Der klimatische Einfluss von Sonnenaktivitätsschwankungen auf das Erdklima wird kontrovers diskutiert. Das verwundert, denn die Literaturlage ist eigentlich klar: Die Handschrift der Sonne wurde in unzähligen Fallstudien eindrucksvoll beschrieben. Gehen Sie mal zu Google Scholar und suchen nach „solar forcing“. Resultat: 17.500 Treffer.
Heute stellen wir Ihnen einige neuere Arbeiten vor:
Nitka & Burnecki (2019) konnten einen Einfluss der Sonnenaktivität in den Regenfälle der USA finden, und zwar in einigen Monaten und mit Zeitverzögerungseffekten:
Impact of solar activity on precipitation in the United States
In this paper we analyze the relationship between the sunspot numbers and the average monthly precipitation measured at meteorological stations in the US. The results indicate that there is a significant correlation between the solar activity and the monthly average precipitation data for selected months and time delays. In order to confirm the relationship, for the precipitation data we check the forecasting abilities of a popular time series model with and without additional information on the sun activity. Namely, first we fit the autoregressive moving average (ARMA) time series model to the US precipitation data and calculate one-step ahead forecasts. Next, we repeat the same steps with the ARMA model with exogenous input (ARMAX) which is the sunspot number data. We show that the forecast errors are essentially lower for the ARMAX model for months and time delays found in the correlation analysis.
Wallace (2019) untersuchte die Wasserführung von Flüssen im Westen der USA und fand eine gute Korrelation mit der Sonne. Die Verbindung scheint über die solar beeinflussten Passatwinde zu geschehen:
Application of lagged correlations between solar cycles and hydrosphere components towards sub-decadal forecasts of streamflows in the Western USA
Trade winds localized within the Western Equatorial Pacific express lagged and statistically significant correlations to sunspot numbers as well as to streamflow in rivers of the Southern Rocky Mountains. Both correlation sets were integrated in a linear regression analysis to produce relatively accurate sub-decadal streamflow forecasts for an annual and a 5-year average. In comparison to the autocorrelation technique, the prototyped method yielded the highest correlations, the highest goodness-of-fit scores, and the lowest root mean squared errors, for both the 5-year average and the annual average assignments. Of all of the cases examined, the highest Kolmogorov-Smirnov test scores between observation and prediction were found for the single solar-based forecast 5 years in advance for the 60-month average streamflow of the Animas River in New Mexico.
Roy (2018) entdeckte den solaren 11-Jahreszyklus im arktischen Winterklima. Der Mechanismus läuft über die Stratosphäre und den Ozeanzyklus der Arktischen Oszillation (AO):
Solar cyclic variability can modulate winter Arctic climate
This study investigates the role of the eleven-year solar cycle on the Arctic climate during 1979–2016. It reveals that during those years, when the winter solar sunspot number (SSN) falls below 1.35 standard deviations (or mean value), the Arctic warming extends from the lower troposphere to high up in the upper stratosphere and vice versa when SSN is above. The warming in the atmospheric column reflects an easterly zonal wind anomaly consistent with warm air and positive geopotential height anomalies for years with minimum SSN and vice versa for the maximum. Despite the inherent limitations of statistical techniques, three different methods – Compositing, Multiple Linear Regression and Correlation – all point to a similar modulating influence of the sun on winter Arctic climate via the pathway of Arctic Oscillation. Presenting schematics, it discusses the mechanisms of how solar cycle variability influences the Arctic climate involving the stratospheric route. Compositing also detects an opposite solar signature on Eurasian snow-cover, which is a cooling during Minimum years, while warming in maximum. It is hypothesized that the reduction of ice in the Arctic and a growth in Eurasia, in recent winters, may in part, be a result of the current weaker solar cycle.
Der solare 11-Jahreszyklus hat übrigens nicht nur die Atmosphäre der Erde beeinflusst, sondern auch die von Uranus und Neptun, wie Aplin und Harrison (2016, 2017) dokumentieren konnten:
Solar‐Driven Variation in the Atmosphere of Uranus
Long‐term measurements (1972–2015) of the reflectivity of Uranus at 472 and 551 nm display variability that is incompletely explained by seasonal effects. Spectral analysis shows that this nonseasonal variability tracks the 11 year solar cycle. Two mechanisms could cause solar modulation: (a) nucleation onto ions or electrons created by galactic cosmic rays (GCR) or (b) UV‐induced aerosol color changes. Ion‐aerosol theory is used to identify expected relationships between reflectivity fluctuations and GCR flux, tested with multiple regression and compared to the linear response predicted between reflectivity and solar UV flux. The statistics show that 24% of the variance in reflectivity fluctuations at 472 nm is explained by GCR ion‐induced nucleation, compared to 22% for a UV‐only mechanism. Similar GCR‐related variability exists in Neptune’s atmosphere; hence, the effects found at Uranus provide the first example of common variability in two planetary atmospheres driven through energetic particle modulation by their host star.
Determining solar effects in Neptune’s atmosphere
Long-duration observations of Neptune’s brightness at two visible wavelengths provide a disk-averaged estimate of its atmospheric aerosol. Brightness variations were previously associated with the 11-year solar cycle, through solar-modulated mechanisms linked with either ultraviolet or galactic cosmic ray (GCR) effects on atmospheric particles. Here, we use a recently extended brightness data set (1972–2014), with physically realistic modelling to show, rather than alternatives, ultraviolet and GCR are likely to be modulating Neptune’s atmosphere in combination. The importance of GCR is further supported by the response of Neptune’s atmosphere to an intermittent 1.5- to 1.9-year periodicity, which occurred preferentially in GCR (not ultraviolet) during the mid-1980s. This periodicity was detected both at Earth, and in GCR measured by Voyager 2, then near Neptune. A similar coincident variability in Neptune’s brightness suggests nucleation onto GCR ions. Both GCR and ultraviolet mechanisms may occur more rapidly than the subsequent atmospheric particle transport.
Und hier noch ein Paper zum Thema von Zherebtsov et al. 2019:
Solar variability manifestations in weather and climate characteristics
We discuss the issues of primary importance to understand the nature of climate changes in the 20th century and main physical processes responsible for these changes and present a physical model for the solar activity (SA) effect on climate characteristics. A key concept of this model is the heliogeophysical disturbance effect on the Earth climate system parameters driving the long-wave radiation flux moving away from the Earth out into space in high-latitude regions. We address the solar activity effect on the changes in the temperature of the atmosphere and of the World Ocean. The aa–index of the geomagnetic activity (GA) was used as an SA proxy index. We discuss the results of analyzing the regularities and peculiarities of the tropospheric and sea surface temperature (SST) responses to both separate heliogeophysical disturbances and long-term changes in solar and geomagnetic activity. The structure of the tropospheric and SST temperature responses was shown to feature a spatial time irregularity. We revealed the regions, where long-term SST changes are determined mainly by SA variations.
Wenn Sie mehr zur Klimawirkung der Sonne auf das Erdklima wissen wollen, empfehlen wir Ihnen das folgende Interview der britischen Solarspezialistin Joanna D. Haigh:
Und hier noch Erläuterungen von Valentina Zharkova (Northumbria University) zur Klimawirkung der Sonne: