Radan Huth

Classifications of Atmospheric Circulation Patterns

We review recent advances in classifications of circulation patterns as a specific research area within synoptic climatology. The review starts with a general description of goals of classification and the historical development in the field. We put circulation classifications into a broader context within climatology and systematize the varied methodologies and approaches. We characterize three basic groups of classifications: subjective (also called manual), mixed (hybrid), and objective (computer‐assisted, automated). The roles of cluster analysis and principal component analysis in the classification process are clarified. Several recent methodological developments in circulation classifications are identified and briefly described: the introduction of nonlinear methods, objectivization of subjective catalogs, efforts to optimize classifications, the need for intercomparisons of classifications, and the progress toward an optimum, if possible unified, classification method. Among the recent tendencies in the applications of circulation classifications, we mention a more extensive use in climate studies, both of past, present, and future climates, innovative applications in the ensemble forecasting, increasing variety of synoptic–climatological investigations, and steps above from the troposphere. After introducing the international activity within the field of circulation classifications, the COST733 Action, we briefly describe outputs of the inventory of classifications in Europe, which was carried out within the Action. Approaches to the evaluation of classifications and their mutual comparisons are also reviewed. A considerable part of the review is devoted to three examples of applications of circulation classifications: in historical climatology, in analyses of recent climate variations, and in analyses of outputs from global climate models.

Statistical Downscaling of Daily Temperature in Central Europe

Abstract Statistical downscaling methods and potential large-scale predictors are intercompared for winter daily mean temperature in a network of stations in central and western Europe. The methods comprise (i) canonical correlation analysis (CCA), (ii) singular value decomposition analysis, (iii) multiple linear regression (MLR) of predictor principal components (PCs) with stepwise screening, (iv) MLR of predictor PCs without screening (i.e., all PCs are forced to enter the regression model), and (v) MLR of gridpoint values with stepwise screening (pointwise regression). The potential predictors include two circulation variables (sea level pressure and 500-hPa heights) and two temperature variables (850-hPa temperature and 1000–500-hPa thickness). The methods are evaluated according to the accuracy of specification (in terms of rmse and variance explained), their temporal structure (characterized by lag-1 autocorrelations), and their spatial structure (characterized by spatial correlations and objectivel...

AN INTERCOMPARISON OF COMPUTER-ASSISTED CIRCULATION CLASSIFICATION METHODS

Five different methods that have been used for classification of circulation patterns (correlation method, sums-of-squares method, average linkage, K-means, and rotated principal component analysis) are examined as to their ability to detect dominant circulation types. The performance of the methods is evaluated according to the degree of meeting the following demands made on the groups formed: The groups should (i) be consistent when pre-set parameters are changed, (ii) be well separated both from each other and from the entire data set, (iii) be stable in space and time, and (iv) reproduce the predefined types. All the methods proved to be capable of yielding meaningful classifications. None of them can be thought of as the best in all aspects. Which method to use will depend mainly on the aim of the classification. Nevertheless, the principal component analysis is most successful in reproducing the predefined types and is therefore considered as the most promising method among those examined.

Sensitivity of Local Daily Temperature Change Estimates to the Selection of Downscaling Models and Predictors

Abstract A number of statistical downscaling models are applied to the Canadian Climate Centre general circulation model (CCCM) outputs to provide climate change estimates for local daily surface temperature at a network of 39 stations in central and western Europe. Several different linear downscaling methods (multiple linear regression of gridded values, multiple linear regression of principal components, canonical correlation analysis) are applied to a number of sets of predictors (500- and 1000-hPa heights, 850-hPa temperature, 1000–500-hPa thickness, and their combinations) defined on a grid over the Euro–Atlantic domain. The temperature change estimates are shown to vary widely among the methods as well as among the predictors, both in their areal mean, spatial pattern, and elevation dependence in the Alpine region. The most counterintuitive result is the dependence of the estimated warming on the number of principal components (PCs) of predictors: the larger the number of PCs, the higher the warmin...

Solar modulation of Northern Hemisphere winter blocking

The blocking response to the 11-year solar cycle is investigated for 44 winters (1955-1999) and stratified according to the level of solar activity and the phase of the Quasi-Biennial Oscillation (QBO). Several blocking features are modulated by solar activity, irrespective of the QBO phase, but the responses amplify under the QBO-west phases. Solar activity modulates the preferred locations for blocking occurrence over both Oceans, causing local frequency responses therein. Over the Pacific Ocean high/low solar activity induces an enhanced blocking activity over its eastern/western part. Atlantic blocking occurrence increases for both (high/low) solar phases, with a spatial dependent response confined to western/eastern Atlantic. Although solar effects are negligible in blocking frequency for the entire Atlantic sector, other blocking features exhibit significant responses. Low solar Atlantic blocking episodes last longer, are located further east and become more intense than high solar blocking events. The implications of these solar-related changes are discussed. Our results suggest that the excessively cold conditions recorded in Europe during the Maunder Minimum may have arisen from an eastward shift of long-lasting blockings with near-normal frequencies.

