Greenland melting | 25-year awards | Fall is coming


new chairs

A herd of new chairs for the computer labs in The Department of Geography migrated into Walker Building this week. Existing chairs are being repurposed to grad offices and worn out chairs are on their way to salvage.


The Dutton e-Education Institute will hold a reception for Online Geospatial Education program summer graduates on Saturday, August 10, 11:45 a.m. to 1:15 p.m. Graduate summer commencement is Saturday, August 10, 2019, 2:30 p.m. at The Bruce Jordan Center.

Undergraduate Research Opportunities Connection (UROC) is now accepting applications for research and professional development projects for Fall 2019.

Mark your calendar for the Geography Fall Welcome Picnic on September 14. For more information and to RSVP go to:

Call For Papers: 1st IEEE ICDM Workshop on Deep Learning for Spatiotemporal Data, Algorithms, and Systems (DeepSpatial 2019) November 8, 2019, Beijing, China.

Save the date for the Penn State GIS Day events held on Tuesday, November 12, 2019.


From Scientific American
Historic Greenland Melt Is a “Glimpse of the Future”

Luke Trusel is quoted

Greenland is in the midst of one of its strongest melting events on record, as a major heat wave—the same one that scorched much of Europe last month—grips the Arctic.

Ice sheet experts have been keeping careful watch as the event unfolds, taking note of its extraordinary progress. Throughout July, Greenland lost an estimated total of 197 billion metric tons of ice, researcher Ruth Mottram of the Danish Meteorological Institute tweeted early Wednesday morning. That day, the largest melt day of the month, the institute estimated that more than half the ice sheet was experiencing some level of surface melting, and about 10 billion tons of ice was lost in a single day.

Related coverage:

Faculty and Staff News of Record: 25-Year Awards, July 2019

Todd Bacastow, Cynthia A. Brewer, Andrew M. Carleton recognized


Dynamically Optimized Unstructured Grid (DOUG) for Analog Ensemble of numerical weather predictions using evolutionary algorithms

Weiming Hu, Guido Cervone
Computers & Geosciences
The Analog Ensemble is a statistical technique that generates probabilistic forecasts using a current deterministic prediction, a set of historical predictions, and the associated observations. It generates ensemble forecasts by first identifying the most similar past predictions to the current one, and then summarizing the corresponding observations. This is a computationally efficient solution for ensemble modeling because it does not require multiple numerical weather prediction simulations, but a single model realization. Despite this intrinsic computational efficiency, the required computation can grow very large because atmospheric models are routinely run with increasing resolutions. For example, the North American Mesoscale forecast system contains over 262 792 grid points to generate a 12 km prediction. The North American Mesoscale model generally uses a structured grid to represent the domain, despite the fact that certain physical changes occur non-uniformly across space and time. For example, temperature changes tend to occur more rapidly in mountains than plains. An evolutionary algorithm is proposed to dynamically and automatically learn the optimal unstructured grid pattern. This iterative evolutionary algorithm is guided by Darwinian evolutionary rule generation and instantiation to identify grid vertices. Analog computations are performed only at vertices. Therefore, minimizing the number of vertices and identifying their locations are paramount to optimizing the available computational resources, minimizing queue time, and ultimately achieving better results. The optimal unstructured grid is then reused to guide the predictions for a variety of applications like temperature and wind speed.

Relationships of West Greenland supraglacial melt‐lakes with local climate and regional atmospheric circulation

