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Climatological numerical models (e.g., IGRF, IRI, MSIS, HWM93/07), commonly written in FORTRAN, are often used within the upper atmosphere research community for a wide variety of applications (e.g., initializing values in numerical models and for comparisons against measured data). Here we present pyglow, a Python module that includes wrappers for climatological models. In this way, the climatological models can be accessed in the high-level and scriptable Python programming language. This implementation provides quick access to each model under a common framework. Pyglow is open- sourced (https://github.com/timduly4/pyglow/) to encourage improvement and expansion of the code base. pyglow: Upper atmosphere climatological models in Python Timothy M. Duly [email protected] Daniel J. Fisher [email protected] University of Illinois at Urbana-Champaign Abstract High-Level Low-Level Fortran Execution pyglow CCMC web service f2py / gfortran IRI MSIS IGRF HWM93 HWM07 pyglow module Python Fortran Introduction Example Usage 1 # Example Python script using pyglow 2 # and its climatological models 3 # to plot profile of airglow emission. 4 # and electron density 5 # 6 from matplotlib.pyplot import * 7 import numpy as np 8 from datetime import datetime, timedelta 9 from pyglow.pyglow import Point 10 11 matplotlib.rcParams.update({ ’font.size’ : 16}) 12 13 # Setting lat, lon, and a range of altitudes 14 lat = 18.37 # Arecibo 15 lon = -66.62 16 alts = np.linspace(85,1000,500) 17 18 # set time (i.e., dn) 19 dn_lt = datetime(2012, 3, 22, 0, 0) 20 tz = np.ceil(lon/15.) 21 dn_ut = dn_lt - timedelta(hours=tz) 22 23 # airglow calculation using pyglow: 24 ag, ne = [], [] 25 for alt in alts: 26 pt = Point(dn_ut, lat, lon, alt) 27 28 pt.run_iri() 29 pt.run_msis() 30 pt.run_airglow() 31 32 ag.append(pt.ag6300) 33 ne.append(pt.ne) 34 35 # plot data: 36 figure(1, figsize=(7,8)); clf() 37 semilogy(ag, alts, ’-k’ , lw=4, label= ’$V_{630.0}$’ ) 38 grid() 39 ylim([alts[0],alts[-1]]) 40 the_yticks = np.arange(100,1001,100) 41 yticks(the_yticks,the_yticks) 42 xlabel( ’Volume Emission Rate [ph/cm$^3$/$s$]’ ) 43 ylabel( ’Altitude [km]’ ) 44 legend(loc= ’lower right’ ) 45 46 ax2 = gca().twiny() 47 ax2.semilogx(ne, alts, ’--b’ , lw=4, label= ’$n_e$’ ) 48 xlabel( ’Electron density [items/cm$^3$]’ ,color= ’blue’ ) 49 ax2.legend(loc= ’upper right’ ) 50 51 draw(); show() 52 savefig( ’../images/pyglow-example.png’ , dpi=200) pyglow is installed system-wide and can be imported in a script Instance of the Point class is instantiated (all inputs to the climatological models are a function of a time and a spatial location) Here two models are called (which are needed for the airglow calculation) Once the climatological values are executed, member data from the pt object are available In this example, profiles of the electron density and 630.0-nm airglow emission are produced in ~50 lines of code! Climatological Model Description Terms Modeled Reference IRI International Reference Ionosphere Plasma Bilitza and Reinisch [2008] MSIS Mass Spectrometer Incoherent Scatter Radar Neutral Picone [2002] HWM93/07 Horizontal Wind Model 1993 / 2007 Neutral Wind Hedin and Biondi [1996] IGRF International Geomagnetic Reference Field Magnetic Field Finlay et al. [2010] • There are primarily two different methods to access climatological models: compiling the FORTRAN code or using a web service provided by the Community Coordinated Modeling Center (CCMC) • Both offer various levels of computer architecture abstraction • In terms of abstraction level, pyglow is between these two, offering access to climatological models in the scriptable Python programming language • pyglow offers access to several climatological models for various upper atmosphere parameters • Future models can be easily implemented as they become available to the research community • f2py (available in numpy) is used as the “glue” between the pyglow module and the Fortran models • Access to models under common framework enables derived parameters to be calculated (e.g., airglow emission) and synergy between models (e.g., integrating electron densities along magnetic field line) • pyglow is used to calculate a dip angle contour map in conjunction with the Basemap package for producing high quality maps • Combining the climatological models and Basemap under a common framework provide quick development of results • Example generating many electron density profiles (from IRI) for both solar maximum (top) and solar minimum (bottom) • ~50 lines of code are used to generate this figure, all contained within one script • pyglow can also be used to easily plot solar index data • In addition to F10.7 and F10.7A values, Kp and Ap indices are provided in pyglow Additional Examples • pyglow can be used for comparison of climatological values against experimental data • In this example, monthly averaged HWM93/07 neutral winds are compared with Fabry-Perot interferometer measurements References Bilitza, D., and B. Reinisch (2008), International Reference Ionosphere 2007: Improvements and new parameters, Advances in Space Research, 42(4), 599–609, doi:10.1016/j.asr.2007.07.048. Finlay, C. C., S. Maus, C. D. Beggan, T. N. Bondar, A. Chambodut, T. a. Chernova, A. Chulliat, V. P. Golovkov, B. Hamilton, M. Hamoudi, R. Holme, G. Hulot, W. Kuang, B. Langlais, V. Lesur, F. J. Lowes, H. Luhr, S. Macmillan, M. Mandea, S. McLean, C. Manoj, M. Menvielle, I. Michaelis, N. Olsen, J. Rauberg, M. Rother, T. J. Sabaka, A. Tangborn, L. Tøffner Clausen, E. Thebault, a. W. P. Thomson, I. Wardinski, Z. Wei, and T. I. Zvereva (2010), International Geomagnetic Reference Field: the eleventh generation, Geophysical Journal International, 183(3), 1216–1230, doi:10.1111/j.1365-246X.2010.04804.x. Hedin, A., E. Fleming, A. Manson, F. Schmidlin, S. Avery, R. Clark, S. Franke, G. Fraser, T. Tsuda, F. Vial, and R. Vincent (1996), Empirical wind model for the upper, middle and lower atmosphere, Journal of Atmospheric and Terrestrial Physics, 58(13), 1421–1447, doi: 10.1016/0021-9169(95)00122-0. Picone, J. M. (2002), NRLMSISE-00 empirical model of the atmosphere: Statistical comparisons and scientific issues, Journal of Geophysical Research, 107 (A12), 1–16, doi: 10.1029/2002JA009430. Time is set for a single location
