Quantifying daytime heating biases in marine air temperature observations from ships
Cropper, Thomas ORCID: https://orcid.org/0000-0002-3696-7905; Berry, David ORCID: https://orcid.org/0000-0002-3862-3479; Cornes, Richard ORCID: https://orcid.org/0000-0002-7688-4485; Kent, Elizabeth ORCID: https://orcid.org/0000-0002-6209-4247. 2023 Quantifying daytime heating biases in marine air temperature observations from ships. Journal of Atmospheric and Oceanic Technology. 13, pp. 10.1175/JTECH-D-22-0080.1
Before downloading, please read NORA policies.Preview |
Text
1520-0426-JTECH-D-22-0080.1.pdf - Published Version Available under License Creative Commons Attribution 4.0. Download (1MB) | Preview |
Abstract/Summary
Marine air temperatures recorded on ships during the daytime are known to be biased warm on average due to energy storage by the superstructure of the vessels. This makes unadjusted daytime observations unsuitable for many applications including for the monitoring of long-term temperature change over the oceans. In this paper a physics-based approach is used to estimate this heating bias in ship observations from ICOADS. Under this approach, empirically determined coefficients represent the energy transfer terms of a heat budget model which quantifies the heating bias and is applied as a function of cloud cover and the relative wind speed over individual ships. The coefficients for each ship are derived from the anomalous diurnal heating relative to nighttime air temperature. Model coefficients, cloud cover and relative wind speed are then used to estimate the heating bias ship-by-ship and generate nighttime-equivalent time series. A variety of methodological approaches were tested. Application of this method enables the inclusion of some daytime observations in climate records based on marine air temperatures, allowing an earlier start date and giving an increase in spatial coverage compared to existing records that exclude daytime observations.
Item Type: | Publication - Article |
---|---|
Digital Object Identifier (DOI): | 10.1175/JTECH-D-22-0080.1 |
ISSN: | 0739-0572 |
Date made live: | 24 Jan 2023 13:08 +0 (UTC) |
URI: | https://nora.nerc.ac.uk/id/eprint/533912 |
Actions (login required)
View Item |
Document Downloads
Downloads for past 30 days
Downloads per month over past year