text: """Read and combine raw weather data for future climate."""
  
  import argparse
  import glob
  import os
  
  import pandas as pd
  
  from ideotype.weafile_process import (read_wea,
                                        wea_combine,
                                        wea_preprocess,
                                        wea_summarize,
                                        make_weafile)
  from ideotype import DATA_PATH
  
  
  # Step 0: set up args and parameters
  # Setup argparse for terminal control
  a = argparse.ArgumentParser(
      description='additional info to setup project directories and files'
  )
  
  a.add_argument(
      'future_year',
      type=str,
      help='future time point for climate projections - 2050 or 2100')
  
  # Fetch args
  args = a.parse_args()
  
  # Step 0: Check if solrad.csv files are copied into directory
  solrad_files = len(glob.glob(
          f'/home/disk/eos8/ach315/upscale/weadata/'
          f'process_f{args.future_year}/solrad_*.csv'))
  if solrad_files == 0:
      raise ValueError(
          f'solrad files not copied to process_f{args.future_year} yet!')
  
  # Step 1: Read weather files
  print('*** step 1: read wea data')
  read_wea(1961, 2010, climate_treatment=int(args.future_year))
  # no need to read_solrad since we assume no change in solrad
  # and that data is directly copied from /weadata/process
  
  # Step 2: Combine weather data for all years
  print('*** step 2: combine wea data')
  basepath = (f'/home/disk/eos8/ach315/upscale/weadata/'
              f'process_f{args.future_year}')
  wea_combine(basepath)
  
  # Step 3: Preprocess combined weather files
  print('*** step 3: preprocess combined wea data')
  # paths
  basepath_siteyears = os.path.join(DATA_PATH, 'siteyears')
  wea_folder = f'f{args.future_year}'
  outpath = os.path.join(
      '/home/disk/eos8/ach315/upscale/weadata/data', wea_folder)
  # preprocess
  df_temp, df_rh, df_precip, df_solrad = wea_preprocess(basepath)
  
  # Step 4. Summarize site-year weather info
  print('*** step 4: summarize site-year wea info')
  # parameters & paths
  gseason_start_weasummary = 3
  gseason_end_weasummary = 10
  outpath_wea = os.path.join(DATA_PATH, 'wea')
  # the step of determining site-years is already done when making
  # weather files for 'present' sims, so did not repeat for future climate
  # instead, just use the already existing site-years
  siteyears_filtered = pd.read_csv(
      os.path.join(basepath_siteyears, 'siteyears_control_fixpd.csv'), dtype=str)
  # summarize wea
  df_wea = wea_summarize(siteyears_filtered,
                         df_temp, df_rh, df_precip, df_solrad,
                         gseason_start_weasummary, gseason_end_weasummary)
  df_wea.to_csv(
      os.path.join(outpath_wea, f'wea_summary_f{args.future_year}.csv'),
      index=False)
  
  # Step 5: Convert met data into individual maizsim weather data files
  print('*** step 5: make wea file')
  make_weafile(siteyears_filtered, df_temp, df_rh, df_precip, df_solrad, outpath,
               climate_treatment=int(args.future_year))
  