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Below is a synopsis of several different climate science projects I have worked on over the past 10 years @ the University of Idaho.  I have particular experience with large climate variable datasets (NetCDF), climate-focused web services (THREDDS), as well as using climate variables in relationship to other related variables to explore differing spatial and temporal relationships.


Pacific Northwest Climate Conference 2018

PNWCC 2018 Poster

As part of the PNWCC, I’m presenting a decision tree analysis of agricultural commodity loss and its relationship to climate.




CIRC (2014-present)

Predictive outputs of machine learning model for agricultural commodity loss and climate

Climate Impacts Research Consortium (CIRC).  CIRC is the a NOAA RISA research team that is exploring climatic impacts in the Pacific Northwest.  Currently in year 3 of 5, my work on this project is to develop data mining approaches to explore how climate is related to agriculture – with efforts to extend this methodology to other areas.  Our research can be seen @ http://www.dmine.io.



REACCHPNA (2011-2017)

REACCHPNA Data Management Poster (2016)

The Regional Approaches to Climate Change for Pacific Northwest Agriculture (www.reacchpna.org) was a five-year coordinated agricultural project (CAP), funded by the USDA, to explore relationships of agriculture with climate.  Over 200 researchers @ three different institutions (Oregon State, Washington State, and the University of Idaho) worked to develop several research programs in the areas of climate variability, climate modeling, GHG analysis, farm-level commodity analysis, social impacts to climate, as well as data management of agriculture and climate data.


REACCHPNA Statistical Atlas (2017)

As part of the REACCH team, applications were developed  to ingest and expose climate data using GIS, THREDDS, Linux and python.  Over 40 web services were developed from researcher content, and used to expose results of analysis to the public and the funding agency.  From a social science perspective, we developed an agricultural statistical atlas to related collected longitudinal perceptions of climate with quantitative agricultural landscape systems (right).  The atlas contains differing map views of survey questions in relationship to agricultural commodity systems.