Beispiel #1
0
def pt_from_entropy(SA, entropy):
    r"""Calculates potential temperature with reference pressure p_ref = 0 dbar
    and with entropy as an input variable.

    Parameters
    ----------
    SA : array_like
         Absolute salinity [g kg :sup:`-1`]
    entropy : array_like
              specific entropy [J kg :sup:`-1` K :sup:`-1`]

    Returns
    -------
    pt : array_like
         potential temperature [:math:`^\circ` C (ITS-90)]
         with reference sea pressure (p_ref) = 0 dbar.

    See Also
    --------
    TODO

    Notes
    -----
    TODO

    Examples
    --------
    >>> import seawater.gibbs as gsw
    >>> SA = [34.7118, 34.8915, 35.0256, 34.8472, 34.7366, 34.7324]
    >>> entropy = [400.3892, 395.4378, 319.8668, 146.7910, 98.6471, 62.7919]
    >>> gsw.pt_from_entropy(SA, entropy)
    array([ 28.78317983,  28.42095483,  22.78495274,  10.23053207,
             6.82921333,   4.32453778])

    References
    ----------
    .. [1] IOC, SCOR and IAPSO, 2010: The international thermodynamic equation
    of seawater - 2010: Calculation and use of thermodynamic properties.
    Intergovernmental Oceanographic Commission, Manuals and Guides No. 56,
    UNESCO (English), 196 pp. See appendix  A.10.

    Modifications:
    2011-04-03. Trevor McDougall and Paul Barker.
    """

    SA = np.maximum(SA, 0)

    part1 = 1 - SA / SSO
    part2 = 1 - 0.05 * part1
    ent_SA = (cp0 / Kelvin) * part1 * (1 - 1.01 * part1)
    c = (entropy - ent_SA) * part2 / cp0
    pt = Kelvin * (np.exp(c) - 1)
    dentropy_dt = cp0 / ((Kelvin + pt) * part2)  # Initial dentropy_dt.

    for Number_of_iterations in range(0, 3):
        pt_old = pt
        dentropy = entropy_from_pt(SA, pt_old) - entropy
        # This is half way through the modified method
        # (McDougall and Wotherspoon, 2012)
        pt = pt_old - dentropy / dentropy_dt
        ptm = 0.5 * (pt + pt_old)
        dentropy_dt = -gibbs_pt0_pt0(SA, ptm)
        pt = pt_old - dentropy / dentropy_dt

    """maximum error of 2.2x10^-6 degrees C for one iteration. maximum error is
    1.4x10^-14 degrees C for two iterations (two iterations is the default,
    "for Number_of_iterations = 1:2")."""

    return pt
Beispiel #2
0
def pt_from_CT(SA, CT):
    r"""Calculates potential temperature (with a reference sea pressure of zero
    dbar) from Conservative Temperature.

    Parameters
    ----------
    SA : array_like
         Absolute salinity [g kg :sup:`-1`]
    CT : array_like
         Conservative Temperature [:math:`^\circ` C (ITS-90)]

    Returns
    -------
    pt : array_like
         potential temperature referenced to a sea pressure of zero dbar
         [:math:`^\circ` C (ITS-90)]

    See Also
    --------
    specvol_anom

    Notes
    -----
    This function uses 1.5 iterations through a modified Newton-Raphson (N-R)
    iterative solution procedure, starting from a rational-function-based
    initial condition for both pt and dCT_dpt.

    Examples
    --------
    >>> import gsw
    >>> SA = [34.7118, 34.8915, 35.0256, 34.8472, 34.7366, 34.7324]
    >>> CT = [28.8099, 28.4392, 22.7862, 10.2262, 6.8272, 4.3236]
    >>> gsw.pt_from_CT(SA, CT)
    array([ 28.78317705,  28.4209556 ,  22.78495347,  10.23053439,
             6.82921659,   4.32453484])

    References
    ----------
    .. [1] IOC, SCOR and IAPSO, 2010: The international thermodynamic equation
    of seawater - 2010: Calculation and use of thermodynamic properties.
    Intergovernmental Oceanographic Commission, Manuals and Guides No. 56,
    UNESCO (English), 196 pp. See sections 3.1 and 3.3.

