• Keine Ergebnisse gefunden

Wind vortex in the model

N/A
N/A
Protected

Academic year: 2022

Aktie "Wind vortex in the model"

Copied!
1
0
0

Wird geladen.... (Jetzt Volltext ansehen)

Volltext

(1)

SCI-POM1193

References:

-- Sukoriansky S., B. Galperin, V. Perov, 2005: Application of a New Spectral Theory of Stably Strati- fied Turbulence to the Atmospheric Boundary Layer over Sea Ice. Bound.-Lay. Meteorol., 117

-- Hines et al, 2011: Development and Testing of Polar WRF. Part III: Arctic Land, J. Clim., 24 -- Statistics for the wind direction were partly done using the Circular Statistics Toolbox: P. Berens, CircStat, 2009: A Matlab Toolbox for Circular Statistics, Journal of Statistical Software, 31(10) -- Map colors based on www.ColorBrewer2.org, by Cynthia A. Brewer, Pennsylvania State University

BREMERHAVEN Am Handelshafen 12 27570 Bremerhaven Telefon 0471 4831-0 www.awi.de

Corinna Ziemer, Ulrike Wacker, Jörg Hartmann (AWI), Torsten Sachs (GFZ) (uwacker@awi.de)

Comparison of aircraft observations and PWRF simulations in the Canadian tundra

Motivation of the study

Mackenzie delta in NW-Canada, Modis image, 2012/07/29 (NASA).

Short edge approx. 200km

Flight pattern on July 4th, 2012

Polar5 (P5) aircraft (photo C. Lüpkes, AWI)

On July 4th, a reversal in wind direction on the horizontal flight track was observed during two hours (three overpasses). The ins- truments also recorded a local increase in methane concentration.

It was assumed that a small vortex had formed, which was not resolved in the synop-

tic weather charts. 1.90ppm

1.95ppm 2.00ppm

-136° -135° -134° 68°00′

68°30′

69°00′

50km

0 0

200 800

2m/s 2m/s

Inuvik

BP50704h04

Wind speed (arrows) and methane concentration (colour) along one horiz. flight track on July 4th

In July 2012, the campaign AirMeth of AWI and GFZ (Potsdam, Germany) collected meteorological data in the Mackenzie delta (NW Canada). The Polar5 (P5) aircraft measured temperature, wind vector and methane concentration along horizontal flight tracks in low altitudes and along steep ascends and descends through the boundary layer.

2 m/s

We present high-resolution model simulations • to investigate the hypothesis of the vortex, • to compare aircraft data with model data.

Model configuration

d01 We use the PolarWRF (Version 3.4.1) of

NCAR/OSU in three domains of 24, 8, and 2.67 km resolution (two-way nesting).

Starting time of the innermost domain is 2012/07/04 00 UTC, with each parent domain starting 6 hours earlier.

Boundary layer scheme is QNSE (Sukorians- ky et al 2005). As vertical resolutions, we use:

a) 55 vertical levels total, 7 in the lower 1km.

b) 47 vertical levels total, 14 in the lower 1km.

Model domain 1 with inset domains 2 and 3. Blue circle: position of the prevailing low pressure system. Green line in d03: flight track.

Wind vortex in the model

The model simulations (QNSE-a) show the development of a wind vortex. The vortex is most pronounced around 19 UTC (local time zone is UTC - 6). The reversal of the wind direction has been observed by the aircraft also at earlier times.

The north-easterly wind at the coast is deflected southwards by the mountain range.

500 500

500 1000

Lat [ o ]

Lon [ o]

17:00 UTC

−137 −136.5 −136 −135.5 −135 −134.5 −134 67.5

68 68.5 69 69.5 70

500 500

500 1000

Lat [ o ]

Lon [ o]

18:00 UTC

−137 −136.5 −136 −135.5 −135 −134.5 −134 67.5

68 68.5 69 69.5 70

Wind speed (colours, [m/s]) and direction (arrows) in 100m height a.s.l. in the northern Mackenzie delta region.

Non-coloured area has an elevation of more than 100m.

500 500

500 1000

Lat [ o ]

Lon [ o]

19:00 UTC

−137 −136.5 −136 −135.5 −135 −134.5 −134 67.5

68 68.5 69 69.5 70

0 2 4 6 8 10 [m/s]12

Comparison of P5 and PWRF data

−136.5 −136 −135.5 −135 −134.5 −134 67.5

68 68.5 69 69.5

500

500

0

Lon [ o] Lat [o ]

N E S W N

−136.5 −136 −135.5 −135 −134.5 −134 67.5

68 68.5 69 69.5

500

500

0

Lon [ o] Lat [o ]

10 12 14 16 18 20 22

−136.5 −136 −135.5 −135 −134.5 −134 67.5

68 68.5 69 69.5

500

500

0

Lon [ o] Lat [o ]

0 1 2 3 4 5 6 7 8

Air temperature [°C ] Wind speed [m/s] Wind direction

• PWRF temperature data show a warm bias as also documented by Hines et al (2011). Note the overestimation of cold air inflow from the sea from north-west.

