ATMOS/pyatmos/msise/nrlmsise00.py
2020-03-30 11:07:55 +08:00

1056 lines
38 KiB
Python

# -------------------------------------------------------------------- #
# ------------------- nrlmisise-00 model 2001 -------------------- #
# -------------------------------------------------------------------- #
'''
pyatmos nrlmsise00
This submodule defines the following functions:
nrlmsis00_data - Read the data block from nrlmsis00_data.npz
tselec -
glatf -
ccor -
ccor2 -
scalh -
dnet -
zeta -
densm -
densu -
g0
sumex
sg0
lengendre
globe7
glob7s
gtd7
dtd7d
gts7
nrlmsise00
'''
import numpy as np
from astropy.time import Time
from scipy.interpolate import CubicSpline
from pyshtools.legendre import PLegendreA,PlmIndex
import pkg_resources
from .spaceweather import get_sw
from .utils import wraplon,hms2s,hms2h
# ======================== read data block ========================== #
def nrlmsis00_data():
'''
Read the data block from nrlmsis00_data.npz
Usage: pt,pd,ps,pdl,ptm,pdm,ptl,pma,sam,pavgm = nrlmsis00_data()
Inputs:
None
Outputs:
pt: [float array] TEMPERATURE
pd: [2d float array] DENSITY of HE, O, N2, Total mass, O2, AR, H, N, HOT O
ps: [float array] S PARAM
pdl: [2d float array] TURBO
ptm: [float array]
pdm: [2d float array]
ptl: [2d float array]
pma: [2d float array]
sam: [float array] SEMIANNUAL MULT SAM
pavgm: [float array] MIDDLE ATMOSPHERE AVERAGES
'''
data_path = pkg_resources.resource_filename('pyatmos', 'data/')
data = np.load(data_path+'nrlmsis00_data.npz')
pt,pd,ps,pdl = data['pt'],data['pd'],data['ps'],data['pdl']
ptm,pdm,ptl,pma = data['ptm'],data['pdm'],data['ptl'],data['pma']
sam,pavgm = data['sam'],data['pavgm']
return pt,pd,ps,pdl,ptm,pdm,ptl,pma,sam,pavgm
# ============================= tselec ============================== #
def tselec(switches):
# len(switches) is equal to 23
flags = {'sw':np.zeros(23),'swc':np.zeros(23)}
for i in range(23):
if i != 8:
if switches[i] == 1:
flags['sw'][i] = 1
else:
flags['sw'][i] = 0
if switches[i] > 0:
flags['swc'][i] = 1
else:
flags['swc'][i] = 0
else:
flags['sw'][i] = switches[i]
flags['swc'][i] = switches[i]
return flags
# ============================= glatf =============================== #
def glatf(lat):
c2 = np.cos(2*np.deg2rad(lat))
gv = 980.616*(1 - 0.0026373*c2)
reff = 2*gv/(3.085462E-6 + 2.27E-9*c2)*1E-5
return gv,reff
# ============================= ccor ================================ #
def ccor(alt,r,h1,zh):
'''
Chemistry/dissociation correction for msis models
alt - altitude
r - target ratio
h1 - transition scale length
zh - altitude of 1/2 R
'''
e = (alt - zh)/h1
if e > 70:
return 1
elif e < -70:
return np.exp(r)
else:
return np.exp(r/(1 + np.exp(e)))
# ============================== ccor2 ============================== #
def ccor2(alt,r,h1,zh,h2):
'''
Chemistry/dissociation correction for msis models
alt - altitude
r - target ratio
f1 - transition scale length 1
zh - altitude of 1/2 R
h2 - transition scale length 2
'''
e1 = (alt - zh)/h1
e2 = (alt - zh)/h2
if e1 > 70 or e2 > 70:
return 1
if e1 < -70 and e2 < -70:
return np.exp(r)
ex1,ex2 = np.exp([e1,e2])
ccor2v = r/(1 + 0.5*(ex1 + ex2))
return np.exp(ccor2v)
# =============================== scalh ============================= #
def scalh(alt,xm,temp,gsurf,re):
rgas = 831.4
g = rgas*temp/(gsurf/(1 + alt/re)**2*xm)
return g
# ================================ dnet ============================= #
def dnet(dd,dm,zhm,xmm,xm):
'''
Turbopause correction for msis models
Root mean density
dd - diffusive density
dm - full mixed density
zhm - transition scale length
xmm - full mixed molecular weight
xm - species molecular weight
dnet - combined density
'''
a = zhm/(xmm - xm)
if not (dm > 0 and dd > 0):
print('dnet log error {0:.1f} {1:.1f} {2:.1f}'.format(dm,dd,xm))
if dd == 0 and dm == 0: dd = 1
if dm == 0: return dd
if dd == 0: return dm
ylog = a*np.log(dm/dd)
if ylog < -10: return dd
if ylog > 10: return dm
a = dd*(1 + np.exp(ylog))**(1/a)
return a
# ================================ zeta ============================= #
def zeta(zz,zl,re):
return (zz - zl)*(re + zl)/(re + zz)
# =============================== densm ============================= #
def densm(alt, d0, xm, tz, zn3, tn3, tgn3, zn2, tn2, tgn2,gsurf,re):
