Skip to content
Snippets Groups Projects
Commit 5c307bd9 authored by tomrink's avatar tomrink
Browse files

snapshot...

parent dc935183
No related branches found
No related tags found
No related merge requests found
Hide whitespace changes
Inline Side-by-side
modules/amv/intercompare.py
+ 71
− 44
View file @ 5c307bd9
......@@ -1032,7 +1032,7 @@ def best_fit(amv_spd, amv_dir, amv_prs, amv_lat, amv_lon, fcst_spd, fcst_dir, fc
print('Pressure Profile: ')
print(fcst_prs)
if (abs(SatwindBestFitU - amv_uwind) > 4.0) or (abs(SatwindBestFitV - amv_vwind) > 4.0):
if (abs(SatwindBestFitU - amv_uwind) > 4.0) or (abs(SatwindBestFitV - amv_vwind) > 4.0):
print('U Diff: {0}'.format(abs(SatwindBestFitU - amv_uwind)))
print('V Diff: {0}'.format(abs(SatwindBestFitV - amv_vwind)))
......@@ -1041,17 +1041,16 @@ def best_fit(amv_spd, amv_dir, amv_prs, amv_lat, amv_lon, fcst_spd, fcst_dir, fc
return bf_data
def best_fit_altitude(amv_spd, amv_dir, amv_alt, amv_lat, amv_lon, fcst_spd, fcst_dir, fcst_alt, test_a=True, test_b=True):
def best_fit_altitude(amv_spd, amv_dir, amv_alt, amv_lat, amv_lon, fcst_spd, fcst_dir, fcst_alt,
alt_top=25000.0, alt_bot=0.0):
verbose = False
fcst_num_levels = fcst_spd.shape[0]
alt_diff = 1000.0
alt_top = 20000.0
alt_bot = 0
alt_diff_test = 500.0
flag = 3
bf_tup = (None, None, None, flag)
bf_tup = (np.nan, np.nan, np.nan, flag)
if amv_alt > alt_top:
if verbose:
print('AMV location lat,lon,lat ({0},{1},{2}) is higher than max altitude {3}'.format(amv_lat, amv_lon, amv_alt, alt_top))
......@@ -1063,7 +1062,7 @@ def best_fit_altitude(amv_spd, amv_dir, amv_alt, amv_lat, amv_lon, fcst_spd, fcs
# 1d array of indices to consider for best fit height
kk = np.where((fcst_alt > alt_min) & (fcst_alt < alt_max))
if len(kk[0]) == 0:
if kk[0].size == 0:
if verbose:
print('AMV location lat,lon,alt ({0},{1},{2}) failed to find fcst alt around AMV'.format(amv_lat,amv_lon,amv_alt))
return bf_tup
......@@ -1085,7 +1084,7 @@ def best_fit_altitude(amv_spd, amv_dir, amv_alt, amv_lat, amv_lon, fcst_spd, fcs
# Find the model level of best-fit pressure, from the minimum vector difference.
min_vec_diff = min(vec_diff[kk])
imin = np.where(vec_diff == min_vec_diff)
if len(imin[0]) == 0:
if imin[0].size == 0:
if verbose:
print('AMV location lat,lon,alt ({0},{1},{2}) failed to find min vector difference in layers around AMV'.format(amv_lat,amv_lon,amv_alt))
return bf_tup
......@@ -1093,49 +1092,77 @@ def best_fit_altitude(amv_spd, amv_dir, amv_alt, amv_lat, amv_lon, fcst_spd, fcs
imin = imin[0][0]
imin = kk[0][imin]
if imin == fcst_num_levels - 1:
if verbose:
print('AMV location lat,lon,alt ({0},{1},{2}) failed to find min vector difference in layers around AMV'.format(amv_lat,amv_lon,amv_alt))
return bf_tup
a2 = fcst_alt[imin]
v2 = vec_diff[imin]
if imin == 0:
return bf_tup
a2 = fcst_alt[imin]
v2 = vec_diff[imin]
a1 = fcst_alt[imin-1]
v2 = vec_diff[imin-1]
a3 = fcst_alt[imin+1]
v3 = vec_diff[imin+1]
sat_wind_best_fit_alt = a2
sat_wind_best_fit_u = fcst_uwind[imin]
sat_wind_best_fit_v = fcst_vwind[imin]
