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Revision ad6af007

Added by Benoit Parmentier about 9 years ago

running assessment part2 South America

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climate/research/oregon/interpolation/global_run_scalingup_assessment_part2.R
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#Analyses, figures, tables and data are also produced in the script.
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#AUTHOR: Benoit Parmentier
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#CREATED ON: 03/23/2014
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#MODIFIED ON: 09/23/2015
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#MODIFIED ON: 10/05/2015
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#Version: 4
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#PROJECT: Environmental Layers project
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#COMMENTS: analyses for run 10 global analyses,all regions 1500x4500km with additional tiles to increase overlap
......
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#On NEX


  		




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#contains all data from the run by Alberto


  		




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#in_dir1 <- "/nobackupp4/aguzman4/climateLayers/output4" #On NEX


  		




  
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#in_dir1 <- " /nobackupp6/aguzman4/climateLayers/out_15x45/" #On NEX


  		




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#parent output dir for the current script analyes


  		




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#out_dir <- "/nobackup/bparmen1/" #on NEX


  		




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#in_dir_shp <- "/nobackupp4/aguzman4/climateLayers/output4/subset/shapefiles/"


  		




  ......




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interpolation_method <- c("gam_CAI") #PARAM2


  		




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#out_suffix<-"run10_global_analyses_01282015"


  		




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#out_suffix <- "output_run10_1000x3000_global_analyses_02102015"


  		




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out_suffix <- "run10_1500x4500_global_analyses_pred_1982_09152015" #PARAM3


  		




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out_dir <- "/data/project/layers/commons/NEX_data/output_run10_1500x4500_global_analyses_pred_1982_09152015" #PARAM4


  		




  
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out_suffix <- "run10_1500x4500_global_analyses_pred_1992_10052015" #PARAM3


  		




  
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out_dir <- "/data/project/layers/commons/NEX_data/output_run10_1500x4500_global_analyses_pred_1992_10052015" #PARAM4


  		




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create_out_dir_param <- FALSE #PARAM 5


  		




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mosaic_plot <- FALSE #PARAM6


  		




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#if daily mosaics NULL then mosaicas all days of the year


  		




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day_to_mosaic <- c("19820101","19820102","19820103","19820104","19820105",


  		




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                   "19820106","19820107","19820108","19820109","19820110",


  		




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                   "1982011")


  		




  
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day_to_mosaic <- c("19920101","19920102","19920103")


  		




  
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CRS_WGS84 <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +towgs84=0,0,0") #Station coords WGS84 #CONSTANT1


  		




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CRS_locs_WGS84<-CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +towgs84=0,0,0") #Station coords WGS84


  		




  ......




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  p <- bubble(summary_metrics_v_subset,"n_missing",main=paste("Missing per tile and by ",model_name[j]," for ",


  		




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                                                              threshold_missing_day[i]))


  		




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  p1 <- p+p_shp


  		




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  print(p1)


  		




  
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  try(print(p1)) #error raised if number of missing values below a threshold does not exist


  		




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  #plot(ac_mod1,cex=(ac_mod1$rmse1)*2,pch=1,add=T)


  		




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  #title(paste("Averrage RMSE per tile and by ",model_name[i]))


  		




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