# Calculate Temperature and Density Profiles for lower atmos.
# call zeta
rgas = 831.4
densm_tmp = d0
tz_tmp = tz
mn3,mn2 = len(zn3),len(zn2)
if alt > zn2[0]:
if xm == 0:
densm_tmp = tz
return densm_tmp,tz_tmp
else:
densm_tmp = d0
return densm_tmp,tz_tmp
# stratosphere/mesosphere temperature
if alt > zn2[mn2-1]:
z = alt
else:
z = zn2[mn2-1]
mn = mn2
xs,ys = [np.zeros(mn) for i in range(2)]
z1,z2 = zn2[0],zn2[mn-1]
t1,t2=tn2[0],tn2[mn-1]
zg,zgdif = zeta(z,z1,re),zeta(z2,z1,re)
# set up spline nodes
for k in range(mn):
xs[k] = zeta(zn2[k],z1,re)/zgdif
ys[k] = 1/tn2[k]
yd1 = -tgn2[0]/t1**2*zgdif
yd2 = -tgn2[1]/t2**2*zgdif*((re + z2)/(re + z1))**2
# calculate spline coefficients
cs = CubicSpline(xs,ys,bc_type=((1,yd1),(1,yd2)))
x = zg/zgdif
y = cs(x)
# temperature at altitude
tz_tmp = 1/y
if xm != 0:
# calaculate stratosphere / mesospehere density
glb = gsurf/(1 + z1/re)**2
gamm = xm*glb*zgdif/rgas
# Integrate temperature profile
yi = cs.integrate(xs[0],x)
expl = gamm*yi
if expl > 50:
expl = 50
# Density at altitude
densm_tmp = densm_tmp*(t1/tz_tmp)*np.exp(-expl)
if alt > zn3[0]:
if xm == 0:
densm_tmp = tz_tmp
return densm_tmp,tz_tmp
else:
return densm_tmp,tz_tmp
# troposhere / stratosphere temperature
z = alt
mn = mn3
xs,ys = [np.zeros(mn) for i in range(2)]
z1,z2 = zn3[0],zn3[mn-1]
t1,t2 = tn3[0],tn3[mn-1]
zg,zgdif = zeta(z,z1,re),zeta(z2,z1,re)
# set up spline nodes
for k in range(mn):
xs[k] = zeta(zn3[k],z1,re)/zgdif
ys[k] = 1/tn3[k]
yd1 = -tgn3[0]/t1**2*zgdif
yd2 = -tgn3[1]/t2**2*zgdif*((re+z2)/(re+z1))**2
# calculate spline coefficients
cs = CubicSpline(xs,ys,bc_type=((1,yd1),(1,yd2)))
x = zg/zgdif
y = cs(x)
# temperature at altitude
tz_tmp = 1/y
if xm != 0:
# calaculate tropospheric / stratosphere density
glb = gsurf/(1 + z1/re)**2
gamm = xm*glb*zgdif/rgas
# Integrate temperature profile
yi = cs.integrate(xs[0],x)
expl = gamm*yi
if expl > 50: expl = 50
# Density at altitude
densm_tmp = densm_tmp*(t1/tz_tmp)*np.exp(-expl)
if xm == 0:
densm_tmp = tz_tmp
return densm_tmp,tz_tmp
else:
return densm_tmp,tz_tmp
# =============================== densu ============================= #
def densu (alt,dlb,tinf,tlb,xm,alpha,tz,zlb,s2,zn1,tn1,tgn1,gsurf,re):
# Calculate Temperature and Density Profiles for MSIS models
# New lower thermo polynomial
# call: zeta,
rgas = 831.4
densu_tmp = 1
mn1 = len(zn1)
# joining altitudes of Bates and spline
za = zn1[0]
if alt > za:
z = alt
else:
z = za
# geopotential altitude difference from ZLB
zg2 = zeta(z,zlb,re)
# Bates temperature
tt = tinf - (tinf - tlb)*np.exp(-s2*zg2)
ta = tz = tt
densu_tmp = tz_tmp = tz
if alt < za:
# calculate temperature below ZA
# temperature gradient at ZA from Bates profile
dta = (tinf - ta)*s2*((re + zlb)/(re + za))**2
tgn1[0],tn1[0] = dta,ta
if alt > zn1[mn1-1]:
z = alt
else:
z = zn1[mn1-1]
mn = mn1
xs,ys = [np.zeros(mn) for i in range(2)]
z1,z2 = zn1[0],zn1[mn-1]
t1,t2 = tn1[0],tn1[mn-1]
# geopotental difference from z1
zg,zgdif = zeta(z,z1,re),zeta(z2,z1,re)
# set up spline nodes
for k in range(mn):
xs[k] = zeta(zn1[k],z1,re)/zgdif
ys[k] = 1/tn1[k]
# end node derivatives
yd1 = -tgn1[0]/t1**2*zgdif
yd2 = -tgn1[1]/t2**2*zgdif*((re + z2)/(re + z1))**2
# calculate spline coefficients
cs = CubicSpline(xs,ys,bc_type=((1,yd1),(1,yd2)))
x = zg/zgdif
y = cs(x)
# temperature at altitude
tz_tmp = 1/y
densu_tmp = tz_tmp
if xm == 0: return densu_tmp,tz_tmp
# calculate density above za
glb = gsurf/(1 + zlb/re)**2
gamma = xm*glb/(s2*rgas*tinf)
expl = np.exp(-s2*gamma*zg2)
if expl > 50: expl = 50
if tt <= 0: expl = 50
# density at altitude
densa = dlb*(tlb/tt)**(1 + alpha + gamma)*expl
densu_tmp = densa
if alt >= za: return densu_tmp,tz_tmp
# calculate density below za
glb = gsurf/(1 + z1/re)**2
gamm = xm*glb*zgdif/rgas
# integrate spline temperatures
yi = cs.integrate(xs[0],x)
expl = gamm*yi
if expl > 50: expl = 50
if tz_tmp <= 0: expl = 50
# density at altitude
densu_tmp = densu_tmp*(t1/tz_tmp)**(1 + alpha)*np.exp(-expl)
return densu_tmp,tz_tmp
# =============== 3hr magnetic activity functions =================== #
# Eq. A24d
def g0(a,p):
return (a - 4 + (p[25] - 1)*(a - 4 + (np.exp(-np.abs(p[24])*(a - 4)) - 1) / np.abs(p[24])))
