1. By Joshua Tobias
Climate Risk Analysis
for Adaptation
(Spring 2014)

2. Snowfall, Transportation and a
Changing Climate…
• Winter can impact many different socio-economic
sectors, including tourism, agriculture, and
water management. However, transportation
appears to be the most directly impacted.
• The NY Department of Transportation (NYSDOT)
is responsible for maintaining up to 43,488 miles
of roads on an annual basis
• Snow removal and the spreading of road salt
are essential for maintaining safety for the number
of motorists that traverse these routes.
• In the 2012-2013 season alone, an average of
754,000 tons of road salts was deposited along
such roadways

3. Snow and Salt…
• The amount of salt purchased for an
upcoming is based on a number of
factors, including seasonal forecasts
produced by the National Ocean and
Atmospheric Administration.
• Much research has been done to
understand how winter weather is
changing in response to global climate
change.
• The National Highway Research
Program has stated that a reduction in
the number of freezing days will
occur, but the number of extreme
precipitation events will increase.

4. Prior Studies of Trends…
• Seasonal Snowfall Increasing:
Kunkel et al. (2013)
• No Seasonal Increase/ Increased Lake-Effect:
Snowfall:
Burakoswki et al. (2008)
Burnett et al. (2003)
Ellis and Johnson (2004)
• Agreement that increased frequency in extreme
events associated with Lake-enhancement and
Lake-effect will occur.
• CAN BE APPLICABLE TO
Department of Transportation Research.

5. • Negative NAO allows trigger major cold air outbreaks, that can lead to lake-
effect and other extreme winter weather events.
• La Nina shifts storm tracks to the North, interacting with colder air on the
Northern Borders.
Causes of Extreme Winter Trends?

6. Applications for Road Management and Salt Use
• By confirming the relationship between local snowfall trends and
the two climate indices, better regional winter forecasts could
be made.
• Planning can be made prior to the season and also during actual
events.
• Help manage the growing
use of salt that is being
experienced nation-wide.

7. Why forecast for road salt?
• Unfortunately, the increased use of road salt has lead to run-off leeching into
local aquifers. 60-90% of salt content in some aquifers could be attributed to road
salt. This can disrupt and damage local ecosystems and affect human health.
• The use of salt can also lead to corrosion and wear of infrastructures, like roads
and bridges.
• Further effects have been documented by The Cary Institute of Ecosystem Studies
in Millbrook, NY .

8. Project Methods
• Investigated the recent trends in
snowfall amounts within Upstate NY
 determined current state of the
hydro-climate.
• Time series of annual snowfall
trends at two locations:
• Buffalo, NY
• Albany, NY
• Calculated the average Winter
Season ENSO and NAO Indices
(November-March) and placed them on
a time series, against the snowfall
trends.
• Correlations determined, but not
expected explicitly with the averaging
used.

9. Results (Snowfall Trends)
• Noticeable downward trends in snowfall at both locations.

10. Results (Buffalo)
• Seasonal snowfall increased
between the periods of 1998-
2002 and 2006-2009. Both of
these time periods were
associated with La Nina
events. A drop in snowfall
also appears between 1997-
1998.
The relationship between the NAO
and Buffalo snowfall is
unfortunately less apparent .
Negative Phase NAO periods
associated with increase snowfall were
only observed from 2001-2002 and
2004-2006. Could be modulating with
ENSO.

11. Results (Albany)
• Similar results in Albany,
with La Nina periods in
the 1998-2002 and 2002-
2006 time periods again
show an overall increase
in snowfall.
• Again, the NAO relation is
not as apparent and could
be reinforcing the already
present NAO.
• Slight increases in
seasonal accumulation
did occur for the periods
of 1995-1997 and 2004 -
2005, in association with
weak negative NAOs.

12. Conclusions
• Actual correlations were low between the annual
snowfall and the indices. Could have been due to the
method used or internal variability. Trends were still
apparent.
• ENSO will remain the dominant mode of
variability in sea surface temps and weather patterns,
with larger amplitudes in variability. According to the
IPCC 5th Report , climate modeling with ENSO has
improved with models generating results similar to
actual observations.
• NAO’s spatial and temporal patterns CAN be generated,
but results are best for the winter months.
According to the IPCC 5th Report, the NAO will
continue to display a large amplitude of variability.
However, averages will trend more toward positive.
Snowfall vs.
Index
Correlation
Buffalo vs.
ENSO
-.391
Buffalo vs.
NAO
.013
Albany vs.
ENSO
-.064
Albany vs.
NAO
.290

13. Recommendations (Macro Approach)
Better determine the amount of road salt to be purchased, based on refined
seasonal forecasts and other atmospheric variables:
• Seasonal Forecasts: Special focus on ENSO may be used to determine
whether an increased number of storms will be possible during a winter
season. A seasonal forecast of the NAO may also be examined, to determine
whether it may create condition that could enhance the winter nature of a storm.
• Modeling Salt Use: A Finland study suggests that modeling salt use,
based on monthly average temperatures is possible. However, this method
proves highly variable with area (Venäläinen, 2001).

