On the predictability of mesoscale convective systems: Two-dimensional simulations

Matthew S. Wandishin, David J. Stensrud, Steven Mullen, Louis J. Wicker

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

Mesoscale convective systems (MCSs) are a dominant climatological feature of the central United States and are responsible for a substantial fraction of warm season rainfall. Yet very little is known about the predictability of MCSs. To help alleviate this situation, a series of ensemble simulations of an MCS are performed on a two-dimensional, storm-scale (Δx = 1 km) model. Ensemble member perturbations in wind speed, relative humidity, and instability are based on current 24-h forecast errors from the North American Model (NAM). The ensemble results thus provide an upper bound on the predictability of mesoscale convective systems within realistic estimates of environmental uncertainty, assuming successful convective initiation. The simulations are assessed by considering an ensemble member a success when it reproduces a convective system of at least 20 km in length (roughly the size of two convective cells) within 100 km on either side of the location of the MCS in the control run. By that standard, MCSs occur roughly 70% of the time for perturbation magnitudes consistent with 24-h forecast errors. Reducing the perturbations for all fields to one-half the 24-h error values increases the MCS success rate to over 90%. The same improvement in forecast accuracy would lead to a 30%-40% reduction in maximum surface wind speed uncertainty and a roughly 20% reduction in the uncertainty in maximum updraft strength, and initially slower growth in the uncertainty in the size of the MCS. However, the occurrence of MCSs drops below 50% as the midlayer mean relative humidity falls below 65%. The response of the model to reductions in forecast errors for instability, moisture, and wind speed is not consistent and cannot be easily generalized, but each can have a substantial impact on forecast uncertainty.

Original languageEnglish (US)
Pages (from-to)773-785
Number of pages13
JournalWeather and Forecasting
Volume23
Issue number5
DOIs
StatePublished - 2008

Fingerprint

convective system
simulation
wind velocity
perturbation
relative humidity
updraft
surface wind
moisture
forecast
rainfall

ASJC Scopus subject areas

  • Atmospheric Science

Cite this

On the predictability of mesoscale convective systems : Two-dimensional simulations. / Wandishin, Matthew S.; Stensrud, David J.; Mullen, Steven; Wicker, Louis J.

In: Weather and Forecasting, Vol. 23, No. 5, 2008, p. 773-785.

Research output: Contribution to journalArticle

Wandishin, Matthew S. ; Stensrud, David J. ; Mullen, Steven ; Wicker, Louis J. / On the predictability of mesoscale convective systems : Two-dimensional simulations. In: Weather and Forecasting. 2008 ; Vol. 23, No. 5. pp. 773-785.
@article{d5463cac21a8436dabf18761ab249889,
title = "On the predictability of mesoscale convective systems: Two-dimensional simulations",
abstract = "Mesoscale convective systems (MCSs) are a dominant climatological feature of the central United States and are responsible for a substantial fraction of warm season rainfall. Yet very little is known about the predictability of MCSs. To help alleviate this situation, a series of ensemble simulations of an MCS are performed on a two-dimensional, storm-scale (Δx = 1 km) model. Ensemble member perturbations in wind speed, relative humidity, and instability are based on current 24-h forecast errors from the North American Model (NAM). The ensemble results thus provide an upper bound on the predictability of mesoscale convective systems within realistic estimates of environmental uncertainty, assuming successful convective initiation. The simulations are assessed by considering an ensemble member a success when it reproduces a convective system of at least 20 km in length (roughly the size of two convective cells) within 100 km on either side of the location of the MCS in the control run. By that standard, MCSs occur roughly 70{\%} of the time for perturbation magnitudes consistent with 24-h forecast errors. Reducing the perturbations for all fields to one-half the 24-h error values increases the MCS success rate to over 90{\%}. The same improvement in forecast accuracy would lead to a 30{\%}-40{\%} reduction in maximum surface wind speed uncertainty and a roughly 20{\%} reduction in the uncertainty in maximum updraft strength, and initially slower growth in the uncertainty in the size of the MCS. However, the occurrence of MCSs drops below 50{\%} as the midlayer mean relative humidity falls below 65{\%}. The response of the model to reductions in forecast errors for instability, moisture, and wind speed is not consistent and cannot be easily generalized, but each can have a substantial impact on forecast uncertainty.",
author = "Wandishin, {Matthew S.} and Stensrud, {David J.} and Steven Mullen and Wicker, {Louis J.}",
year = "2008",
doi = "10.1175/2008WAF2007057.1",
language = "English (US)",
volume = "23",
pages = "773--785",
journal = "Weather and Forecasting",
issn = "0882-8156",
publisher = "American Meteorological Society",
number = "5",