    .. [2] McDougall T. J., D. R. Jackett, P. M. Barker, C. Roberts-Thomson,
    R. Feistel and R. W. Hallberg, 2010:  A computationally efficient 25-term
    expression for the density of seawater in terms of Conservative
    Temperature, and related properties of seawater.

    Modifications:
    2011-03-29. Trevor McDougall, David Jackett, Claire Roberts-Thomson and
    Paul Barker.
    """

    SA, CT, mask = strip_mask(SA, CT)
    SA = np.maximum(SA, 0)

    s1 = SA * 35. / SSO

    a0 = -1.446013646344788e-2
    a1 = -3.305308995852924e-3
    a2 = 1.062415929128982e-4
    a3 = 9.477566673794488e-1
    a4 = 2.166591947736613e-3
    a5 = 3.828842955039902e-3

    b0 = 1.000000000000000e+0
    b1 = 6.506097115635800e-4
    b2 = 3.830289486850898e-3
    b3 = 1.247811760368034e-6

    a5CT = a5 * CT
    b3CT = b3 * CT
    CT_factor = (a3 + a4 * s1 + a5CT)
    pt_num = a0 + s1 * (a1 + a2 * s1) + CT * CT_factor
    pt_den = b0 + b1 * s1 + CT * (b2 + b3CT)
    pt = pt_num / pt_den

    dCT_dpt = pt_den / (CT_factor + a5CT - (b2 + b3CT + b3CT) * pt)

    # 1.5 iterations through the modified Newton-Rapshon iterative method
    CT_diff = CT_from_pt(SA, pt) - CT
    pt_old = pt
    pt = pt_old - CT_diff / dCT_dpt  # 1/2-way through the 1st modified N-R.
    ptm = 0.5 * (pt + pt_old)

    # This routine calls gibbs_pt0_pt0(SA, pt0) to get the second derivative of
    # the Gibbs function with respect to temperature at zero sea pressure.

    dCT_dpt = -(ptm + Kelvin) * gibbs_pt0_pt0(SA, ptm) / cp0
    pt = pt_old - CT_diff / dCT_dpt  # End of 1st full modified N-R iteration.
    CT_diff = CT_from_pt(SA, pt) - CT
    pt_old = pt
    pt = pt_old - CT_diff / dCT_dpt  # 1.5 iterations of the modified N-R.
    # Abs max error of result is 1.42e-14 deg C.
    return np.ma.array(pt, mask=mask, copy=False)
Beispiel #3
0
def pt0_from_t(SA, t, p):
    r"""Calculates potential temperature with reference pressure, pr = 0 dbar.
    The present routine is computationally faster than the more general
    function "pt_from_t(SA, t, p, pr)" which can be used for any reference
    pressure value.

    Parameters
    ----------
    SA : array_like
         Absolute salinity [g kg :sup:`-1`]
    t : array_like
        in situ temperature [:math:`^\circ` C (ITS-90)]
    p : array_like
        pressure [dbar]

    Returns
    -------
    pt0 : array_like
          potential temperature relative to 0 dbar [:math:`^\circ` C (ITS-90)]

    See Also
    --------
    entropy_part, gibbs_pt0_pt0, entropy_part_zerop

    Notes
    -----
    pt_from_t  has the same result (only slower)

    Examples
    --------
    >>> import gsw
    >>> SA = [34.7118, 34.8915, 35.0256, 34.8472, 34.7366, 34.7324]
    >>> t = [28.7856, 28.4329, 22.8103, 10.2600, 6.8863, 4.4036]
    >>> p = [10, 50, 125, 250, 600, 1000]
    >>> gsw.pt0_from_t(SA, t, p)
    array([ 28.78319682,  28.42098334,  22.7849304 ,  10.23052366,
             6.82923022,   4.32451057])

    References
    ----------
    .. [1] IOC, SCOR and IAPSO, 2010: The international thermodynamic equation
    of seawater - 2010: Calculation and use of thermodynamic properties.
    Intergovernmental Oceanographic Commission, Manuals and Guides No. 56,
    UNESCO (English), 196 pp. See section 3.1.

