Proxy Measures of Past Climates Current Weather Finish Cryosphere Significance of Climate Proxies Types of Proxies Role of Proxies in Reconstructing Past Climate Limitations and Strengths For Next Class: Read Thompson 2000 Selected slides from: www.mun.ca/geog/courses/rwhite/Lec4.2_MeasuringPastClimate.ppt
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Proxy Measures of Past Climates
Current Weather Finish Cryosphere Significance of Climate Proxies Types of Proxies Role of Proxies in Reconstructing Past Climate Limitations and StrengthsFor Next Class: Read Thompson 2000
Climate reconstruction Improves our understanding of environmental
response to climate variability and climate change
Provides perspective on current climate Requires identification of a link between
quantitative climate
forcing and
environmental response
The Earth warmed by 0.6°C (1°F) during the 20th century.
Paleoclimatology (the study of past climates), can help place this warming in the context of natural climate variability.
Until recently, most reconstructions of climate variations over the last ~1000 years focused on specific locations or regions.
Because widespread, reliable instrumental records are available only for the last ~100-150 years, scientists estimate climatic conditions in the more distant past by analyzing proxy evidence.
What kinds of climate proxies can be used to estimate surface temperatures (last 2000+
years)?
What kinds of climate proxies can be used to estimate surface temperatures (last 2000+
years)? Tree rings Corals Ocean and lake sediments (varves) Cave deposits (speleothems) Ice cores Pollen deposits Packrat middens Glaciers Documentary evidence (historical records, paintings,
For most proxies, statistical techniques are used to define the relationship between the proxy measurements and the concurrent instrumental records.
Then, this relationship is used to reconstruct the past climate from the remaining proxy data.
Steps involved Collect proxy data Dating the proxy data (e.g., matching growth
rings of trees to calendar year) Calibration – usually, this involves using
regression to relate the proxy measurement to know climatic conditions
Validation – basically tests the skill of the calibration
Reconstruction – once the proxy/climate relationship is established, we again use regression to predict what past climate was like
What are the limitations and strengths of large-scale climate reconstructions?
1. The instrumental record is short (~100-150 years at most)
This provides somewhat limited information needed to calibrate and validate the models used to reconstruct
2. The relationship between the proxy data and the climate variable being reconstructed (e.g., temperature) may have varied over time.
limitations
3. There is no consensus among scientists as to which statistical methods/formulae are most appropriate for calibrating and validating the models.
Thus, different teams of researchers could reach different conclusions when dealing with the same proxy data (e.g., the “hockey stick” controversy)
limitations
4. Spatial limitations – collecting proxy data is both time consuming and expensive. This limits the amount of data available in terms of spatial coverage.
Spatial pattern of ice core sampling in Antarctica and Greenland
Key strengths of proxy measures
1. Proxy records are meaningful recorders of environmental variables. The science is sound as the connections between the proxy-derived data and climate variability are well established.
Strengths
2. Tree ring-derived data are especially valuable in climate reconstruction as they often represent regions (i.e., multiple sites within a region are sampled and replication is a key element of the scientific method).
Strengths
3. Most surface temperature reconstructions incorporate proxy data from a variety of sources over wide geographic areas. Thus, even if we start to remove individual records, the overall results remain robust.
Strengths
4. The same general trends (e.g., temperature trends) emerge from multiple reconstructions.
From about 1600 till the present, the confidence in the general character of climate reconstructions is high. Why?
Different reconstructions based on different types of proxy evidence, different selections of proxy data of a given type, and different methodologies yield similar results.