}

TY - JOUR

T1 - On the predictability of mesoscale convective systems

T2 - Two-dimensional simulations

AU - Wandishin, Matthew S.

AU - Stensrud, David J.

AU - Mullen, Steven

AU - Wicker, Louis J.

PY - 2008

Y1 - 2008

N2 - Mesoscale convective systems (MCSs) are a dominant climatological feature of the central United States and are responsible for a substantial fraction of warm season rainfall. Yet very little is known about the predictability of MCSs. To help alleviate this situation, a series of ensemble simulations of an MCS are performed on a two-dimensional, storm-scale (Δx = 1 km) model. Ensemble member perturbations in wind speed, relative humidity, and instability are based on current 24-h forecast errors from the North American Model (NAM). The ensemble results thus provide an upper bound on the predictability of mesoscale convective systems within realistic estimates of environmental uncertainty, assuming successful convective initiation. The simulations are assessed by considering an ensemble member a success when it reproduces a convective system of at least 20 km in length (roughly the size of two convective cells) within 100 km on either side of the location of the MCS in the control run. By that standard, MCSs occur roughly 70% of the time for perturbation magnitudes consistent with 24-h forecast errors. Reducing the perturbations for all fields to one-half the 24-h error values increases the MCS success rate to over 90%. The same improvement in forecast accuracy would lead to a 30%-40% reduction in maximum surface wind speed uncertainty and a roughly 20% reduction in the uncertainty in maximum updraft strength, and initially slower growth in the uncertainty in the size of the MCS. However, the occurrence of MCSs drops below 50% as the midlayer mean relative humidity falls below 65%. The response of the model to reductions in forecast errors for instability, moisture, and wind speed is not consistent and cannot be easily generalized, but each can have a substantial impact on forecast uncertainty.

AB - Mesoscale convective systems (MCSs) are a dominant climatological feature of the central United States and are responsible for a substantial fraction of warm season rainfall. Yet very little is known about the predictability of MCSs. To help alleviate this situation, a series of ensemble simulations of an MCS are performed on a two-dimensional, storm-scale (Δx = 1 km) model. Ensemble member perturbations in wind speed, relative humidity, and instability are based on current 24-h forecast errors from the North American Model (NAM). The ensemble results thus provide an upper bound on the predictability of mesoscale convective systems within realistic estimates of environmental uncertainty, assuming successful convective initiation. The simulations are assessed by considering an ensemble member a success when it reproduces a convective system of at least 20 km in length (roughly the size of two convective cells) within 100 km on either side of the location of the MCS in the control run. By that standard, MCSs occur roughly 70% of the time for perturbation magnitudes consistent with 24-h forecast errors. Reducing the perturbations for all fields to one-half the 24-h error values increases the MCS success rate to over 90%. The same improvement in forecast accuracy would lead to a 30%-40% reduction in maximum surface wind speed uncertainty and a roughly 20% reduction in the uncertainty in maximum updraft strength, and initially slower growth in the uncertainty in the size of the MCS. However, the occurrence of MCSs drops below 50% as the midlayer mean relative humidity falls below 65%. The response of the model to reductions in forecast errors for instability, moisture, and wind speed is not consistent and cannot be easily generalized, but each can have a substantial impact on forecast uncertainty.

UR - http://www.scopus.com/inward/record.url?scp=65549090837&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=65549090837&partnerID=8YFLogxK

U2 - 10.1175/2008WAF2007057.1

DO - 10.1175/2008WAF2007057.1

M3 - Article

AN - SCOPUS:65549090837

VL - 23

SP - 773

EP - 785

JO - Weather and Forecasting

JF - Weather and Forecasting

SN - 0882-8156

IS - 5

ER -