prysm-api 0.5.1

The API for PRoxY System Modeling (PRYSM)

prysm-api

The API for PRoxY System Modeling (PRYSM). Currently, it supports PSMs listed below:

• Ice-core d18O
• Tree-ring width with VSLite
• Tree-ring cellulose
• Tree MXD
• Coral d18O and Sr/Ca
• Speleothem d18O
• Varve thickness

How to install

Simply

pip install prysm-api LMRt  # LMRt provides many useful functions necessary for prysm-api

To use VS-Lite, in R

install.packages("devtools")
devtools::install_github("fzhu2e/VSLiteR")

Usage examples

• Calling VS-Lite

import prysm

res = prysm.forward(
    'prysm.vslite',                 # psm name
    lat_obs, lon_obs,               # lat/lon of the target location
    lat, lon, time,                 # dimension variables of the environmentals
    {                               # environmental variables:
        'tas': tas,                 # surface air temperature in (time, lat, lon) [K]
        'pr': pr,                   # precipitation rate in (time, lat, lon) [kg/m2/s]
    },
    T1=8, T2=23, M1=0.01, M2=0.05,  # PSM specific parameters
)

Here res is a dictionary that includes the pseudoproxy values and the corresponding timepoints, plus other output for diagnostics.

• Calling the PSM for ice core d18O

import prysm

res = prysm.forward(
    'prysm.ice.d18O',               # psm name
    lat_obs, lon_obs,               # lat/lon of the target location
    lat, lon, time,                 # dimension variables of the environmentals
    {                               # environmental variables:
        'tas': tas,                 # surface air temperature in (time, lat, lon) [K]
        'pr': pr,                   # precipitation rate in (time, lat, lon) [kg/m2/s]
        'psl': psl,                 # sea-level pressure in (time, lat, lon) [Pa]
        'd18Opr': d18Opr,           # precipitation d18O in (time, lat, lon) [permil]
    },
)

References

• Dee, S., J. Emile-Geay, M. N. Evans, A. Allam, E. J. Steig, and D. m. Thompson, 2015: PRYSM: An open-source framework for PRoxY System Modeling, with applications to oxygen-isotope systems. J. Adv. Model. Earth Syst., 7, 1220–1247, doi:10.1002/2015MS000447.
• Dee, S. G., N. J. Steiger, J. Emile-Geay, and G. J. Hakim, 2016: On the utility of proxy system models for estimating climate states over the common era. J. Adv. Model. Earth Syst., 8, 1164–1179, doi:10.1002/2016MS000677.
• Dee, S. G., L. A. Parsons, G. R. Loope, J. T. Overpeck, T. R. Ault, and J. Emile-Geay, 2017: Improved spectral comparisons of paleoclimate models and observations via proxy system modeling: Implications for multi-decadal variability. Earth and Planetary Science Letters, 476, 34–46, doi:10.1016/j.epsl.2017.07.036.
• Dee, S. G., J. M. Russell, C. Morrill, Z. Chen, and A. Neary, 2018: PRYSM v2.0: A Proxy System Model for Lacustrine Archives. Paleoceanography and Paleoclimatology, 33, 1250–1269, doi:10.1029/2018PA003413.

License

MIT License (see the details here)

How to cite

If you find this package useful and use it in your research, please cite it with DOI:

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