This was a cool Christmas present! Each year, participants in IIASA’s Young Scientists’ Summer Program (YSSP) have a slim chance of going back to Austria for a further 3 months of research, funded by grants from generous donors who believe that much in the institute’s mission. From some 51 final projects submitted by last summer’s cohort, 13 papers were nominated by our immediate supervisors for consideration for (what are usually) 2 grants, the Peccei and Mikhalevich Awards.
This year, the cohort’s final projects were so strong that the selection committee decided to award 4 grants; so, with the financial assistance of IIASA’s Director General, two YSSPers won Peccei Awards (Cesar Terrer Moreno, with honors, for “Global Consequences of Nitrogen – Mycorrhizal Effects on the Land C Sink Under Rising CO2”; and Clara Orthofer for “Shale gas & South Africa’s energy future – too costly, too late?”) and two won Mikhalevich Awards (me, with honors, for “Simulated Impact of Paleoclimate Change on Fremont Native American Maize Farming in Utah”; and Wei Qi for “Simplifying the complex: Alternative measures of bilateral migration”). All 4 of us will now have the chance to go back in Laxenburg for 3 more months for more systems informed research. For my part, I would like to improve the environmental drivers of the crop model to incorporate canyon dynamics and run the sites again with “dynamically downscaled” regional climate model (RCM) derived values. RCMs offer superior opportunities to study extreme events and their consequences on Ancestral Puebloan farming as well as independent downscaling of local climatologies.
But what really feels nice is to be favorably judged in comparison to the projects of all of my excellent colleagues. Both Cesar and I came in with good computational experience; so we had a good sense of what was possible in 3 months and probably erred on the conservative side. I do not know for certain, but I suspect a similar story for Clara and Wei. If I could, there are many others I would like to award for their ambition. Not least among these would be Kemen Austin (Duke University) and Chibulu “Lu Lu” Luo (University of Toronto) who attempted to use machine learning to tackle important problems of land transformation for Palm Oil in Southeast Asia and urbanization in Sub-Saharan Africa, using open-source and remotely sensed data, making their projects scalable and transferable; Omid Mazdiyasni (UC Irvine) who worked on heat waves and human vulnerability in India; Maria Xylia (KTH Royal Institute of Technology, Sweden) whose model for electric public transit in Stockholm was put into effect a few months ago, after wrestling with nightmarishly munty public transit data; and many others. To all of YSSP2016: Prost!