Transcript Daria’s Thesis - University of Delaware

Characteristics and Trends of
North American Snowfall from
a Comprehensive Gridded
Data Set
Daria Kluver
MS Thesis Presentation
Department of Geography
University of Delaware
April 10, 2007
Outline
• Introduction
• Brief review of Previous
literature
• Aims of this study
• Data Verification
• Snowfall Climatology
• Trend Analysis
• Teleconnection Analysis
• Conclusions
http://www.wunderground.com/blog/smadsen8486/archive.html?tstamp=200601
http://www.cfcl.com/~vlb/weblog/images/WinterTimeRoad.jpeg
Introduction
• The factors controlling each snowfall event are numerous, and
sometimes last for only a few hours (Leathers et al. (1993)).
• In contrast, snow cover studies, concerned with the presence of
the snow cover over at least several days, incorporate a low
temperature persistence factor (Harrington et al., 1987).
• Because of these differences, snowfall may be more
representative of the short-term meteorological events that
produce it.
• There have recently been several snow cover, and snow water
equivalent (SWE), studies yet few have assessed the trends,
climatological aspects, and climate change indication
capabilities of actual snowfall (IPCC, 2001, Leathers et al.,
1993).
North American Snowfall
•
Half-century snowfall trends show decreases in the Pacific North West
and increases in the Ohio River Valley (Scott and Kaiser, 2003,2004)
•
Great Lakes/Upper Mid-West and High Plains experienced increases in
snowfall from 1945-1984 (Leathers et al., 1993).
– Number and intensity of Alberta Clippers
•
Studies on Lake-effect snowfall show increases (Burnett et al, 2003;
Ellis and Leathers, 1996; and Leather and Ellis, 1996; Scott and Kaiser,
2003, 2004)
•
In southern Canadian regions increases in frequency of snowfall events
corresponds to increases in winter snow cover (Brown and Goodison,
1996). However, reduced spring snowfall events is associated with
decreased snow cover duration.
•
Snowfall’s human impacts and cost (Changnon, 1979; Schmidlin,
1993).
Teleconnections and snowfall
• Arctic Oscillation- leading empirical
orthogonal function of wintertime
monthly mean Northern Hemisphere
sea level pressure.
– Positive phase corresponds to low
pressure over the polar region and high
pressure at the midlatitudes. Oceanic
storms in the Pacific are pushed to the
North, so the western U.S is dryer, Alaska
is wetter. East of the Rocky Mountains
cold weather outbreaks are not as severe.
www.cpc.noaa.gov
• North Atlantic Oscillation (NAO)fluctuation in sea level pressure
between two centers of action (Azores
high and Icelandic low). It is the
leading wintertime mode of variability in
the Atlantic basin.
– Positive years have stronger than normal
subtropical high pressure center and
deeper than normal Icelandic low. This
larger pressure difference leads to stronger
storms crossing the Atlantic Ocean at a
more northerly track. Associated with warm
and wet winters in both Europe and the
eastern United States.
http://www.ldeo.columbia.edu/NAO/
• El Nino Southern Oscillation
(ENSO)- phenomenon in the
equatorial Pacific that affects
precipitation, pressure and wind
patterns in the tropics. Its effect
on the position of the mid-latitude
jet stream influences U.S. storm
tracks.
– Warm phase strengthens the upper
level ridge off western North America,
producing warmer temperatures.
While the more frequent/stronger
Pacific storms in the Pacific Northwest
during a cold phase produces cool
http://www.cpc.noaa.gov/products/analysis_monitoring/ensocycle/nawinter.html
and wet conditions.
• Pacific Decadal Oscillation (PDO)- Pacific
Ocean phenomenon, defined as a leading model
of multi-decadal variability in SSTs in the
extratropical North Pacific.
– Warm (positive) phase is characterized by cool SSTs
in the central North Pacific, a more intense Aleutian
low, and warm SSTs along the West Coast of North
America. There is correspondingly wet periods in the
coastal Gulf of Alaska.
http://jisao.washington.edu/pdo/
• Pacific North American Index (PNA)fluctuation of the mid-tropospheric
mean flow resulting in an
intensification or damping of the
typical PNA pattern.
– Positive years, the flow is more meridional
(ridge over the Rocky Mountains, trough in
eastern North America), and during
negative years, the flow is more zonal.
This changes temperature characteristics,
and frequency of precipitation across
North America.
www.cpc.noaa.gov
• Few snowfall studies
• No studies cover all of North America
• Few studies looking at teleconnection
patterns
• Existing studies have spatial or temporal
limitations.
Aims of study
• Determine the quality of a new gridded data set
• Construct a climatology of North American
snowfall
• Calculate trends in various snowfall
characteristics
• Identify correlations between snowfall and
teleconnection patterns
Data
•1 by 1 interpolated snowfall data
(Dyer and Mote, 2006) from U.S.
