Currently in a phase between the post-fieldwork blues of last month (still) and thoughts and enthusiasm for next months re-visit (now with 50% extra sun). The time is mostly spent thinking about what can be done with the mountains of data I will have stored on my computer at the end of the melt season and what I want to achieve with it.
If each station has a sample of temperature every 10 minutes for both the air and the ground below it (some with humidity), for 3-5 months and there is a total of 15 stations, PLUS... a complete array of data from two automatic weather stations which record radiation from the sky and the ground, the wind speed and direction, humidity of the air, temperature and more... There are more units of data than I can even put the effort into counting. On top of that there will be data from:
-A pro-glacial station recording discharge and possibly electro-conductivity (no dye tracing this year though),
-Ablation measurements from an ablation stake at each station location
-My own body weight in photos if printed (hopefully some time lapse imagery too!)....
On the whole... the fun fieldwork component to this research project definitely is balanced by an equally non-fun organisation and processing of data. The results and findings of such a rich and highly resolute dataset will most likely be very interesting.... but there are going to be some painstakingly long hours to come to that stage, which I am not looking forward to so much :) .
The main focus of my planning at the current time is using past years of data on the Miage Glacier (studied since 2005 by my supervisor) to understand the main forcing mechanisms upon temperature variations and most importantly using a slightly larger dataset from last year to predict temperatures across the glacier.
If we apply the knowledge of temperature lapse rates, that I rambled on about back in
February then we can attempt to make estimates on what temperatures across the glacier should be. Using data from two stations to predict temperature for a station between them (as shown by the red circle in the image below) would be similar to the typical approach adopted by many modelling studies (with various success)... and that is what I have done for some data from 2013.
As is described by a detailed meteorological study of the Miage between 2005-07 by
Brock et al. (2010), the temperature variations are controlled less by the increase in the altitude than they are by the debris beneath them, which heats under the shortwave receipts from the sun and heats the above by convection. Therefore assuming a certain temperature increase between two stations with lapse rates is not a million miles off.... but also not that accurate at peak daytime hours when the heating from below is strongest.
If the dashed line is our measured temperature at the middle station shown above, predictions using a constant change of temperature with elevation throughout the day from:
1) Environmental lapse rates (blueish line)
2) Average lapse rates for the Miage (purple line)
3) Lapse rates which change throughout the day (green line)
all fail to successfully replicate temperature at this middle station, particularly beyond midday because of heating of the ground debris.
Therefore the prediction of temperature over debris glaciers is likely to better when assessed from the variation in surface characteristics such as the thickness of the debris.
Short of digging up the entire debris surface from the glacier, we have to infer thickness from relationships with the surface temperature which can be observed at certain times of day with thermal imagery from satellites (technology eh?). But this has its limitations and assumptions also. Anyone interested should definitely read the paper by
Foster et al. (2012) which is focused on this very issue for the Miage Glacier.
The importance being that debris on top of the ice is very important in controlling the interactions with the atmosphere and a glaciers response to climate. This debris thickness is constantly evolving and it flows with the glacier down slope and is fed by the surrounding mountains (some interesting news on that next week!). Therefore, the study of debris glaciers will likely become more globally apparent into the future.
References
Brock, B. W., Mihalcea, C., Kirkbride, M. P., Diolaiuti, G., Cutler, M. E. J., & Smiraglia, C. (2010). Meteorology and surface energy fluxes in the 2005–2007 ablation seasons at the Miage debris-covered glacier, Mont Blanc Massif, Italian Alps. Journal of Geophysical Research, 115(D9), D09106. doi:10.1029/2009JD013224
Foster, L. A., Brock, B. W., Cutler, M. E. J., & Diotri, F. (2012). Instruments and Methods A physically based method for estimating supraglacial debris thickness from thermal band remote-sensing data. Journal of Glaciology, 58(210), 677–691. doi:10.3189/2012JoG11J194