    .. [2] McDougall T. J., D. R. Jackett, P. M. Barker, C. Roberts-Thomson,
    R. Feistel and R. W. Hallberg, 2010:  A computationally efficient 25-term
    expression for the density of seawater in terms of Conservative
    Temperature, and related properties of seawater.

    Modifications:
    2011-03-29. Trevor McDougall, David Jackett, Claire Roberts-Thomson and
    Paul Barker.
    """

    SA = np.maximum(SA, 0)

    s1 = SA * (35. / SSO)

    pt0 = t + p * (8.65483913395442e-6 -
             s1 * 1.41636299744881e-6 -
              p * 7.38286467135737e-9 +
              t * (-8.38241357039698e-6 +
             s1 * 2.83933368585534e-8 +
              t * 1.77803965218656e-8 +
              p * 1.71155619208233e-10))

    dentropy_dt = cp0 / ((Kelvin + pt0) * (1 - 0.05 * (1 - SA / SSO)))

    true_entropy_part = entropy_part(SA, t, p)

    for Number_of_iterations in range(0, 2, 1):
        pt0_old = pt0
        dentropy = entropy_part_zerop(SA, pt0_old) - true_entropy_part
        # Half way the mod. method (McDougall and Wotherspoon, 2012).
        pt0 = pt0_old - dentropy / dentropy_dt
        pt0m = 0.5 * (pt0 + pt0_old)
        dentropy_dt = -gibbs_pt0_pt0(SA, pt0m)
        pt0 = pt0_old - dentropy / dentropy_dt

    """maximum error of 6.3x10^-9 degrees C for one iteration. maximum error is
    1.8x10^-14 degrees C for two iterations (two iterations is the default,
    "for Number_of_iterations = 1:2").  These errors are over the full
    "oceanographic funnel" of McDougall et al. (2010), which reaches down to
    p = 8000 dbar."""

    return pt0
Beispiel #4
0
def pt_from_CT(SA, CT):
    r"""Calculates potential temperature (with a reference sea pressure of zero
    dbar) from Conservative Temperature.

    Parameters
    ----------
    SA : array_like
         Absolute salinity [g kg :sup:`-1`]
    CT : array_like
         Conservative Temperature [:math:`^\circ` C (ITS-90)]

    Returns
    -------
    pt : array_like
         potential temperature referenced to a sea pressure of zero dbar
         [:math:`^\circ` C (ITS-90)]

    See Also
    --------
    specvol_anom

    Notes
    -----
    This function uses 1.5 iterations through a modified Newton-Raphson (N-R)
    iterative solution procedure, starting from a rational-function-based
    initial condition for both pt and dCT_dpt.

    Examples
    --------
    >>> import gsw
    >>> SA = [34.7118, 34.8915, 35.0256, 34.8472, 34.7366, 34.7324]
    >>> CT = [28.8099, 28.4392, 22.7862, 10.2262, 6.8272, 4.3236]
    >>> gsw.pt_from_CT(SA, CT)
    array([ 28.78317705,  28.4209556 ,  22.78495347,  10.23053439,
             6.82921659,   4.32453484])

    References
    ----------
    .. [1] IOC, SCOR and IAPSO, 2010: The international thermodynamic equation
    of seawater - 2010: Calculation and use of thermodynamic properties.
    Intergovernmental Oceanographic Commission, Manuals and Guides No. 56,
    UNESCO (English), 196 pp. See sections 3.1 and 3.3.

    .. [2] McDougall T. J., D. R. Jackett, P. M. Barker, C. Roberts-Thomson,
    R. Feistel and R. W. Hallberg, 2010:  A computationally efficient 25-term
    expression for the density of seawater in terms of Conservative
    Temperature, and related properties of seawater.