• Low wind speed inland is well reproduced by the model. Wind speeds at the coast are higher in PWRF than observed with P5.

• Simulated wind direction shows reversal at 135.5° W, 69.1° N as also seen in aircraft data.

Aircraft data (coloured line) and a subset of WRF data (QNSE-a) at matching vertical model level. Shown is a selected flight track from south to north, 18:00 to 18:30 UTC, at 100 m mean height a.s.l. .

Statistics for low horizontal flights

Statistics are shown for horizontal flight tracks in chronological order (16 - 20 UTC) and in increasing heights (51, 29, 55, 102, 284, 495, 503m) as bias (PWRF - P5, first row) and root mean square error (RMSE, second row). Big dot for flight track shown before (#4).

• warm bias of PWRF exhibited on every flight track • simulated wind speed mostly higher than observed

• direction of PWRF-wind often turned clockwise as compared to P5-wind • no scheme (QNSE- a or b) has the lowest RMSE for all tracks or all shown quantities, so none can be preferred

#1 #2 #3 #4 #5 #6 #7

0 0.5

1 1.5

2 2.5

3

flight track number

RMSE (T) [°C]

#1 #2 #3 #4 #5 #6 #7

0 0.5 1 1.5 2 2.5

flight track number

RMSE (UV) [m/s]

#1 #2 #3 #4 #5 #6 #7

0 10 20 30 40

flight track number

RMSE (PHI) [deg.]

#1 #2 #3 #4 #5 #6 #7

−3

−2

−1 0 1 2 3

flight track number

Bias (T) [° C] QNSE−a

QNSE−b

#1 #2 #3 #4 #5 #6 #7

−3

−2

−1 0 1 2 3

flight track number

Bias (UV) [m/s]

Air temperature Wind speed Wind direction

#1 #2 #3 #4 #5 #6 #7

−180

−90 0 90 180

flight track number

Bias (PHI) [deg.]

Vertical profiles of temperature

Vertical profiles of potential temperature from P5 aircraft (descending flights) and PWRF (gridpoint of mean hori- zontal aircraft position), taken in north, middle and south of the long horizontal flight leg. P5 surface data is shown as measured at the lowest aircraft height (grey: range of measured surface temperature).

−136.5 −136 −135.5 −135 −134.5 −134 67.5

68 68.5 69 69.5

500

1000

Lat [o ]

Lon [ o]

Measurement Positions

flight track vertical profile

• different vertical model resolutions (a, b) are relevant near the coast.

• unstable boundary layer in the north is not captured in PWRF data.

• sharp temperature increase at 350 or 500m height is only seen in P5 data.

2800 285 290 295

0.2 0.4 0.6 0.8 1

North − 17:00 UTC

Tpot [K]

z [km]

PWRF − QNSE−a PWRF − QNSE−b P5 data

PWRF surface data P5 surface data

2800 285 290 295

0.2 0.4 0.6 0.8 1

Middle − 17:15 UTC

Tpot [K]

z [km]

2800 285 290 295

0.2 0.4 0.6 0.8 1

South − 17:45 UTC

Tpot [K]

z [km]

Summary

The observed wind vortex is resolved in the high-resolution PWRF simu- lations. The position of the vortex is well matched, but wind speed and temperature show some deviations. The selected vertical resolution sig- nificantly influences the results, as also does the selected PBL scheme (not shown). All in all, no configuration can be preferred.

Referenzen

ÄHNLICHE DOKUMENTE

Three measurements (E/q k , time of flight, E SSD ) from the pulse height raw data are used to character- ize the solar wind ions from the solar wind sector, and part of

Reasonable predictions where such downhole measurement subs may be positioned along predefined vertical-, tangential- and horizontal well paths are stated based on

The elicitation of risk attitudes and time preferences can help to understand production and investment decision behavior. In particular the effect of urbanization on these

With the signing of the armistice to the Korean War, the land boundary agreement became the military demarcation line (MDL) near the 38 th parallel, buffered by a 2.5 mile-

a trajectory in the love space (see Figure 4) representing the predicted time evolution of the involvement of Scarlett and Rhett, eleven chronologically ordered short segments of

If boundary faces of the mesh are flat, far away from the mountains and wind direction is normal to the face the mesh file is very good for CFD simulation.. But

parapatric speciation model of Doebeli and Dieckmann (2003) by letting dispersal and

For each time point during the mean odor responses at all four concentration levels, we correlated the Euclidean distance matrix of odor response patterns with the chemical