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@prefix dcterms: <> .
@prefix xsd: <> .
@prefix prov: <> .
@prefix dbpedia_owl: <> .
@prefix gcis: <> .
@prefix rdf: <> .
@prefix rdfs: <> .

   dcterms:identifier "nca4-heat-projections-for-msas-panel--5-process";

## Duration of the activity
   dcterms:extent [ rdf:value "350 hours"^^xsd:string ] ;

## Output datafiles   
   dbpedia_owl:filename "Urban_heat-proj-for-MSAs_v10.png; on TSU Resources site"^^xsd:string;

## Computing environment
   gcis:computingEnvironmentsUsed "Ubuntu linux and Mac OS-X"^^xsd:string;
## assignment of responsibility to an agent for an activity, indicating that the agent 
## had a role in the activity. It further allows for a plan to be specified, which is
## the plan intended by the agent to achieve some goals in the context of this activity.

   prov:qualifiedAssociation [
      a prov:Association ;
      prov:agent [
         a prov:SoftwareAgent, gcis:Software ;
         rdfs:label "NCO 4.4.4,OpenLava 3.2,OpenMPI 1.10.7,Python 2.7.12,QGIS,R"^^xsd:string;
      ] ;
      prov:hadPlan [
         a prov:Plan; 
         rdf:value "Stage 1:<br/>For each of the 32 CMIP5 models downscaled by LOCA (listed below), for each grid point, the annual number of days with a maximum temperature greater than 95F was determined for each year for the historical period (1950-2005), and under both the RCP4.5 and RCP8.5 emissions scenarios for the future period (2006-2100).<br/><br/>CMIP5 models:<br/>ACCESS1-0, ACCESS1-3, bcc-csm1-1, bcc-csm1-1-m, CanESM2, CCSM4, CESM1-BGC, CESM1-CAM5, CMCC-CM, CMCC-CMS, CNRM-CM5, CSIRO-Mk3-6-0, EC EARTH, FGOALS-g2, GFDL-CM3, GFDL-ESM2G, GFDL-ESM2M, GISS-E2-H-p1, GISS-E2-R-p1, HadGEM2-AO, HadGEM2-CC, HadGEM2-ES, inmcm4, IPSL-CM5A-LR, IPSL-CM5A-MR, MIROC5, MIROC-ESM-CHEM, MIROC-ESM, MPI-ESM-LR, MPI-ESM-MR, MRI-CGCM3, NorESM1-M<br/><br/>Stage 2:<br/>1. CMIP5 model grid points within the Charleston, SC Metropolitan Statistical Area (MSA) were defined.<br/>2. Time-ordered annual values of the average annual number of days with a maximum temperature greater than 95F for these grid cells were extracted for each model for the historical period, and under both the RCP4.5 and RCP8.5 scenarios for the future period.<br/>3. Averages over the periods of 1976-2005, 2016-2045, 2036-2065, and 2070-2099 were calculated for each grid cell, model, and scenario.<br/>4. The change for each future time period, relative to 1976-2005, was calculated for each model, under each scenario.<br/>5. Ensemble averages for each grid cell were calculated from these single-model averages using a vector of model weights, using the weighting strategy of Sanderson et al. (2017):<br/>Sanderson, B. M., Wehner, M., and Knutti, R.: Skill and independence weighting for multi-model assessments, Geosci. Model Dev., 10, 2379-2395,, 2017.<br/>6. A spatial average of these values across all grid cells in the specified MSA, and an associated range across models were calculated. The range is defined as the difference between the 5th and 95th percentiles. The value of the 50th percentile was also calculated, each using the R quantiles function.<br/>7. These values were graphed. For consistency in methodology between the mean and range calculations, percentile values were used. Minimal differences were found between the 50th percentile of models and the weighted multi-model mean.<br/>See, \"lmi_nca4_technical_documentation_v3.docx\" and \"README_tt_v2\" for a more detailed methodology."^^xsd:string;
      ] ;
   ] ;

   a prov:Activity .

## The following entity was derived from a dataset using this activity
   prov:wasDerivedFrom <>;
   prov:wasGeneratedBy <>.