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Wolverine Climate Change Snow Refugia Study

Sector: Advanced Electronics • Location: United States of America

Source: Grants.gov

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1.Snow Refugia Modeling (CU) a. Perform fine scale (approx. 250 meter)hyrologic modeling using the Distributed Hydrology Soil Vegetation Model (DHSVM) for two sub⿐regions of appproximately 1000 km2, or for similar areal coverage distributed within the core region of interest for wolverine habitat. Choices of specific sub⿐regions will be done in consultation with Dr. Steve Torbit of FWS.

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The project “Wolverine Climate Change Snow Refugia Study” is an infrastructure initiative in the Advanced Electronics sector, located in United States of America. Taiyo aggregates data on it from Grants.gov.

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Description

Description

1.Snow Refugia Modeling (CU) a. Perform fine scale (approx. 250 meter)hyrologic modeling using the Distributed Hydrology Soil Vegetation Model (DHSVM) for two sub⿐regions of appproximately 1000 km2, or for similar areal coverage distributed within the core region of interest for wolverine habitat. Choices of specific sub⿐regions will be done in consultation with Dr. Steve Torbit of FWS. The following simulations are proposed: i.Historic (observed) simulation with for the period 2000⿐2015 ii. Baseline Simulation (may be identical to (i) if ⿿delta⿝ method is used). iii. Future simulations for mid⿐21st century (nominally 2014⿐2070) for high and low rates of climate change. Additional simulation for medium rate of change if time and resources permit. b. Evaluation of historic (observed) simulation results against MODIS(satellite remote sensed) snowcover, and if appropriate SNOTEL and streamgage measurements within the sub⿐regions that are modeled. c. Analysis of simulation outputs for the presence of absence of ⿿snow refugia⿝ ⿐⿐areas that preferentially retain snow under climate change d. Provide digital maps of snow water equivalent and snow depth maps in digital form for critical periods of the year for wolverine habitat from the simulations. 2. Historic snowpack variability analysis (PSD) a. Analyze historic variability in snow cover from satellite remote sensing (MODIS snow cover product), including Identification of areas on the current landscape where Springtime snow cover is resilient during high and low precipitation years, and warm and cold years. This analysis will be done based on data availability for the period 2001⿐2015. b. Provide digital gridded data of snow cover including percent of years in which snow is retained, and any potential analog years for climate change if found. 3. Other Tasks (CU; PSD) a. Consultation with FWS on interpretation of model output, data access, and potential further analysis of model output throughout the project, including potential travel to meetings. b. Writing draft and Final reports for FWS and manuscript for submission for publication c. Data storage (i.e. computer hardware to store big datasets (CU) 4. Deliverables (CU) a. Draft Report summarizing preliminary results from DHSVM modeling detailed in (1)for one sub⿐region (mid⿐December 2016) b. Digital gridded data of snowpack for one sub⿐region (mid⿐December 2016) c. Additional Digital gridded data detailed in (1) above (January 2017) d. Final Report chapters of DHSVM modeling (1) above. (end of project) 5. Deliverables (PSD) a. Draft Report summarizing preliminary results from historic snowpack variability analysis (mid⿐December 2016). b. Digital gridded data detailed in (2) for first region of interest (crown of continent). (mid⿐December 2016) c. Additional digital gridded data for Colorado Region (January 2017) d. Final Report chapters on (2) and synthesis of results. (end of project)

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