# Eq. A24c
def sumex(ex):
return (1 + (1 - ex**19)/(1 - ex)*ex**0.5)
# Eq. A24a
def sg0(ex,p,ap):
# call sumex, g0
return (g0(ap[1],p) + g0(ap[2],p)*ex + g0(ap[3],p)*ex**2 + \
g0(ap[4],p)*ex**3 + (g0(ap[5],p)*ex**4 + \
g0(ap[6],p)*ex**12)*(1-ex**8)/(1-ex))/sumex(ex)
# ================== Associated Legendre polynomials ================ #
def lengendre(g_lat,lmax = 8):
# Index of PLegendreA_x can be calculated by PlmIndex(l,m)
x = np.sin(np.deg2rad(g_lat))
PLegendreA_x = PLegendreA(lmax,x)
return PLegendreA_x
# =============================== globe7 ============================ #
def globe7(p,inputp,flags):
# calculate G(L) function
# Upper Thermosphere Parameters
# call: lengendre,sg0
t = np.zeros(15)
sr = 7.2722E-5
dr = 1.72142E-2
hr = 0.2618
apdf = 0
apt = np.zeros(4)
tloc = inputp['lst']
if not (flags['sw'][6]==0 and flags['sw'][7]==0 and flags['sw'][13]==0):
stloc,ctloc = np.sin(hr*tloc),np.cos(hr*tloc)
s2tloc,c2tloc = np.sin(2*hr*tloc),np.cos(2*hr*tloc)
s3tloc,c3tloc = np.sin(3*hr*tloc),np.cos(3*hr*tloc)
cd32 = np.cos(dr*(inputp['doy'] - p[31]))
cd18 = np.cos(2*dr*(inputp['doy'] - p[17]))
cd14 = np.cos(dr*(inputp['doy'] - p[13]))
cd39 = np.cos(2*dr*(inputp['doy'] - p[38]))
# F10.7 effect
df = inputp['f107'] - inputp['f107A']
dfa = inputp['f107A'] - 150
t[0] = p[19]*df*(1 + p[59]*dfa) + p[20]*df**2 + p[21]*dfa + p[29]*dfa**2
f1 = 1 + (p[47]*dfa + p[19]*df + p[20]*df**2)*flags['swc'][0]
f2 = 1 + (p[49]*dfa + p[19]*df + p[20]*df**2)*flags['swc'][0]
plg = lengendre(inputp['g_lat'])
# time independent
t[1] = p[1]*plg[3] + p[2]*plg[10] + p[22]*plg[21] + p[14]*plg[3]*dfa*flags['swc'][0] + p[26]*plg[1]
# symmetrical annual
t[2] = p[18]*cd32
# symmetrical semiannual
t[3] = (p[15] + p[16]*plg[3])*cd18
# asymmetrical annual
t[4] = f1*(p[9]*plg[1] + p[10]*plg[6])*cd14
# asymmetrical semiannual
t[5] = p[37]*plg[1]*cd39
# diurnal
if flags['sw'][6]:
t71 = p[11]*plg[4]*cd14*flags['swc'][4]
t72 = p[12]*plg[4]*cd14*flags['swc'][4]
t[6] = f2*((p[3]*plg[2] + p[4]*plg[7] + p[27]*plg[16] + t71) * ctloc + (p[6]*plg[2] + p[7]*plg[7] + p[28]*plg[16] + t72)*stloc)
# semiannual
if flags['sw'][7]:
t81 = (p[23]*plg[8] + p[35]*plg[17])*cd14*flags['swc'][4]
t82 = (p[33]*plg[8] + p[36]*plg[17])*cd14*flags['swc'][4]
t[7] = f2*((p[5]*plg[5] + p[41]*plg[12] + t81)*c2tloc +(p[8]*plg[5] + p[42]*plg[12] + t82)*s2tloc)
# terdiurnal
if flags['sw'][13]:
t[13] = f2*((p[39]*plg[9] + (p[93]*plg[13] + p[46]*plg[24])*cd14*flags['swc'][4])*s3tloc + (p[40]*plg[9]+(p[94]*plg[13] + p[48]*plg[24])*cd14*flags['swc'][4])*c3tloc)
# magnetic activity based on daily ap
if flags['sw'][8] == -1:
ap = inputp['ap_a']
if p[51]!= 0:
exp1 = np.exp(-10800*np.abs(p[51])/(1 + p[138]*(45 - np.abs(inputp['g_lat']))))
if exp1 > 0.99999: exp1 = 0.99999
if p[24] < 1E-4: p[24] = 1E-4
apt[0] = sg0(exp1,p,ap)
# apt[1] = sg2(exp1,p,ap)
# apt[2] = sg0(exp2,p,ap)
# apt[3] = sg2(exp2,p,ap)
if flags['sw'][8]:
t[8] = apt[0]*(p[50] + p[96]*plg[3] + p[54]*plg[10] + \
(p[125]*plg[1] + p[126]*plg[6] + p[127]*plg[15])*cd14*flags['swc'][4] + \
(p[128]*plg[2] + p[129]*plg[7] + p[130]*plg[16])*flags['swc'][6]*np.cos(hr*(tloc - p[131])))
else:
apd = inputp['ap'] - 4
p44 = p[43]
p45 = p[44]
if p44 < 0: p44 = 1E-5
apdf = apd + (p45 - 1)*(apd + (np.exp(-p44*apd) - 1)/p44)
if flags['sw'][8]:
t[8]=apdf*(p[32] + p[45]*plg[3] + p[34]*plg[10] + \
(p[100]*plg[1] + p[101]*plg[6] + p[102]*plg[15])*cd14*flags['swc'][4] +
(p[121]*plg[2] + p[122]*plg[7] + p[123]*plg[16])*flags['swc'][6]*np.cos(hr*(tloc - p[124])))
if flags['sw'][9] and inputp['g_lon'] > -1000:
# longitudinal
if flags['sw'][10]:
t[10] = (1 + p[80]*dfa*flags['swc'][0])*((p[64]*plg[4] + p[65]*plg[11] + p[66]*plg[22]\
+ p[103]*plg[2] + p[104]*plg[7] + p[105]*plg[16]\
+ flags['swc'][4]*(p[109]*plg[2] + p[110]*plg[7] + p[111]*plg[16])*cd14)*np.cos(np.deg2rad(inputp['g_lon'])) \
+(p[90]*plg[4]+p[91]*plg[11]+p[92]*plg[22] + p[106]*plg[2]+p[107]*plg[7]+p[108]*plg[16]\
+ flags['swc'][4]*(p[112]*plg[2] + p[113]*plg[7] + p[114]*plg[16])*cd14)*np.sin(np.deg2rad(inputp['g_lon'])))
# ut and mixed ut, longitude
if flags['sw'][11]:
