Classification of glaciers during summer in Southern Rocky Mountain Trench using surface albedo and temperature anomalies

Author(s):  
Ali Naeimi ◽  
Martin Sharp

<p>Under most atmospheric conditions, the albedo and temperature of surface snow and ice are two of the main influences on the energy budget for glacier melting. Given that surface albedo and temperature are linked, knowing where and when negative albedo and positive surface temperature anomalies coincide is important for identifying locations and time periods in which anomalously high rates of surface melting are likely. We used measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on NASA's AQUA and TERRA satellites to map the albedo and surface temperature of snow and ice  on glaciers in the of Southern Rocky Mountain Trench ecoregion in the summer months (June-August) from 2000 to 2018. We use these data to identify specific regions and time periods in which low albedo and high surface temperature coincide since these conditions are likely to support anomalously high rates of surface melting. We also use these data to identify regions/periods in which albedo is particularly low while surface temperature is average or low, since such conditions suggest localized and/or short-term decoupling between the two parameters. We found anomalously low albedo and average/low temperature consistently at multiple glaciers during time periods when there were major forest fire events. We suggest the low albedo results from deposition of pyrogenic carbon from forest fires. We found that, on average, ~25% of the glaciers in the region experienced increasingly negative albedo anomalies and increasingly positive temperature anomalies in summer months from 2000 to 2018. However, we also found that for ~45% of the glaciers that are small, there was a poor correlation between the timing of albedo and temperature anomalies. Our results indicate that the correlation between albedo and temperature was weaker for the small glaciers, and identify specific glaciers that are likely the most vulnerable to climate warming.</p>

2013 ◽  
Vol 26 (14) ◽  
pp. 5124-5138 ◽  
Author(s):  
Yi Deng ◽  
Tae-Won Park ◽  
Ming Cai

Abstract On the basis of the total energy balance within an atmosphere–surface column, an attribution analysis is conducted for the Northern Hemisphere (NH) atmospheric and surface temperature response to the northern annular mode (NAM) in boreal winter. The local temperature anomaly in the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) is decomposed into partial temperature anomalies because of changes in atmospheric dynamics, water vapor, clouds, ozone, surface albedo, and surface dynamics with the coupled atmosphere–surface climate feedback–response analysis method (CFRAM). Large-scale ascent/descent as part of the NAM-related mean meridional circulation anomaly adiabatically drives the main portion of the observed zonally averaged atmospheric temperature response, particularly the tropospheric cooling/warming over northern extratropics. Contributions from diabatic processes are generally small but could be locally important, especially at lower latitudes where radiatively active substances such as clouds and water vapor are more abundant. For example, in the tropical upper troposphere and stratosphere, both cloud and ozone forcings are critical in leading to the observed NAM-related temperature anomalies. Radiative forcing due to changes in water vapor acts as the main driver of the surface warming of southern North America during a positive phase of NAM, with atmospheric dynamics providing additional warming. In the negative phase of NAM, surface albedo change drives the surface cooling of southern North America, with atmospheric dynamics providing additional cooling. Over the subpolar North Atlantic and northern Eurasia, atmospheric dynamical processes again become the largest contributor to the NAM-related surface temperature anomalies, although changes in water vapor and clouds also contribute positively to the observed surface temperature anomalies while change in surface dynamics contributes negatively to the observed temperature anomalies.


2021 ◽  
pp. 102098
Author(s):  
F. Neptalí Morales-Serna ◽  
Lorenia Olivas-Padilla ◽  
Emigdio Marín-Enriquez ◽  
Juan M. Osuna-Cabanillas ◽  
Hugo Aguirre-Villaseñor ◽  
...  

2021 ◽  
Vol 10 (8) ◽  
pp. 500
Author(s):  
Lianwei Li ◽  
Yangfeng Xu ◽  
Cunjin Xue ◽  
Yuxuan Fu ◽  
Yuanyu Zhang

It is important to consider where, when, and how the evolution of sea surface temperature anomalies (SSTA) plays significant roles in regional or global climate changes. In the comparison of where and when, there is a great challenge in clearly describing how SSTA evolves in space and time. In light of the evolution from generation, through development, and to the dissipation of SSTA, this paper proposes a novel approach to identifying an evolution of SSTA in space and time from a time-series of a raster dataset. This method, called PoAIES, includes three key steps. Firstly, a cluster-based method is enhanced to explore spatiotemporal clusters of SSTA, and each cluster of SSTA at a time snapshot is taken as a snapshot object of SSTA. Secondly, the spatiotemporal topologies of snapshot objects of SSTA at successive time snapshots are used to link snapshot objects of SSTA into an evolution object of SSTA, which is called a process object. Here, a linking threshold is automatically determined according to the overlapped areas of the snapshot objects, and only those snapshot objects that meet the specified linking threshold are linked together into a process object. Thirdly, we use a graph-based model to represent a process object of SSTA. A node represents a snapshot object of SSTA, and an edge represents an evolution between two snapshot objects. Using a number of child nodes from an edge’s parent node and a number of parent nodes from the edge’s child node, a type of edge (an evolution relationship) is identified, which shows its development, splitting, merging, or splitting/merging. Finally, an experiment on a simulated dataset is used to demonstrate the effectiveness and the advantages of PoAIES, and a real dataset of satellite-SSTA is used to verify the rationality of PoAIES with the help of ENSO’s relevant knowledge, which may provide new references for global change research.


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