2017
DOI: 10.1002/2017jd027205
|View full text |Cite
|
Sign up to set email alerts
|

Evaluation of an Improved Quasi‐stochastic Collection Model Through Precipitation Prediction Over North Central Mongolia

Abstract: One of the key components of bin microphysics schemes is the quasi‐stochastic collection equation that describes the collection process of cloud particles. The normal quasi‐stochastic model, hereafter the NQS model, assumes that the time step is infinitesimally small, so that a cloud particle can collide with other cloud particle only once within the time step. However, since the time step is finite, a cloud particle can collide with other cloud particle more than one time within the time step. Hence, the impr… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2018
2018
2018
2018

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 29 publications
0
1
0
Order By: Relevance
“…Quantifying and reducing errors associated with numerically calculating DSD evolution in bin schemes has been a significant challenge since their inception. Numerous studies over the past several decades have focused on improving the numerical treatment of drop growth caused by condensation and collisioncoalescence (e.g., Kovetz and Olund 1969;Bleck 1970;Young 1974;Soong 1974;Tzivion et al 1987;Stevens et al 1996a;Liu et al 1997;Bott 1998;Tzivion et al 1999;Alfonso 2015;Lkhamjav et al 2017). For example, a simple method that conserves bulk mass by treating drop growth as first-order upwind advection in mass space was proposed by Kovetz and Olund (1969), but this led to rather inaccurate solutions for condensational growth (Liu et al 1997) and rapid, artificial generation of precipitation (Ochs and Yao 1978).…”
Section: Introductionmentioning
confidence: 99%
“…Quantifying and reducing errors associated with numerically calculating DSD evolution in bin schemes has been a significant challenge since their inception. Numerous studies over the past several decades have focused on improving the numerical treatment of drop growth caused by condensation and collisioncoalescence (e.g., Kovetz and Olund 1969;Bleck 1970;Young 1974;Soong 1974;Tzivion et al 1987;Stevens et al 1996a;Liu et al 1997;Bott 1998;Tzivion et al 1999;Alfonso 2015;Lkhamjav et al 2017). For example, a simple method that conserves bulk mass by treating drop growth as first-order upwind advection in mass space was proposed by Kovetz and Olund (1969), but this led to rather inaccurate solutions for condensational growth (Liu et al 1997) and rapid, artificial generation of precipitation (Ochs and Yao 1978).…”
Section: Introductionmentioning
confidence: 99%