Friday, May 23, 2014

New paper finds natural variability of N Carolina climate explained by solar activity & AMO

A paper published today in Nonlinear Processes in Geophysics finds "the natural variability of climate change in NC [North Carolina] during 1950–2009 can be explained mostly by the AMO [Atlantic Multidecadal Oscillation] and solar activity." 

Prior papers have also found the AMO driven by solar activity. Climate scientists claim the tiny 0.1% variations in total solar irradiance over solar cycles cannot affect climate, but this paper and many others suggest that solar amplification mechanisms including via ocean oscillations can cause large scale effects on climate. 

Nonlin. Processes Geophys., 21, 605-615, 2014

M. Gorji Sefidmazgi1, M. Sayemuzzaman2, A. Homaifar1, M. K. Jha3, and S. Liess4
1North Carolina A&T State University, Dept. of Electrical Engineering, Greensboro, USA
2North Carolina A&T State University, Dept. of Energy and Environmental Systems, Greensboro, USA
3North Carolina A&T State University, Dept. of Civil, Architectural and Environmental Engineering, Greensboro, USA
4University of Minnesota, Department of Soil, Water and Climate, St. Paul, USA

Abstract. In order to analyze low-frequency variability of climate, it is useful to model the climatic time series with multiple linear trends and locate the times of significant changes. In this paper, we have used non-stationary time series clustering to find change points in the trends. Clustering in a multi-dimensional non-stationary time series is challenging, since the problem is mathematically ill-posed. Clustering based on the finite element method (FEM) is one of the methods that can analyze multidimensional time series. One important attribute of this method is that it is not dependent on any statistical assumption and does not need local stationarity in the time series. In this paper, it is shown how the FEM-clustering method can be used to locate change points in the trend of temperature time series from in situ observations. This method is applied to the temperature time series of North Carolina (NC) and the results represent region-specific climate variability despite higher frequency harmonics in climatic time series. Next, we investigated the relationship between the climatic indices with the clusters/trends detected based on this clustering method. It appears that the natural variability of climate change in NC [North Carolina] during 1950–2009 can be explained mostly by AMO and solar activity.

1 comment:

  1. Furthermore, the AMO is modulated by the solar cycle.

    There are some interesting lags and leadings, but you can see how for each solar cycle peak there's a corresponding peak in the AMO.

    The relative size of each peak is about 0.1 C, which is quite large when you consider the AMO is based on sea surface temperatures.

    Any climate scientist who does not accept how large the solar effect is over the solar cycle and the de Vries cycle has their head in a bag.