    Modifications:
    2011-03-29. Trevor McDougall, David Jackett, Claire Roberts-Thomson and
    Paul Barker.
    """

    SA, CT, mask = strip_mask(SA, CT)

    s1 = SA * 35. / SSO

    a0 = -1.446013646344788e-2
    a1 = -3.305308995852924e-3
    a2 = 1.062415929128982e-4
    a3 = 9.477566673794488e-1
    a4 = 2.166591947736613e-3
    a5 = 3.828842955039902e-3

    b0 = 1.000000000000000e+0
    b1 = 6.506097115635800e-4
    b2 = 3.830289486850898e-3
    b3 = 1.247811760368034e-6

    a5CT = a5 * CT
    b3CT = b3 * CT
    CT_factor = (a3 + a4 * s1 + a5CT)
    pt_num = a0 + s1 * (a1 + a2 * s1) + CT * CT_factor
    pt_den = b0 + b1 * s1 + CT * (b2 + b3CT)
    pt = pt_num / pt_den

    dCT_dpt = pt_den / (CT_factor + a5CT - (b2 + b3CT + b3CT) * pt)

    # 1.5 iterations through the modified Newton-Rapshon iterative method
    CT_diff = CT_from_pt(SA, pt) - CT
    pt_old = pt
    pt = pt_old - CT_diff / dCT_dpt  # 1/2-way through the 1st modified N-R.
    ptm = 0.5 * (pt + pt_old)

    # This routine calls gibbs_pt0_pt0(SA,pt0) to get the second derivative of
    # the Gibbs function with respect to temperature at zero sea pressure.

    dCT_dpt = -(ptm + Kelvin) * gibbs_pt0_pt0(SA, ptm) / cp0
    pt = pt_old - CT_diff / dCT_dpt  # End of 1st full modified N-R iteration.
    CT_diff = CT_from_pt(SA, pt) - CT
    pt_old = pt
    pt = pt_old - CT_diff / dCT_dpt  # 1.5 iterations of the modified N-R.

    return np.ma.array(pt, mask=mask, copy=False)
Beispiel #5
0
def pt_from_entropy(SA, entropy):
    r"""Calculates potential temperature with reference pressure p_ref = 0 dbar
    and with entropy as an input variable.

    Parameters
    ----------
    SA : array_like
         Absolute salinity [g kg :sup:`-1`]
    entropy : array_like
              specific entropy [J kg :sup:`-1` K :sup:`-1`]

    Returns
    -------
    pt : array_like
         potential temperature [:math:`^\circ` C (ITS-90)]
         with reference sea pressure (p_ref) = 0 dbar.

    See Also
    --------
    TODO

    Notes
    -----
    TODO

    Examples
    --------
    >>> import seawater.gibbs as gsw
    >>> SA = [34.7118, 34.8915, 35.0256, 34.8472, 34.7366, 34.7324]
    >>> entropy = [400.3892, 395.4378, 319.8668, 146.7910, 98.6471, 62.7919]
    >>> gsw.pt_from_entropy(SA, entropy)
    array([ 28.78317983,  28.42095483,  22.78495274,  10.23053207,
             6.82921333,   4.32453778])

    References
    ----------
    .. [1] IOC, SCOR and IAPSO, 2010: The international thermodynamic equation
    of seawater - 2010: Calculation and use of thermodynamic properties.
    Intergovernmental Oceanographic Commission, Manuals and Guides No. 56,
    UNESCO (English), 196 pp. See appendix  A.10.

    Modifications:
    2011-04-03. Trevor McDougall and Paul Barker.
    """

    SA.clip(0, np.inf)

    n0, n1 = 0, 1

    part1 = 1 - SA / SSO
    part2 = 1 - 0.05 * part1
    ent_SA = (cp0 / Kelvin) * part1 * (1 - 1.01 * part1)
    c = (entropy - ent_SA) * part2 / cp0
    pt = Kelvin * (np.exp(c) - 1)
    dentropy_dt = cp0 / ((Kelvin + pt) * part2)  # Initial dentropy_dt.

