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  • 1
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    Methods for Exploring Spatial and Temporal Variability of Extreme Events in Climate Data (2008)
    American Meteorological Society
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    Publication Date: 2008-05-15
    Description: This study presents various statistical methods for exploring and summarizing spatial extremal properties in large gridpoint datasets. Extremal properties are inferred from the subset of gridpoint values that exceed sufficiently high, time-varying thresholds. A simple approach is presented for how to choose the thresholds so as to avoid sampling biases from nonstationary differential trends within the annual cycle. The excesses are summarized by estimating parameters of a flexible generalized Pareto model that can account for spatial and temporal variation in the excess distributions. The effect of potentially explanatory factors (e.g., ENSO) on the distribution of extremes can be easily investigated using this model. Smooth spatially pooled estimates are obtained by fitting the model over neighboring grid points while accounting for possible spatial variation across these points. Extreme value theory methods are also presented for how to investigate the temporal clustering and spatial dependency (teleconnections) of extremes. The methods are illustrated using Northern Hemisphere monthly mean gridded temperatures for June–August (JJA) summers from 1870 to 2005.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
    Published by American Meteorological Society
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  • 2
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    Simple Nonparametric Techniques for Exploring Changing Probability Distributions of Weather (2005)
    American Meteorological Society
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    Publication Date: 2005-11-01
    Description: Anthropogenic influences are expected to cause the probability distribution of weather variables to change in nontrivial ways. This study presents simple nonparametric methods for exploring and comparing differences in pairs of probability distribution functions. The methods are based on quantiles and allow changes in all parts of the probability distribution to be investigated, including the extreme tails. Adjusted quantiles are used to investigate whether changes are simply due to shifts in location (e.g., mean) and/or scale (e.g., variance). Sampling uncertainty in the quantile differences is assessed using simultaneous confidence intervals calculated using a bootstrap resampling method that takes account of serial (intraseasonal) dependency. The methods are simple enough to be used on large gridded datasets. They are demonstrated here by exploring the changes between European regional climate model simulations of daily minimum temperature and precipitation totals for winters in 1961–90 and 2071–2100. Projected changes in daily precipitation are generally found to be well described by simple increases in scale, whereas minimum temperature exhibits changes in both location and scale.
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    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
    Published by American Meteorological Society
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  • 3
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    Observed Trends and Teleconnections of the Siberian High: A Recently Declining Center of Action (2005)
    American Meteorological Society
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    Publication Date: 2005-05-01
    Description: This study investigates variability in the intensity of the wintertime Siberian high (SH) by defining a robust SH index (SHI) and correlating it with selected meteorological fields and teleconnection indices. A dramatic trend of –2.5 hPa decade−1 has been found in the SHI between 1978 and 2001 with unprecedented (since 1871) low values of the SHI. The weakening of the SH has been confirmed by analyzing different historical gridded analyses and individual station observations of sea level pressure (SLP) and excluding possible effects from the conversion of surface pressure to SLP. SHI correlation maps with various meteorological fields show that SH impacts on circulation and temperature patterns extend far outside the SH source area extending from the Arctic to the tropical Pacific. Advection of warm air from eastern Europe has been identified as the main mechanism causing milder than normal conditions over the Kara and Laptev Seas in association with a strong SH. Despite the strong impacts of the variability in the SH on climatic variability across the Northern Hemisphere, correlations between the SHI and the main teleconnection indices of the Northern Hemisphere are weak. Regression analysis has shown that teleconnection indices are not able to reproduce the interannual variability and trends in the SH. The inclusion of regional surface temperature in the regression model provides closer agreement between the original and reconstructed SHI.
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    Topics: Geography , Geosciences , Physics
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  • 4
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    Atlantic Atmosphere–Ocean Interaction: A Stochastic Climate Model–Based Diagnosis (2005)
    American Meteorological Society
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    Publication Date: 2005-04-01
    Description: A simple linear stochastic climate model of extratropical wintertime ocean–atmosphere coupling is used to diagnose the daily interactions between the ocean and the atmosphere in a fully coupled general circulation model. Monte Carlo simulations with the simple model show that the influence of the ocean on the atmosphere can be difficult to estimate, being biased low even with multiple decades of daily data. Despite this, fitting the simple model to the surface air temperature and sea surface temperature data from the complex general circulation model reveals an ocean-to-atmosphere influence in the northeastern Atlantic. Furthermore, the simple model is used to demonstrate that the ocean in this region greatly enhances the autocorrelation in overlying lower-tropospheric temperatures at lags from a few days to many months.
