Varied Diagnosis of the Observed Surface Temperature Trends in the Southeast United States

Abstract

This paper diagnoses the temperature trends in maximum (T max ) and minimum temperatures (T min ) over a selection of 65 stations spread over the southeast United States (SEUS) from three observed datasets. They are the Cooperative Observer network program (COOP), the COOP data corrected for documented shifts in time of observation (COOP1), and the COOP data additionally corrected for documented changes in instrumentation (COOP2). These 65 stations have been isolated for having the three observed datasets for the same time period from 1948 to 2009. The authors' comparisons suggest that COOP2 displays stronger warming (cooling) trends in T max (T min ) compared with COOP1 in all four seasons. This is consistent with the expectation from the bias correction applied for the instrument change. In comparison, the differences between COOP and COOP2 are relatively larger. In the spring, summer, and fall seasons, the median T max trend is warming in COOP2 while it is cooling in COOP. In the winter season, the median trends of T max in the two datasets are positive, but their magnitudes are substantially different. Similarly, in the winter, summer, and fall seasons, the warming trend in T min in COOP is contrary to the cooling trend in COOP2. In the spring season, the median trend in T min is comparable between the two datasets. COOP2 shows the relationship of trends in T min , with the extent of urbanization in these 65 stations, to be statistically significant and to be consistent with expectations from theory in contrast to the COOP data.

MOTEDAS: a new monthly temperature database for mainland Spain and the trend in temperature (1951–2010)

“…National and regional climate studies have revealed spatial differences in warming trends, and considerable attention has been paid to the quality of data and its effects on temperature trends (see Misra and Michael, ; Rohde et al , ). The problem appears to be a never‐ending story because homogenization still cannot guarantee absolute quality of a database, even if it certainly improves data quality and trend estimation (Venema et al , ).…”

Downscaled climate projections for the Southeast United States: evaluation and use for ecological applications

“…The number of days with below-freezing temperatures has decreased by 4 to 7 days per year for most of the Southeast since the mid-1970s (Karl and others, 2009). More recently, and Misra and Michael (2013) have shown that the observed temperature trends in the Southeast are affected by land-cover and land-use changes (e.g., irrigation or urbanization). The National Climate Assessment contains further information regarding the climate of the Southeast U.S. (accessed August 13, 2014, at http://www.globalchange.gov/ncadac).…”

Recent trend in temperature evolution in Spanish mainland (1951–2010): from warming to hiatus

“…The hiatus sometimes has been only accepted during winter (Cohen et al, 2013), and finally no consensus exists, and Foster and Rahmstorf (2011) and more recently Karl et al (2015) have neglected the hiatus and suggested that the warming rate has remained almost constant until the present. At the same time, temperature evolution has been extensively analysed not only as a consequence of the detection of hiatus (Foster and Rahmstorf, 2011;Hunt, 2011;Kaufmann et al, 2011;Parker, 2011;Cohen et al, 2013;England et al, 2014), but also because satellite observations from 1979 are currently being compared with surface observations (Douglas et al, 2004;Klotzbach et al, 2009), and because regional analyses have detected negative temperature trends, particularly in the United States and China, offering a new and controversial problem in which the quality of data and local factors must be taken into account (Lebassi et al, 2009;Quirk 2012;Capparelli et al, 2013;Misra and Michael, 2013;Peng et al, 2014).…”