pro SUB_accumulate_step5, var_combine_all, var_mean_all, var_std_all, var_combine, var_mean, var_std, $
                          nobs_all=var_nobs_all, nobs_this=nobs_this, time_all = var_time_all, time_this = time_this

if n_elements(var_combine) eq 0 then begin ; if var_combine is empty, then insert dummy column; required by json format

  size_this = size(var_combine_all,/dim)
  if n_elements(var_mean_all) gt 0 then begin 
    var_mean_all= [var_mean_all, transpose(fltarr(size_this))+!values.f_nan]
    var_std_all= [var_std_all, transpose(fltarr(size_this))+!values.f_nan]
    if ARG_PRESENT(nobs_this) then begin
      var_nobs_all = [var_nobs_all, transpose(fltarr(size_this))+!values.f_nan]
    endif
    if ARG_PRESENT(time_this) then begin
      var_time_all= [var_time_all, time_this]
    endif
  endif

endif else begin

  if n_elements(var_mean_all) eq 0 then begin ; the first element, simply give the current value

    var_combine_all = var_combine
    var_mean_all =  transpose(var_mean)
    var_std_all  =  transpose(var_std)
    if ARG_PRESENT(nobs_this) then begin
      var_nobs_all = transpose(nobs_this)
    endif
    if ARG_PRESENT(time_this) then begin
      var_time_all = time_this
    endif

  endif else begin

    existing = 0
    for combine_loop = 0, n_elements(var_combine)-1 do begin

      this_id = where(var_combine_all eq var_combine[combine_loop], this_num)

      if this_num eq 0 then begin ; new combine, rebuild the whole line for the new combine

        ;print,'new combine'

        var_combine_all = [var_combine_all, var_combine[combine_loop]]
        size_this = size(var_mean_all,/dim)

        var_mean_all= [transpose(var_mean_all), transpose(fltarr(size_this[0]))+!values.f_nan]
        var_mean_all= transpose(var_mean_all)

        var_std_all= [transpose(var_std_all), transpose(fltarr(size_this[0]))+!values.f_nan]
        var_std_all= transpose(var_std_all)

        if ARG_PRESENT(nobs_this) then begin
          var_nobs_all= [transpose(var_nobs_all), transpose(fltarr(size_this[0]))+!values.f_nan]
          var_nobs_all= transpose(var_nobs_all)
        endif

        ;; if the new combine is the first one, then actually we need to append column one time. 
        if combine_loop eq 0 then begin ; only append once
          size_this = size(var_combine_all,/dim)
          var_mean_all= [var_mean_all, transpose(fltarr(size_this))+!values.f_nan]
          var_std_all= [var_std_all, transpose(fltarr(size_this))+!values.f_nan]
          if ARG_PRESENT(nobs_this) then begin
            var_nobs_all= [var_nobs_all, transpose(fltarr(size_this))+!values.f_nan]
          endif
          if ARG_PRESENT(time_this) then begin
            var_time_all= [var_time_all, time_this]
          endif
          existing=1
        endif 

        var_mean_all[-1, -1] = var_mean[combine_loop]
        var_std_all[-1, -1] = var_std[combine_loop]
        if ARG_PRESENT(nobs_this) then begin
          var_nobs_all[-1, -1] = nobs_this[combine_loop]
        endif

      endif else begin  ; existing combine, append to column

        ;print,'existing combine'

        if existing eq 0 then begin ; only append once
          size_this = size(var_combine_all,/dim)
          var_mean_all= [var_mean_all, transpose(fltarr(size_this))+!values.f_nan]
          var_std_all= [var_std_all, transpose(fltarr(size_this))+!values.f_nan]
          if ARG_PRESENT(nobs_this) then begin
            ;print,'size(var_nobs_all):',size(var_nobs_all)
            ;print,'size_this:',size_this
            var_nobs_all= [var_nobs_all, transpose(fltarr(size_this))+!values.f_nan]
          endif
          if ARG_PRESENT(time_this) then begin
            var_time_all= [var_time_all, time_this]
          endif
          existing = 1
        endif 

        var_mean_all[-1, this_id] = var_mean[combine_loop]
        var_std_all[-1, this_id] = var_std[combine_loop]

        if ARG_PRESENT(nobs_this) then begin
          var_nobs_all[-1, this_id] = nobs_this[combine_loop]
        endif

      endelse
      ;print,'-----------'

    endfor ; combine_loop

  endelse  ; n_elements(var_mean_all) eq 0 
endelse ; n_elements(var_combine) eq 0

end