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    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 5
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    The Variability of Seasonality (2005)
    American Meteorological Society
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    Publication Date: 2005-01-01
    Description: Seasons are the complex nonlinear response of the physical climate system to regular annual solar forcing. There is no a priori reason why they should remain fixed/invariant from year to year, as is often assumed in climate studies when extracting the seasonal component. The widely used econometric variant of Census Method II Seasonal Adjustment Program (X-11), which allows for year-to-year variations in seasonal shape, is shown here to have some advantages for diagnosing climate variability. The X-11 procedure is applied to the monthly mean Niño-3.4 sea surface temperature (SST) index and global gridded NCEP–NCAR reanalyses of 2-m surface air temperature. The resulting seasonal component shows statistically significant interannual variations over many parts of the globe. By taking these variations in seasonality into account, it is shown that one can define less ambiguous ENSO indices. Furthermore, using the X-11 seasonal adjustment approach, it is shown that the three cold ENSO episodes after 1998 are due to an increase in amplitude of seasonality rather than being three distinct La Niña events. Globally, variations in the seasonal component represent a substantial fraction of the year-to-year variability in monthly mean temperatures. In addition, strong teleconnections can be discerned between the magnitude of seasonal variations across the globe. It might be possible to exploit such relationships to improve the skill of seasonal climate forecasts.
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  • 6
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    Granger Causality of Coupled Climate Processes: Ocean Feedback on the North Atlantic Oscillation (2006)
    American Meteorological Society
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    Publication Date: 2006-04-01
    Description: This study uses a Granger causality time series modeling approach to quantitatively diagnose the feedback of daily sea surface temperatures (SSTs) on daily values of the North Atlantic Oscillation (NAO) as simulated by a realistic coupled general circulation model (GCM). Bivariate vector autoregressive time series models are carefully fitted to daily wintertime SST and NAO time series produced by a 50-yr simulation of the Third Hadley Centre Coupled Ocean–Atmosphere GCM (HadCM3). The approach demonstrates that there is a small yet statistically significant feedback of SSTs on the NAO. The SST tripole index is found to provide additional predictive information for the NAO than that available by using only past values of NAO—the SST tripole is Granger causal for the NAO. Careful examination of local SSTs reveals that much of this effect is due to the effect of SSTs in the region of the Gulf Steam, especially south of Cape Hatteras. The effect of SSTs on NAO is responsible for the slower-than-exponential decay in lag-autocorrelations of NAO notable at lags longer than 10 days. The persistence induced in daily NAO by SSTs causes long-term means of NAO to have more variance than expected from averaging NAO noise if there is no feedback of the ocean on the atmosphere. There are greater long-term trends in NAO than can be expected from aggregating just short-term atmospheric noise, and NAO is potentially predictable provided that future SSTs are known. For example, there is about 10%–30% more variance in seasonal wintertime means of NAO and almost 70% more variance in annual means of NAO due to SST effects than one would expect if NAO were a purely atmospheric process.
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    Topics: Geography , Geosciences , Physics
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  • 7
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    Toward an Integrated Seasonal Forecasting System for South America (2006)
    American Meteorological Society
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    Publication Date: 2006-08-01
    Description: This study proposes an objective integrated seasonal forecasting system for producing well-calibrated probabilistic rainfall forecasts for South America. The proposed system has two components: (i) an empirical model that uses Pacific and Atlantic sea surface temperature anomalies as predictors for rainfall and (ii) a multimodel system composed of three European coupled ocean–atmosphere models. Three-month lead austral summer rainfall predictions produced by the components of the system are integrated (i.e., combined and calibrated) using a Bayesian forecast assimilation procedure. The skill of empirical, coupled multimodel, and integrated forecasts obtained with forecast assimilation is assessed and compared. The simple coupled multimodel ensemble has a comparable level of skill to that obtained using a simplified empirical approach. As for most regions of the globe, seasonal forecast skill for South America is low. However, when empirical and coupled multimodel predictions are combined and calibrated using forecast assimilation, more skillful integrated forecasts are obtained than with either empirical or coupled multimodel predictions alone. Both the reliability and resolution of the forecasts have been improved by forecast assimilation in several regions of South America. The Tropics and the area of southern Brazil, Uruguay, Paraguay, and northern Argentina have been found to be the two most predictable regions of South America during the austral summer. Skillful rainfall forecasts are generally only possible during El Niño or La Niña years rather than in neutral years.
