How Temperature Trends Vary with Specific Humidity in the Tropical Lower Troposphere in ERA5.
Saved in:
| Title: | How Temperature Trends Vary with Specific Humidity in the Tropical Lower Troposphere in ERA5. |
|---|---|
| Authors: | Roundy, Paul E.1 (AUTHOR) proundy@albany.edu |
| Source: | Journal of Climate. Aug2025, Vol. 38 Issue 15, p3815-3823. 9p. |
| Subjects: | Humidity, Global temperature changes, Troposphere, Climate change, Statistical reliability |
| Abstract: | The rate of change of temperature during 1979–2020 is assessed as a continuous function of specific humidity for the tropical lower troposphere using ERA5 reanalysis data and a modulation regression technique. Statistical stability is assessed through a Monte Carlo experiment and for consistency with bulk data through bivariate histograms that show how the broader distributions of moisture and temperature have evolved together over time. Reanalysis ensemble spread is also assessed. Results show that warming rates exceed 2 K century−1 in dry air over land and water at 900 hPa but are significantly smaller in moist air over water and near zero in the moistest air over land. Cooling at 900 hPa is demonstrated for the global tropics and for the tropical oceans near 1000 hPa at specific humidities near a mass fraction of 0.01. These cooling results may be driven by decadal internal variability or a forced response to CO2 in the southeast Pacific basin. Similar cooling does not occur over land. Significance Statement: Warming of the tropical lower troposphere in the ERA5 reanalysis is occurring several times faster in dry air than in moist air. Moist air over land warms relatively little, while moist air over the oceans has been averaging warming at about a degree per century. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Climate is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
Be the first to leave a comment!
