Re: Model Observation Evaluation exmaple

[Lee, Kyo (329C-Affiliate)]

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) 
<maziyar.boust...@jpl.nasa.gov> 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
> maziyar.boust...@jpl.nasa.gov<mailto:maziyar.boust...@jpl.nasa.gov>
> 
> 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 
> <alex.good...@colostate.edu<mailto:alex.good...@colostate.edu>>
> Date: Wednesday, June 4, 2014 4:25 PM
> To: "dev@climate.apache.org<mailto:dev@climate.apache.org>" 
> <dev@climate.apache.org<mailto:dev@climate.apache.org>>
> Cc: "Boustani, Maziyar (398F)" 
> <maziyar.boust...@jpl.nasa.gov<mailto:maziyar.boust...@jpl.nasa.gov>>, Paul 
> Loikith <paul.c.loik...@jpl.nasa.gov<mailto:paul.c.loik...@jpl.nasa.gov>>
> 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) 
> <chris.a.mattm...@jpl.nasa.gov<mailto:chris.a.mattm...@jpl.nasa.gov>> 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: chris.a.mattm...@nasa.gov<mailto:chris.a.mattm...@nasa.gov>
> 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 
> <alex.good...@colostate.edu<mailto:alex.good...@colostate.edu>>
> Reply-To: "dev@climate.apache.org<mailto:dev@climate.apache.org>" 
> <dev@climate.apache.org<mailto:dev@climate.apache.org>>
> Date: Wednesday, June 4, 2014 3:53 PM
> To: "Boustani, Maziyar (398F)" 
> <maziyar.boust...@jpl.nasa.gov<mailto:maziyar.boust...@jpl.nasa.gov>>
> Cc: "Loikith, Paul C (329C-Affiliate)" 
> <paul.c.loik...@jpl.nasa.gov<mailto:paul.c.loik...@jpl.nasa.gov>>,
> "dev@climate.apache.org<mailto:dev@climate.apache.org>" 
> <dev@climate.apache.org<mailto:dev@climate.apache.org>>
> 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.pdf
>> 
>> 
>> On Wed, Jun 4, 2014 at 4:48 PM, Boustani, Maziyar (398F) <
>> maziyar.boust...@jpl.nasa.gov<mailto:maziyar.boust...@jpl.nasa.gov>> 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
>>> maziyar.boust...@jpl.nasa.gov<mailto:maziyar.boust...@jpl.nasa.gov>
>>> 
>>> 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)" 
>>> <maziyar.boust...@jpl.nasa.gov<mailto:maziyar.boust...@jpl.nasa.gov>>
>>> Date: Wednesday, June 4, 2014 3:12 PM
>>> To: Paul Loikith 
>>> <paul.c.loik...@jpl.nasa.gov<mailto:paul.c.loik...@jpl.nasa.gov>>, 
>>> "good...@apache.org<mailto:good...@apache.org>" <
>>> good...@apache.org<mailto:good...@apache.org>>
>>> Cc: "dev@climate.apache.org<mailto:dev@climate.apache.org>" 
>>> <dev@climate.apache.org<mailto:dev@climate.apache.org>>
>>> 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
>>> maziyar.boust...@jpl.nasa.gov<mailto:maziyar.boust...@jpl.nasa.gov>
>>> 
>>>  <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
>