Assignment 3 - Akshat Raj
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ASL320- Assignment 3 AKSHAT RAJ – 2011CH10065 - From this site, retrieve the temperature anomalies averaged over the Globe and India (Annual Mean temperature) Global Temperature Anomaly – Global mean temperature (C) - Using air temperature above sea ice: 14.771 +/- 0.047 - Using water temperature below sea ice: 15.310 +/- 0.047
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ASL320 - IIT Delhi - Akshat Raj - Assignment - Berkeley Earth - Krishna Achutarao - Climate Change - Impacts, Adaptation and Mitigation
Transcript of Assignment 3 - Akshat Raj
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ASL320 - Assignment 3 AKSHAT RAJ 2011CH10065
- From this site, retrieve the temperature anomalies averaged over the Globe and India (Annual Mean temperature)
Global Temperature Anomaly
Global mean temperature (C)
- Using air temperature above sea ice: 14.771 +/- 0.047
- Using water temperature below sea ice: 15.310 +/- 0.047
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India Temperature Anomaly
Estimated Jan 1951-Dec 1980 absolute temperature (C): 24.17 +/- 0.16
- Plot the Global and India temperature anomalies ON THE SAME FIGURE
It can be observed the average temperature over India is much greater than the global average.
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Global Vs Indian Temp. Anomalies
Global India
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- Retrieve mean temperature "anomaly" data for two cities of your choice - one near the coast and one in the interior of a continent.
Kansas City (Interior city in USA)
Average Temperature for Kansas City - 12.12 +/- 0.41 C
New York (Coastal City)
Average Temperature for New York - 9.96 +/- 0.25 C
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Kansas City - Temperature Anomaly from Average Temp.
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New York - Temperature Anomaly from Average Temp.
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- Plot the temperature anomalies for the 2 cities ON THE SAME FIGURE
All in all we see very similar anomalies, in the temperature, although being a coastal region, New
York is coder than Kansas City.
- Look for the following "other" temperature datasets: CRUTEM4, GISTEMP and NOAA National Climatic Data Centre. Can you describe how these are different?
Berkeley Earth uses data from a large number of weather stations, and then processes the
data statistically, providing weights to the data from various stations, instead of
homogenisation. Also, they employ Krigging Technique (Statistical Technique, to predict data
for places from the limited sampling points they have) and avoid gridding as much as
possible.
CRUTEM is a dataset derived from air temperatures near to the land surface recorded at
weather stations across all continents of Earth.
NASA GISTEMP We see that the data shows the earth temperature lesser than Berkeley,
but with similar variability. NASA uses homogenisation and gridding and takes data only
from some specific weather stations, unlike Berkeley Earth.
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NOAA Data gives a higher Change in temperature most probably due to homogenisation,
and also, because there are less measuring sites in regions like Artic and Antarctica.
