Not exact matches
Although they
create jobs and bring in money to local and national economies, airports also
create noise, pollution and transport
problems as well as taking up vast tracts of land.
But it
creates another
problem, as was exhibited in 2004: Dems had so many candidates who were in game just to get «free» public funding and personal name recognition that voices of more serious candidates drowned in the
noise.
As an addendum, the reason that natural variability is often talked about is because the historical observed record is used to test and constrain the models [and the assumptions that they have made about step 0 and step 3], but the natural variability
creates a signal to
noise problem.
There has been a recent emphasis in decadal - scale prediction, and also
creating a marriage between climate and fields such as synoptic - dynamic meteorology... something relatively new (and a different sort of
problem, than say, estimating the boundary condition change in a 2xCO2 world); as Susan Solomon mentioned in her writing, a lot of people have become much more focused on the nature of the «
noise» inherent within the climate system, something which also relates to Kevin Trenberth's remarks about tracking Earth's energy budget carefully.
These gaps were not obvious from a visual inspection and would have
created huge
problems with water leaks, uncomfortable drafts,
noise transfer, and a high risk of condensation and mold growth.
General Introduction Two Main Goals Identifying Patterns in Time Series Data Systematic pattern and random
noise Two general aspects of time series patterns Trend Analysis Analysis of Seasonality ARIMA (Box & Jenkins) and Autocorrelations General Introduction Two Common Processes ARIMA Methodology Identification Phase Parameter Estimation Evaluation of the Model Interrupted Time Series Exponential Smoothing General Introduction Simple Exponential Smoothing Choosing the Best Value for Parameter a (alpha) Indices of Lack of Fit (Error) Seasonal and Non-seasonal Models With or Without Trend Seasonal Decomposition (Census I) General Introduction Computations X-11 Census method II seasonal adjustment Seasonal Adjustment: Basic Ideas and Terms The Census II Method Results Tables Computed by the X-11 Method Specific Description of all Results Tables Computed by the X-11 Method Distributed Lags Analysis General Purpose General Model Almon Distributed Lag Single Spectrum (Fourier) Analysis Cross-spectrum Analysis General Introduction Basic Notation and Principles Results for Each Variable The Cross-periodogram, Cross-density, Quadrature - density, and Cross-amplitude Squared Coherency, Gain, and Phase Shift How the Example Data were
Created Spectrum Analysis — Basic Notations and Principles Frequency and Period The General Structural Model A Simple Example Periodogram The
Problem of Leakage Padding the Time Series Tapering Data Windows and Spectral Density Estimates Preparing the Data for Analysis Results when no Periodicity in the Series Exists Fast Fourier Transformations General Introduction Computation of FFT in Time Series
You have to consider that it just might be less trouble to simply ignore the
noise, because reprimanding them will
create conflict and bad feelings and that can
create much bigger
problems later.