clim_yearlist<-list_tmp

  }

    list_param_runClim_KGCAI<-list(j,s_raster,covar_names,lst_avg,list_models,dst,var,y_var_name, out_prefix,out_path)

    names(list_param_runClim_KGCAI)<-c("list_index","covar_rast","covar_names","lst_avg","list_models","dst","var","y_var_name","out_prefix","out_path")

    clim_method_mod_obj<-mclapply(1:12, list_param=list_param_runClim_KGCAI, runClim_KGCAI,mc.preschedule=FALSE,mc.cores = 6) #This is the end bracket from mclapply(...) statement

  #TODO : Same call for all functions!!! Replace by one "if" for all multi time scale methods...

  #The methods could be defined earlier as constant??

    #input a list:note that ghcn.subsets is not sampling_obj$data_day_ghcn

    i<-1

    list_param_run_prediction_daily_deviation <-list(i,clim_yearlist,sampling_obj,dst,var,y_var_name, interpolation_method,out_prefix,out_path)

  ################### PREPARE RETURN OBJECT ###############

  #Will add more information to be returned

    raster_prediction_obj<-list(clim_method_mod_obj,method_mod_obj,validation_mod_obj,tb_diagnostic_v,

                                summary_metrics_v,summary_month_metrics_v)

    names(raster_prediction_obj)<-c("clim_method_mod_obj","method_mod_obj","validation_mod_obj","tb_diagnostic_v",

# 5)runGAMFusion <- function(i,list_param) : daily step for fusion method, perform daily prediction

#

#AUTHOR: Benoit Parmentier                                                                       

#PROJECT: NCEAS INPLANT: Environment and Organisms --TASK#363--   

##Comments and TODO:

  out_path<-list_param$out_path

  #Model and response variable can be changed without affecting the script

  #### STEP 2: PREPARE DATA

  LST_name<-lst_avg[j] # name of LST month to be matched

  data_month$LST<-data_month[[LST_name]]

  if (var=="TMAX"){   

    data_month$y_var<-data_month$TMax #Adding TMax as the variable modeled

  }

  #mod_list<-fit_models(list_formulas,data_month) #only gam at this stage

  #cname<-paste("mod",1:length(mod_list),sep="") #change to more meaningful name?

  #Adding layer LST to the raster stack  

  pos<-match("LST",names(s_raster)) #Find the position of the layer with name "LST", if not present pos=NA

  s_raster<-addLayer(s_raster,LST)            #Adding current month

  #Now generate file names for the predictions...

  names(list_out_filename)<-cname  

  for (k in 1:length(list_out_filename)){