Title: A Comprehensive Analysis of Uncertainties in Warm-Rain Parameterizations in Climate Models Based on In Situ Measurements

Journal Article · · Journal of the Atmospheric Sciences
ORCiD logo [1];  [2];  [3];  [2]
  1. a Physics Department, University of Maryland, Baltimore County, Baltimore, Maryland, b Goddard Earth Sciences Technology and Research, University of Maryland, Baltimore County, Baltimore, Maryland
  2. c Department of Geography and Atmospheric Science, University of Kansas, Lawrence, Kansas
  3. d Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

Abstract Because of the coarse grid size of Earth system models (ESMs), representing warm-rain processes in ESMs is a challenging task involving multiple sources of uncertainty. Previous studies evaluated warm-rain parameterizations mainly according to their performance in emulating collision–coalescence rates for local droplet populations over a short period of a few seconds. The representativeness of these local process rates comes into question when applied in ESMs for grid sizes on the order of 100 km and time steps on the order of 20–30 min. We evaluate several widely used warm-rain parameterizations in ESM application scenarios. In the comparison of local and instantaneous autoconversion rates, the two parameterization schemes based on numerical fitting to stochastic collection equation (SCE) results perform best. However, because of Jessen’s inequality, their performance deteriorates when grid-mean, instead of locally resolved, cloud properties are used in their simulations. In contrast, the effect of Jessen’s inequality partly cancels the overestimation problem of two semianalytical schemes, leading to an improvement in the ESM-like comparison. In the assessment of uncertainty due to the large time step of ESMs, it is found that the rainwater tendency simulated by the SCE is roughly linear for time steps smaller than 10 min, but the nonlinearity effect becomes significant for larger time steps, leading to errors up to a factor of 4 for a time step of 20 min. After considering all uncertainties, the grid-mean and time-averaged rainwater tendency based on the parameterization schemes is mostly within a factor of 4 of the local benchmark results simulated by SCE.

Research Organization:
Colorado State Univ., Fort Collins, CO (United States); Univ. of Kansas, Lawrence, KS (United States); Univ. of Maryland Baltimore County (UMBC), Baltimore, MD (United States)
Sponsoring Organization:
USDOE; USDOE Office of Science (SC)
Grant/Contract Number:
SC0020057; SC0021167; SC0023083
OSTI ID:
2406508
Journal Information:
Journal of the Atmospheric Sciences, Journal Name: Journal of the Atmospheric Sciences Journal Issue: 7 Vol. 81; ISSN 0022-4928
Publisher:
American Meteorological SocietyCopyright Statement
Country of Publication:
United States
Language:
English