I smell Review Board :)

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Chris Mattmann, Ph.D.
Chief Architect
Instrument Software and Science Data Systems Section (398)
NASA Jet Propulsion Laboratory Pasadena, CA 91109 USA
Office: 168-519, Mailstop: 168-527
Email: [email protected]
WWW:  http://sunset.usc.edu/~mattmann/
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Adjunct Associate Professor, Computer Science Department
University of Southern California, Los Angeles, CA 90089 USA
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-----Original Message-----
From: <Lee>, "Kyo   (329C-Affiliate)" <[email protected]>
Reply-To: "[email protected]" <[email protected]>
Date: Wednesday, June 4, 2014 8:28 PM
To: "[email protected]" <[email protected]>
Subject: Re: Model Observation Evaluation exmaple

>Hi Mazi,
>
>We do not have to make the new metric from scratch.
>As I told you two weeks ago, someone just needs to reform the following
>function that Kim and I updated last year.
>
>--------------------------------------------------------------------------
>-
>def calcClimSeason(monthBegin, monthEnd, dataset1):
>    '''
>    Purpose ::
>       Calculate seasonal mean montheries and climatology for both 3-D
>and point time series.
>       For example, to calculate DJF mean time series, monthBegin = 12,
>monthEnd =2
>       This can handle monthBegin=monthEnd i.e. for climatology of a
>specific month
>
>    Input::
>        monthBegin - an integer for the beginning month (Jan =1)
>        monthEnd - an integer for the ending month (Jan = 1)
>        dataset1 - 3d numpy array of data in (t,lat,lon) or 1d numpy
>array montheries
>
>    Output::
>        tSeries - if 3d numpy was entered, 3d (number of years/number of
>years -1 if monthBegin > monthEnd,lat,lon),
>        if 1d data entered it is a montheries of the data of length
>number of years
>        means - if 3d numpy was entered, 2d (lat,lon), if 1d data entered
>        it is a floating point number representing the overall mean
>    '''
>    if monthBegin > monthEnd:
>        # Offset the original array so that the the first month
>        # becomes monthBegin, note that this cuts off the first year of
>data
>        offset = slice(monthBegin - 1, monthBegin - 13)
>        data = misc.reshapeMonthlyData(dataset1[offset])
>        monthIndex = slice(0, 13 - monthBegin + monthEnd)
>    else:
>        # Since monthBegin <= monthEnd, just take a slice containing
>those months
>        data = misc.reshapeMonthlyData(dataset1)
>        monthIndex =  slice(monthBegin - 1, monthEnd)
>
>    tSeries = data[:, monthIndex].mean(axis = 1)
>    means = tSeries.mean(axis = 0)
>    return tSeries, means
>--------------------------------------------------------------------------
>------------------------
>
>Cheers,
>Kyo
>
>
>On Jun 4, 2014, at 4:41 PM, Boustani, Maziyar (398F)
><[email protected]> wrote:
>
>> I guess the best solution here is to add the new Metric
>>"calcBiasAberageOverTime" to our Metrics and use that in this example to
>>be able to generate one plot.
>> 
>> ........................
>> Maziyar Boustani
>> Software Engineer - GIS Developer
>> Science Data Understanding Group
>> Jet Propulsion Laboratory, California Institute of Technology
>> 4800 Oak Grove Drive,
>> Pasadena, CA, 91109
>> [email protected]<mailto:[email protected]>
>> 
>> On Jun 4, 2014, at 4:29 PM, Loikith, Paul C (329C-Affiliate) wrote:
>> 
>> Yes agreed.  I'm guessing the issue here is the use of "calcBias" vs.
>>"calcBiasAveragedOverTime."  The later module from metrics.py would
>>accomplish this.
>> 
>> I definitely agree about the colorbar too.
>> 
>> Hope all is well.
