will be discussed in relation to the CR-cloud connection hypothesis, as an extension to previous Forbush decreases studies and other related literature.

Although over centennial and greater timescales solar variability may be one of the most influential climate forcing agents, the extent to which solar activity may influence climate over shorter time periods is still currently poorly understood. If such a link is operating, it is likely via a mechanism connected to one (or a combination) of the following three parameters: total solar irradiance (TSI), ultraviolet (UV) spectral irradiance, or the galactic cosmic ray (GCR) flux. In this work, we present an analysis based around a superposed epoch (composite) approach focusing on the largest TSI variations obtained from the Active Cavity Radiometer Irradiance Monitor (ACRIM) reconstructions occurring over short (daily) timescales. Using this composite together with the cloud data (ISCCP, MODIS) we test for the presence of a possible link between solar activity and cloud cover over large areas of the globe. The statistical significance of the obtained correlations are evaluated using rigorous statistical techniques such as Monte Carlo simulations. The relevance of our results are also examined in relation to a suggested GCR cloud cover link.

La variabilidad solar es una de las principales influencias naturales del clima terrestre, y que afecta profundamente a los procesos biológicos. Se ha propuesto que algunos de estos procesos biológicos alteran el albedo y por tanto tienen un impacto en el clima. En este trabajo investigamos la relación entre la irradiancia total solar (ITS) y la concentración de Dimetilsulfuro (DMS), que es producido por algas marinas. El DMS se ha mencionado frecuentemente como un forzamiento climático a través de su efecto en las nubes y por tanto en el albedo. En el presente trabajo encontramos que las series temporales de la IST y el DMS muestran una correlación. Para ello utilizamos un esquema probabilístico, la Función de Información Mutua (FIM), que es una medida de la dependencia entre los parámetros de interés. La FIM presenta una dependencia con el ciclo solar: valores mayores aparecen durante épocas de baja actividad solar (épocas de menor IST), mientras que los valores menores se presentan durante tiempos de alta actividad solar (mayor IST). En otras palabras, la dependencia entre IST y DMS es más fuerte durante épocas de actividad solar menor que durante actividad solar mayor.

Resumen En este trabajo se estima la sensibilidad de la temperatura del modelo WRF a cambios en la Radiacion Solar Total (RST). Las simulaciones se realizaron para una region centrada en el Atlantico norte, incluyendo partes del Este de Norteamerica, Oeste de Europa y Noroeste de Africa. Para esto, se realizaron 4 simulaciones iguales, donde el unico parametro que se modifico fue la RST. Adicionalmente, se realizo una quinta simulacion donde se cambiaron las condiciones iniciales atmosfericas, para comparar el efecto del cambio de la RST sobre la temperatura con el de un cambio en el dia de inicio de la integracion. Se compararon promedios mensuales de temperatura para cada simulacion obteniendose que tanto los cambios en las condiciones iniciales como los de la RST tienen un impacto medible en la temperatura de la region de estudio. Se presenta tambien una estimacion de la sensibilidad del modelo usando parametros adimensionales. Con estos experimentos numericos encontramos algunos rasgos que permitirian 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 tambien 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.Palabras clave: WRF, sensibilidad de la temperatura, radiacion solar total, Atlantico Norte, tecnica de parametros adimensionales.