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Climate Research (climate + research)

Distribution by Scientific Domains
Mathematics and Statistics25%

Selected Abstracts

On the use of generalized linear models for interpreting climate variability

ENVIRONMETRICS, Issue 7 2005
Richard E. Chandler
Abstract Many topical questions in climate research can be reduced to either of two related problems: understanding how various different components of the climate system affect each other, and quantifying changes in the system. This article aims to justify the addition of generalized linear models to the climatologist's toolkit, by demonstrating that they offer an intuitive and flexible approach to such problems. In particular, we provide some suggestions as to how ,typical' climatological data structures may be represented within the GLM framework. Recurring themes include methods for space,time data and the need to cope with large datasets. The ideas are illustrated using a dataset of monthly U.S. temperatures. Copyright © 2005 John Wiley & Sons, Ltd. [source]

Pattern hunting in climate: a new method for finding trends in gridded climate data

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 1 2007
A. Hannachi
Abstract Trends are very important in climate research and are ubiquitous in the climate system. Trends are usually estimated using simple linear regression. Given the complexity of the system, trends are expected to have various features such as global and local characters. It is therefore important to develop methods that permit a systematic decomposition of climate data into different trend patterns and remaining no-trend patterns. Empirical orthogonal functions and closely related methods, widely used in atmospheric science, are unable in general to capture trends because they are not devised for that purpose. The present paper presents a novel method capable of systematically capturing trend patterns from gridded data. The method is based on an eigenanalysis of the covariance/correlation matrix obtained using correlations between time positions of the sorted data, and trends are associated with the leading nondegenerate eigenvalues. Application to simple low-dimensional time series models and reanalyses data are presented and discussed. Copyright © 2006 Royal Meteorological Society. [source]

In search of simple structures in climate: simplifying EOFs

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 1 2006
A. Hannachi
Abstract Empirical orthogonal functions (EOFs) are widely used in climate research to identify dominant patterns of variability and to reduce the dimensionality of climate data. EOFs, however, can be difficult to interpret. Rotated empirical orthogonal functions (REOFs) have been proposed as more physical entities with simpler patterns than EOFs. This study presents a new approach for finding climate patterns with simple structures that overcomes the problems encountered with rotation. The method achieves simplicity of the patterns by using the main properties of EOFs and REOFs simultaneously. Orthogonal patterns that maximise variance subject to a constraint that induces a form of simplicity are found. The simplified empirical orthogonal function (SEOF) patterns, being more ,local', are constrained to have zero loadings outside the main centre of action. The method is applied to winter Northern Hemisphere (NH) monthly mean sea level pressure (SLP) reanalyses over the period 1948,2000. The ,simplified' leading patterns of variability are identified and compared to the leading patterns obtained from EOFs and REOFs. Copyright © 2005 Royal Meteorological Society. [source]

On the role of statistics in climate research

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 6 2004
Francis W. Zwiers
Abstract We review the role of statistical analysis in the climate sciences. Special emphasis is given to attempts to construct dynamical knowledge from limited observational evidence, and to the ongoing task of drawing detailed and reliable information on the state, and change, of climate that is needed, for example, for short-term and seasonal forecasting. We conclude with recommendations of how to improve the practice of statistical analysis in the climate sciences by drawing more efficiently on relevant developments in statistical mathematics. Copyright © 2004 Environment Canada. Published by John Wiley & Sons, Ltd. [source]

Two decades of urban climate research: a review of turbulence, exchanges of energy and water, and the urban heat island

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 1 2003
A. John Arnfield
Abstract Progress in urban climatology over the two decades since the first publication of the International Journal of Climatology is reviewed. It is emphasized that urban climatology during this period has benefited from conceptual advances made in microclimatology and boundary-layer climatology in general. The role of scale, heterogeneity, dynamic source areas for turbulent fluxes and the complexity introduced by the roughness sublayer over the tall, rigid roughness elements of cities is described. The diversity of urban heat islands, depending on the medium sensed and the sensing technique, is explained. The review focuses on two areas within urban climatology. First, it assesses advances in the study of selected urban climatic processes relating to urban atmospheric turbulence (including surface roughness) and exchange processes for energy and water, at scales of consideration ranging from individual facets of the urban environment, through streets and city blocks to neighbourhoods. Second, it explores the literature on the urban temperature field. The state of knowledge about urban heat islands around 1980 is described and work since then is assessed in terms of similarities to and contrasts with that situation. Finally, the main advances are summarized and recommendations for urban climate work in the future are made. Copyright © 2003 Royal Meteorological Society. [source]

Daily dataset of 20th-century surface air temperature and precipitation series for the European Climate Assessment

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 12 2002
A. M. G. Klein Tank
Abstract We present a dataset of daily resolution climatic time series that has been compiled for the European Climate Assessment (ECA). As of December 2001, this ECA dataset comprises 199 series of minimum, maximum and/or daily mean temperature and 195 series of daily precipitation amount observed at meteorological stations in Europe and the Middle East. Almost all series cover the standard normal period 1961,90, and about 50% extends back to at least 1925. Part of the dataset (90%) is made available for climate research on CDROM and through the Internet (at http://www.knmi.nl/samenw/eca). A comparison of the ECA dataset with existing gridded datasets, having monthly resolution, shows that correlation coefficients between ECA stations and nearest land grid boxes between 1946 and 1999 are higher than 0.8 for 93% of the temperature series and for 51% of the precipitation series. The overall trends in the ECA dataset are of comparable magnitude to those in the gridded datasets. The potential of the ECA dataset for climate studies is demonstrated in two examples. In the first example, it is shown that the winter (October,March) warming in Europe in the 1976,99 period is accompanied by a positive trend in the number of warm-spell days at most stations, but not by a negative trend in the number of cold-spell days. Instead, the number of cold-spell days increases over Europe. In the second example, it is shown for winter precipitation between 1946 and 1999 that positive trends in the mean amount per wet day prevail in areas that are getting drier and wetter. Because of its daily resolution, the ECA dataset enables a variety of empirical climate studies, including detailed analyses of changes in the occurrence of extremes in relation to changes in mean temperature and total precipitation. Copyright © 2002 Royal Meteorological Society. [source]

Detection and correction of artificial shifts in climate series

JOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES C (APPLIED STATISTICS), Issue 3 2004
Henri Caussinus
Summary., Many long instrumental climate records are available and might provide useful information in climate research. These series are usually affected by artificial shifts, due to changes in the conditions of measurement and various kinds of spurious data. A comparison with surrounding weather-stations by means of a suitable two-factor model allows us to check the reliability of the series. An adapted penalized log-likelihood procedure is used to detect an unknown number of breaks and outliers. An example concerning temperature series from France confirms that a systematic comparison of the series together is valuable and allows us to correct the data even when no reliable series can be taken as a reference. [source]

Disaggregating qualitative data from Asian American college students in campus racial climate research and assessment

NEW DIRECTIONS FOR INSTITUTIONAL RESEARCH, Issue 142 2009
Samuel D. Museus
The disaggregation of qualitative data can provide a more nuanced understanding of the diverse experiences within the Asian American student population. [source]