diff --git a/pcmdi_metrics/precip_variability/lib/lib_variability_across_timescales.py b/pcmdi_metrics/precip_variability/lib/lib_variability_across_timescales.py
index 5f54506c7..74352ec9a 100644
--- a/pcmdi_metrics/precip_variability/lib/lib_variability_across_timescales.py
+++ b/pcmdi_metrics/precip_variability/lib/lib_variability_across_timescales.py
@@ -63,7 +63,7 @@ def precip_variability_across_timescale(
     # Write data (nc file)
     outfilename = "PS_pr." + str(dfrq) + "_regrid.180x90_" + dat + ".nc"
     custom_dataset = xr.merge([freqs, ps, rn, sig95])
-    custom_dataset.to_netcdf(path=os.path.join(outdir(output_type="diagnostic_results"), outfilename))
+    custom_dataset.to_netcdf(path=os.path.join(outdir.replace("%(output_type)","diagnostic_results"), outfilename))
         
     # Power spectum of anomaly
     freqs, ps, rn, sig95 = Powerspectrum(anom, nperseg, noverlap)
@@ -72,7 +72,7 @@ def precip_variability_across_timescale(
     # Write data (nc file)
     outfilename = "PS_pr." + str(dfrq) + "_regrid.180x90_" + dat + "_unforced.nc"
     custom_dataset = xr.merge([freqs, ps, rn, sig95])
-    custom_dataset.to_netcdf(path=os.path.join(outdir(output_type="diagnostic_results"), outfilename))
+    custom_dataset.to_netcdf(path=os.path.join(outdir.replace("%(output_type)","diagnostic_results"), outfilename))
         
     # Write data (json file)
     psdmfm["RESULTS"][dat] = {}
@@ -83,7 +83,7 @@ def precip_variability_across_timescale(
         "PS_pr." + str(dfrq) + "_regrid.180x90_area.freq.mean_" + dat + ".json"
     )
     JSON = pcmdi_metrics.io.base.Base(
-        outdir(output_type="metrics_results"), outfilename
+        outdir.replace("%(output_type)","metrics_results"), outfilename
     )
     JSON.write(
         psdmfm,
diff --git a/pcmdi_metrics/precip_variability/variability_across_timescales_PS_driver.py b/pcmdi_metrics/precip_variability/variability_across_timescales_PS_driver.py
index c606be499..45d4e4ee1 100644
--- a/pcmdi_metrics/precip_variability/variability_across_timescales_PS_driver.py
+++ b/pcmdi_metrics/precip_variability/variability_across_timescales_PS_driver.py
@@ -3,8 +3,6 @@
 import glob
 import os
 
-from genutil import StringConstructor
-
 from pcmdi_metrics.mean_climate.lib.pmp_parser import PMPParser
 from pcmdi_metrics.precip_variability.lib import (
     AddParserArgument,
@@ -34,13 +32,12 @@
 
 # Create output directory
 case_id = param.case_id
-outdir_template = param.process_templated_argument("results_dir")
-outdir = StringConstructor(
-    str(outdir_template(output_type="%(output_type)", mip=mip, case_id=case_id))
-)
+outdir_template = param.results_dir
+outdir_template = outdir_template.replace("%(mip)",str(mip)).replace("%(case_id)",str(case_id))
 for output_type in ["graphics", "diagnostic_results", "metrics_results"]:
-    os.makedirs(outdir(output_type=output_type), exist_ok=True)
-    print(outdir(output_type=output_type))
+    outdir = outdir_template.replace("%(output_type)",output_type)
+    os.makedirs(outdir, exist_ok=True)
+    print(outdir)
 
 # Check data in advance
 file_list = sorted(glob.glob(os.path.join(modpath, mod)))
@@ -57,5 +54,5 @@
 syr = prd[0]
 eyr = prd[1]
 precip_variability_across_timescale(
-        file_list, syr, eyr, dfrq, mip, dat, var, fac, nperseg, noverlap, outdir, cmec
+        file_list, syr, eyr, dfrq, mip, dat, var, fac, nperseg, noverlap, outdir_template, cmec
     )