the effect of downsloping on precipitation distributions in the capital district of new york state...
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The Effect of Downsloping on Precipitation Distributions in the Capital District of New York State
Kyle J. Pallozzi and Lance F. Bosart
Department of Atmospheric and Environmental Sciences
University at Albany/SUNY
Albany, NY 12222
Robert Gaza
New York State Department of Environmental Conservation
Albany, NY 12233 NROW XVAlbany, NY
Wednesday 12 November 2014
Support Provided by: SUNY RF STEMUndergraduate Research Grant
Background and Motivation
• Terrain Influences in the Northeast
– Rain shadowing in the Wyoming Valley of Pennsylvania
(Brady and Waldstreicher 2001)
– 1998 Mechanicville, NY tornadogenesis (LaPenta et al. 2005)
– 1995 Great Barrington, MA tornadogenesis (Bosart et al. 2006)
– Severe weather distribution in eastern New York and western
New England (Wasula et al. 2002)
Background and Motivation
• Why should this be studied:– Topographic features play a large role in the Capital
District’s weather– Past experience: Complicating factor in forecasting
precipitation distributions during winter storms
Topographic Map of New York State
Source: maps.com
Catskills
Heldebergs
Taconics
Greens
Berkshires
KALB Wind Rose (2003-2012)
Source: Western Regional Climate Center
Hurricane Sandy Precipitation
Source: AHPS Precipitation Analysis Source:ESRL
Hurricane Sandy Precipitation
Albany received only 3.3 mm (0.13 in) of precipitation
Source: Interior of Eastern New York Weather Observers
Objectives
• Seek predictors to address these questions:– When will downsloping events occur?– What will the magnitude of precipitation reduction be? – What will the westward extent of reduced precipitation be?
• Want predictors to be operationally useful• Candidate predictors are:
– 850 hPa wind– 925 hPa wind– Mean vector 850 hPa wind– Mean vector 925 hPa wind
Methodology
Data
• KALB Radisonde Data– 850 hPa and 925 hPa winds
• NARR (North American Regional Reanalysis)– Mean vector 850 hPa and 925 hPa winds (3 h)
• Focus of Study: Capital District (NY)• Problem: ASOS stations too widely spaced to
provide precipitation data• Solution: Interior of Eastern New York Weather
Observers– Network of observers in the Albany area run by Bob Gaza
Station Selections
• Reliable Observers• Oriented in a west-east line through Albany
across varying terrain
Eastern New York Weather Observers
165
15 1187
146
13
50 km
Location Elevation (m)
165 438
15 213
1 97
187 84
146 196
13 451
Methodology
• Time period: 2002-2003 through 2012-2013• Criteria for an event
– Greater than 0.5” (12.7 mm) of precipitation at location 165 or 15 (western locations)
– October 15 through April 15
• 161 storms met criteria
Methodology
• Calculated mean 850 and 925 hPa vector winds (NARR)
• Separated storms into twelve 30 degree bins• Composite precipitation totals in each bin at
the locations• Repeated process for KALB radiosonde data
– Examined four bins (030-150 degrees) of data– Threshold: 20 kt for 850 hPa – Threshold: 15 kt for 925 hPa
Results
850 hPa Mean Vector Wind vs. Precipitation (NARR)
0-30 30-60 60-90 90-120 120-150 150-1800
10
20
30
40
50
60
70
80
#165#15#1#187#146#13