National Weather Service (NWS)
cooperative stations and the
Canadian daily surface observations
•The interpolation was completed
using the Spheremap spatial
interpolation program, (Willmott et.
al, 1984; Shepard, 1968)
•quality controlled using criteria
from Robinson (1989)
•The period of record is 1900-2000
with a daily resolution
•Grid values for each day include
maximum snowfall, minimum
snowfall, median snowfall, mean
snowfall, standard deviation.
• In this study, mean snowfall
values were chosen to approximate
the daily value at each grid point.
Data Verification Results
Number of reporting stations per season
10000
mean number of stations
9000
8000
7000
6000
5000
4000
mean number of stations
3000
2000
1000
0
1880
1900
1920
1940
1960
1980
2000
2020
Season
Snow season is July 1 to June 30.
From a total of 2891 grid cells.
1900
1909
1929
1939
1959
1919
1949
The first ~50 years of the record had a large
increase in the number of reporting stations
contributing to the interpolation
The first season with reporting
stations
Period of Record with Station Data. Calculated as last
season – first season from 1900 to 1999.
Last season with reporting
stations
Grids with 100 seasons period of record.
Grids with >=75 seasons period of
record.
Grids with >= 90 seasons period of
record.
Grids with >=50 seasons period of
record.
We wanted to find a period of
record with the best spatial
coverage possible
Grids with >=25 seasons period of
record.
This becomes an issue when trends are calculated.
Example:
total snowfall per season for -114/36
1400
20
total snowfall
1200
number of stations
Linear (total snowfall)
15
800
10
y = -8.1912x + 16271
R 2 = 0.5469
600
5
400
200
0
0
1880
-200
1900
1920
1940
1960
season
1980
2000
2020
-5
number o f stations
total sno wfall (mm)
1000
Solution: determine a criteria for grid cells to be blacked out.
Black out grids with 10 or more seasonal differences that are greater than or equal to
10% of the number of stations over the period 1949 through 1999. Gray grid cells
indicate no station data in the cell for the period of record.
Summary of Data verification
results
• Potential data problems
– Number of stations vary greatly with time
– Only 50% of grid cells have a reporting station within
them at a given time.
– Spatially, before the 1940s few regions have continuous
coverage of grid cells containing stations within them.
– Grid cell timeseries illustrates how changes in station
density can effect trend analysis.
• Reasons for problems
– Data has historically be available where there are people
to record it
– Number of stations depend on amount of government
funding available
– Earlier data that has been recorded on paper is still in the
process of being digitized.
Data verification results cont.
• The reliability of this data set is maximized by selecting a
time period with the most consistent data distribution
possible
– Reduces the amount of variability and bias due to
uneven spatial coverage.
– 1949 to 1999 most consistent data distribution
• Some grid cells are deemed unreliable and left out of the
trend analysis
Snowfall Climatology
Mean seasonal snowfall over the time
period 1949 to 1999
Remember: Snow season is July 1 to June 30.
Seasonal coefficient of variation over the
time period 1949 to 1999
Seasonal maximum snowfall over the
time period 1949 to 1999
Seasonal minimum snowfall over the
time period 1949 to 1999
This shows that the 1° by 1° resolution can capture smaller features
Pacific Northwest mean snowfall over the Northeast mean snowfall over the time period
time period 1949 to 1999
1949 to 1999
Summary of Climatology
• The annual cycle of North American snowfall is well
documented by this data set.
– Summer-Few grid cells with any mean snowfall, with the
exception of Northern Canada
– Autumn-consistent snowfall moves south from Canada,
first is the Rocky Mountains, then western U.S.,
northeastern U.S. and Great Lakes. Canada and Alaska
grid cells also have minimum values above zero.
– Winter-high mean values in southern Alaska, intermountain west, eastern Canada and Great Lakes region.
– Spring-mean snowfall values decrease. Ephemeral snow
line moves north.
• Data set’s fine scale resolution identifies smaller
scale features in the regional maps.
Snowfall Trends 1949-1999
• Least squares linear regressions are calculated
between each variable and time.
– Slope of the linear regression identifies temporal
changes in the dependent variable
• Correlation coefficients are calculated but not
shown. Of interest to this study are physically
significant changes in snowfall over time and
highlighting statistically significant grid cells with
physically insignificant trends would be a
distraction.
Total seasonal snowfall, slope of
the linear regression for 1949 to
1999.
Number of seasonal snowfall events,
slope of the linear regression for 1949
to 1999
Date of first seasonal snowfall, slope of the
linear regression for 1949 to 1999
Length of snowfall season, slope of the
linear regression for 1949 to 1999.
Date of last seasonal snowfall, slope of the
linear regression for 1949 to 1999.
