We present a high-resolution daily temperature data set, CHIRTS-daily, which is derived by merging the monthly Climate Hazards center InfraRed Temperature with Stations climate record with daily temperatures from version 5 of the European Centre for Medium-Range Weather Forecasts Re-Analysis. We demonstrate that remotely sensed temperature estimates may more closely represent true conditions than those that rely on interpolation, especially in regions with sparse in situ data. By leveraging remotely sensed infrared temperature observations, CHIRTS-daily provides estimates of 2-meter air temperature for 1983–2016 with a footprint covering 60°S-70°N. We describe this data set and perform a series of validations using station observations from two prominent climate data sources. The validations indicate high levels of accuracy, with CHIRTS-daily correlations with observations ranging from 0.7 to 0.9, and very good representation of heat wave trends.
Bibliographical noteFunding Information:
This work was supported by the National Science Foundation Award Abstract #1639214 INFEWS/T1: Understanding multi-scale resilience options for vulnerable regions, US Geological Survey cooperative agreement #G09AC000001, USAID cooperative agreement: Early identification and forecasts of reduced-yield agricultural seasons in the Developing World, and the USGS Drivers of Drought project. The Climate Hazards Center acknowledges support from the Defense Advanced Research Projects Agency (DARPA) World Modelers Program under Army Research Office (ARO) prime contract no. W911NF-18-1-0018. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the position or the policy of the Government or the Prime Contract (DARPA and ARO), and no such official endorsement by either should be inferred. The views and conclusions presented in this article do, however, represent the views of the U.S. Geological Survey. The authors thank Climate Hazards Center’s technical writer, Juliet Way-Henthorne, for providing professional editing.
© 2020, The Author(s).
Copyright 2020 Elsevier B.V., All rights reserved.
PubMed: MeSH publication types
- Journal Article
- Research Support, U.S. Gov't, Non-P.H.S.
- Research Support, Non-U.S. Gov't