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Hans von Storch

Abstract

The technique of “inflating” in downscaling, which makes the downscaled climate variable have the right variance, is based on the assumption that all local variability can be traced back to large-scale variability. For practical situations this assumption is not valid, and inflation is an inappropriate technique. Instead, additive, randomized approaches should be adopted.

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Frauke Feser
and
Hans von Storch

Abstract

This study explores the possibility of reconstructing the weather of Southeast Asia for the last decades using an atmospheric regional climate model, the Climate version of the Lokal-Modell (CLM). For this purpose global National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalyses data were dynamically downscaled to 50 km and in a double-nesting approach to 18-km grid distance. To prevent the regional model from deviating significantly from the reanalyses with respect to large-scale circulation and large-scale weather phenomena, a spectral nudging technique was used.

The performance of this technique in dealing with Southeast Asian typhoons is now examined by considering an ensemble of one simulated typhoon case. This analysis is new insofar as it deals with simulations done in the climate mode (so that any skill of reproducing the typhoon is not related to details of initial conditions), is done in ensemble mode (the same development is described by several simulations), and is done with a spectral nudging constraint (so that the observed large-scale state is enforced in the model domain). This case indicates that tropical storms that are coarsely described by the reanalyses are correctly identified and tracked; considerably deeper core pressure and higher wind speeds are simulated compared to the driving reanalyses. When the regional atmospheric model is run without spectral nudging, significant intraensemble variability occurs; also additional, nonobserved typhoons form. Thus, the insufficiency of lateral boundary conditions alone for determining the details of the dynamic developments in the interior becomes very clear. The same lateral boundary conditions are consistent with different developments in the interior. Several sensitivity experiments were performed concerning varied grid distances, different initial starting dates of the simulations, and changed spectral nudging parameters.

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Frauke Feser
and
Hans von Storch

Abstract

A two-dimensional discrete spatial filter was developed. It serves as a means to classify meteorological fields on a limited-area grid according to their spatial dimensions by filtering certain wavenumber ranges. Thereby it performs an isotropic spatial-scale separation of the atmospheric fields. A general algorithm was developed, which allows the construction of a filter that closely approximates a specific isotropic response function. The filter is simple in the construction and easy to apply while giving reasonable results. The method allows for considerable flexibility in choosing this specific response. This way, low-, band-, and high-pass filters are obtained. Examples show an effective scale separation of atmospheric fields on limited-area grids that can be used for process studies, model evaluation, or comparisons.

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Frank Kauker
and
Hans von Storch

Abstract

A 15-yr simulation of an ocean general circulation model, exposed to atmospheric forcing as provided by the ECMWF reanalysis 1979–93, is analyzed with respect to the statistics of the surface circulation of the North Sea on timescales of days to several weeks in winter.

The first two EOFs of surface circulation are found to represent the bulk of the variability (72%). They are broadly consistent with the limited observational record. The first EOF represents regimes with one gyre flushing the entire North Sea, either with clockwise orientation (15% of time) or with counterclockwise orientation (30% of time). These regimes are excited by northeasterly and, respectively, southwesterly wind. The second EOF is representative for two opposite regimes with two bipolar patterns in the northern and southern part of the North Sea (45% of time). For a certain range of both EOFs coefficients, the North Sea circulation ceases (10% of time).

The circulation of the North Sea in winter is highly variable; the regimes change frequently. Only 40% of the one-gyre regimes persist for longer than 5 days, and the bipolar pattern regimes rarely extend for more than 5 days.

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Hans von Storch
and
Gerhard Hannoschöck

Abstract

Statistical properties of estimated nonisotropic principal vectors [empirical orthogonal functions (EOFs)] are reviewed and discussed. The standard eigenvalue estimator is nonnormally distributed and biased: the largest one becomes overestimated, the smallest ones underestimated. Generally, the variance of the eigenvalue estimate is large. The standard eigenvalue estimator may be used to define an unbiased estimator, which, however, exhibits an increased variance. If a fixed set of EOFs is used, the FOF coefficients are not stochastically independent. The variances of the low-indexed coefficients become considerably overestimated by the respective estimated eigenvalues, those of the high-indexed coefficients underestimated. If the ratio of degrees of freedom to sample size is one-half or even less, these disadvantages are still current as is demonstrated by an example.

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Ute Luksch
and
Hans von Storch

Abstract

A stochastic specification for monthly mean wintertime eddy heat transport conditional upon the monthly mean circulation is proposed. The approach is based on an analog technique. The nearest neighbor for the monthly mean streamfunction (at 850 and 300 hPa) is searched for in a library composed of monthly data of a 1268-yr control simulation with a coupled ocean–atmosphere model. To reduce the degrees of freedom a limited area (the North Atlantic sector) is used for the analog specification. The monthly means of northward transient eddy flux of temperature (at 750 hPa) are simulated as a function of these analogues.

The stochastic model is applied to 300 years of a paleosimulation (last interglacial maximum around 125 kyr BP). The level of variability of the eddy heat flux is reproduced by the analog estimator, as well as the link between monthly mean circulation and synoptic-scale variability. The changed boundary conditions (solar radiation and CO2 level) cause the Eemian variability to be significantly reduced compared to the control simulation. Although analogues are not a very good predictor of heat fluxes for individual months, they turn out to be excellent predictors of the distribution (or at least the variance) of heat fluxes in an anomalous climate.

