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Scopeusing data from the "
CLIMATE TIME SERIES Browser" (named the Tool afterwards) correlate the evolution of the length of three glaciers in one geographic area (the Alps) with the Temperatures measured in some stations located near them.
Identify suitable glaciers and stationsI searched the stations as locations above 1500 meters in the Alpls with suitable Temperature data coverage:
- have recent data in oder to spot changes occurring more recently (after 1950)
- have data in the range 1900-1950 to allow for data normalisation.
I could find only few stations:
- Sonnblick (Austria, 3109mt)
- Saentis (Switzerland, 2500mt)
- St. Bernard (Switzerland, 2460mt)
See Ref 01 URL in the Tool to visualise this selection.
Then I selected in the Forcings/Records menu of the Tool three glaciers with the criteria to be as much as possible close to the selected stations and also to have a set of data covering the same timespan:
- Wurten glacier -> SonnblicK
- Pizol glacier -> Saentis
- Mer de Glace glacier -> St. Bernard
Get dataPhase1: export Stations and Glacier data to a Spreadsheet in Google Docs (the Spreadsheet afterwards). This file can be accessed through URL at Ref 02. I have compacted all data in a single sheet called "Stations_no_Normalised_and_Glaciers".
Phase2: normalise Stations data with respect to 1900-1950 period. I have created in the same format a single sheet called "Stations_Normalised_and_Glaciers".
Phase3: I selected one Model in the AR5 Models portfolio and get data for different scenarios. I have selected the IPSL-CM5A model and extracted data for the Historical, rcp26 and rcp85 scenarios Data have been imported in the Spreadsheet in a sheet called "Model_Scenario".
Processing & FindingsI have tried to verify if there is some degree of correlation between Temperatures and Glaciers length. We would expect a negative correlation as an increase of the Temperature in the area should result in more melted Ice and reduce length. I selected the timeframe from 1960 to 2000 and run correlations shifting back and forward the Glacier data in order to evaluate for example a delayed impact of Temperature. The result is shown in the Spreadsheet in the sheet named "Correlation Chart" and it is rather contradictory. Only the Satis/Pizol graph follow expectation with a -0.30 correlation increasing to 0.50 shifting Glacier data one year ahead. Other two graphs are not consistent with the assumption, showing more correlation in the past.
Looking at Ref 03 it seems the correlation could be more complex and involve annual mass-balance, summer/winter temperĀature difference and winter precipitation.
Then I looked at the model data and see how they compared with registered data. I used a bit of spreadsheet filtering and the SLOPE function to get the Delta Temperature in each decade from 1900 to 2050. I charted the results which confirm a trend of increasing delta Temperature even if in some cases we had decades with big increase in the order of 2 Celsius / Decade. All details in the Spreadsheet in a sheet called "Model_Scenarios_Charts".