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Yanjun Guo and Yihui Ding

; Wang and Gaffen 2001 ). China has a dense radiosonde network that was launched in the 1950s; the network includes 116 radiosonde stations and mandatory pressure levels specified by the World Meteorological Organization ( WMO 1996 ). However, previous research of the free-atmosphere climatology only used data from several of the stations ( Zhai and Eskridge 1996 ). Elucidating trends in free-atmosphere temperature over China based on valid radiosonde data should provide insight into important

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David R. Easterling, Grant Goodge, Matthew J. Menne, Claude N. Williams Jr., and David Levinson

1. Introduction The globally averaged annual surface temperature time series since 1900 (e.g., Folland et al. 2001 ; Levinson et al. 2004 ) appears to be characterized by three distinct periods with differing temporal trends. During the early part of the record a positive trend occurs through the early 1940s, which is followed by a period of little change or possibly a slight negative trend. Since the late 1970s, however, the observed trend in global surface air temperature is approximately 0

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Luis A. Gil-Alana

1. Introduction The main purpose of this article is to examine if there are significant trends in the global and hemispheric temperature anomaly series. Denoting a time series for temperature anomalies by y t , the standard approach is to employ a simple linear regression model of form testing the significance of the estimated slope coefficient for β in (1) . It is not uncommon to find estimates of β based on ordinary least squares (OLS). However, statistical inference based on

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John R. Lanzante

-tropospheric maximum in warming that was not found in an adjusted radiosonde temperature dataset ( Thorne et al. 2005 ). Further studies of another of the adjusted datasets ( Lanzante et al. 2003a ), involving diagnoses of radiosonde data alone ( Sherwood et al. 2005 ), as well as comparisons with independent satellite data ( Randel and Wu 2006 ) suggest that even the adjusted radiosonde temperature data are afflicted by spurious cooling trends. In summary, evidence suggests that biases in the trends computed from

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Yinghui Liu, Jeffrey R. Key, and Xuanji Wang

extremely important climate change variable, because it integrates changes in the surface energy budget and atmospheric circulation ( Serreze et al. 2000 ). Due to the paucity of conventional observations in the Arctic, especially over the Arctic Ocean, an evaluation of trends in surface temperature is challenging. Rigor et al. (2000) analyzed the seasonal mean and trends of surface air temperature based on observations from buoys, manned drifting stations, and land meteorological stations, with

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Sarah T. Gille

(and respond to) atmospheric temperatures. Temperature records of 30- to 50-yr duration from the Antarctic Peninsula indicate surface air temperature trends of 3.3° to 5.6°C per century (see supplementary material of Vaughan et al. 2001 ), though temperatures in the interior of the Antarctic continent appear not to show a statistically significant warming trend during the same time period (e.g., Doran et al. 2002 ; Chapman and Walsh 2007 ). This temperature rise is associated both with increased

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Shouraseni Sen Roy and Fei Yuan

1. Introduction In recent decades there has been a rising awareness of climate change, largely due to a better understanding of long-term changes in climatic processes at different spatial scales. A leading manifestation of climate change is rising temperatures, which have widespread impacts on different components of the earth–atmosphere system. According to the fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC), there has been a linear increasing trend of 0.74°C

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Melissa S. Bukovsky

1. Introduction Regional climate models (RCMs) should be able to capture large-scale temperature trends when forcing for these trends is included in the driving boundary conditions. This is logical, but it is only recently that the RCM community has tested its models’ performances in this way, and examples are still not prevalent in the literature. Testing for skill in reproducing trends is a relatively recent phenomenon (e.g., Giorgi et al. 2004 ), while testing for general skill in regional

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Holly A. Titchner, P. W. Thorne, M. P. McCarthy, S. F. B. Tett, L. Haimberger, and D. E. Parker

1. Introduction There has been much debate surrounding tropical tropospheric temperatures since the first attempt to create a satellite-based climate dataset ( Spencer and Christy 1990 ). Climate models predict amplification of the observed tropical warming trends at the surface ( Santer et al. 2005 ; Karl et al. 2006 ), with maximum warming rates expected in the middle and upper troposphere. The observations are currently inadequately characterized to statistically robustly inform on this

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John R. Lanzante and Melissa Free

. Ironically, reconciliation of the conflicting trend estimates was not the result of a narrower range of observational estimates, but instead an expanded range that better encompasses comparable estimates from climate models. Although estimates of large-scale, long-term temperature changes at the surface are reasonably well constrained, those from the highest-quality datasets available for the troposphere and the stratosphere still span a considerable range ( Karl et al. 2006 ). The reason for the

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