Transcript Meteorological Processes Impacting Cold-Air Pools Future

Introduction
• High wintertime ozone concentrations in rural areas
associated with oil and gas development and high
particulate concentrations in urban areas are topics
of concern in Western US basins
• The physical processes that contribute to the
formation, maintenance, and decay of persistent
wintertime cold-air pools (CAPs) are only partially
understood
• Weather Research and
Forecasting (WRF) model
Great
simulations used in concert
Salt
Lake
with observations from the
Basin
Uintah
Persistent Cold Air Pool and
Basin
Uintah Basin Ozone Studies
Utah
• Ongoing efforts to improve
model
capability
to
simulate
cold
pool
conditions
Meteorological Processes Impacting Cold-Air Pools
(a)
A multitude of atmospheric processes contribute to CAPs (Lareau et al.
2013). Forecasting CAP intensity, vertical structure, cloudiness, and decay
remains difficult (Lareau and Horel 2015)
The CAPs are sensitive to clouds. Clear skies and fresh
snowpack results in colder nighttime temperatures.
Stratus clouds are more optically thick to infrared
radiation than ice fogs and result in more surface
warming. Cloud-topped CAPs are generally deeper
with less polluted surface layers, and may be less
susceptible to erosion by weak weather systems
(b)
(b)
Snow Cover
Snow cover has a significant impact on CAPs through nocturnal radiative
cooling and daytime reflection of incoming solar insolation. The presence
of snow cover decreases simulated 2-m temperatures by 2-12 ᵒC. The SLV
is less sensitive to snow cover variations than the Uintah Basin due to the
increased urban land use and adjacent Great Salt Lake (GSL)
(a)
Boundary-Layer Clouds
(a)
(b)
(c)
Great
Salt
Lake Salt
Lake
Valley
(c)
Average simulated 2-m
temperature
(in
°C)
between 31 January and
6 February 2013 for (a)
snow and (b) no snow
Great Salt Lake Temperature
Plan view of the Salt Lake Valley. MODIS true color images on (a) 2040 UTC 12
December 2010 and (b) 1900 UTC 6 January 2011. (c) 2-m Temperature difference (°C)
between SNOW and NO SNOW WRF simulation for 27-31 January 2011 CAP
(a)
(c)
(b)
(d)
Time-height of potential temperature (K) 27-31
January 2011 for LES simulations with (a) full snow
cover in SLV, (b) GSL -3 ᵒC cool lake temperature
anomaly, and (c) +3 ᵒC warm lake temperature
anomaly
Numerical studies show that Salt Lake Valley
CAPs are sensitive to GSL temperature. A
colder lake results in greater advection of
high-stability cold air inland in the afternoon
associated with the lake breeze front. A colder
lake also results in more widespread and
Average 2-m daytime temperature difference (°C)
27-31 January 2011 between +3 C warm lake
persistent low clouds which cool the daytime for
temperature anomaly (left) and -3 C cool lake
temperature anomaly (right)
boundary layer
ᵒ
Background
ᵒ
• Elevated PM2.5 in Salt Lake Valley
Large population, high vehicle emissions
• Elevated O3 in Uintah Basin
Significant industrial fossil fuel extraction activities,
shallow cold pool and highly reflective snow surface
Warming and Cooling Aloft and Large-Scale Flow
Simulated 2-m temperature (°C, left) and wind speed (m s-1, right)
during a partial CAP mix-out event
Persistent wintertime CAPs are largely driven by changes in mid-level
weather patterns. High pressure moving over the intermountain west often
results in rapid warming at mountaintop level, while complex topography blocks warm advection at the lower levels and
entraps cold air in the basins. A strong cold front with rapid cooling aloft is often required to destroy the CAP. Weaker weather
systems may bring partial mix-outs to upwind portions of basins (Lareau and Horel 2014)
Future Work
Improving Numerical Weather Prediction of Cold Air Pools
Ɵ PBL: YSU
Snow Depth and Albedo
ΔX 1335 m
Weather Research and Forecasting
WRF Mesoscale
(WRF) Model
• Run as mesoscale model (ΔX
~1.33 km) and as large-eddy
simulation (ΔX ~0.250 km)
• 2-3 nested grids
• Large-eddy simulations (LES)
without PBL scheme, 1.5 order
TKE subgrid-scale turbulence
closure
• Mesoscale simulation uses YSU
PBL scheme
• Thompson microphysics (with
and without Neemann et al.
