The shifting probability distribution of global daytime and night‐time temperatures

Abstract

[1] Using a global observational dataset of daily gridded maximum and minimum temperatures we investigate changes in the respective probability density functions of both variables using two 30-year periods; 1951-1980 and 1981-2010. The results indicate that the distributions of both daily maximum and minimum temperatures have significantly shifted towards higher values in the latter period compared to the earlier period in almost all regions, whereas changes in variance are spatially heterogeneous and mostly less significant. However asymmetry appears to have decreased but is altered in such a way that it has become skewed towards the hotter part of the distribution. Changes are greater for daily minimum (night-time) temperatures than for daily maximum (daytime) temperatures. As expected, these changes have had the greatest impact on the extremes of the distribution and we conclude that the distribution of global daily temperatures has indeed become "more extreme" since the middle of the 20th century. Citation: Donat, M. G., and L. V.Alexander (2012), The shifting probability distribution of global daytime and night-time temperatures, Geophys. Res. Lett., 39,

Range of monthly mean hourly land surface air temperature diurnal cycle over high northern latitudes

“…Major findings from previous analyses of these data include the global warming in the past century, the amplification of warming over high latitudes, and the faster increase of monthly Tn with time than that of monthly Tx leading to the negative trend of monthly mean DTR (MDTR) [Karl et al, 1993;Easterling et al, 1997;Vose et al, 2005;Trenberth et al, 2007;Donat and Alexander, 2012]. Furthermore, the decrease of MDTR with time is not spatially uniform in observations [Easterling et al, 1997] or general circulation models [Stone and Weaver, 2003].…”

Evaluation of CORDEX-Arctic daily precipitation and temperature-based climate indices over Canadian Arctic land areas

“…A similar method was adopted by Alexander et al (2006) in the analysis of global climate annual indices from a subset of 200 temperature and 350 precipitation stations across the globe. Donat and Alexander (2012), Hansen et al (2012), and Hansen and Sato (2016) used probability density distributions of temperature anomalies over specific regions rather than absolute-value distributions because the anomalies have a higher spatial correlation, while absolute mean temperatures can vary over short spatial scales (Hawkins and Sutton 2016). Consequently, even a few stations can capture the temporal characteristics of anomalies over a large region.…”

Rising air and stream-water temperatures in Chesapeake Bay region, USA

“…Although climate normal periods are 30 years (e.g., Donat and Alexander 2012), our 51-year dataset required the use of two 25-year periods for comparison of the anomalies. We constructed probability density functions (pdfs) for 1961-1985 (former period) and 1986-2010 (latter period) relative to 1971-2000 for both AT and WT following methods of Donat and Alexander (2012). We tested for differences in the means of the anomalies of the former and latter periods using a Student's t-test and a Rank Sum test.…”