Estimated global contributions to the global mean temperature based on the product between the spatial patterns shown in figure 1 and the time series for ENSO, GHGs, and GCR respectively
Rasmus E Benestad
10.6084/m9.figshare.1011927.v1
https://iop.figshare.com/articles/figure/_Estimated_global_contributions_to_the_global_mean_temperature_based_on_the_product_between_the_spat/1011927
<p><strong>Figure 2.</strong> Estimated global contributions to the global mean temperature based on the product between the spatial patterns shown in figure <a href="http://iopscience.iop.org/1748-9326/8/3/035049/article#erl479051fig1" target="_blank">1</a> and the time series for ENSO, GHGs, and GCR respectively. The grey curve shows the sum of the three variables. GISSTEMP is in black and 20C reanalysis in dark grey.</p> <p><strong>Abstract</strong></p> <p>Variations in the annual mean of the galactic cosmic ray flux (GCR) are compared with annual variations in the most common meteorological variables: temperature, mean sea-level barometric pressure, and precipitation statistics. A multiple regression analysis was used to explore the potential for a GCR response on timescales longer than a year and to identify 'fingerprint' patterns in time and space associated with GCR as well as greenhouse gas (GHG) concentrations and the El Niño–Southern Oscillation (ENSO). The response pattern associated with GCR consisted of a negative temperature anomaly that was limited to parts of eastern Europe, and a weak anomaly in the sea-level pressure (SLP), but coincided with higher pressure over the Norwegian Sea. It had a similarity to the North Atlantic Oscillation (NAO) in the northern hemisphere and a wave train in the southern hemisphere. A set of Monte Carlo simulations nevertheless indicated that the weak amplitude of the global mean temperature response associated with GCR could easily be due to chance (<em>p</em>-value = 0.6), and there has been no trend in the GCR. Hence, there is little empirical evidence that links GCR to the recent global warming.</p>
2013-09-23 00:00:00
nao
20 C reanalysis
ray flux
regression analysis
precipitation statistics
Abstract Variations
gisstemp
slp
temperature response
North Atlantic Oscillation
time series
wave train
ghg
Monte Carlo simulations
Norwegian Sea
temperature anomaly
enso
response pattern
GCR response
greenhouse gas
links GCR
Environmental Science