Matthew J. Menne

TL;DR: The most recent version of ICOADS (R3.0) has been updated and updated from version 4 to version 5 in this article, with more realistic spatiotemporal variations, better representation of high-latitude SSTs, and ship SST biases calculated relative to more accurate buoy measurements.

Abstract: A database is described that has been designed to fulfill the need for daily climate data over global land areas. The dataset, known as Global Historical Climatology Network (GHCN)-Daily, was developed for a wide variety of potential applications, including climate analysis and monitoring studies that require data at a daily time resolution (e.g., assessments of the frequency of heavy rainfall, heat wave duration, etc.). The dataset contains records from over 80 000 stations in 180 countries and territories, and its processing system produces the official archive for U.S. daily data. Variables commonly include maximum and minimum temperature, total daily precipitation, snowfall, and snow depth; however, about two-thirds of the stations report precipitation only. Quality assurance checks are routinely applied to the full dataset, but the data are not homogenized to account for artifacts associated with the various eras in reporting practice at any particular station (i.e., for changes in systematic...

TL;DR: An updated global surface temperature analysis reveals that global trends are higher than those reported by the Intergovernmental Panel on Climate Change, especially in recent decades, and that the central estimate for the rate of warming during the first 15 years of the 21st century is at least as great as the last half of the 20th century.

TL;DR: The Global Historical Climatology Network-Monthly (GHCN-M) data set has been an internationally recognized source of data for the study of observed variability and change in land surface temperature.

TL;DR: In this article, a new and improved uncertainty analysis for the Goddard Institute for Space Studies Surface Temperature product version 4 (GISTEMP v4) is presented, which incorporates independently derived estimates for ocean data processing, station homogenization, and other structural biases.