Evolution and Distribution of Record-Breaking High and Low Monthly Mean Temperatures

The ratio of record highs to record lows is examined with respect to extent of time series for monthly mean temperatures within the continental United States for 1900-2006. In counting the number of records that occur in a single year, the authors find a ratio greater than unity in 2006, increasing nearly monotonically as the time series increases in length via a variable first year over 1900-76. For example, in 2006, the ratio of record highs to record lows approximate to 13:1 with 1950 as the first year and approximate to 25:1 with 1900 as the first year; both ratios are an order of magnitude greater than 3 sigma for stationary simulations. This indicates a warming trend. It is also found that records are more sensitive to trends in time series of monthly averages than in time series of corresponding daily values. When the last year (1920-2006, starting in 1900) is varied, it is found that the ratio of record highs to record lows is strongly correlated with the ensemble mean temperature. Correlation coefficients are 0.76 and 0.82 for 1900-2006 and 1950-2006, respectively; 3 sigma = 0.3 for pairs of uncorrelated stationary time series. Similar values are found for globally distributed time series:0.87 and 0.92 for 1900-2006 and 1950-2006, respectively. The ratios evolve differently, however:global ratios increase throughout (1920-2006) whereas continental U. S. ratios decrease from about 1940 to 1970. Last, the geographical and seasonal distributions of trends are considered by summing records over time rather than ensemble. In the continental United States, the greatest excess of record highs occurs in February (approximate to 2:1) and the greatest excess of record lows occurs in October (approximate to 2:3). In addition, ratios are pronounced in certain regions:in February in the Midwest the ratio approximate to 5:2, and in October in the Southeast the ratio approximate to 1:2.