The current version does not need "precipFlag". This flag has been used to 
specify unit conversion with the CRU3.0 precipitation data which (kg/m2/s) is 
different from other datasets (mm/day); this step in the current version is 
done via metadata information and is transparent to users. Thus, I suggest 
dropping "precipFlag" in the current version.

We may reinstate "variableFlag" to point specific variables (e.g., temperature, 
cloudiness, shortwave radiation, etc.). For example, I use "precipFlag" in my 
hydro prototype because bias correction of precipitation is done differently 
from temperature. This can be included in a future version with clearer view on 
future expansion for supporting specific users.




-----------------------------------------------------------------------------------------------------
Jinwon Kim
Dept. Atmospheric and Oceanic Sciences and
Joint Institute for Regional Earth System Science and Engineering
University of California, Los Angeles
Los Angeles, CA 90095-1565
________________________________________
From: Cameron Goodale (JIRA) [[email protected]]
Sent: Thursday, May 23, 2013 12:59 PM
To: [email protected]
Subject: [jira] [Created] (CLIMATE-47) precipFlag attribute within the Model 
class needs to be refactored

Cameron Goodale created CLIMATE-47:
--------------------------------------

             Summary: precipFlag attribute within the Model class needs to be 
refactored
                 Key: CLIMATE-47
                 URL: https://issues.apache.org/jira/browse/CLIMATE-47
             Project: Apache Open Climate Workbench
          Issue Type: Improvement
          Components: rcmet
    Affects Versions: 0.1-incubating
            Reporter: Cameron Goodale
            Assignee: Cameron Goodale
             Fix For: 0.1-incubating


There is a precipFlag attribute within the Model class.  This has been used for 
computation and unit conversions.

As the code is changing we need to handle this attribute better.  We can either 
get rid of it entirely, or decide on better rules for handling this information.

If anyone else has experience working with precip data and has suggestions for 
way to handle this let us know.

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