    for Number_of_iterations in range(0, 3):
        pt_old = pt
        dentropy = entropy_from_pt(SA, pt_old) - entropy
        pt = pt_old - dentropy / dentropy_dt  # Half way through mod. method.
        ptm = 0.5 * (pt + pt_old)
        dentropy_dt = -gibbs_pt0_pt0(SA, ptm)
        pt = pt_old - dentropy / dentropy_dt

    """maximum error of 2.2x10^-6 degrees C for one iteration. maximum error is
    1.4x10^-14 degrees C for two iterations (two iterations is the default,
    "for Number_of_iterations = 1:2")."""

    return pt
Beispiel #6
0
def pt0_from_t(SA, t, p):
    r"""Calculates potential temperature with reference pressure, pr = 0 dbar.
    The present routine is computationally faster than the more general
    function "pt_from_t(SA, t, p, pr)" which can be used for any reference
    pressure value.

    Parameters
    ----------
    SA : array_like
         Absolute salinity [g kg :sup:`-1`]
    t : array_like
        in situ temperature [:math:`^\circ` C (ITS-90)]
    p : array_like
        pressure [dbar]

    Returns
    -------
    pt0 : array_like
          potential temperature relative to 0 dbar [:math:`^\circ` C (ITS-90)]

    See Also
    --------
    entropy_part, gibbs_pt0_pt0, entropy_part_zerop

    Notes
    -----
    pt_from_t  has the same result (only slower)

    Examples
    --------
    >>> import gsw
    >>> SA = [34.7118, 34.8915, 35.0256, 34.8472, 34.7366, 34.7324]
    >>> t = [28.7856, 28.4329, 22.8103, 10.2600, 6.8863, 4.4036]
    >>> p = [10, 50, 125, 250, 600, 1000]
    >>> gsw.pt0_from_t(SA, t, p)
    array([ 28.78319682,  28.42098334,  22.7849304 ,  10.23052366,
             6.82923022,   4.32451057])

    References
    ----------
    .. [1] IOC, SCOR and IAPSO, 2010: The international thermodynamic equation
    of seawater - 2010: Calculation and use of thermodynamic properties.
    Intergovernmental Oceanographic Commission, Manuals and Guides No. 56,
    UNESCO (English), 196 pp. See section 3.1.

    .. [2] McDougall T. J., D. R. Jackett, P. M. Barker, C. Roberts-Thomson,
    R. Feistel and R. W. Hallberg, 2010:  A computationally efficient 25-term
    expression for the density of seawater in terms of Conservative
    Temperature, and related properties of seawater.

    Modifications:
    2011-03-29. Trevor McDougall, David Jackett, Claire Roberts-Thomson and
    Paul Barker.
    """

    s1 = SA * (35. / SSO)

    pt0 = t + p * (8.65483913395442e-6 -
             s1 * 1.41636299744881e-6 -
              p * 7.38286467135737e-9 +
              t * (-8.38241357039698e-6 +
             s1 * 2.83933368585534e-8 +
              t * 1.77803965218656e-8 +
              p * 1.71155619208233e-10))

    dentropy_dt = cp0 / ((Kelvin + pt0) * (1 - 0.05 *
                                        (1 - SA / SSO)))

    true_entropy_part = entropy_part(SA, t, p)

    for Number_of_iterations in range(0, 2, 1):
        pt0_old = pt0
        dentropy = entropy_part_zerop(SA, pt0_old) - true_entropy_part
        pt0 = pt0_old - dentropy / dentropy_dt  # Half way through mod. method.
        pt0m = 0.5 * (pt0 + pt0_old)
        dentropy_dt = -gibbs_pt0_pt0(SA, pt0m)
        pt0 = pt0_old - dentropy / dentropy_dt

    """maximum error of 6.3x10^-9 degrees C for one iteration. maximum error is
    1.8x10^-14 degrees C for two iterations (two iterations is the default,
    "for Number_of_iterations = 1:2").  These errors are over the full
    "oceanographic funnel" of McDougall et al. (2010), which reaches down to
    p = 8000 dbar."""

    return pt0