t[11]=(1 + p[95]*plg[1])*(1 + p[81]*dfa*flags['swc'][0])*\
(1 + p[119]*plg[1]*flags['swc'][4]*cd14)*\
((p[68]*plg[1] + p[69]*plg[6] + p[70]*plg[15])*np.cos(sr*(inputp['sec'] - p[71])))
t[11] += flags['swc'][10]*(p[76]*plg[8] + p[77]*plg[17] + p[78]*plg[30])*\
np.cos(sr*(inputp['sec'] - p[79]) + 2*np.deg2rad(inputp['g_lon']))*(1 + p[137]*dfa*flags['swc'][0])
# ut, longitude magnetic activity
if flags['sw'][10]:
if flags['sw'][8] == -1:
if p[51]:
t[12] = apt[0]*flags['swc'][10]*(1 + p[132]*plg[1])*\
((p[52]*plg[4] + p[98]*plg[11] + p[67]*plg[22])* np.cos(np.deg2rad(inputp['g_lon'] - p[97])))\
+ apt[0]*flags['swc'][10]*flags['swc'][4]*(p[133]*plg[2] + p[134]*plg[7] + p[135]*plg[16])*\
cd14*np.cos(np.deg2rad(inputp['g_lon'] - p[136])) + apt[0]*flags['swc'][11]* \
(p[55]*plg[1] + p[56]*plg[6] + p[57]*plg[15])*np.cos(sr*(inputp['sec'] - p[58]))
else:
t[12] = apdf*flags['swc'][10]*(1 + p[120]*plg[1])*((p[60]*plg[4] + p[61]*plg[11] + p[62]*plg[22])*\
np.cos(np.deg2rad(inputp['g_lon']-p[63])))+apdf*flags['swc'][10]*flags['swc'][4]* \
(p[115]*plg[2] + p[116]*plg[7] + p[117]*plg[16])* \
cd14*np.cos(np.deg2rad(inputp['g_lon'] - p[118])) \
+ apdf*flags['swc'][11]*(p[83]*plg[1] + p[84]*plg[6] + p[85]*plg[15])* np.cos(sr*(inputp['sec'] - p[75]))
# parms not used: 82, 89, 99, 139-149
tinf = p[30]
for i in range(14):
tinf = tinf + np.abs(flags['sw'][i])*t[i]
return tinf,[dfa,plg,ctloc,stloc,c2tloc,s2tloc,s3tloc,c3tloc,apdf,apt]
# =============================== glob7s ============================ #
def glob7s(p,inputp,flags,varli):
# version of globe for lower atmosphere 10/26/99
# call: lengendre,sg0
pset = 2
t = np.zeros(14)
dr = 1.72142E-2
[dfa,plg,ctloc,stloc,c2tloc,s2tloc,s3tloc,c3tloc,apdf,apt] = varli
# confirm parameter set
if p[99] == 0: p[99] = pset
if p[99] != pset:
print("Wrong parameter set for glob7s")
return -1
for j in range(14):
t[j] = 0
cd32 = np.cos(dr*(inputp['doy'] - p[31]))
cd18 = np.cos(2*dr*(inputp['doy'] - p[17]))
cd14 = np.cos(dr*(inputp['doy'] - p[13]))
cd39 = np.cos(2*dr*(inputp['doy'] - p[38]))
# F10.7
t[0] = p[21]*dfa
# time independent
t[1] = p[1]*plg[3] + p[2]*plg[10] + p[22]*plg[21] + p[26]*plg[1] + p[14]*plg[6] + p[59]*plg[15]
# symmetrical annual
t[2] = (p[18] + p[47]*plg[3] + p[29]*plg[10])*cd32
# symmetrical semiannual
t[3] = (p[15] + p[16]*plg[3] + p[30]*plg[10])*cd18
# asymmetrical annual
t[4] = (p[9]*plg[1] + p[10]*plg[6] + p[20]*plg[15])*cd14
# asymmetrical semiannual
t[5] = p[37]*plg[1]*cd39;
# diurnal
if flags['sw'][6]:
t71 = p[11]*plg[4]*cd14*flags['swc'][4]
t72 = p[12]*plg[4]*cd14*flags['swc'][4]
t[6] = ((p[3]*plg[2] + p[4]*plg[7] + t71)*ctloc + (p[6]*plg[2] + p[7]*plg[7] + t72)*stloc)
# semidiurnal
if flags['sw'][7]:
t81 = (p[23]*plg[8] + p[35]*plg[17])*cd14*flags['swc'][4]
t82 = (p[33]*plg[8] + p[36]*plg[17])*cd14*flags['swc'][4]
t[7] = ((p[5]*plg[5] + p[41]*plg[12] + t81)*c2tloc + (p[8]*plg[5] + p[42]*plg[12] + t82)*s2tloc)
# terdiurnal
if flags['sw'][13]:
t[13] = p[39]*plg[9]*s3tloc + p[40]*plg[9]*c3tloc
# magnetic activity
if flags['sw'][8]:
if flags['sw'][8]==1:
t[8] = apdf * (p[32] + p[45]*plg[3]*flags['swc'][1])
if flags['sw'][8]==-1:
t[8]=(p[50]*apt[0] + p[96]*plg[3]*apt[0]*flags['swc'][1])
# longitudinal
if not (flags['sw'][9]==0 or flags['sw'][10]==0 or inputp['g_lon']<=-1000):
t[10] = (1 + plg[1]*(p[80]*flags['swc'][4]*np.cos(dr*(inputp['doy'] - p[81]))\
+ p[85]*flags['swc'][5]*np.cos(2*dr*(inputp['doy'] - p[86])))\
+ p[83]*flags['swc'][2]*np.cos(dr*(inputp['doy'] - p[84]))\
+ p[87]*flags['swc'][3]*np.cos(2*dr*(inputp['doy'] - p[88])))\
*((p[64]*plg[4] + p[65]*plg[11] + p[66]*plg[22]\
+ p[74]*plg[2] + p[75]*plg[7] + p[76]*plg[16])*np.cos(np.deg2rad(inputp['g_lon']))\
+ (p[90]*plg[4] + p[91]*plg[11] + p[92]*plg[22]\
+ p[77]*plg[2] + p[78]*plg[7] + p[79]*plg[16])*np.sin(np.deg2rad(inputp['g_lon'])))
tt = 0
for i in range(14):
tt += np.abs(flags['sw'][i])*t[i]
return tt
# =============================== gtd7 ============================== #
def gtd7(inputp,switches):
tz = 0
zn3 = np.array([32.5,20.0,15.0,10.0,0.0])
zn2 = np.array([72.5,55.0,45.0,32.5])
zmix= 62.5
output = {'d':{'He':0,'O':0,'N2':0,'O2':0,'AR':0,'RHO':0,'H':0,'N':0,'ANM O':0},\
