Compung and the Development of ClimateEngine.org

Katherine Hegewisch, Donovan VanSant, John Abatzoglou Department of Geography, University of Idaho Outline

Google Resources: ¥ – raster data storage ¥ Engine – data processing ¥ – base map, geocoding • Google Fusion – vector data storage • - web hosng

Non-Google Resources: ¥ GitHub- code development ¥ Python • Twier Bootstrap - web framework • Highcharts, d3- SVG

ClimateEngine.org Tool: ¥ Remote sensing and meteorological datasets ¥ Mapping and Time Series ¥ Customizable views How We Got Started

● White House Data Iniave: connecng decision makers with data-driven tools ● Google commitment: 1 petabyte of storage for climate and remote sensing datasets and cloud compung resources ● Google Faculty Award: integraon of datasets for drought monitoring

Tyler Erickson Google Google Cloud Google’s storage for popular raster data Google takes care of processing so ‘science’ can be started earlier

Data catalog and workspace: hps://earthengine.google.org/

Geng datasets on cloud: ● demonstrate wide appeal/use for data ● Creave Commons License Google Earth Engine Google’s processing power

¥ 1000s of Earth Engine Processors with Direct connecon to data on Google Cloud=high speed ¥ Javascript/Python API and a User’s Guide hps://developers.google.com/earth-engine/

Playground Environment hps://ee-api.appspot.com/

Get an Account: hps://developers.google.com/earth-engine/ service_account

Google Maps Google’s mapping service

Google Maps

● Base Maps ● KML Layers ● Point Markers ● Geo Locaon

Google Maps Api V3: https://developers.google.com/maps/documentation/javascript/ Google Fusion Tables Google’s storage for vector data

Creang a Fusion table

¥ Users upload their vector data(.csv,.kml,ods,.xls) hps://support.google.com/fusiontables/answer/2571232 ¥ User retrieve the fusion table id

Javascript Code to Put Fusion Table on Google Map pointerFT.setOpons({ query: { select: 'geometry', from: ‘1AOrGgpc4pCQLjmQTY5bHiivT-7h3dcIKdcCSyioz’, where: ” ’Name' CONTAINS ’California’ ", }, map:pointerMap, }); Google App Engine Google’s web hosng

Web Hosng ¥ Plaorm as a Service (PaaS) Web hosng on appspot.com ¥ Availability: trusted developers, free for academic/non-profit ¥ Developer Console: hps://console.developers.google.com/project

GitHub and TeamWork Server Side Code Back End Development

● Python 2.7 ● webapp2: Python Web Framework ● Oauth2.0: authencaon to GEE ● Jinja2: python templang ● Modules: numpy,json,dateme, logging and threading Client Side Code Front End Development

● Twier Bootstrap: CSS framework, responsive design ● jQuery: JavaScript Library, cross-browser stability ● Javascript Library for SVG: ○ Highcharts= -me series ○ d3.js - colorbars CLIMATEENGINE.ORG

Desert Research Instute, University of Idaho ClimateEngine.org Mapping Interface

Desert Research Instute, University of Idaho ClimateEngine.org Time Series Interface

Desert Research Instute, University of Idaho ClimateEngine.org Google Cloud Datasets

Google Cloud Datasets Accessed

● Landsat Remote Sensing ● MODIS Remote Sensing ● METDATA Gridded Meteorological ● CFS Reanalysis ● CHIRPS Precipitaon

Desert Research Instute, University of Idaho ClimateEngine.org Variables Accessed

Types of Variables Accessed

● Precipitaon, Temperature ● Humidity, Wind, Radiaon ● Fire Indices ● Vegetaon Indices ● Drought Indices ● Snow Cover

Desert Research Instute, University of Idaho ClimateEngine.org Custom Interface

Custom Calculaons Custom Stascs

Custom Date Ranges

Desert Research Instute, University of Idaho ClimateEngine.org Applicaon: 2015 Sierra Nevada Snowpack

Desert Research Instute, University of Idaho ClimateEngine.org Applicaon: 2015 California Drought

Desert Research Instute, University of Idaho ClimateEngine.org Point Locaons

Desert Research Instute, University of Idaho ClimateEngine.org Time Series Analysis

Mulple-Region Comparisons Mulple-Year Comparisons

Intra-Year Comparisons

Desert Research Instute, University of Idaho ClimateEngine.org