Powerpoint template for scientific poster

1
What do glaciers tell us about climate
variability and climate change? Gerard H.
Roe Department of Earth and Space Sciences,
University of Washington
6. Are glaciers good detectors of climate
change? The climate is warming, and glaciers are
retreating because of it, but are glaciers, by
themselves, independent evidence of that warming?
In other words if we threw away all instrumental
data, would the glaciers alone be enough to
conclude a climate change was occurring? Glaciers
and trend detection A standard test for trend
detection is the Students t-test- Where t
is the t-statistic DL is the linear trend sL is
the standard deviation of natural variability n
is degrees of freedom length of record/ (2 ?
response time) The challenge here is we have to
reply on models to know sL. Typical numbers for
the Northwest if we consider the last 100
years, (the period of anthropogenic influence on
climate) DL200m, n7 (based on a 7-yr
response time), t1.85 for 95 significance. This
would require the natural glacier variability,
sL, to be less than 45m for the trend to be
declared significant, or nearly an order
of magnitude less than what is modeled in Figure
5. This is very unlikely. Issues Recent
retreat trends are stronger, but the shorter
record has fewer degrees of freedom, so the
conclusion is the same. Glaciers are retreating
globally. Surely thats enough to prove climate
change? Almost certainly, yes. But glaciers
within a single region are not independent
measures since they experience generally similar
climate. Degrees-of-freedom have to be carefully
calculated.
Abstract Glaciers respond to long-term climate
changes and also to the year-to-year fluctuations
inherent in a constant climate. Differentiating
between these factors is critical for the correct
interpretation of past glacier fluctuations, and
for the correct attribution of current changes.
Previous work has established that century-scale,
kilometer-scale fluctuations can occur in a
constant climate. This study asks two further
questions of practical significance how likely
is an excursion of a given magnitude in a given
amount of time, and how large a trend in length
is statistically significant? A linear model
permits analytical answers wherein the
dependencies on glacier geometry and climate
setting can be clearly understood. The
expressions are validated with a dynamic glacier
model. The likelihood of glacier excursions is
well characterized by extreme-value statistics,
though probabilities are acutely sensitive to
some poorly-known glacier properties.
Conventional statistical tests can be used for
establishing the significance of an observed
glacier trend. However it is important to
determine the independent information in the
observations, which can be effectively estimated
from the glacier geometry. Finally, the retreat
of glaciers around Mt. Baker in Washington State
is consistent with, but not independent proof of,
the regional climate warming that is established
from the instrumental record.

• 4. Glaciers undergo
• century-scale, kilometer-scale fluctuations, even
  in a constant climate.
• Figure 5 A 500 year segment of a 10,000 yr
  simulation of the glacier response to interannual
  climate variability. A standard flowline model
  calibrated to Mt. Baker, WA, was used. The lower
  panels are white-noise realizations of
  interannual fluctuations in accumulation and
  melt-season temperature, and for which a 30-yr
  running mean is also shown. The upper panel shows
  the response of the two glacier models.
  Kilometer-scale, century-scale glacier
  fluctuations occur in this simulated climate that
  by construction has no persistence.

• 2. Much interannual climate variability is well
  characterized by white noise.

• Figure 3. (a) Annual mean precipitation recorded
  at Diablo Dam near Mt Baker, over the last
  seventy-five years, equal to 1.890.36(1s) m
  yr-1 (b) melt-season (JJAS) temperature at the
  same site, equal to 16.80.78(1s) oC these
  atmospheric variables at this site are
  statistically uncorrelated and both are
  indistinguishable from normally-distributed white
  noise with the same mean and variance. The
  commonly performed application of a five-year
  running mean imparts the artificial appearance of
  multi-year regimes. Random realizations of white
  noise are shown for annual-mean accumulation
  (panels (c) and (e)) and for melt-season
  temperature (panels (d) and (f)). Note the
  general visual similarity of the random
  realizations and the observations.
• It is common to find very little persistence in
  instrumental records (see Burke and Roe (2010)
  for Europe, Huybers and Roe (2009) for the
  Pacific Northwest, Stouffer et al., 2000, more
  generally)
• The vast majority of the climate variance in the
  instrumental is consistent with random
  year-to-year fluctuation with little to no
  persistence (or memory). These fluctuations are
  integrated in time by the glacier which responds
  on longer timescales.

• 5. What are odds of an advance or retreat in a
  given period of time?
• .

Figure 1 Major Mount Baker glaciers superposed
on a contour map (c.i. 250 m) Glaciers are
shown at their Little Ice Age maxima, 1930, and
present positions. What is the correct
interpretation of the cause of these changes?

• 7. Lessons
• Century-scale, kilometer scale glacier
  fluctuations occur in a constant climate.
• It is the memory intrinsic to the glacier, not
  the climate that is responsible for these
  fluctuation.
• The interpretation of the cause of past glaciers
  fluctuations should factor in the potential role
  of interannual variability.
• Mt. Baker glaciers are not by themselves
  independent evident of the warming that is
  established from the instrumental record.
• Glaciers are messy thermometers!
• References
• Burke, E.E., and G.H. Roe, 2010 The persistence
  of memory in the climatic forcing of European
  glaciers. In preparation.
• Huybers, K.M., and G.H. Roe, 2009 Glacier
  response to regional patterns of climate
  variability. J. Climate, 22, 4606-4620.
• Roe and O'Neal, 2009 The response of glaciers to
  intrinsic climate variability observations and
  models of late-Holocene variations in the Pacific
  Northwest. J. Glaciol., 55, 839-854.
• Roe., 2010 What do glaciers tell us about
  climate variability and climate change?
  Submitted, available at http//earthweb.ess.washin
  gton.edu/roe/GerardWeb/Publications.html.
• Stouffer, R.J., G. Hegerl and S. Tett, 2000 A
  comparison of surface air temperature variability
  in three 1000-yr coupled oceanatmosphere model
  integrations. J. Climate, 13(3), 513-537.
• Vanmarcke, E., 1983 Random Fields Analysis and
  Synthesis. The MIT Press, Cambridge, 382 pp.

• 3. How does a glacier respond to this forcing?
• A climate that has no persistence is equivalent
  to white noise its power spectrum is flat.
• Glacier dynamics act as a low-pass filter,
  damping high frequencies, but admitting low
  frequencies (illustrated below).
• Therefore a constant climate with no persistence
  produces low frequency glacier fluctuations
• n.b. there is equal power at all frequencies,
  but the phases are random so components different
  frequencies cancel out, leaving no persistence in
  the time series.

• Figure 6 The probability of exceeding a given
  maximum total excursion (i.e., maximum advance
  minus maximum retreat), in any 1000 yr period.
  Crosses shows calculations from the dynamic model
  output. The curves are calculated from analytical
  expressions in Vanmarcke (1983).
• Extreme value statistics (e.g., Vanmarcke, 1983)
  can be used to predict the likelihood of an
  excursion in a given period of time. Such
  formula are very successful in describing the
  dynamic glacier model.
• So for the example shown here (Mt. Baker, Wa), in
  any 1000-yr period in a constant climate, you
  are
• -Very likely (gt95) to see a total excursion
  of gt1.4km
• -Very unlikely (lt5) to see a total excursion
  of gt2.2km

Fig. 2