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downscaling2/Data/bias.html

@@ -63,7 +63,7 @@
   <p class="medium">Precipitation Biases</p>
 
   <p class="normal"> 
-  Many COOP stations report days with weak precipitation as zero precipitation leading to an under-reporting of "wet days" and an artificial precipitation amount histogram. These same stations also tend to round precipitation to the nearest 5 hundredths of an inch instead of the nearest hundredth of an inch (see <a href="https://journals.ametsoc.org/view/journals/bams/88/6/bams-88-6-899.xml" target="_blank">Daly et al. 2007</a>). For the CMIP5 downscaling, poor stations were identified by calculating the ratio of days with precipitation amounts from 1 to 4 hundredths of an inch to the days with 5 hundredths of an inch. The poor station are then discarded from any further calculations. For the new CMIP6 downscaling, a new method for correcting the bias that keeps the station is developed.
+  Many COOP stations report days with weak precipitation as zero precipitation leading to an under-reporting of "wet days" and an artificial precipitation amount histogram. These same stations also tend to round precipitation to the nearest 5 hundredths of an inch instead of the nearest hundredth of an inch (see <a href="https://journals.ametsoc.org/view/journals/bams/88/6/bams-88-6-899.xml" target="_blank">Daly et al. 2007</a>). For the CMIP5 downscaling, poor stations were identified by calculating the ratio of days with precipitation amounts from 1 to 4 hundredths of an inch to the days with 5 hundredths of an inch. The poor stations are then discarded from any further calculations. For the new CMIP6 downscaling, a new method for correcting the bias that keeps the station is used.
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downscaling2/Data/hour.html

@@ -63,7 +63,7 @@
   <p class="medium">Hour of Observation</p>
 
   <p class="normal"> 
-  For many stations the hour of observation given in the Metadata is incorrect. This fact is obvious when looking at temporally lagged correlations between nearby stations. An iterative method to correct the hour of observation errors was developed based on the observed versus the expected lagged correlation. The station with worst agreement between observed and expected is corrected first. Then all lagged correlations are completed again, and the next worst station is corrected until some threshold. 
+  For many stations the hour of observation given in the Metadata is incorrect. This fact is obvious when looking at temporally lagged correlations between nearby stations. An iterative method to correct the hour of observation errors was developed based on the observed versus the expected lagged correlation. The station with worst agreement between observed and expected is corrected first. Then all lagged correlations are calculated again, and the next worst station is corrected until some error threshold. 
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downscaling2/Interp/method.html

@@ -62,7 +62,7 @@
   <p class="medium">Method</p>
 
   <p class="normal"> 
-  Provided certain assumptions hold, Kriging is best linear unbiased interpolator. However, for our situation, Kriging can be problematic because the station weights can sometimes be negative, which will lead to unrealistic negative precipitation. Therefore a modified version of Kriging is developed in which each station weight in constrained to be greater than or equal to zero. While this solves the negative precipitation issue, it also inhibits the ability of Kriging to extrapolate beyond the range of the station values. To fix this issue, the station values are first normalized by the PRISM climatology (divide by climatology for precipitation, subtract climatology for temperature), next this quantity is interpolated via modified Kriging, and finally the gridded PRSIM climatology is applied.
+  Provided certain assumptions hold, Kriging is best linear unbiased interpolator. However, for our situation, Kriging can be problematic because the station weights can sometimes be negative, which will lead to unrealistic negative precipitation. Therefore a modified version of Kriging is developed in which each station weight is constrained to be greater than or equal to zero. While this solves the negative precipitation issue, it also inhibits the ability of Kriging to extrapolate beyond the range of the station values. To fix this issue, the station values are first normalized by the PRISM climatology (divide by climatology for precipitation, subtract climatology for temperature), next this quantity is interpolated via modified Kriging, and finally the gridded PRSIM climatology is reapplied.
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