333 research outputs found
An evaluation of the accuracy of some radar wind profiling techniques
Major advances in Doppler radar measurement in optically clear air have made it feasible to monitor radial velocities in the troposphere and lower stratosphere. For most applications the three dimensional wind vector is monitored rather than the radial velocity. Measurement of the wind vector with a single radar can be made assuming a spatially linear, time invariant wind field. The components and derivatives of the wind are estimated by the parameters of a linear regression of the radial velocities on functions of their spatial locations. The accuracy of the wind measurement thus depends on the locations of the radial velocities. The suitability is evaluated of some of the common retrieval techniques for simultaneous measurement of both the vertical and horizontal wind components. The techniques considered for study are fixed beam, azimuthal scanning (VAD) and elevation scanning (VED)
Power-law persistence and trends in the atmosphere: A detailed study of long temperature records
We use several variants of the detrended fluctuation analysis to study the
appearance of long-term persistence in temperature records, obtained at 95
stations all over the globe. Our results basically confirm earlier studies. We
find that the persistence, characterized by the correlation C(s) of temperature
variations separated by s days, decays for large s as a power law, C(s) ~
s^(-gamma). For continental stations, including stations along the coastlines,
we find that gamma is always close to 0.7. For stations on islands, we find
that gamma ranges between 0.3 and 0.7, with a maximum at gamma = 0.4. This is
consistent with earlier studies of the persistence in sea surface temperature
records where gamma is close to 0.4. In all cases, the exponent gamma does not
depend on the distance of the stations to the continental coastlines. By
varying the degree of detrending in the fluctuation analysis we obtain also
information about trends in the temperature records.Comment: 5 pages, 4 including eps 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
Global climate models violate scaling of the observed atmospheric variability
We test the scaling performance of seven leading global climate models by
using detrended fluctuation analysis. We analyse temperature records of six
representative sites around the globe simulated by the models, for two
different scenarios: (i) with greenhouse gas forcing only and (ii) with
greenhouse gas plus aerosol forcing. We find that the simulated records for
both scenarios fail to reproduce the universal scaling behavior of the observed
records, and display wide performance differences. The deviations from the
scaling behavior are more pronounced in the first scenario, where also the
trends are clearly overestimated.Comment: Accepted for publishing in Physical Review Letter
Nonlinear Volatility of River Flux Fluctuations
We study the spectral properties of the magnitudes of river flux increments,
the volatility. The volatility series exhibits (i) strong seasonal periodicity
and (ii) strongly power-law correlations for time scales less than one year. We
test the nonlinear properties of the river flux increment series by randomizing
its Fourier phases and find that the surrogate volatility series (i) has almost
no seasonal periodicity and (ii) is weakly correlated for time scales less than
one year. We quantify the degree of nonlinearity by measuring (i) the amplitude
of the power spectrum at the seasonal peak and (ii) the correlation power-law
exponent of the volatility series.Comment: 5 revtex pages, 6 page
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
Multifractal detrended fluctuation analysis of nonstationary time series
We develop a method for the multifractal characterization of nonstationary
time series, which is based on a generalization of the detrended fluctuation
analysis (DFA). We relate our multifractal DFA method to the standard partition
function-based multifractal formalism, and prove that both approaches are
equivalent for stationary signals with compact support. By analyzing several
examples we show that the new method can reliably determine the multifractal
scaling behavior of time series. By comparing the multifractal DFA results for
original series to those for shuffled series we can distinguish multifractality
due to long-range correlations from multifractality due to a broad probability
density function. We also compare our results with the wavelet transform
modulus maxima (WTMM) method, and show that the results are equivalent.Comment: 14 pages (RevTex) with 10 figures (eps
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