VALUE - A Framework to Validate Downscaling Approaches for Climate Change Studies

VALUE is an open European network to validate and compare downscaling methods for climate change research. VALUE aims to foster collaboration and knowledge exchange between climatologists, impact modellers, statisticians, and stakeholders to establish an interdisciplinary downscaling community. A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. In this paper, we present the key ingredients of this framework. VALUEs main approach to validation is user- focused: starting from a specific user problem, a validation tree guides the selection of relevant validation indices and performance measures. Several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur: what is the isolated downscaling skill? How do statistical and dynamical methods compare? How do methods perform at different spatial scales? Do methods fail in representing regional climate change? How is the overall representation of regional climate, including errors inherited from global climate models? The framework will be the basis for a comprehensive community-open downscaling intercomparison study, but is intended also to provide general guidance for other validation studies.

Time Structure of Observed, GCM-Simulated, Downscaled, and Stochastically Generated Daily Temperature Series

The time structure of simulated daily maximum and minimum temperature series, produced by several different methods, is compared with observations at six stations in central Europe. The methods are statistical downscaling, stochastic weather generator, and general circulation models (GCMs). Outputs from control runs of two GCMs are examined: ECHAM3 and CCCM2. Four time series are constructed by statistical downscaling using multiple linear regression of 500-hPa heights and 1000-/500-hPa thickness: (i) from observations with variance reproduced by the inflation technique, (ii) from observations with variance reproduced by adding a white noise process, and (iii) from the two GCMs. Two runs of the weather generator were performed, one considering and one neglecting the annual cycle of lag-0 and lag-1 correlations among daily weather characteristics. Standard deviation and skewness of day-to-day temperature changes and lag-1 autocorrelations are examined. For heat and cold waves, the occurrence frequency, mean duration, peak temperature, and mean position within the year are studied. Possible causes of discrepancies between the simulated and observed time series are discussed and identified. They are shown to stem, among others, from (i) the absence of physics in downscaled and stochastically generated series, (ii) inadequacies of treatment of physical processes in GCMs, (iii) assumptions of linearity in downscaling equations, and (iv) properties of the underlying statistical model of the weather generator. In downscaling, variance inflation is preferable to the white noise addition in most aspects as the latter results in highly overestimated day-to-day variability. The inclusion of the annual cycle of correlations into the weather generator does not lead to an overall improvement of the temperature series produced. None of the methods appears to be able to reproduce all the characteristics of time structure correctly.

Properties of the circulation classification scheme based on the rotated principal component analysis

SummaryThe study addresses some methodological issues of application of principal component analysis (PCA) to the classification of circulation patterns. The obliquely rotated PCA in T-mode (i.e. with time observations corresponding to variables and grid points to realizations) is applied to 500 hPa geopotential heights over Europe and adjacent parts of Atlantic Ocean. The solutions are examined for various numbers of principal components rotated, and for both raw and anomaly data, with the aim to find the way of determining the optimum number of circulation types. This is done, among others, by examining temporal and spatial stability of solutions, their compliance with simple structure requirements, and temporal behaviour of classifications. Some of the solutions that are pre-selected according to the rule based upon the separation between successive eigenvalues prove to perform considerably better than unselected ones; some of them do not. Which pre-selected solutions should be given preference is impossible to decide in advance, without a detailed scrutiny. Nevertheless, even after such a scrutiny is done, more than a single classification are acceptable. The final choice of the optimum solution depends on the aims of the intended study: It should balance the demands on statistical stability of types and on resemblance between types and daily patterns classified with them.

Continental-Scale Circulation in the UKHI GCM

Abstract The ability of the U. K. Meteorological Office High Resolution General Circulation Model (UKHI GCM) to simulate atmospheric circulation of continental scales, and the influence on circulation of doubled concentrations of greenhouse gases simulated by the same model, are investigated. The 500-hPa geopotential heights are examined over the European and North American continental-scale domains. Two aspects of circulation are considered: circulation types and modes of variability. The principal component analysis is employed as the analysis technique. The UKHI GCM is shown to have several characteristic deficiencies in simulating continental-scale circulation, which are consistent with the analyses of circulation in other models. 1) The simulated jets are too strong and shifted southward. 2) The simulated meridional circulation is too weak. 3) The simulated circulation types are more persistent than the actual. 4) The model reproduces low-frequency (teleconnection) patterns only to a limited extent. ...

Potential of continental-scale circulation for the determination of local daily surface variables

SummaryThis study deals with one aspect of statistical downscaling, viz. links between the continental-scale upper-air circulation and surface weather variables on a daily scale. The circulation-to-weather links are expressed in terms of multiple regression between either grid point values or intensities of circulation variability modes and weather elements, including temperature variables, relative humidity, cloudiness, sunshine duration, zonal and meridional wind components, precipitation, and atmospheric pressure. The upper-air circulation influences the surface pressure, temperature and zonal wind most strongly. The relative humidity, cloudiness and sunshine duration appear not to be connected with circulation in winter at all. The low-frequency part of circulation (i.e. processes with periods longer than 10 days) is most efficient in specifying surface weather variables. The circulation-to-weather links manifest considerable intra- and interdecadal variations, posing doubts on the applicability of the ‘downscaling-from-circulation’ method of constructing climate change scenarios.