14. Recommendations (Micro Approach)
Refine practices that can increase the practical use of
salt during an event (Kelly et al, 2010):
• Road Weather Information System: The increased
use of this weather system on plows can determine
whether atmospheric conditions provide an
environment where salt is effective for melt.
• Temperature Sensors Installed on Plows: Can
determine road conditions, such as temperature, which
allow drivers to better target where to deposit salt.
• Variable mixtures of salt: Salt may be mixed with
either water ( as brine) or sand may be more viable for
deicing and increasing traction in warmer conditions.

15. Questions?

16. References
Andersson, A. K., & Chapman, L. (2011). The impact of climate change on winter road maintenance and traffic
accidents in West Midlands, UK. Accident Analysis & Prevention, 43(1), 284-289.
Burakowski, E. A., Wake, C. P., Braswell, B., & Brown, D. P. (2008). Trends in wintertime climate in the
northeastern United States: 1965–2005. Journal of Geophysical Research: Atmospheres (1984–2012), 113(D20)
Burnett, A. W., Kirby, M. B., Mullins, H. T., & Patterson, W. P. (2003). Increasing Great Lake–effect snowfall
during the twentieth century: A regional response to global warming?. Journal of Climate, 16(21).
DOT Center for Climate Change and Environmental Forecasting (2002). The Potential Impacts of
Climate Change on Transportation.
Ellis, A. W., & Johnson, J. J. (2004). Hydroclimatic analysis of snowfall trends associated with the North American
Great Lakes. Journal of Hydrometeorology,5(3).
IPCC (2013). IPCC Fifth Assessment Report: Working Group I Report.
Chapter 9: Evaluations of Climate Models
Chapter 14: Climate Phenomena and their Relevance for Future Regional Climate Change
Johansson, A. (2007). Prediction Skill of the NAO and PNA from Daily to Seasonal Time Scales. Journal Of
Climate, 20(10). 1957-1975.
Jung, T., Vitart, F., Ferranti, L., & Morcrette, J. J. (2011). Origin and predictability of the extreme negative NAO
winter of 2009/10. Geophysical Research Letters, 38(7).
Kelly, V.R., Findlay, S.E.G., Schlesinger, W.H., Chatrchyan, A.M., Menking, K. 2010. Road Salt: Moving Toward the
Solution. The Cary Institute of Ecosystem Studies.
Koetse, M. J., & Rietveld, P. (2009). The impact of climate change and weather on transport: An overview of
empirical findings. Transportation Research Part D: Transport and Environment, 14(3), 205-221.

17. References (cont.)
Kunkel, K. E., Karl, T. R., Brooks, H., Kossin, J., Lawrimore, J. H., Arndt, D. & Wuebbles, D. (2013). Monitoring and
understanding trends in extreme storms: State of knowledge. Bulletin of the American Meteorological Society,94(4), 499-
514.
Lashmet, Michael. Snow and Ice Control. New York Department of Transportation.
https://www.dot.ny.gov/divisions/operating/oom/transportation-maintenance/snow-and-ice
Maze, T. H., Agarwai, M., & Burchett, G. (2006). Whether weather matters to traffic demand, traffic safety, and traffic
operations and flow. Transportation research record: Journal of the transportation research board, 1948(1), 170-176.
National Cooperative Highway Research Program. Climate Change, Extreme Weather Events
and the Highway System: A Practitioner’s Guide.
New York Department of Transportation. Snow and Ice Control Guidelines. (Revised 2012)
https://www.dot.ny.gov/divisions/operating/oom/transportation-maintenance/repository/HMG%20Section5.pdf
Patten, J. M., Smith, S. R., & O'Brien, J. J. (2002, January). Impacts of ENSO on United States snowfall frequencies. In 13th
Symposium on Global Change and Climate Variations.
Salt Institute. Road Salt Saves Lives and Protects. Commerce.
Seager, R., Kushnir, Y., Nakamura, J., Ting, M., & Naik, N. (2010). Northern Hemisphere winter snow anomalies: ENSO, NAO
and the winter of 2009/10.Geophysical Research Letters, 37(14).
Taschetto, Andréa S., Alexander Sen Gupta, Nicolas C. Jourdain, Agus Santoso, Caroline C. Ummenhofer, Matthew H.
England (2014). Cold Tongue and Warm Pool ENSO Events in CMIP5: Mean State and Future Projections. J. Climate, 27,
2861–2885.
Venäläinen, A. (2001), Estimation of road salt use based on winter air temperature. Met. Apps, 8: 333–338.
doi: 10.1017/S1350482701003085