850 hPa Mean Wind Vector
Prec
ipita
tion
(mm
)
n=5
n=13
n=11 n=24n=5n=8
850 hPa Mean Vector Wind vs. Precipitation (NARR)
180-210 210-240 240-270 270-300 300-330 330-3600
5
10
15
20
25
30
35
40
45
50
#165#15#1#187#146#13
850 hPa Mean Wind Vector
Prec
ipita
tion
(mm
)
n=14 n=5
n=2
n=43n=30
n=1
850 hPa Wind Direction vs. Precipitation (RAOB)
30-60 60-90 90-120 120-1500
10
20
30
40
50
60
70
80
#165#15#1#187#146#13
850 hPa Wind Direction
Prec
ipita
tion
(mm
)
n=8
n=20n=34
n=6
925 hPa Mean Vector Wind vs. Precipitation (NARR)
0-30 30-60 60-90 90-120 120-150 150-1800
10
20
30
40
50
60
#165#15#1#187#146#13
925 hPa Mean Wind Vector
Prec
ipita
tion
(mm
)
n=10
n=19 n=16
n=32 n=28n=18
925 hPa Mean Vector Wind vs. Precipitation (NARR)
180-210 210-240 240-270 270-300 300-330 330-3600
5
10
15
20
25
30
35
40
#165#15#1#187#146#13
925 hPa Mean Wind Vector
Prec
ipita
tion
(mm
)
n=18
n=8
n=2 n=4
n=2
n=4
925 hPa Wind Direction vs. Precipitation (RAOB)
30-60 60-90 90-120 120-1500
10
20
30
40
50
60
#165#15#1#187#146#13
925 hPa Wind Direction
Prec
ipita
tion
(mm
)
n=14
n=13 n=18n=55
Concluding Remarks• Sd
• Results show that easterly winds at 850 hPa and 925
hPa lead to downsloping and reductions in precipitation
totals for eastern portions of the study area
– Overall pattern was generally what was expected
– Very little difference in precipitation totals at
locations 146 and 13
Future Work• Sd
• Examine other variables with the end goal of better addressing the exact magnitude and western extent of downsloping
• Incorporate Radar Data
-potentially scale observed precipitation to radar estimates throughout the cases
850 direction #165 #15 #1 #187 #146 #13 events
0-30 17.1 18.2 19.1 20.3 32.5 31.6 5 2.7 2.93 3.07 7.44 9.07 10.5 30-60 37.6 35.8 34 28.7 34.4 34.4 8 20.9 18 17.6 14.4 14.3 10.5 60-90 74.6 58.2 48.6 42.4 36 38.6 5 23.9 21.2 16.1 14.4 16.5 15.5 90-120 46.7 41.1 35.4 32.3 30.4 31.1 13 29.1 22.4 20.7 23.6 20.8 19.2 120-150 33.4 34.2 29.9 25 22 20.9 11 18.2 17.4 16.8 13 11.1 8.62 150-180 31.3 34.1 30.3 26.4 24.1 23 24 18 19 18.9 16.1 18.3 17.1 180-210 27.2 28.4 28.6 26.6 26.7 26.1 43 15.2 14.8 14.2 14.2 14.6 14.9 210-240 21.2 22.5 22.1 21.4 26.3 27.8 30 11.1 11.2 12.4 12 15.6 16.6 240-270 19.1 21.4 20.4 18.7 25 25.5 14 8.87 8.84 10.5 10.7 14.7 14.3 270-300 15.5 12.7 17.8 16.9 18.9 23.6 5 8.29 4.95 4.28 4.94 6.78 12.6 300-330 35.8 37 35.7 35.3 43.1 42.6 2 7.18 2.33 1.62 3.59 23.9 21.7 330-360 14 17.5 13.7 9.14 12.4 15.2 1 0 0 0 0 0 0
925 direction #165 #15 #1 #187 #146 #13 events
0-30 30.8 29.3 28.7 24.7 32.2 32.4 18 17.3 15 15.4 12.7 14.7 13.6 30-60 55 51.3 45.3 39.5 40.2 40.8 10 28.7 20.4 16.9 15.2 13.9 13.9 60-90 40.2 36.9 33.3 30.9 30.2 28.4 19 27.9 21.7 21.4 22.3 19.3 16.9 90-120 34.8 36.6 33.3 27.4 25.9 25.8 16 18.5 19.7 19.8 16 18 17 120-150 24 26.6 24.3 21.3 17.7 17.2 32 11.7 11.8 10.8 10.1 7.99 7.59 150-180 27.1 27.2 28 27.1 28.2 27.9 28 15.8 15.7 14.2 14.7 15.1 15.8 180-210 18.7 19.6 19 18.6 26 28.3 18 9.17 8.79 8.54 8.98 16.3 17.8 210-240 16.2 18 16.5 17.1 19.9 21 8 4.54 2.7 3.57 7.44 8.68 6.96 240-270 25.4 28.5 30.1 24.9 30.6 30.7 2 12.9 7.54 12.4 19.4 19.9 19.4 270-300 16.9 16.6 17.4 18.3 25.8 33 4 4.06 4.02 4.49 6.87 12.7 16.1 300-330 21.5 27.8 25.4 22.7 19.1 20.6 2 13.1 15.3 16.2 14.2 10.1 9.34 330-360 31.6 32 29.7 32.9 37.3 36.6 4 24.9 23 19.3 17.6 21.7 20.7
