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Elevation-dependent warming

Global warming is not uniform across the various regions of the world.  While surface air temperature has increased of about 1°C in the last century on average over the globe, warming hasn't happened everywhere at the same rate.
High-altitude mountain regions, for instance, have experienced more rapid and intense warming than the surrounding lower-lying areas or compared to the global mean, similarly to the warming amplification found in the Arctic. Mountains play a crucial role in climate dynamics and heavily influence downstream regions. “What happens in the mountains doesn’t stay in the mountains” and the most outstanding example of the immense value of mountains is probably the role they play as reservoir of fresh water used for drinking purposes, irrigation and agriculture, and energy production.
The enhancement of warming rates with elevation, so called elevation-Dependent Warming (EDW), is an important topic the research community has faced in the recent decades, because of its possible negative impacts on high-altitude cryosphere system including changes in glacier dynamics and snow resources. With very few exceptions, almost everywhere in the world terrestrial glaciers have experienced a sharp retreat in the recent decades, and Italian glaciers do not constitute an exception.
Unfortunately, mountains are difficult to study, they are remote and often inaccessible, and it is expensive and often challenging to find ways of effectively monitoring what is happening. Records of weather patterns at high altitudes are extremely sparse:  the density of weather stations above 4,500 m is roughly one-tenth that in areas below that elevation. Long-term data, crucial for detecting patterns, doesn’t yet exist above 5,000 m anywhere in the world (MRI, 2015). Despite these limitations, the measurements so far available in the various mountain regions of the world, from the Himalayas-Tibetan plateau to the Alps, for the Rockies to the Andes, have confirmed that mountains are warming more rapidly than surrounding regions. The most striking evidence of EDW comes from the Tibetan plateau. Here temperatures have risen steadily over the past 50 years and the rate of change is speeding up. Masked by this general climate warming are pronounced differences at different elevations. Over the past 20 years temperatures above 4,000 m have warmed nearly 75 per cent faster than temperatures in areas below 2,000 m (Figure 1, MRI 2015 and references therein). 

Figure 1: Elevation-dependent warming over and around the Tibetan Plateau. Annual mean surface air temperature (TA) over 3 time periods. Bars represent elevation and trend magnitude is plotted on the y axis according to the 8 elevation ranks of 122 stations. The presentation format is similar to ref. 76 for ease of comparison. Adapted from MRI, 2015


EDW has been studied over the Alpine region too, highlighting the existence of a differential heating with elevation, with some differences from region to region and from one elevation band to another over the same mountain range. Swiss Alps have been studied more than other mountainous ranges owing to the dense network of in-situ stations available proving long-term time series. EDW was found to exist there, especially in winter and spring, driven by changes (decreases) in surface albedo and related ice-albedo feedback mechanisms (Beniston, 1997).

Regional and global climate models have also been used to study EDW and in particular to understand the mechanisms behind this phenomenon, providing projections for the future decades. Most studies performed so far have been focused on the Himalayas-Tibetan Plateau (Fig. 2 provides and example, from Palazzi et al., 2016) and the Rocky mountains of north America (Rangwala et al., 2013, 2016). Among the reasons examined for faster rates of temperature increase in mountain regions are the loss of snow and ice and the increasing release of heat in the high-altitude atmosphere due to increase in atmospheric moisture, clouds, aerosols.

Figure 2: Change between the period 2071–2100 and the period 1971– 2000 of the minimum temperature as a function of surface elevation in winter for the CMIP5 multi-model mean (2 × 2 degrees horizontal resolution). The slope of linear regression (°C/km) is indicated (red considering the altitude range from the surface up to about 5000 m, in blue from 1500 m upwards); a star in parentheses indicates the statistical significance of the elevational trend. 

Improved observations, satellite-based remote sensing and climate model simulations are all needed to gain a true picture of warming in mountain regions and there is still much to be understood about the EDW phenomenon. In the framework of NextData we will perform EDW studies focused on the Italian Alps, both to highlight the specificity of this mountain range and to frame the Alpine region in a wider context through comparison with other mountain ranges. EDW in the Alps will be analyzed through the analysis of in-situ station data collected in WP1.1 (Task 3) and by numerical simulations aimed at characterizing the EDW and its mechanisms in the past and in future projections (WP 2.5 and WP 2.6), as well as identifying the most vulnerable areas expected in the future. In particular, state of the art simulations from the regional and global climate model experiments CORDEX and CMIP5 will be analyzed as well as specific simulations performed with the EC-Earth model run by ISAC-CNR at different increasing horizontal resolutions up to 16 km, comparable with that achieved by current hydrostatic regional climate models. 
An example of preliminary analysis is provided in Figure 3, showing the spatial maps of the changes in the minimum temperature between the average in the period 2039-2068 and the average in the period 1979-2008, obtained from the EC-Earth GCM run at ~16 km (T1279) and ~80 km (T255) horizontal resolution. Blue dots overplotted in the maps indicate the pixel that are expected to become snow or ice free in the future compared to the past

Figure 3: Changes in the minimum temperature between the average in the period 2039-2068 and the average in the period 1979-2008, obtained from the EC-Earth GCM run at ~16 km (T1279) and ~80 km (T255) horizontal resolution. Blue dots overplotted in the maps indicate the pixel that are expected to become snow or ice free in the future compared to the past.



  • MRI EDW Working Group (Pepin N, Bradley R S, Diaz HF, Baraer M, Caceres EB, Forsythe N, Fowler H, Greenwood G, Hashmi MZ, Liu XD, Miller JR, Ning L, Ohmura A, Palazzi E, Rangwala I, Schöner W, Severskiy I, Shahgedanova M, Wang MB, Williamson SN, and Yang DQ, Elevation- dependent warming in mountain regions of the world, Nature Climate Change 5:424–430, DOI 10.1038/nclimate2563 (2015)
  • Beniston M, Diaz H, Bradley R, Climatic change at high elevation sites: an overview, Clim Change 36:233–251, DOI 10.1023/A:1005380714349 (1997)
  • Palazzi E, Filippi L, von Hardenberg J, Insights into elevation-dependent warming in the Tibetan Plateau-Himalayas from CMIP5 model simulations, Clim Dyn, DOI 10.1007/s00382-016-3316-z (2016)
  • Rangwala I, Miller JR (2012) Climate change in mountains: a review of elevation-dependent warming and its possible causes. Clim Change 114:527–547. doi:10.1007/s10584-012-0419-3
  • Rangwala I, Sinsky E, Miller RJ, Amplified warming projections for high al- titude regions of the Northern hemisphere mid-latitudes from CMIP5 mod- els, Environ Res Lett 8:024040(9pp), DOI 10.1088/1748-9326/8/2/024040 (2013)
  • Rangwala I, Sinsky E and Miller RJ, Variability in projected elevation de- pendent warming in boreal midlatitude winter in CMIP5 climate mod- els and its potential drivers, Clim Dyn 46(7):2115–2122 DOI 10.1007/ s00382-015-2692-0 (2016)