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Simon H. Lee
,
Michael K. Tippett
, and
Lorenzo M. Polvani

is the goal of the present study. We here define a set of daily, year-round weather regimes in a domain centered on North America. We systematically test the sensitivity of the results to various methodological choices to demonstrate both the robustness of our classification and the reasons for the choices we make. We then link each weather regime to key meteorological variables and other modes of climate variability, and quantify trends and variability in regime frequency since 1979. The regimes

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Jeremy Johnston
,
Jennifer M. Jacobs
, and
Eunsang Cho

review of snow classification approaches, 2) introduce a novel data-driven time series approach to capture snow seasonality using snow-covered area observations, 3) apply this method to gap-filled snow-cover datasets (MODIS; 2000–22), 4) validate and compare against existing climate and snow classes, and 5) explore multidecadal trends in snow regimes. These efforts supply an up-to-date summary of the current state of global snow seasonality and new classification datasets suitable for numerous

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Stefanie M. Herrmann
and
Karen I. Mohr

dual-wet-season regime; 4) in East Africa, from dual season to single season or multiple seasons; 5) in southern Africa, from single season to dual or multiple seasons; and 6) in central Africa, from nonseasonal humid to a single- or dual-wet-season regime. Whether more systematic transitions between climatological seasonality regimes are expected under projected climate change remains to be studied. 4. Summary and conclusions This study developed a continental-scale seasonality classification for

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Pham Thi Thanh Nga
,
Pham Thanh Ha
, and
Vu Thanh Hang

). This regionalization is different from the latest Köppen–Geiger classification used in the climate world map ( Kottek et al. 2006 ), where Vietnam has only four climatic zones: equatorial monsoon (Am), equatorial savannah with dry winter (Aw), subtropical with constant precipitation (Cfa), and subtropical with dry winter (Cwa). Recently, Polo et al. (2015a) applied cluster analysis to the continental region of Vietnam for climatic regionalization using the spatial distribution of solar irradiance

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Xiuzhen Li
,
Wen Zhou
, and
Yongqin David Chen

1. Introduction The climate in China differs throughout its vast territory because of differences in latitude, elevation, wind direction, and distance to oceans. A good understanding of how the climate varies by region is of great importance in a wide variety of applications. They include not only simply identifying regions with similar climate variability but also forecasting seasonal climate and applying hydrological measures, such as drought evaluation. Many climate classification schemes

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T. Sohail
and
J. D. Zika

T18 , they modified the criteria to reflect the prevailing conditions in the simulation. Furthermore, they proposed the addition of a fourth, cool regime. This redefinition is illustrative of the fact that present regime classifications are inherently subjective and, thus, need to be modified to fit different datasets, models, and future scenarios. To enhance the utility of such shelf regime definitions across Antarctic studies, there is a need to objectively define the location of Antarctic

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Johnathan P. Kirk
and
Gordon A. Cromley

-scale atmospheric behavior or vice versa. This is typically investigated by employing a classification scheme, which characterizes the wide variety of atmospheric conditions for a certain location over time into a manageable sample of representative weather types or patterns ( Davis and Kalkstein 1990 ; Yarnal 1993 ). Many different strategies exist for producing classifications, but one that has emerged recently in climate literature, which is also ideally suited for connecting weather patterns to discrete

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Shannon Mason
,
Christian Jakob
,
Alain Protat
, and
Julien Delanoë

were found to have the greatest effect on the overall SW radiation budget in the area: an optically thick midtopped cloud regime and a very frequent low cloud regime. A similar method based on mean cloud-top properties is frequently used for model evaluation (see Williams and Webb 2009 ). Historically, climate models have tended to overestimate frontal cloud and optically thick low cloud while underrepresenting optically thin low cloud (e.g., trade cumulus) and midtopped clouds ( Webb et al. 2001

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Budong Qian
,
Xuebin Zhang
,
Kai Chen
,
Yang Feng
, and
Ted O’Brien

, H. , 1995 : Misuses of statistical analysis in climate research. Analysis of Climate Variability: Applications of Statistical Techniques, H. von Storch and A. Navarra, Eds., Springer, 11–26 . Wang , X. L. , and V. R. Swail , 2001 : Changes of extreme wave heights in Northern Hemisphere oceans and related atmospheric circulation regimes. J. Climate , 14 , 2204 – 2220 . Wheaton , E. , and Coauthors , 2005 : Lessons learned from the Canadian drought years 2001 and 2002

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Tanlong Dai
,
Wenjie Dong
,
Yan Guo
,
Tao Hong
,
Dong Ji
,
Shili Yang
,
Di Tian
,
Xiaohang Wen
, and
Xian Zhu

of years in the period 1948–75 before abrupt change, n 2 is the number of years classified as after abrupt change, and N 2 is the number of years in the period 1976–2005 after the abrupt change. The last classification parameter, ε , characterizes the ability of phase space to represent the abrupt change, that is to say, the fit to the climate factors combined into the phase space with the abrupt change in the phase space. In this study, ε is divided into four classes: when ε < 70%, the

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