Ceilo toolbox (Auxiliary functions)¶
Ceilo tools module¶
This is the main toolbox designed to aid main processsing by reading and writing to files and processing data.
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ceilotools.algmlh(allprf, method, mlh, i, z, tarr, t, uplim)[source]¶ - Algorithms used for Mixed-layer Height determination.This script computes the mlh through an iterative approach and calls the relevant method.
A combined approach, named C2, due to the fact that it was the second version of a Combined algorithm uses both the gradient method and the wavelet method to find the boundary layer top. This was the algorithm used in [GarciaFSB+18].
Parameters
- allprf: np.nadarray
- backscattering matrix
- method: string
- String calling a MLH determination method, either of the following strings are accepted: ‘WT’, ‘Gradient’, ‘IPM’, ‘C2’.
- tarr : np.array
- Time-array, usually decimal hours.
- mlh : numpy.nadarray
- Mixed-layer height array, usually len(mlh)=144.
- i : int
- Integer of current time-step. Ranging from 0-143.
- z : np.array
- Height-array usually length 500, start=10, end=5000, t_step=10 [m]
- t : numpy.narray-float
- Time float of this specific computation.
- uplim : string
- Upper-limit of maximum MLH possible.
rtype: mlh: float
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ceilotools.writemlh(outputfile, horas, mlhs, station)[source]¶ Write of mixed-layer file to txt file, using standard heading. For instance:
Parameters
- outputfile: string
- Output filename. Usually a ‘txt’.
- horas : numpy.narray-float
- Time vector as hourly decimals. 0., 0.166, …, 23.83.
- mlhs : numpy.narray-float
- Mixed-layer heights vector.
- **station*: string
- Station string
Return type: None See Also
secondary.
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ceilotools.writematrix(outputfile, matrix, zeta, hour_vec, station, date, runv)[source]¶ Write of backscattering matrix to txt file, using standard heading. For instance:
Parameters
- outputfile: string
- Output filename. Usually a ‘txt’.
- matrix: numpy.nadarray
- Backscattering matrix mxn where m is the length of time vector, or number of decimal hours in the particular day and n is the length of height vector, usually 500 (10-5000 m every 10 m).
- hour_vec : numpy.narray-float
- Time vector as hourly decimals. 0., 0.166, …, 23.83.
- date : string
- Date of measurement (typically %Y%m%d)
- **station*: string
- Station string
Return type: None See Also
writemlh
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ceilotools.cloudfilter(allprf, tarr, z, datestring)[source]¶ Cloud filter
This function computes the cloud filter equations described in [Teschke (2008),Garcia-Franco (2017), Garcia-Franco et.al. (2018)]
Parameters
- allprf: np.nadarray
- backscattering matrix
- tarr : np.array
- Time-array, usually decimal hours.
- z : np.array
- Height-array usually length 500, start=10, end=5000, t_step=10 [m]
- datestring : string
- String for date, typically %Y%m%d, e.g., 20160305
Return type: datetimearray, flag vector: temps returns all datetimes where cloud or precipitation has been found, flag vector is a numpy array with the dimensions of tarr where clouds are depicted as 1 and clear-sky conditions as 0.
Statistical filter
\[\beta_\sigma (z,t)=B(z,t)\sigma(t)\]\[\mu=\frac{1}{N_zN_t}\sum_z\sum_t\beta_\sigma(z,t)\]\[\sum=\frac{1}{N_zN_t-1}\sum_z\sum_t[\beta_\sigma(z,t)-\mu]^2.\]\[B_N=\mu+3\sqrt{\sum}\]- \(B(z,t)\) Backscattering matrix
- \(\sigma(t)\) Variance over time $t$.
- \(\mu\) Global mean of beta_sigma(z,t)
- \(\sum\) Global variance of beta_sigma(z,t)
- \(z_{max}\) Maximum integration level [m]
- \(B_N\) Threshold for determining cloud or no cloud, function of both global mean and variance.
B_N defines the threshold value used for determining whether or not a profile at time t presents cloud and precipiation or not. If B(z,t)>B_N then cloud and precipitation are present. Else, clear-sky conditions are considered.
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ceilotools.runningMeanFast(x, N)[source]¶ Running mean of array x over a window of size N.
Parameters
- x: np.array
- Numpy array, usually 1D, to average over a moving or running mean.
- N: numpy.nadarray
- Size of moving average window.
rtype: np.array averaged with running mean. Note
This script makes use of numpy.convolve.
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ceilotools.writenumofprof(outputfile, numofprof, t, estacion, date)[source]¶ Write number of backscattering profiles used for every 10-min averaged window.
Parameters
- outputfile: string
- Output filename. Usually a ‘txt’.
- numofprof: int
- Number of profiles used for average
- t : numpy.narray-float
- Time vector as hourly decimals. 0., 0.166, …, 23.83.
- date : string
- Date of measurement (typically %Y%m%d)
- **estacion*: string
- Station string
rtype: None See Also
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ceilotools.readmatrixfile(filename)[source]¶ Write of backscattering matrix to txt file, using standard heading. For instance:
Parameters
- filename: string
- Input filename. Usually a ‘txt’.
Return type: z,tarr,allprf height and time vector and backscattering matrix. See Also