September
October
November
December
January
February
April
May
March
March
Monthly Trends:
Summary of Trend Analysis
• Decreases in of up to -30 mm of snowfall per halfcentury in the Pacific Northwest
• Increases in total seasonal snowfall are seen in several
areas across the continent
– Alaska, the Great Plains, the Great Lakes, Northeast United
States, and reliable grid cells in northern Canada of as much as
30 mm over the period
• a shorter snow season in Southern California and parts
of the Rocky mountains, reduced at both ends of the
annual cycle.
• Monthly trend maps identify the largest changes in
monthly snowfall as occurring in the winter and spring
months.
Teleconnection patterns
Data
Teleconnection
Pattern
Data source
Record
length
Arctic Oscillation (AO)
Climate Prediction Center’s Monitoring
and Data Index page
1950 -2004
North Atlantic Oscillation
(NAO)
Climate Prediction Center’s Monitoring
and Data Index page
1821-2000
Pacific North American
(PNA) index
Climate Prediction Center’s Monitoring
and Data Index page
1950-2004
Pacific Decadal Oscillation
(PDO)
University of Washington website
1900-2000
Southern Oscillation Index
(SOI)
University of East Anglia Climate
Research Unit’s Data site
1866-2003.
• In order to identify basic relationships between
snowfall and teleconnection patterns, simple
linear regressions as well as Pearson correlation
coefficients are calculated.
• These calculations are done monthly for each of
the 5 teleconnection patterns and snowfall.
• Only maps with strong, visible signals are
shown.
Arctic Oscillation and monthly snowfall
North Atlantic Oscillation and monthly snowfall
Pacific Decadal Oscillation and monthly snowfall
Pacific North American index and monthly snowfall
Southern Oscillation Index and monthly snowfall
• For each month a multilinear stepwise regression is
calculated between monthly snowfall (dependent
variable) and the AO, NAO, PDO, PNA, and SOI
(independent variables).
• Time period used for this analysis is 1950 to 1999
due to availability of teleconnection data.
• A multiple linear regression model
– is built with stepwise selection of independent variables.
– This is done using the variance-covariance matrix of the
monthly snowfall and monthly teleconnection data.
– This method of analysis is useful in this situation because
it allows the observational data (snowfall) to be
characterized by several different variables
(teleconnection data).
September
December
March
October
January
November
February
April
Multilinear Stepwise Regressions
Summary of Teleconnections
•
AO– general negative correlation between the eastern half of the United States
and the AO are consistent with the previous literature.
– During a positive AO phase, the reduction of cold air outbreaks east of the
Rocky Mountains leads to higher temperatures. This could cause the
precipitation to fall more frequently as rain rather than snow, decreasing the
snowfall amounts in these regions during a positive AO.
•
NAO– Correlations most likely related to changes of the mid-tropospheric flow,
such as an eastward displacement of the eastern trough (Bradbury et
al.,2002) during its negative phase
– which could explain the negative correlations with the northern Great Plains
in September, and the Great Lakes/ Eastern United States in October.
•
PDO– striking areas of strong correlations that are fairly persistent throughout the
snow season.
– The negative correlations in the Pacific Northwest are consistent with
previous findings of decreases in winter precipitation in the Pacific
Northwest and of a strengthened Aleutian low during positive (warm)
phases (Gedalof and Mantua, 2002).
• PNA– Similar to the PDO.
– Negative correlations in the Pacific Northwest correspond to
the more meridional characteristics of the Pacific North
American pattern during the positive phase of the PNA index
(the ridge over the western part of the continent is
accentuated, resulting in changes in storm tracks and higher
temperatures).
– The positive correlations in the eastern United States are
associated with the deepening of the eastern trough, which
results in colder temperatures and changes in storm tracks
(Leathers et al., 1991; Serreze et al., 1998; Bradbury et al.,
2002; Notaro et al., 2006).
• SOI– Largest correlations in the central United States, along with a
small area of positive correlations in the West.
• Multilinear stepwise regressions
– teleconnection patterns can account for up to 70 % of the
variance in snowfall, principally in the Pacific Northwest.
Conclusions
• The Dyer and Mote (2006) gridded snowfall product for
North America is a unique and useful data set for
climatological studies. However, a thorough
understanding of the limitations of the data is necessary
before using the gridded product.
• The Rocky Mountains, coastal Alaska, Great Lakes
snowbelts and southeastern Canada have the largest
snowfall accumulations on the continent. Smallest
accumulations are found along the southern tier of the
United States.
• Temporal trends in snowfall identified in this study agree
with previous work. Large decreases in snowfall are
seen in the Pacific Northwest, and increases in snowfall
are seen in several areas across the continent
• Atmospheric teleconnections account for a substantial
amount of variation in snowfall, especially the AO, PDO,
and PNA.
• Future research is warranted in many areas.
– In order to improve predictions of North American
snowfall, the relationship between teleconnection
patterns and snowfall requires more exploration.
– More detailed studies of regional
teleconnection/snowfall relationships could
enhance our understanding of the physical
processes involved in the statistical relationships.
– Finally, continued extension of the trend analysis
into the past can aid in the attribution of climate
change.