't':{'TINF':0,'TG':0}}
flags = tselec(switches)
# Latitude variation of gravity (none for sw[1]=0)
xlat = inputp['g_lat']
if flags['sw'][1]==0: xlat = 45
gsurf,re = glatf(xlat)
pt,pd,ps,pdl,ptm,pdm,ptl,pma,sam,pavgm = nrlmsis00_data()
xmm = pdm[2,4]
# thermosphere/mesosphere (above zn2[0])
if inputp['alt'] > zn2[0]:
altt = inputp['alt']
else:
altt = zn2[0]
tmp = inputp['alt']
inputp['alt'] = altt
soutput,dm28,[meso_tn1,meso_tn2,meso_tn3,meso_tgn1,meso_tgn2,meso_tgn3],[dfa,plg,ctloc,stloc,c2tloc,s2tloc,s3tloc,c3tloc,apdf,apt] = gts7(inputp,flags,gsurf,re)
altt = inputp['alt']
inputp['alt'] = tmp
# metric adjustment
dm28m = dm28*1E6
output['t']['TINF'] = soutput['t']['TINF']
output['t']['TG'] = soutput['t']['TG']
if inputp['alt'] >= zn2[0]:
output['d'] = soutput['d']
return output
# lower mesosphere/upper stratosphere (between zn3[0] and zn2[0])
# Temperature at nodes and gradients at end nodes
# Inverse temperature a linear function of spherical harmonics
varli = [dfa,plg,ctloc,stloc,c2tloc,s2tloc,s3tloc,c3tloc,apdf,apt]
meso_tgn2[0] = meso_tgn1[1]
meso_tn2[0] = meso_tn1[4]
meso_tn2[1] = pma[0,0]*pavgm[0]/(1-flags['sw'][19]*glob7s(pma[0], inputp, flags,varli))
meso_tn2[2] = pma[1,0]*pavgm[1]/(1-flags['sw'][19]*glob7s(pma[1], inputp, flags,varli))
meso_tn2[3] = pma[2,0]*pavgm[2]/(1-flags['sw'][19]*flags['sw'][21]*glob7s(pma[2], inputp, flags,varli))
meso_tgn2[1] = pavgm[8]*pma[9,0]*(1+flags['sw'][19]*flags['sw'][21]*glob7s(pma[9], inputp, flags,varli))*meso_tn2[3]*meso_tn2[3]/(pma[2,0]*pavgm[2])**2
meso_tn3[0] = meso_tn2[3]
if inputp['alt'] <= zn3[0]:
# lower stratosphere and troposphere (below zn3[0])
# Temperature at nodes and gradients at end nodes
# Inverse temperature a linear function of spherical harmonics
meso_tgn3[0] = meso_tgn2[1]
meso_tn3[1] = pma[3,0]*pavgm[3]/(1-flags['sw'][21]*glob7s(pma[3], inputp, flags,varli))
meso_tn3[2] = pma[4,0]*pavgm[4]/(1-flags['sw'][21]*glob7s(pma[4], inputp, flags,varli))
meso_tn3[3] = pma[5,0]*pavgm[5]/(1-flags['sw'][21]*glob7s(pma[5], inputp, flags,varli))
meso_tn3[4] = pma[6,0]*pavgm[6]/(1-flags['sw'][21]*glob7s(pma[6], inputp, flags,varli))
meso_tgn3[1] = pma[7,0]*pavgm[7]*(1+flags['sw'][21]*glob7s(pma[7], inputp, flags,varli)) *meso_tn3[4]*meso_tn3[4]/(pma[6,0]*pavgm[6])**2
# linear transition to full mixing below znz[0]
dmc = 0
if inputp['alt'] > zmix:
dmc = 1 - (zn2[0]-inputp['alt'])/(zn2[0] - zmix)
dz28 = soutput['d']['N2']
# N2 density
dmr = soutput['d']['N2'] / dm28m - 1
output['d']['N2'],tz = densm(inputp['alt'],dm28m,xmm, tz, zn3, meso_tn3, meso_tgn3, zn2, meso_tn2, meso_tgn2,gsurf,re)
output['d']['N2'] = output['d']['N2'] * (1 + dmr*dmc)
# HE density
dmr = soutput['d']['He'] / (dz28 * pdm[0,1]) - 1
output['d']['He'] = output['d']['N2'] * pdm[0,1] * (1 + dmr*dmc)
# O density
output['d']['O'] = 0
output['d']['ANM O'] = 0
# O2 density
dmr = soutput['d']['O2'] / (dz28 * pdm[3,1]) - 1
output['d']['O2'] = output['d']['N2'] * pdm[3,1] * (1 + dmr*dmc)
# AR density
dmr = soutput['d']['AR'] / (dz28 * pdm[4,1]) - 1
output['d']['AR'] = output['d']['N2'] * pdm[4,1] * (1 + dmr*dmc)
# Hydrogen density
output['d']['H'] = 0
# Atomic nitrogen density
output['d']['N'] = 0
# Total mass density
output['d']['RHO'] = 1.66E-24 * (4 * output['d']['He'] + 16 * output['d']['O'] + 28 * output['d']['N2']\
+ 32 * output['d']['O2'] + 40 * output['d']['AR'] + output['d']['H'] + 14 * output['d']['N'])
output['d']['RHO'] = output['d']['RHO']/1000
# temperature at altitude
dd,tz = densm(inputp['alt'], 1, 0, tz, zn3, meso_tn3, meso_tgn3, zn2, meso_tn2, meso_tgn2,gsurf,re)
output['t']['TG'] = tz
return output
# =============================== gtd7d ============================= #
def gtd7d(inputp, flags):
output = gtd7(inputp, flags)
output['d']['RHO'] = 1.66E-24 * (4 * output['d']['He'] + 16 * output['d']['O'] + 28 * output['d']['N2']\
+ 32 * output['d']['O2'] + 40 * output['d']['AR'] + output['d']['H'] + 14 * output['d']['N'] + 16 * output['d']['ANM O'])
output['d']['RHO'] = output['d']['RHO']/1000
return output
# =============================== gts7 ------------------------------ #
def gts7(inputp,flags,gsurf,re):