>> 
>> Paul
>> 
>> From: Alex Goodman
>><[email protected]<mailto:[email protected]>>
>> Date: Wednesday, June 4, 2014 4:25 PM
>> To: "[email protected]<mailto:[email protected]>"
>><[email protected]<mailto:[email protected]>>
>> Cc: "Boustani, Maziyar (398F)"
>><[email protected]<mailto:[email protected]>>,
>>Paul Loikith 
>><[email protected]<mailto:[email protected]>>
>> Subject: Re: Model Observation Evaluation exmaple
>> 
>> Hi Paul,
>> 
>> I think I wasn't sure what was exactly in Mazi plots. I thought what
>>was being shown was the bias averaged for each year. Instead it sounds
>>like the data was temporally regridded from monthly data to yearly data
>>first, (eg, the annual average surface temperatures were calculated
>>first, then the bias metric was ran on the temporally regridded data).
>>What I was trying to say was that from visually inspecting the plots
>>alone, a plot of the average values of all five of them would probably
>>look similar to each individual plot. Sorry if I worded that poorly...
>>in any case I think your suggestion is the correct one, what should be
>>plotted is just the mean bias at each grid point for the five-year
>>period.
>> 
>> Also another side-note: When plotting biases or anomalies, it is
>>generally ideal to have the 0 contour at the center of the colorbar.
>>Currently you must manually enter the contour levels into one of the
>>arguments of the contour plotting function to achieve this. Finding an
>>elegant way to do this automatically was an often requested feature of
>>the OCW plotting interface that I unfortunately never found the time to
>>implement. Just something to think about.
>> 
>> Also, thanks for the kind regards Chris, I am doing well.
>> 
>> Alex
>> 
>> 
>> On Wed, Jun 4, 2014 at 5:06 PM, Mattmann, Chris A (3980)
>><[email protected]<mailto:[email protected]>>
>>wrote:
>> THanks guys, Alex, great to see you!
>> 
>> ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
>> Chris Mattmann, Ph.D.
>> Chief Architect
>> Instrument Software and Science Data Systems Section (398)
>> NASA Jet Propulsion Laboratory Pasadena, CA 91109 USA
>> Office: 168-519, Mailstop: 168-527
>> Email: [email protected]<mailto:[email protected]>
>> WWW:  http://sunset.usc.edu/~mattmann/
>> ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
>> Adjunct Associate Professor, Computer Science Department
>> University of Southern California, Los Angeles, CA 90089 USA
>> ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
>> 
>> 
>> 
>> 
>> 
>> 
>> -----Original Message-----
>> From: Alex Goodman
>><[email protected]<mailto:[email protected]>>
>> Reply-To: "[email protected]<mailto:[email protected]>"
>><[email protected]<mailto:[email protected]>>
>> Date: Wednesday, June 4, 2014 3:53 PM
>> To: "Boustani, Maziyar (398F)"
>><[email protected]<mailto:[email protected]>>
>> Cc: "Loikith, Paul C (329C-Affiliate)"
>><[email protected]<mailto:[email protected]>>,
>> "[email protected]<mailto:[email protected]>"
>><[email protected]<mailto:[email protected]>>
>> Subject: Re: Model Observation Evaluation exmaple
>> 
>>> Hi Mazi,
>>> 
>>> I am in agreement with Paul. It is also clear from a quick inspection
>>>of
>>> your plots that the model bias for each year is identical, so plotting
>>> just
>>> the 5-year average bias would give you sufficient information. You
>>>might
>>> want to take a quick glance at IPCC AR5 WG I, Ch. 9 [1] for some good
>>> examples.
>>> 
>>> Thanks,
>>> Alex
>>> 
>>> [1] -
>>> 
>>>http://www.climatechange2013.org/images/report/WG1AR5_Chapter09_FINAL.pd
>>>f
>>> 
>>> 
>>> On Wed, Jun 4, 2014 at 4:48 PM, Boustani, Maziyar (398F) <
>>> [email protected]<mailto:[email protected]>>
>>>wrote:
>>> 
>>>> Here is the attached [1].
