def cal_GeostrophicCurrent_from_SSH(ssh, product_n = 3):
ns_dist = subroutine.dist_on_sphere([0.0, - 0.5], [0.0, 0.5])
xgrid, ygrid, zgrid = D.get_grid_value('ht', product_n)
yn = ygrid.size
xn = xgrid.size
Ug = np.zeros((yn, xn))
Vg = np.zeros((yn, xn))
xgrid_new = np.zeros(xn)
ygrid_new = np.zeros(yn)
for j in range(0, yn):
if j == yn - 1:
ygrid_new[j] = 0.5 * (ygrid[j] + ygrid[j] + 1)
Ug[j, :] = np.nan
Vg[j, :] = np.nan
else:
y0 = j
y1 = j + 1
ygrid_new[j] = 0.5 * (ygrid[y0] + ygrid[y1])
if abs(ygrid_new[j]) <= 2.0: # 赤道付近においては地衡流は計算しない
Ug[j, :] = np.nan
Vg[j, :] = np.nan
else:
ew_dist = subroutine.dist_on_sphere([0.0, ygrid_new[j]], [1.0, ygrid_new[j]])
f = subroutine.f0(ygrid_new[j])
for i in range(0, xn):
x0 = i
if i == xn - 1:
x1 = 0
lon = 0.5 * (xgrid[i] + xgrid[i] + 1.0)
else:
x1 = i + 1
lon = 0.5 * (xgrid[x0] + xgrid[x1])
if j == 1:
xgrid_new[i] = lon
ssh00 = ssh[y0, x0]
ssh01 = ssh[y1, x0]
ssh10 = ssh[y0, x1]
ssh11 = ssh[y1, x1]
a = Using_jit.average_of_2data(ssh01, ssh11)
b = Using_jit.average_of_2data(ssh00, ssh10)
c = Using_jit.average_of_2data(ssh10, ssh11)
d = Using_jit.average_of_2data(ssh00, ssh01)
Ug[j, i] = -g / f * (a - b) / ns_dist
Vg[j, i] = g / f * (c - d) / ew_dist
return Ug, Vg, xgrid_new, ygrid_new
def cal_EkmanCurrent_from_tau(taux, tauy, ygrid, nu): zgrid = - np.arange(N) - 0.5 xn = taux.shape[1] yn = taux.shape[0] zn = zgrid.size Ue = np.zeros((yn, xn, zn)) Ve = np.zeros((yn, xn, zn)) Ue_new = np.zeros((yn, xn, M)) Ve_new = np.zeros((yn, xn, M)) for j in range(0, yn): if abs(ygrid[j]) <= 2.0: Ue[j, :, :] = np.nan Ve[j, :, :] = np.nan else: f = subroutine.f0(ygrid[j]) r = np.sqrt(np.abs(f) / (2.0 * nu)) for i in range(0, xn): if ygrid[j] > 0.0: T = ( - taux[j, i] + tauy[j, i]) / (taux[j, i] + tauy[j, i]) Au = (taux[j, i] + tauy[j, i]) / (np.sqrt(2.0) * r * nu * rho0) Av = Au else: T = ( - taux[j, i] - tauy[j, i]) / (taux[j, i] - tauy[j, i]) Au = (taux[j, i] - tauy[j, i]) / (np.sqrt(2.0) * r * nu * rho0) Av = -Au Ue[j, i, :] = Au * np.exp( r * zgrid[:]) * (np.cos(r * zgrid[:]) - T * np.sin(r * zgrid[:])) Ve[j, i, :] = Av * np.exp( r * zgrid[:]) * (np.sin(r * zgrid[:]) + T * np.cos(r * zgrid[:])) for m in range(0, M): Ue_new[:, :, m] = np.average(Ue[:, :, L*m:L*(m + 1)], axis = 2) Ve_new[:, :, m] = np.average(Ve[:, :, L*m:L*(m + 1)], axis = 2) return Ue_new, Ve_new