# Thermospheric portion of NRLMSISE-00
# See gtd7 for more extensive comments
# alt > 72.5 km!
# call: nrlmsis00_data, globe7, densu
output = {'d':{'He':0,'O':0,'N2':0,'O2':0,'AR':0,'RHO':0,'H':0,'N':0,'ANM O':0},\
't':{'TINF':0,'TG':0}}
tz = 0
dm28 = 0
meso_tn1,meso_tn3 = [np.zeros(5) for i in range(2)]
meso_tn2 = np.zeros(4)
meso_tgn1,meso_tgn2,meso_tgn3 = [np.zeros(2) for i in range(3)]
zn1 = np.array([120.0, 110.0, 100.0, 90.0, 72.5])
dr = 1.72142E-2
alpha = np.array([-0.38, 0.0, 0.0, 0.0, 0.17, 0.0, -0.38, 0.0, 0.0])
altl = np.array([200.0, 300.0, 160.0, 250.0, 240.0, 450.0, 320.0, 450.0])
pt,pd,ps,pdl,ptm,pdm,ptl,pma,sam,pavgm = nrlmsis00_data()
za = pdl[1,15]
zn1[0] = za
# tinf variations not important below za or zn1[0]
if inputp['alt'] > zn1[0]:
tinf_tmp,varli = globe7(pt,inputp,flags)
tinf = ptm[0]*pt[0] * (1+flags['sw'][15]*tinf_tmp)
else:
tinf = ptm[0]*pt[0]
output['t']['TINF'] = tinf
# gradient variations not important below zn1[4]
if inputp['alt'] > zn1[4]:
tinf_tmp,varli = globe7(ps,inputp,flags)
grad = ptm[3]*ps[0] * (1+flags['sw'][18]*tinf_tmp)
else:
grad = ptm[3]*ps[0]
tinf_tmp,varli = globe7(pd[3],inputp,flags)
tlb = ptm[1] * (1 + flags['sw'][16]*tinf_tmp)*pd[3,0]
s = grad/(tinf - tlb)
# Lower thermosphere temp variations not significant for density above 300 km
if inputp['alt'] < 300:
meso_tn1[1] = ptm[6]*ptl[0,0]/(1.0-flags['sw'][17]*glob7s(ptl[0], inputp, flags,varli))
meso_tn1[2] = ptm[2]*ptl[1,0]/(1.0-flags['sw'][17]*glob7s(ptl[1], inputp, flags,varli))
meso_tn1[3] = ptm[7]*ptl[2,0]/(1.0-flags['sw'][17]*glob7s(ptl[2], inputp, flags,varli))
meso_tn1[4] = ptm[4]*ptl[3,0]/(1.0-flags['sw'][17]*flags['sw'][19]*glob7s(ptl[3], inputp, flags,varli))
meso_tgn1[1] = ptm[8]*pma[8,0]*(1.0+flags['sw'][17]*flags['sw'][19]*glob7s(pma[8], inputp, flags,varli))*meso_tn1[4]*meso_tn1[4]/(ptm[4]*ptl[3,0])**2
else:
meso_tn1[1]=ptm[6]*ptl[0,0]
meso_tn1[2]=ptm[2]*ptl[1,0]
meso_tn1[3]=ptm[7]*ptl[2,0]
meso_tn1[4]=ptm[4]*ptl[3,0]
meso_tgn1[1]=ptm[8]*pma[8,0]*meso_tn1[4]*meso_tn1[4]/(ptm[4]*ptl[3,0])**2
# N2 variation factor at Zlb
tinf_tmp,varli = globe7(pd[2],inputp,flags)
g28 = flags['sw'][20]*tinf_tmp
# variation of turbopause height
zhf = pdl[1,24]*(1+flags['sw'][4]*pdl[0,24]*np.sin(np.deg2rad(inputp['g_lat']))*np.cos(dr*(inputp['doy']-pt[13])))
output['t']['TINF'] = tinf
xmm = pdm[2,4]
z = inputp['alt']
# N2 density
# Diffusive density at Zlb
db28 = pdm[2,0]*np.exp(g28)*pd[2,0]
# Diffusive density at Alt
output['d']['N2'],output['t']['TG'] = densu(z,db28,tinf,tlb,28,alpha[2],output['t']['TG'],ptm[5],s,zn1,meso_tn1,meso_tgn1,gsurf,re)
dd = output['d']['N2']
# Turbopause
zh28 = pdm[2,2]*zhf
zhm28 = pdm[2,3]*pdl[1,5]
xmd = 28 - xmm
# Mixed density at Zlb
b28,tz = densu(zh28,db28,tinf,tlb,xmd,(alpha[2]-1),tz,ptm[5],s, zn1,meso_tn1,meso_tgn1,gsurf,re)
if flags['sw'][14] and z <= altl[2]:
# Mixed density at Alt
dm28,tz = densu(z,b28,tinf,tlb,xmm,alpha[2],tz,ptm[5],s,zn1,meso_tn1,meso_tgn1,gsurf,re)
# Net density at Alt
output['d']['N2'] = dnet(output['d']['N2'],dm28,zhm28,xmm,28)
# HE density
# Density variation factor at Zlb
tinf_tmp,varli = globe7(pd[0],inputp,flags)
g4 = flags['sw'][20]*tinf_tmp
# Diffusive density at Zlb
db04 = pdm[0,0]*np.exp(g4)*pd[0,0]
# Diffusive density at Alt
output['d']['He'],output['t']['TG'] = densu(z,db04,tinf,tlb, 4,alpha[0],output['t']['TG'],ptm[5],s,zn1,meso_tn1,meso_tgn1,gsurf,re)
dd = output['d']['He']
if flags['sw'][14] and z<altl[0]:
# Turbopause
zh04 = pdm[0,2]
# Mixed density at Zlb
b04,output['t']['TG'] = densu(zh04,db04,tinf,tlb,4-xmm,alpha[0]-1,output['t']['TG'],ptm[5],s,zn1,meso_tn1,meso_tgn1,gsurf,re)
# Mixed density at Alt
dm04,output['t']['TG'] = densu(z,b04,tinf,tlb,xmm,0,output['t']['TG'],ptm[5],s,zn1,meso_tn1,meso_tgn1,gsurf,re)
zhm04 = zhm28
# Net density at Alt
output['d']['He'] = dnet(output['d']['He'],dm04,zhm04,xmm,4)
# Correction to specified mixing ratio at ground
rl = np.log(b28*pdm[0,1]/b04)
zc04 = pdm[0,4]*pdl[1,0]
hc04 = pdm[0,5]*pdl[1,1]
# Net density corrected at Alt
output['d']['He'] = output['d']['He']*ccor(z,rl,hc04,zc04)
# O density
# Density variation factor at Zlb
tinf_tmp,varli = globe7(pd[1],inputp,flags)
g16 = flags['sw'][20]*tinf_tmp
# Diffusive density at Zlb
db16 = pdm[1,0]*np.exp(g16)*pd[1,0]
