14 research outputs found
Comment on "Scaling of atmosphere and ocean temperature correlations in observations and climate models"
In a recent letter [K. Fraedrich and R. Blender, Phys. Rev. Lett. 90, 108501
(2003)], Fraedrich and Blender studied the scaling of atmosphere and ocean
temperature. They analyzed the fluctuation functions F(s) ~ s^alpha of monthly
temperature records (mostly from grid data) by using the detrended fluctuation
analysis (DFA2) and claim that the scaling exponent alpha over the inner
continents is equal to 0.5, being characteristic of uncorrelated random
sequences. Here we show that this statement is (i) not supported by their own
analysis and (ii) disagrees with the analysis of the daily observational data
from which the grid monthly data have been derived. We conclude that also for
the inner continents, the exponent is between 0.6 and 0.7, similar as for the
coastline-stations.Comment: 1 page with 2 figure
Long term persistence in the sea surface temperature fluctuations
We study the temporal correlations in the sea surface temperature (SST)
fluctuations around the seasonal mean values in the Atlantic and Pacific
oceans. We apply a method that systematically overcome possible trends in the
data. We find that the SST persistence, characterized by the correlation
of temperature fluctuations separated by a time period , displays two
different regimes. In the short-time regime which extends up to roughly 10
months, the temperature fluctuations display a nonstationary behavior for both
oceans, while in the asymptotic regime it becomes stationary. The long term
correlations decay as with for both
oceans which is different from found for atmospheric land
temperature.Comment: 14 pages, 5 fiure
Volcanic forcing improves Atmosphere-Ocean Coupled General Circulation Model scaling performance
Recent Atmosphere-Ocean Coupled General Circulation Model (AOGCM) simulations
of the twentieth century climate, which account for anthropogenic and natural
forcings, make it possible to study the origin of long-term temperature
correlations found in the observed records. We study ensemble experiments
performed with the NCAR PCM for 10 different historical scenarios, including no
forcings, greenhouse gas, sulfate aerosol, ozone, solar, volcanic forcing and
various combinations, such as it natural, anthropogenic and all forcings. We
compare the scaling exponents characterizing the long-term correlations of the
observed and simulated model data for 16 representative land stations and 16
sites in the Atlantic Ocean for these scenarios. We find that inclusion of
volcanic forcing in the AOGCM considerably improves the PCM scaling behavior.
The scenarios containing volcanic forcing are able to reproduce quite well the
observed scaling exponents for the land with exponents around 0.65 independent
of the station distance from the ocean. For the Atlantic Ocean, scenarios with
the volcanic forcing slightly underestimate the observed persistence exhibiting
an average exponent 0.74 instead of 0.85 for reconstructed data.Comment: 4 figure
Long-term power-law fluctuation in Internet traffic
Power-law fluctuation in observed Internet packet flow are discussed. The
data is obtained by a multi router traffic grapher (MRTG) system for 9 months.
The internet packet flow is analyzed using the detrended fluctuation analysis.
By extracting the average daily trend, the data shows clear power-law
fluctuations. The exponents of the fluctuation for the incoming and outgoing
flow are almost unity. Internet traffic can be understood as a daily periodic
flow with power-law fluctuations.Comment: 10 pages, 8 figure
Detrended fluctuation analysis as a statistical tool to monitor the climate
Detrended fluctuation analysis is used to investigate power law relationship
between the monthly averages of the maximum daily temperatures for different
locations in the western US. On the map created by the power law exponents, we
can distinguish different geographical regions with different power law
exponents. When the power law exponents obtained from the detrended fluctuation
analysis are plotted versus the standard deviation of the temperature
fluctuations, we observe different data points belonging to the different
climates, hence indicating that by observing the long-time trends in the
fluctuations of temperature we can distinguish between different climates.Comment: 8 pages, 4 figures, submitted to JSTA
Investigation on gait by means of factorial moments
By means of Factorial Moments(FM), the long-range correlations embedded in
gait time series are investigated. It is found that FM is an effective tool to
deal with this kind of time series. Keywords: Factorial Moments,Time series,
Long-range correlationsComment: 10pages, 3figures. submitte