Identification

Title

Multiscale weather forecasting sensitivities to urban characteristics and atmospheric conditions during a cold front passage over the Dallas-Fort Worth metroplex

Abstract

<span style="-webkit-text-stroke-width:0px;color:rgb(31, 31, 31);display:inline !important;float:none;font-family:ElsevierGulliver, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif, sans-serif;font-size:16px;font-style:normal;font-variant-caps:normal;font-variant-ligatures:normal;font-weight:400;letter-spacing:normal;orphans:2;text-align:start;text-decoration-color:initial;text-decoration-style:initial;text-decoration-thickness:initial;text-indent:0px;text-transform:none;white-space:normal;widows:2;word-spacing:0px;">Sensitivities of microscale weather modeling to atmospheric conditions and urban layout are investigated utilizing a combination of automated surface observing systems (ASOS) data, 1-km mesoscale numerical weather prediction (NWP), and 5-m nested large-eddy simulation (LES) modeled conditions. The 1-km mesoscale predictions in analysis mode satisfactorily reproduce the observed spatiotemporal evolution of the frontal boundary in terms of wind speed, wind direction, and temperature. The 5-m nested LES simulations follow the large-scale forcing trends while improving wind speed predictions due to explicitly resolving turbulence and building interactions. Moreover, 5-min averaged nested LES results reveal improved temporal variability particularly during the stronger wind and turbulence post-frontal conditions. The skill of the 1-km mesoscale NWP model prediction is compared to coarse-grained LES fields. Probability distributions extracted from the 5-m nested LES predictions exhibit the largest sensitivity to the contrasting meteorological conditions. In contrast, cumulative distributions of TKE additionally expose a marked dependency on the unique distribution of building heights, urban density and clustering in a given area. For the first time, an ensemble forecast methodological design at building-resolving grid spacing is explored. A larger microscale ensemble spread is found for TKE than for wind speed, decreasing with height and modulated by weather conditions.

Resource type

document

Resource locator

Unique resource identifier

code

https://n2t.net/ark:/85065/d72r3x2j

codeSpace

Dataset language

eng

Spatial reference system

code identifying the spatial reference system

Classification of spatial data and services

Topic category

geoscientificInformation

Keywords

Keyword set

keyword value

Text

originating controlled vocabulary

title

Resource Type

reference date

date type

publication

effective date

2016-01-01T00:00:00Z

Geographic location

West bounding longitude

East bounding longitude

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Temporal reference

Temporal extent

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End position

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date type

publication

effective date

2025-03-01T00:00:00Z

Frequency of update

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Conformity

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Use constraints

Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Limitations on public access

None

Responsible organisations

Responsible party

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata on metadata

Metadata point of contact