classes and methods to calculate and plot analog composites from a paleoclimate proxy or an ensemble of paleoclimate proxies
paleopy is written in pure python, and can be installed by running
python setup.py install
in the top-level directory
The `scripts` folder contains two scripts illustrating respectively how `paleopy` processes a *proxy* (`proxy_oper.py`) and an *ensemble of proxies* (`ensemble_oper.py`) from user input passed to the command line.
- proxy_oper.py
→ ./proxy_oper.py --help
usage: proxy_oper.py [-h] [-dj DJSONS] [-pj PJSONS] [-pn PFNAME] [-o OPATH]
[-n SITENAME] [-t PROXY_TYPE] [-lon LON] [-lat LAT]
[-dset DATASET] [-var VARIABLE] [-s SEASON] [-val VALUE]
[-q QUALITATIVE] [-per PERIOD] [-clim CLIMATOLOGY]
[-an CALC_ANOMS] [-dt DETREND] [-a ASPECT] [-e ELEVATION]
[-dc DATING_CONVENTION] [-cal CALENDAR] [-ch CHRONOLOGY]
[-m MEASUREMENT]
optional arguments:
-h, --help show this help message and exit
-dj DJSONS, --djsons DJSONS
the path to the jsons files defining the paths and
parameters of each dataset
-pj PJSONS, --pjsons PJSONS
the path where to save the individual proxy json files
-pn PFNAME, --pfname PFNAME
the name of the JSON file containing the information
for a single proxy
-o OPATH, --opath OPATH
the path where to save the figures
-n SITENAME, --name SITENAME
the name of the site
-t PROXY_TYPE, --type PROXY_TYPE
the type of proxy (coral, Tree-ring, etc)
-lon LON, --longitude LON
the longitude (decimal degree) of the proxy site
-lat LAT, --latitude LAT
the latitude (decimal degree) of the proxy site
-dset DATASET, --dataset DATASET
the dataset to interrogate to draw the analog years
-var VARIABLE, --variable VARIABLE
the variable in the dataset to interrogate to draw the
analog years
-s SEASON, --season SEASON
the season to which the proxy is sensitive
-val VALUE, --value VALUE
the value for the proxy: can be either a float or a
string, if a string, must be in
['WB','B','N','A','WA'] and the `qualitative` flag
must be set to True
-q QUALITATIVE, --qualitative QUALITATIVE
a flag indicating whether the value passed (see above)
is qualitative or not, default to False: i.e.
interpret the value as a float
-per PERIOD, --period PERIOD
the period from which to draw the analog seasons
-clim CLIMATOLOGY, --climatology CLIMATOLOGY
the climatological period with respect to which the
anomalies are calculated
-an CALC_ANOMS, --calc_anoms CALC_ANOMS
True if the anomalies are calculated, False otherwise.
Default is True
-dt DETREND, --detrend DETREND
True if the time-series need detrended, False
otherwise. Default is True
-a ASPECT, --aspect ASPECT
the aspect (in degrees, from 0 to 360)
-e ELEVATION, --elevation ELEVATION
the elevation (in meters)
-dc DATING_CONVENTION, --dating DATING_CONVENTION
the dating convention
-cal CALENDAR, --calendar CALENDAR
the calendar year
-ch CHRONOLOGY, --chronology CHRONOLOGY
the chronology control (i.e. 14C, Historic,
Dendrochronology, etc)
-m MEASUREMENT, --measurement MEASUREMENT
the proxy measurement type (e.g. width for tree rings)
- ensemble_oper.py
→ ./ensemble_oper.py --help
usage: ensemble_oper.py [-h] [-dj DJSONS] [-j PJSONS] [-o OPATH] [-s SEASON]
optional arguments:
-h, --help show this help message and exit
-dj DJSONS, --djsons DJSONS
the path to the jsons files defining the paths and
parameters of each dataset
-j PJSONS, --pjsons PJSONS
the directory containing the proxy json files
-o OPATH, --opath OPATH
the directory in which to save the figures
-s SEASON, --season SEASON
the season to consider: will be checked against the
individual proxies seasons
In the notebooks folder, you will find 4 Jupyter notebooks:
-
proxy.ipynbillustrates how aproxy(an individual proxy) class is instantiated and how the methods are called to process it, including the reconstruction of climate anomalies using the analog approach -
ensemble.ipynbillustrates how anensemble(i.e. a collection of proxies) class is instantiated, then how ones reconstructs climate anomalies using a network of proxies -
WR.ipynbillustrates the reconstruction of Weather Regimes (WR) frequency anomalies from an instance of anensembleclass -
indices.ipynbillustrates the reconstruction of anomalies for a set of climate indices (currently the SOI, NINO 3.4 SSTs, the SAM index and the IOD index)