# Diffusive density at Alt
output['d']['O'],output['t']['TG'] = densu(z,db16,tinf,tlb,16,alpha[1],output['t']['TG'],ptm[5],s, zn1,meso_tn1,meso_tgn1,gsurf,re)
dd = output['d']['O']
if flags['sw'][14] and z <= altl[1]:
# Turbopause
zh16 = pdm[1,2]
# Mixed density at Zlb
b16,output['t']['TG'] = densu(zh16,db16,tinf,tlb,16-xmm,alpha[1]-1, output['t']['TG'],ptm[5],s,zn1,meso_tn1,meso_tgn1,gsurf,re)
# Mixed density at Alt
dm16,output['t']['TG'] = densu(z,b16,tinf,tlb,xmm,0,output['t']['TG'],ptm[5],s,zn1,meso_tn1,meso_tgn1,gsurf,re)
zhm16 = zhm28
# Net density at Alt
output['d']['O'] = dnet(output['d']['O'],dm16,zhm16,xmm,16)
rl = pdm[1,1]*pdl[1,16]*(1+flags['sw'][0]*pdl[0,23]*(inputp['f107A']-150))
hc16 = pdm[1,5]*pdl[1,3]
zc16 = pdm[1,4]*pdl[1,2]
hc216 = pdm[1,5]*pdl[1,4]
output['d']['O'] = output['d']['O']*ccor2(z,rl,hc16,zc16,hc216)
# Chemistry correction
hcc16 = pdm[1,7]*pdl[1,13]
zcc16 = pdm[1,6]*pdl[1,12]
rc16 = pdm[1,3]*pdl[1,14]
# Net density corrected at Alt
output['d']['O'] = output['d']['O']*ccor(z,rc16,hcc16,zcc16)
# O2 density
# Density variation factor at Zlb
tinf_tmp,varli = globe7(pd[4],inputp,flags)
g32 = flags['sw'][20]*tinf_tmp
# Diffusive density at Zlb
db32 = pdm[3,0]*np.exp(g32)*pd[4,0]
# Diffusive density at Alt
output['d']['O2'],output['t']['TG'] = densu(z,db32,tinf,tlb, 32,alpha[3],output['t']['TG'],ptm[5],s, zn1,meso_tn1,meso_tgn1,gsurf,re)
dd = output['d']['O2'];
if flags['sw'][14]:
if z <= altl[3]:
# Turbopause
zh32 = pdm[3,2]
# Mixed density at Zlb
b32,output['t']['TG'] = densu(zh32,db32,tinf,tlb,32-xmm,alpha[3]-1, output['t']['TG'],ptm[5],s,zn1,meso_tn1,meso_tgn1,gsurf,re)
# Mixed density at Alt
dm32,output['t']['TG'] = densu(z,b32,tinf,tlb,xmm,0,output['t']['TG'],ptm[5],s,zn1,meso_tn1,meso_tgn1,gsurf,re)
zhm32 = zhm28
# Net density at Alt
output['d']['O2'] = dnet(output['d']['O2'],dm32,zhm32,xmm,32)
# Correction to specified mixing ratio at ground
rl = np.log(b28*pdm[3,1]/b32)
hc32 = pdm[3,5]*pdl[1,7]
zc32 = pdm[3,4]*pdl[1,6]
output['d']['O2'] = output['d']['O2']*ccor(z,rl,hc32,zc32)
# Correction for general departure from diffusive equilibrium above Zlb */
hcc32 = pdm[3,7]*pdl[1,22]
hcc232 = pdm[3,7]*pdl[0,22]
zcc32 = pdm[3,6]*pdl[1,21]
rc32 = pdm[3,3]*pdl[1,23]*(1+flags['sw'][0]*pdl[0,23]*(inputp['f107A']-150))
# Net density corrected at Alt
output['d']['O2'] = output['d']['O2']*ccor2(z,rc32,hcc32,zcc32,hcc232)
# AR density
# Density variation factor at Zlb
tinf_tmp,varli = globe7(pd[5],inputp,flags)
g40 = flags['sw'][20]*tinf_tmp
# Diffusive density at Zlb
db40 = pdm[4,0]*np.exp(g40)*pd[5,0]
# Diffusive density at Alt
output['d']['AR'],output['t']['TG'] = densu(z,db40,tinf,tlb, 40,alpha[4],output['t']['TG'],ptm[5],s,zn1,meso_tn1,meso_tgn1,gsurf,re)
dd = output['d']['AR']
if flags['sw'][14] and z <= altl[4]:
# Turbopause
zh40 = pdm[4,2]
# Mixed density at Zlb
b40,output['t']['TG'] = densu(zh40,db40,tinf,tlb,40-xmm,alpha[4]-1,output['t']['TG'],ptm[5],s,zn1,meso_tn1,meso_tgn1,gsurf,re)
# Mixed density at Alt
dm40,output['t']['TG'] = densu(z,b40,tinf,tlb,xmm,0,output['t']['TG'],ptm[5],s,zn1,meso_tn1,meso_tgn1,gsurf,re)
zhm40 = zhm28
# Net density at Alt
output['d']['AR'] = dnet(output['d']['AR'],dm40,zhm40,xmm,40)
# Correction to specified mixing ratio at ground
rl = np.log(b28*pdm[4,1]/b40)
hc40 = pdm[4,5]*pdl[1,9]
zc40 = pdm[4,4]*pdl[1,8]
# Net density corrected at Alt
output['d']['AR'] = output['d']['AR']*ccor(z,rl,hc40,zc40)
# Hydrogen density
# Density variation factor at Zlb */
tinf_tmp,varli = globe7(pd[6], inputp, flags)
g1 = flags['sw'][20]*tinf_tmp
# Diffusive density at Zlb
db01 = pdm[5,0]*np.exp(g1)*pd[6,0]
# Diffusive density at Alt
output['d']['H'],output['t']['TG']=densu(z,db01,tinf,tlb,1,alpha[6],output['t']['TG'],ptm[5],s,zn1,meso_tn1,meso_tgn1,gsurf,re)
dd = output['d']['H']
if flags['sw'][14] and z <= altl[6]:
# Turbopause
zh01 = pdm[5,2]
# Mixed density at Zlb
b01,output['t']['TG'] = densu(zh01,db01,tinf,tlb,1-xmm,alpha[6]-1, output['t']['TG'],ptm[5],s,zn1,meso_tn1,meso_tgn1,gsurf,re)
# Mixed density at Alt
dm01,output['t']['TG'] = densu(z,b01,tinf,tlb,xmm,0,output['t']['TG'],ptm[5],s,zn1,meso_tn1,meso_tgn1,gsurf,re)
zhm01 = zhm28
# Net density at Alt
output['d']['H'] = dnet(output['d']['H'],dm01,zhm01,xmm,1)
# Correction to specified mixing ratio at ground
rl = np.log(b28*pdm[5,1]*np.abs(pdl[1,17])/b01)