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    Topics: Geography , Geosciences , Physics
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  • 8
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    Anomalous Spiking in Spectra of XCTD Temperature Profiles (2009)
    American Meteorological Society
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    Publication Date: 2009-06-01
    Description: The high vertical resolution of temperature and salinity measurements from expendable conductivity–temperature–depth (XCTD) instruments can be useful for inferring small-scale mixing rates in the ocean. However, XCTD temperature profiles show distinct spectral spikes at frequencies of 5 and 10 Hz, corresponding to 1 and 2 cycles per five measurement points. Peaks at these same frequencies are often present in the conductivity spectra as well. The spectral spikes occur in XCTD profiles from both the subtropical and subpolar regions. They appear to originate as digital electronic noise within the probes. A finite impulse response filter design procedure was used to develop filters that could remove the spectral spikes while retaining as much high vertical resolution as possible. For most purposes, the application of an 11-point, least squares, low-pass filter proves sufficient for removing the spectral energy at 5 and 10 Hz, and results in an effective minimum vertical resolution of about 0.7 m.
    Print ISSN: 0739-0572
    Electronic ISSN: 1520-0426
    Topics: Geography , Geosciences , Physics
    Published by American Meteorological Society
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  • 9
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    Diagnosis of Variability and Trends in a Global Precipitation Dataset Using a Physically Motivated Statistical Model (2006)
    American Meteorological Society
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    Publication Date: 2006-09-01
    Description: A physically motivated statistical model is used to diagnose variability and trends in wintertime (October–March) Global Precipitation Climatology Project (GPCP) pentad (5-day mean) precipitation. Quasigeostrophic theory suggests that extratropical precipitation amounts should depend multiplicatively on the pressure gradient, saturation specific humidity, and the meridional temperature gradient. This physical insight has been used to guide the development of a suitable statistical model for precipitation using a mixture of generalized linear models: a logistic model for the binary occurrence of precipitation and a Gamma distribution model for the wet day precipitation amount. The statistical model allows for the investigation of the role of each factor in determining variations and long-term trends. Saturation specific humidity qs has a generally negative effect on global precipitation occurrence and with the tropical wet pentad precipitation amount, but has a positive relationship with the pentad precipitation amount at mid- and high latitudes. The North Atlantic Oscillation, a proxy for the meridional temperature gradient, is also found to have a statistically significant positive effect on precipitation over much of the Atlantic region. Residual time trends in wet pentad precipitation are extremely sensitive to the choice of the wet pentad threshold because of increasing trends in low-amplitude precipitation pentads; too low a choice of threshold can lead to a spurious decreasing trend in wet pentad precipitation amounts. However, for not too small thresholds, it is found that the meridional temperature gradient is an important factor for explaining part of the long-term trend in Atlantic precipitation.
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    Topics: Geography , Geosciences , Physics
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  • 10
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    Empirical Orthogonal Functions: The Medium is the Message (2009)
    American Meteorological Society
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    Publication Date: 2009-12-15
    Description: Empirical orthogonal function (EOF) analysis is a powerful tool for data compression and dimensionality reduction used broadly in meteorology and oceanography. Often in the literature, EOF modes are interpreted individually, independent of other modes. In fact, it can be shown that no such attribution can generally be made. This review demonstrates that in general individual EOF modes (i) will not correspond to individual dynamical modes, (ii) will not correspond to individual kinematic degrees of freedom, (iii) will not be statistically independent of other EOF modes, and (iv) will be strongly influenced by the nonlocal requirement that modes maximize variance over the entire domain. The goal of this review is not to argue against the use of EOF analysis in meteorology and oceanography; rather, it is to demonstrate the care that must be taken in the interpretation of individual modes in order to distinguish the medium from the message.
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    Topics: Geography , Geosciences , Physics
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