>>>> 
>>>> [1]: http://oi58.tinypic.com/w7yo2q.jpg
>>>> 
>>>>  ŠŠŠŠŠŠŠŠ
>>>> Maziyar Boustani
>>>> Software Engineer - GIS Developer
>>>> Science Data Understanding Group
>>>> Jet Propulsion Laboratory, California Institute of Technology
>>>> 4800 Oak Grove Drive,
>>>> Pasadena, CA, 91109
>>>> [email protected]<mailto:[email protected]>
>>>> 
>>>> On Jun 4, 2014, at 3:35 PM, Loikith, Paul C (329C-Affiliate) wrote:
>>>> 
>>>> Hi Mazi,
>>>> 
>>>> This should be one plot total.  When you compute a bias,
>>>>conventionally
>>>> it's just one bias for the entire time period so there should be one
>>>> plot.
>>>> You could have multiple plots if you were computing the bias for all 4
>>>> seasons, but for annual there should only be one.
>>>> 
>>>> When you say you temporally regridded to 365 days, what do you mean by
>>>> this?  The model and obs data are monthly, correct?  So shouldn't you
>>>> just
>>>> be computing the mean difference between the obs and the model?
>>>> 
>>>> Please let me know if you need further clarification.
>>>> 
>>>> Thanks,
>>>> 
>>>> Paul
>>>> 
>>>> 
>>>> 
>>>>  From: <Boustani>, "Maziyar (398F)"
>>>><[email protected]<mailto:[email protected]>>
>>>> Date: Wednesday, June 4, 2014 3:12 PM
>>>> To: Paul Loikith
>>>><[email protected]<mailto:[email protected]>>,
>>>>"[email protected]<mailto:[email protected]>" <
>>>> [email protected]<mailto:[email protected]>>
>>>> Cc: "[email protected]<mailto:[email protected]>"
>>>><[email protected]<mailto:[email protected]>>
>>>> Subject: Model Observation Evaluation exmaple
>>>> 
>>>>  Hi Paul and Alex,
>>>> 
>>>> I ran a test code to evaluate one model [1] with one observation[2].
>>>> You
>>>> can find the result as attached.
>>>> This has been temporally regrided for 356 day, so we going to have 5
>>>> years
>>>> of data and that is why we have 5 plots.
>>>> Do you guys thinks this is correct to have one plot for each time or
>>>>it
>>>> should be one plot for entire time?
>>>> 
>>>> Metric = Bias
>>>> parameter_id = 38
>>>> dataset_id = 10
>>>> min_lat = 0
>>>> max_lat = 20
>>>> min_lon = 0
>>>> max_lon = 20
>>>> start_time = 2000-01-01 00:00:00
>>>> end_time = 2004-12-01 00:00:00
>>>> 
>>>> 
>>>> [1] : AFRICA_UQAM-CRCM5_CTL_ERAINT_MM_50km_1989-2008_tas.nc (variable
>>>>=
>>>> TAS)
>>>> [2] : CRU3.1 Daily-Mean Temperature (parmeter_id = 38)
>>>> 
>>>> <model_vs_obs_bias.png>
>>>> 
>>>>  ŠŠŠŠŠŠŠŠ
>>>> Maziyar Boustani
>>>> Software Engineer - GIS Developer
>>>> Science Data Understanding Group
>>>> Jet Propulsion Laboratory, California Institute of Technology
>>>> 4800 Oak Grove Drive,
>>>> Pasadena, CA, 91109
>>>> [email protected]<mailto:[email protected]>
>>>> 
>>>>  <model_vs_obs_bias.png>
>>>> 
>>>> 
>>>> 
>>> 
>>> 
>>> --
>>> Alex Goodman
>>> Graduate Research Assistant
>>> Department of Atmospheric Science
>>> Colorado State University
>> 
>> 
>> 
>> 
>> --
>> Alex Goodman
>> Graduate Research Assistant
>> Department of Atmospheric Science
>> Colorado State University
>> 
>

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