if imin == 0 or imin == (fcst_num_levels - 1):
if verbose:
print('AMV location lat,lon,alt ({0},{1},{2}) min vector difference at top/bottom'.format(amv_lat,amv_lon,amv_alt))
else:
a1 = fcst_alt[imin-1]
v1 = vec_diff[imin-1]
a3 = fcst_alt[imin+1]
v3 = vec_diff[imin+1]
# check not co-linear
if a1 != a2 and a2 != a3:
sat_wind_best_fit_alt = minimize_quadratic(a1, a2, a3, v1, v2, v3)
if sat_wind_best_fit_alt < a1 or sat_wind_best_fit_alt > a3:
sat_wind_best_fit_alt = a2
# Find best fit U and V by linear interpolation:
if a2 != sat_wind_best_fit_alt:
if a2 < sat_wind_best_fit_alt:
lev_below = imin
lev_above = imin + 1
prop = (sat_wind_best_fit_alt - a2) / (a3 - a2)
else:
lev_below = imin - 1
lev_above = imin
prop = (sat_wind_best_fit_alt - a1) / (a2 - a1)
sat_wind_best_fit_u = fcst_uwind[lev_below] * (1.0 - prop) + fcst_uwind[lev_above] * prop
sat_wind_best_fit_v = fcst_vwind[lev_below] * (1.0 - prop) + fcst_vwind[lev_above] * prop
# check contraints
good_constraint = 1
vdiff = np.sqrt((amv_uwind - sat_wind_best_fit_u) ** 2 + (amv_vwind - sat_wind_best_fit_v) ** 2)
if vdiff > 4.0:
good_constraint = 0
flag = 2
mm = np.where(fcst_alt > (sat_wind_best_fit_alt + alt_diff_test))[0]
nn = np.where(fcst_alt < (sat_wind_best_fit_alt - alt_diff_test))[0]
if (np.sum(vec_diff[mm] < (vec_diff + 2.0)) + np.sum(vec_diff[nn] < (vec_diff + 2.0))) > 0:
good_constraint = 0
flag = 1
# Find best fit U and V by linear interpolation:
if a2 == sat_wind_best_fit_alt:
sat_wind_best_fit_u = fcst_uwind[imin]
sat_wind_best_fit_v = fcst_vwind[imin]
if good_constraint == 1:
bf_tup = (sat_wind_best_fit_u, sat_wind_best_fit_v, sat_wind_best_fit_alt, 0)
else:
if a2 < sat_wind_best_fit_alt:
lev_below = imin
lev_above = imin + 1
prop = (sat_wind_best_fit_alt - a2) / (a3 - a2)
else:
lev_below = imin - 1
lev_above = imin
prop = (sat_wind_best_fit_alt - a1) / (a2 - a1)
pass
bf_tup = (None, None, None, flag)
if verbose:
print('*** AMV best-fit ***')
print('AMV -> p/minspd/maxspd: {0} {1} {2}'.format(amv_alt,sat_wind_min_spd,sat_wind_max_spd))
# print('Bestfit -> p1,p2,p3,v1,v2,v3: {0} {1} {2} {3} {4} {5}'.format(p1,p2,p3,v1,v2,v3))
print('Bestfit -> pbest,bfu,bfv,amvu,amvv,bgu,bgv: {0} {1} {2} {3} {4} {5} {6}'.format(
sat_wind_best_fit_alt,sat_wind_best_fit_u,sat_wind_best_fit_v,amv_uwind,amv_vwind,fcst_uwind[imin],fcst_vwind[imin]))
print('Good Constraint: {0}'.format(good_constraint))
print('Minimum Vector Difference: {0}'.format(vec_diff[imin]))
print('Vector Difference Profile: ')
print(vec_diff)
print('Altitude Profile: ')
print(fcst_alt)
sat_wind_best_fit_u = fcst_uwind[lev_below] * (1.0 - prop) + fcst_uwind[lev_above] * prop
sat_wind_best_fit_v = fcst_vwind[lev_below] * (1.0 - prop) + fcst_vwind[lev_above] * prop
if (abs(sat_wind_best_fit_u - amv_uwind) > 4.0) or (abs(sat_wind_best_fit_v - amv_vwind) > 4.0):
print('U Diff: {0}'.format(abs(sat_wind_best_fit_u - amv_uwind)))
print('V Diff: {0}'.format(abs(sat_wind_best_fit_v - amv_vwind)))
return bf_tup
......
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment