Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Statistical Relations Among Precipitation, Atmospheric Moisture and Cloud Parameters in the Arctic Atmosphere

Version 1 : Received: 5 January 2024 / Approved: 8 January 2024 / Online: 9 January 2024 (10:39:32 CET)

A peer-reviewed article of this Preprint also exists.

Matrosov, S.Y. Statistical Relations among Solid Precipitation, Atmospheric Moisture and Cloud Parameters in the Arctic. Atmosphere 2024, 15, 132. Matrosov, S.Y. Statistical Relations among Solid Precipitation, Atmospheric Moisture and Cloud Parameters in the Arctic. Atmosphere 2024, 15, 132.

Abstract

Observations collected during cold season precipitation periods at Utquagvik, Alaska and at the mul-tidisciplinary drifting observatory for study of Arctic climate (MOSAiC) are used to statistically ana-lyze relations among the atmospheric water cycle parameters including the columnar supercooled liq-uid and ice amounts (expressed as liquid water and ice water paths, i.e., LWP and IWP), the integrated water vapor (IWV) and the near-surface snowfall rate. Data come from radar and radiometer-based retrievals and from optical precipitation sensors. While correlation between snowfall rate and LWP is rather weak, correlations coefficients between radar-derived snowfall rate and IWP are high (~ 0.8), which is explained, in part, by generally low LWP/IWP ratios during significant precipitation. Corre-lation coefficients between snowfall rate and IWV are moderate (~0.45). Correlations are generally weaker if snowfall is estimated by optical sensors, which is, in part, due to blowing snow. Correlation coefficients between near-surface temperature and snowfall rates are low (r<0.3). Results from the Alaska and MOSAiC sites are generally similar. These results are not very sensitive to the amount of time averaging (e.g., 15-minute averaging versus daily averages). Observationally-based relations among the water cycle parameters are informative about atmospheric moisture conversion processes and can be used for model evaluations.

Keywords

snowfall; cloud content; water vapor; surface meteorology; correlation analysis; Arctic climate; water cycle

Subject

Physical Sciences, Other

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)
* All users must log in before leaving a comment
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.