Estimating Changes in the Observed Relationship Between Humidity and Temperature Using Noncrossing Quantile Smoothing Splines

Karen A. McKinnon () and Andrew Poppick ()
Additional contact information
Karen A. McKinnon: University of California, Los Angeles
Andrew Poppick: Carleton College

Journal of Agricultural, Biological and Environmental Statistics, 2020, vol. 25, issue 3, No 2, 292-314

Abstract: Abstract The impacts of warm season heat extremes are dependent on both temperature and humidity, so it is critical to properly model their relationship, including how it may be changing. This presents statistical challenges because the bivariate temperature–humidity (measured here by dew point) distribution is complex and spatially variable. Here, we develop a flexible, semiparametric model based on quantile smoothing splines to summarize the distributional dependence of dew point on temperature, including how the dependence is changing with increasing global mean temperature. Noncrossing constraints enforce both the validity of the modeled distributions and the physical constraint that dew point cannot exceed temperature. The proposed method is first demonstrated with four synthetic, representative case studies. We then apply it to data from 2416 weather stations spanning the globe, with a focus on analyzing dew point trends during hot days. In general, dew point is increasing on both hot, humid and hot, dry days in the tropics and high latitudes, but decreasing in the subtropics, especially on hot, dry days. These changes appear to be mostly explained by changes in the temperature–dew point relationship, rather than by increases in temperature with a fixed temperature–dew point relationship.

Keywords: Dew point; Global Summary of the Day; High-dimensional regularization; Noncrossing quantiles; Quantile regression; Quantile smoothing splines (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s13253-020-00393-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jagbes:v:25:y:2020:i:3:d:10.1007_s13253-020-00393-4

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/13253

DOI: 10.1007/s13253-020-00393-4

Access Statistics for this article

Journal of Agricultural, Biological and Environmental Statistics is currently edited by Stephen Buckland

More articles in Journal of Agricultural, Biological and Environmental Statistics from Springer, The International Biometric Society, American Statistical Association
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().