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Cited by 68Meteorological Phenomena and SimulationsClimate variability and modelsPrecipitation Measurement and Analysis

First-Passage-Time Prototypes for Precipitation Statistics

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Stechmann, Samuel N., Neelin, J. David·2014·Journal of the Atmospheric Sciences
DOI 10.1175/jas-d-13-0268.1
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Abstract

Prototype models are presented for time series statistics of precipitation and column water vapor. In these models, precipitation events begin when the water vapor reaches a threshold value and end when it reaches a slightly lower threshold value, as motivated by recent observational and modeling studies. Using a stochastic forcing to parameterize moisture sources and sinks, this dynamics of reaching a threshold is a first-passage-time problem that can be solved analytically. Exact statistics are presented for precipitation event sizes and durations, for which the model predicts a probability density function (pdf) with a power law with exponent −. The range of power-law scaling extends from a characteristic small-event size to a characteristic large-event size, both of which are given explicitly in terms of the precipitation rate and water vapor variability. Outside this range, exponential scaling of event-size probability is shown. Furthermore, other statistics can be computed analytically, including cloud fraction, the pdf of water vapor, and the conditional mean and variance of precipitation (conditioned on the water vapor value). These statistics are compared with observational data for the transition to strong convection; the stochastic prototype captures a set of properties originally analyzed by analogy to critical phenomena. In a second prototype model, precipitation is further partitioned into deep convective and stratiform episodes. Additional exact statistics are presented, including stratiform rain fraction and cloud fractions, that suggest that even very simple temporal transition rules (for stratiform rain continuing after convective rain) can capture aspects of the role of stratiform precipitation in observed precipitation statistics.

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  • Observed distributions of event depths exhibit a power law range.

    “observed distributions of event depths exhibit a power law range [68, 81]”

    From Precipitation Extremes Under Climate Change (2015) · cites this paper as [81]

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  • Precipitation Extremes Under Climate Change

    O’Gorman, P. A. (2015) · Current Climate Change Reports · doi:10.1007/s40641-015-0009-3 · Cited by 831 · see citing works

    “Consideration of the amount of precipitation in a given event (the event depth) may be advantageous because observed distributions of event depths exhibit a power law range [68,81] and thus their response to climate change may be relatively simple to characterize.”
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Related

Authors
Stechmann, S. N., & Neelin, J. D.
Affiliations
  • University of Wisconsin–Madison (US)
  • University of California, Los Angeles (US)
ORCID
Venue
Journal of the Atmospheric Sciences
Publisher
American Meteorological Society
Published
2014-08-28
Volume
71
Issue
9
Pages
3269-3291
ISSN
  • 0022-4928 (ISSN-L)
  • 1520-0469
DOI
10.1175/jas-d-13-0268.1
OpenAlex
W2059813821
Cited by
68
References
60
Citations by year
2026: 4 · 2025: 3 · 2024: 3 · 2023: 5 · 2022: 7 · 2021: 5 · 2020: 8 · 2019: 6 · 2018: 3 · 2017: 9 · 2016: 4 · 2015: 5 · 2014: 3
FWCI
4.65
Type
journal article
Language
en
Open access
Locations
Journal of the Atmospheric Sciences (publishedVersion)
Funders
  • National Science Foundation (1102838)
  • National Oceanic and Atmospheric Administration (NA11OAR4310099)
  • Office of Naval Research (N00014-12-1, N00014, N00014-12-1-0744)
Topics
  • Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Meteorological Phenomena and Simulations
  • Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
  • Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Precipitation Measurement and Analysis
Keywords
precipitation statistics, column water vapor, power-law scaling, cloud fraction, stratiform precipitation, deep convection, precipitation duration

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