Rowley, N. A., Carleton, A. M. and Fegyveresi, J.
International Journal of Climatology
Along the west‐central Greenland ice‐sheet (GrIS) ablation zone, the time of annual maximum occurrence of surface melt lakes, or peak lake period (PLP) averages 18 June–03 July. This study combines atmospheric reanalysis and automatic weather station (AWS) data from the Greenland Climate Network to assess the roles of synoptic circulation patterns and local climate variables, respectively, in the total melt‐lake area and count in the Sermeq Kujalleq Ablation Region (SKAR) for the PLPs of 2000–2016. Melt‐lake information is obtained from analysis of Landsat‐7 images. Two surface climate parameters (e.g., temperature, incoming shortwave radiation) having a strong combined effect on melt‐lake area in the SKAR are the June mean temperature, and May mean incoming solar radiation (r = 0.96). Incorporating the May insolation into a regression equation permits predictability of total melt‐lake area for the study area into late June. June months classified as high melt correlate regionally with mid‐tropospheric ridging, warm air advection, and reduced cloud cover, while low melt June months are associated with a trough, cold advection and greater cloud amount. A localized feature that we found to be prevalent during the high melt years are piteraq, or downsloping winds, which provide additional warming to the SKAR from adiabatic compression. Atmospheric circulation indices comprising the North Atlantic Oscillation (NAOI) teleconnection and Greenland Blocking (GBI) pattern augment the reanalysis gridded data. We find statistically significant correlations of the NAOI and GBI with melt‐lake area (r = −0.62 and r = 0.77, respectively). The correlations with melt‐lake count however, are not significant; greater combined lake area and count tend to accompany the meridional mode of high amplitude Rossby waves and/or anticyclonic blocking in the Greenland sector. Determining the local and synoptic‐scale atmospheric controls on supraglacial lake variability helps clarify the role of climate in the surface hydrology of the GrIS.

Spatial and temporal dynamics of 20th century carbon storage and emissions after wildfire in an old-growth forest landscape

Lucas B. Harris, Andrew E. Scholl, Amanda B. Young, Becky L. Estes, Alan H. Taylor
Forest Ecology and Management
Both fire exclusion and subsequent wildfires have strongly affected carbon storage in fire-prone dry forests, with implications for how carbon storage will change in the future. Using a reconstruction of forest structure in 1899 and pre- and post-fire field data, we quantified changes in carbon stocks in a 2125-ha old-growth mixed conifer forest landscape over a century of fire exclusion and emissions due to a 2013 wildfire. From 1899 to 2002 aboveground carbon storage in live trees increased 2.5-fold from 97 Mg/ha to 263 Mg/ha. Despite burning in an uncharacteristically severe wildfire, the forest still contained 169 Mg/ha of live aboveground tree carbon in 2014. Direct fire emissions were 72 Mg/ha and did not vary with canopy cover loss because emissions were largely driven by consumption of accumulated surface fuels. Areas that burned at low, moderate and high severity in the wildfire contained similar amounts of carbon in 1899, when the forest was still experiencing frequent low severity fire. By 2002 the low severity areas contained 80 and 86 Mg/ha more aboveground live tree carbon than moderate and high severity areas respectively. The wildfire reinforced and amplified these differences in carbon storage that arose during fire exclusion, such that carbon storage following the wildfire was more variable across the landscape. Additionally, the proportion of carbon stored in shade-intolerant, more fire-sensitive species increased. These changes in where and in what tree species carbon is stored, due to the combination of fire exclusion and wildfire, have implications for the potential future stability of these carbon stocks.

Migration as a feature of land system transitions

Claudia Radel, Brad D. Jokisch, Birgit Schmook, Lindsey Carte, Mariel Aguilar-Støen, Kathleen Hermans, Karl Zimmerer, Stephen Aldrich
Current Opinion in Environmental Sustainability
Human migration to and from rural areas is so prominent and persistent globally that land system science must understand how the movement of people is integral to land system transitions both at the origin of migration and at its destination. With a focus on Latin America, we review research on how land change affects migration and how migration affects land systems, to demonstrate that the relationship is complex and context-specific. Various types of migration evidence the challenges of managing land for multiple goals and the needs of diverse groups. A perspective that connects land change in multiple locations is needed. In particular, concepts of telecoupling and translocality can help to further understanding of how globalized economic systems link changes across distant places and capture the economic and non-economic processes that accompany migration and shape land change in multiple, connected locations. Land systems research must anticipate that migration will continue to contribute to complex land systems with multiple users and goals.

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