2014 modifications)
• No meteorology nudging used
• Idealized modifications to snow
cover and albedo applied
Ɵ PBL: none
ΔX 250 m
Modifying the snow depth and
albedo in the Uintah Basin
resulted in improved simulations
of 1-7 February 2013 CAP
(Neemann et al. 2014)
WRF surface albedo at 18:00MST 31 January 2013 for (a) before
and (b) after modifications to WRF snow albedo and vegetation
parameter table. See Neemann et al. 2014
Land Use and Initialization Time
PCAPS Ɵ observations
WRF LES
Contact: [email protected]
Time-height of potential temperature 27-31 January 2011. Top:
WRF Mesoscale simulation; Middle: WRF LES simulation; Bottom:
PCAPS observations
Vertical Mixing and Winds
Large-eddy simulation (LES) less dispersive,
allow cold pool to be deeper and persist
longer. Elevated cloud layers are able to
persists in LES simulation
Left images: NASA SPoRT satellite images: (a) Snow-Cloud product at
1115 MST 2 February 2013 and (b) Nighttime Microphysics RGB product
at 0331 MST 2 February 2013. Right images: Difference between ice fog
and stratus cloud WRF simulations during 31 December-7 February 2013.
(c) 2-m temperature (°C) and (d) downwelling longwave radiation (W m-2)
Recent simulations have shown CAP sensitivity
to variations in land use (USGS vs MODIS vs NLCD
2006 options) as well as initialization time.
Starting a simulation during an ongoing CAP
results in poor CAP simulation
Cloud Occurrence and Type
CAPs are very sensitive to differences
between liquid and ice clouds as well
as clear versus cloudy. Simple
modifications were employed to
produce ice fog in the Uintah Basin
with beneficial results in Neemann et
al. 2014. The WSM3 microphysics
scheme was used to remove
unwanted spurious stratus
• Simulating both clear and cloudy, calm and
disturbed CAPs
• Testing ice fog and aerosol-aware Thompson
schemes (Kim et al. 2014; Thompson &
Eidhammer 2014)
• Testing several other new PBL, surface layer,
and cloud microphysics schemes
• Additional research regarding use of targeted
large-eddy
simulations,
albedo/snow
treatment, land use, and initialization
References
Kim, C. K., and Coauthors, 2014: Numerical modelling of ice fog in
interior Alaska using the weather research and forecasting
model, Pure Appl. Geophys., 1–20.
Lareau, N.P., and Coauthors, 2013: The persistent cold-air pool
study. Bulletin of the American Meteorological Society, 94, 5163
Lareau, N.P., J.D. Horel, 2014: Dynamically Induced Displacements
of a Persistent Cold-Air Pool, Boundary-Layer Meteorology
Lareau, N.P. , and J. Horel, 2014: Turbulent Erosion Of Persistent
Cold-Air Pools: Numerical Simulations. Journal of Atmospheric
Sciences, accepted
Neemann, E., E. Crosman, J. Horel, and L. Avey, 2014: Simulations
of a cold-air pool associated with elevated wintertime ozone in
the Uintah Basin, Utah. ACPD, 14, 1-48
Thompson, G., and T. Eidhammer, 2014: A study of aerosol impacts
on clouds and precipitation development in a large winter
cyclone. Journal of the Atmospheric Sciences, 71, 3636-3658