Numerical Results (NARR)
Bin Average Precipitation and Standard Deviation (mm)
#165 #15 #1 #187 #146 #13 events
47.8 42 39.1 33.9 40.5 38.9 6
28.1 22.1 19.2 16.5 12.6 11.6
71.4 57.6 47.7 42.9 38.5 37.5 8
36.9 26.6 24.8 27.6 24.3 21.1
46.4 39.4 35.6 31.3 30.6 30.8 20
31.4 23.7 22.1 21.6 19.5 18.5
41 39.2 34.9 29.7 28.1 27.4 34
27.4 21.4 19.8 18.1 18.2 16.8
#165 #15 #1 #187 #146 #13 events
56.4 47.2 41.7 37.5 38.3 38.8 14
33.5 24 22.5 23.4 20.9 18.8
38.2 35.1 30.9 27.4 27.4 27.5 13
18.1 18.2 18.1 16.8 16.4 16.1
34.3 31.3 29.3 25 22.6 21.8 18
15.6 12.5 13.8 12.5 15.3 15
28.7 30.4 27.8 24.5 21.5 21.3 55
15.8 15.1 15.1 13.7 13.6 12.8
Bin Average Precipitation and Standard Deviation (mm)
Numerical Results (RAOB)
30-60
60-90
90-120
120-150
850 hPa 925 hPa
Bin Average Precipitation and Standard Deviation (mm) Bin Average Precipitation and Standard Deviation (mm)
850 direction #165 #15 #1 #187 #146 #13 events #165 #15 #1 #187 #146 #13 events 925 direction #165 #15 #1 #187 #146 #13 events #165 #15 #1 #187 #146 #13 events
0-30 17.1 18.2 19.1 20.3 32.5 31.6 5 0-30 30.8 29.3 28.7 24.7 32.2 32.4 18
2.7 2.93 3.07 7.44 9.07 10.5 17.3 15 15.4 12.7 14.7 13.6
30-60 37.6 35.8 34 28.7 34.4 34.4 8 47.8 42 39.1 33.9 40.5 38.9 6 30-60 55 51.3 45.3 39.5 40.2 40.8 10 56.4 47.2 41.7 37.5 38.3 38.8 14
20.9 18 17.6 14.4 14.3 10.5 28.1 22.1 19.2 16.5 12.6 11.6 28.7 20.4 16.9 15.2 13.9 13.9 33.5 24 22.5 23.4 20.9 18.8
60-90 74.6 58.2 48.6 42.4 36 38.6 5 71.4 57.6 47.7 42.9 38.5 37.5 8 60-90 40.2 36.9 33.3 30.9 30.2 28.4 19 38.2 35.1 30.9 27.4 27.4 27.5 13
23.9 21.2 16.1 14.4 16.5 15.5 36.9 26.6 24.8 27.6 24.3 21.1 27.9 21.7 21.4 22.3 19.3 16.9 18.1 18.2 18.1 16.8 16.4 16.1
90-120 46.7 41.1 35.4 32.3 30.4 31.1 13 46.4 39.4 35.6 31.3 30.6 30.8 20 90-120 34.8 36.6 33.3 27.4 25.9 25.8 16 34.3 31.3 29.3 25 22.6 21.8 18
29.1 22.4 20.7 23.6 20.8 19.2 31.4 23.7 22.1 21.6 19.5 18.5 18.5 19.7 19.8 16 18 17 15.6 12.5 13.8 12.5 15.3 15
120-150 33.4 34.2 29.9 25 22 20.9 11 41 39.2 34.9 29.7 28.1 27.4 34 120-150 24 26.6 24.3 21.3 17.7 17.2 32 28.7 30.4 27.8 24.5 21.5 21.3 55
18.2 17.4 16.8 13 11.1 8.62 27.4 21.4 19.8 18.1 18.2 16.8 11.7 11.8 10.8 10.1 7.99 7.59 15.8 15.1 15.1 13.7 13.6 12.8
150-180 31.3 34.1 30.3 26.4 24.1 23 24 150-180 27.1 27.2 28 27.1 28.2 27.9 28
18 19 18.9 16.1 18.3 17.1 15.8 15.7 14.2 14.7 15.1 15.8
180-210 27.2 28.4 28.6 26.6 26.7 26.1 43 180-210 18.7 19.6 19 18.6 26 28.3 18
15.2 14.8 14.2 14.2 14.6 14.9 9.17 8.79 8.54 8.98 16.3 17.8
210-240 21.2 22.5 22.1 21.4 26.3 27.8 30 210-240 16.2 18 16.5 17.1 19.9 21 8
11.1 11.2 12.4 12 15.6 16.6 4.54 2.7 3.57 7.44 8.68 6.96
240-270 19.1 21.4 20.4 18.7 25 25.5 14 240-270 25.4 28.5 30.1 24.9 30.6 30.7 2
8.87 8.84 10.5 10.7 14.7 14.3 12.9 7.54 12.4 19.4 19.9 19.4
270-300 15.5 12.7 17.8 16.9 18.9 23.6 5 270-300 16.9 16.6 17.4 18.3 25.8 33 4
8.29 4.95 4.28 4.94 6.78 12.6 4.06 4.02 4.49 6.87 12.7 16.1
300-330 35.8 37 35.7 35.3 43.1 42.6 2 300-330 21.5 27.8 25.4 22.7 19.1 20.6 2
7.18 2.33 1.62 3.59 23.9 21.7 13.1 15.3 16.2 14.2 10.1 9.34
330-360 14 17.5 13.7 9.14 12.4 15.2 1 330-360 31.6 32 29.7 32.9 37.3 36.6 4
0 0 0 0 0 0 24.9 23 19.3 17.6 21.7 20.7
Numerical Results (Everything)