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Hans von Storch
and
Hinrich Reichardt

Abstract

Past variations of water levels at Cuxhaven, Germany (German bight), are examined, and a scenario for future changes due to expected global warming is derived.

The observational record of Cuxhaven water levels features a linear upward trend in the annual mean water level of about 30 cm 100 yr−1 overlaid by irregular variations due to synoptic disturbances. These irregular storm-related variations are shown to have remained mostly stationary since the beginning of observations until today.

A scenario for future conditions is derived by means of a two-step downscaling approach. First, a “time slice experiment” is used to obtain a regionally disaggregated scenario for the time mean circulation for the time of expected doubling of atmospheric CO2 concentrations. Then, an empirical downscaling model is derived, which relates intramonthly percentiles of storm-related water-level variations at Cuxhaven to variations in the monthly mean air pressure field over Europe and the northern North Atlantic.

Past variations of storm-related intramonthly percentiles are well reproduced by the downscaling model so that the statistical model may be credited with skill. The combined time slice–statistical model “predicts,” for the expect time of doubled atmospheric CO2 concentrations in the decade around 2035, an insignificant rise of the 50%, 80%, and 90% percentiles of storm-related water-level variations in Cuxhaven of less than 10 cm, which is well within the range of natural interdecadal variability. These numbers have to be added to the rise in mean sea level due to thermal expansion and other slow processes.

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Francis W. Zwiers
and
Hans von Storch

Abstract

Recurrence analysis was introduced to infer the degree of separation between a “control” and an “anomaly” ensemble of, say, seasonal means simulated in general circulation model (GCM) experiments. The concept of recurrence analysis is described as a particular application of a statistical technique called multiple discriminant analysis (MDA). Using MDA, univariate recurrence is easily generalized to multicomponent problems. Algorithms that can be used to estimate the level of recurrence and tests that can be used to assess the confidence in a priori specified levels of recurrence are presented.

Several of the techniques are used to reanalyze a series of El Niño sensitivity experiments conducted with the Canadian Climate Centre GCM. The simulated El Niño response in DJF mean 500 mb height are all estimated to be more than 94% recurrent in the tropics and are estimated to be between 90% and 959b recurrent in the Northern Hemisphere between 20° and 60°N latitude.

Discrimination rules that can be used to classify individual realizations of climate as members of the control or “experimental” ensemble are obtained as a by-product of the multiple recurrence analysis. We show that it is possible to make reasonable inferences about the state of the eastern Pacific sea surface temperature by classifying observed DJF 500 mb height fields with discrimination rules derived from the GCM experiments.

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Oliver Krueger
and
Hans von Storch

Abstract

Yearly percentiles of geostrophic wind speeds serve as a widely used proxy for assessing past storm activity. Here, daily geostrophic wind speeds are derived from a geographical triangle of surface air pressure measurements and are used to build yearly frequency distributions. It is commonly believed, however unproven, that the variation of the statistics of strong geostrophic wind speeds describes the variation of statistics of ground-level wind speeds. This study evaluates this approach by examining the correlation between specific annual (seasonal) percentiles of geostrophic and of area-maximum surface wind speeds to determine whether the two distributions are linearly linked in general.

The analyses rely on bootstrap and binomial hypothesis testing as well as on analysis of variance. Such investigations require long, homogeneous, and physically consistent data. Because such data are barely existent, regional climate model–generated wind and surface air pressure fields in a fine spatial and temporal resolution are used. The chosen regional climate model is the spectrally nudged and NCEP-driven regional model (REMO) that covers Europe and the North Atlantic. Required distributions are determined from diagnostic 10-m and geostrophic wind speed, which is calculated from model air pressure at sea level.

Obtained results show that the variation of strong geostrophic wind speed statistics describes the variation of ground-level wind speed statistics. Annual and seasonal quantiles of geostrophic wind speed and ground-level wind speed are positively linearly related. The influence of low-pass filtering is also considered and found to decrease the quality of the linear link. Moreover, several factors are examined that affect the description of storminess through geostrophic wind speed statistics. Geostrophic wind from sea triangles reflects storm activity better than geostrophic wind from land triangles. Smaller triangles lead to a better description of storminess than bigger triangles.

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Jin-Song Xu
and
Hans Von Storch

Abstract

Principal oscillation pattern (POP) analysis is a diagnostic technique for deriving the space-time characteristics of a dataset objectively. A multiyear dataset of monthly mean sea level pressure (SLP) in the area 15°S to 40°S is examined with the POP technique. In the low-frequency band one physically significant pair of patterns is identified, which is clearly associated with the Southern Oscillation (SO).

According to the POP analysis, the 50 may be described as a damped oscillatory sequence of patterns …→P 1P 2-P 1-P 2P 1… having a time scale of two to three years. The first pattern, P1 , representative of the “peak” phase of ENSO, exhibits a dipole with anomalies of opposite sign over the central and eastern Pacific and over the Indian Ocean/Australian sector. The second, P2 , pattern is dominated by an anomaly in the SPCZ region and describes an intermediate, or “onset” phase.

The time coefficients of the two patterns, P1 and P2 , may be interpreted as a bivariate index of the SO. Generalizing the original diagnostic concept, the POP framework is used to predict this index and the traditional univariate SO index.

The POP prediction scheme is tested in a series of hindcast experiments. The scheme turns out to be skillful for a lead time of two to three seasons. In terms of a correlation skill score, the POP model is better than persistence and a conventional ARMA model in hindcasting the traditional SO index.

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