hc01 = pdm[5,5]*pdl[1,11]
zc01 = pdm[5,4]*pdl[1,10]
output['d']['H'] = output['d']['H']*ccor(z,rl,hc01,zc01)
# Chemistry correction
hcc01 = pdm[5,7]*pdl[1,19]
zcc01 = pdm[5,6]*pdl[1,18]
rc01 = pdm[5,3]*pdl[1,20]
# Net density corrected at Alt
output['d']['H'] = output['d']['H']*ccor(z,rc01,hcc01,zcc01)
# Atomic Nitrogen density
# Density variation factor at Zlb */
tinf_tmp,varli = globe7(pd[7],inputp,flags)
g14 = flags['sw'][20]*tinf_tmp
# Diffusive density at Zlb
db14 = pdm[6,0]*np.exp(g14)*pd[7,0]
# Diffusive density at Alt
output['d']['N'],output['t']['TG']=densu(z,db14,tinf,tlb,14,alpha[7],output['t']['TG'],ptm[5],s,zn1,meso_tn1,meso_tgn1,gsurf,re)
dd = output['d']['N']
if flags['sw'][14] and z <= altl[7]:
# Turbopause
zh14 = pdm[6,2]
# Mixed density at Zlb
b14,output['t']['TG'] = densu(zh14,db14,tinf,tlb,14-xmm,alpha[7]-1, output['t']['TG'],ptm[5],s,zn1,meso_tn1,meso_tgn1,gsurf,re)
# Mixed density at Alt
dm14,output['t']['TG'] = densu(z,b14,tinf,tlb,xmm,0,output['t']['TG'],ptm[5],s,zn1,meso_tn1,meso_tgn1,gsurf,re)
zhm14 = zhm28
# Net density at Alt
output['d']['N'] = dnet(output['d']['N'],dm14,zhm14,xmm,14)
# Correction to specified mixing ratio at ground
rl = np.log(b28*pdm[6,1]*np.abs(pdl[0,2])/b14)
hc14 = pdm[6,5]*pdl[0,1]
zc14 = pdm[6,4]*pdl[0,0]
output['d']['N'] = output['d']['N']*ccor(z,rl,hc14,zc14)
# Chemistry correction
hcc14 = pdm[6,7]*pdl[0,4]
zcc14 = pdm[6,6]*pdl[0,3]
rc14 = pdm[6,3]*pdl[0,5]
# Net density corrected at Alt
output['d']['N'] = output['d']['N']*ccor(z,rc14,hcc14,zcc14)
# Anomalous Oxygen density
tinf_tmp,varli = globe7(pd[8],inputp,flags)
g16h = flags['sw'][20]*tinf_tmp
db16h = pdm[7,0]*np.exp(g16h)*pd[8,0]
tho = pdm[7,9]*pdl[0,6]
dd,output['t']['TG'] = densu(z,db16h,tho,tho,16,alpha[8],output['t']['TG'],ptm[5],s, zn1,meso_tn1,meso_tgn1,gsurf,re)
zsht = pdm[7,5]
zmho = pdm[7,4]
zsho = scalh(zmho,16,tho,gsurf,re)
output['d']['ANM O'] = dd*np.exp(-zsht/zsho*(np.exp(-(z-zmho)/zsht)-1))
# total mass density
output['d']['RHO'] = 1.66E-24*(4*output['d']['He']+16*output['d']['O']+28*output['d']['N2']\
+32*output['d']['O2']+40*output['d']['AR']+ output['d']['H']+14*output['d']['N'])
# temperature
z = inputp['alt']
ddum,output['t']['TG'] = densu(z,1, tinf, tlb, 0, 0, output['t']['TG'], ptm[5], s, zn1, meso_tn1, meso_tgn1,gsurf,re)
# convert to g/cm^3
for key in output['d'].keys():
output['d'][key] = output['d'][key]*1.0E6
output['d']['RHO'] = output['d']['RHO']/1000
return output,dm28,[meso_tn1,meso_tn2,meso_tn3,meso_tgn1,meso_tgn2,meso_tgn3],varli
# ============================ nrlmsise00 =========================== #
def nrlmsise00(t,lat,lon,alt,SW_OBS_PRE,omode='NoOxygen',aphmode='NoAph'):
t = Time(t)
lon_wrap = wraplon(lon)
t_yday = t.yday.split(':')
t_ymd = t.iso.split()[0].split('-')
year,doy = int(t_yday[0]),int(t_yday[1])
sec = hms2s(int(t_yday[2]),int(t_yday[3]),float(t_yday[4]))
hour = hms2h(int(t_yday[2]),int(t_yday[3]),float(t_yday[4]))
lst = hour + wraplon(lon)/15
if alt > 80:
f107A,f107,ap,aph = get_sw(SW_OBS_PRE,t_ymd,hour)
else:
f107A,f107,ap,aph = 150,150,4,np.full(7,4)
inputp = {'doy':doy,'year':year,'sec':sec,'alt':alt,'g_lat':lat,'g_lon':lon_wrap,'lst':lst,\
'f107A':f107A,'f107':f107,'ap':ap,'ap_a':aph}
switches = np.ones(23)
if aphmode is 'Aph':
switches[8] = -1 # -1 indicates the use of 3h geomagnetic index
if omode is 'Oxygen':
output = gtd7d(inputp,switches)
elif omode is 'NoOxygen':
output = gtd7(inputp,switches)
else:
raise Exception("'{}' should be either 'Oxygen' or 'NoOxygen'".format(o))
inputp['g_lon'] = lon
inputp_format = {'Year':inputp['year'],'DayOfYear':inputp['doy'],'SecondOfDay':inputp['sec'],'Latitude[deg]':inputp['g_lat'],'Longitude[deg]':inputp['g_lon'],'Altitude[km]':inputp['alt'],'LocalSolarTime[hours]':inputp['lst'],\
'f107Average[10^-22 W/m^2/Hz]':inputp['f107A'],'f107Daily[10^-22 W/m^2/Hz]':inputp['f107'],'ApDaily':inputp['ap'],'Ap3Hourly':inputp['ap_a']}
output_format = {'Density':{'He[1/m^3]':output['d']['He'],'O[1/m^3]':output['d']['O'],'N2[1/m^3]':output['d']['N2'],'O2[1/m^3]':output['d']['O2'],'AR[1/m^3]':output['d']['AR'],'H[1/m^3]':output['d']['H'],'N[1/m^3]':output['d']['N'],'ANM O[1/m^3]':output['d']['ANM O'],'RHO[kg/m^3]':output['d']['RHO']},\
'Temperature':{'TINF[K]':output['t']['TINF'],'TG[K]':output['t']['TG']}}
return inputp_format,output_format