fatm_null=True

[ruohu129]

Hello,Auther!

I'm using your program to build a Rayleigh lookup table. I'm having some difficulties.
In the file “[osoaahelpers.py]”,a new function called “GenRayleighLUT” at line 354, fatm_null=True . When the fatm_null=True, it run OSOAA_MAIN_FATM_NULL.exe. But I didn't found a file called OSOAA_MAIN_FATM_NULL.exe. in my OSOAA program files. So this function will report an error. The same question happens when I use the function "RunAngels" and set fatm_null=True.
I wonder it was my question for my installation of the OSOAA and pyOSOAA programs or a bug in the pyOSOAA program itself.
I'm reconfiguring OSOAA and pyOSOAA. I hope this works.

Regards,
Ruohu

[ruohu129]

Hi @fengqiaogh , thank you for your update to the code. I tried running it, but I encountered an error

Could you please help me troubleshoot or advise on resolving this issue? I really appreciate any guidance you can offer!

[fnemina]

Hello @ruohu129

I don't see the function in the main OSOAA repository, but for the way it works OSOAA_MAIN_FATM_NULL.exe should be a compilation of the OSOAA EXPERT_MODE_FORCED_FSEA_NULL flag set to .TRUE. in the OSOAA_SOS_CORE.F file.

You can check page 69 in the OSOAA tutorial here and how to recompile using this flag and what changes (atmospheric scattering is set to zero).

After you compile it this way you can rename the generated file to OSOAA_MAIN_FATM_NULL.exe and it should work.

Best
Fran

[fengqiaogh]

Hello @ruohu129 and @fnemina

GenRayleighLUT is an experimental function and has not been fully tested yet. I use it to generate the Rayleigh lookup table, and when compared with SeaDAS, the error is minimal.

generate OSOAA_MAIN_FATM_NULL.exe

Change line 137 in the OSOAA_SOS_CORE.F file to #define EXPERT_MODE_FORCED_FSEA_NULL .TRUE., recompile, and rename the executable program to OSOAA_MAIN_FATM_NULL.exe.

generate LUT

Here, I’ll provide an example of calculating the GOCI lookup table.

# angle
solz = np.array([20, 60, 70])
senz = np.linspace(0, 70, 15)
phi = np.arange(5, 180, 5)

# wind
wind_speed = np.array([0])

taur = np.array(
    [3.17e-01, 2.35e-01, 1.55e-01, 9.36e-02, 4.63e-02, 4.10e-02, 2.83e-02, 1.56e-02]
)
s = pyOSOAA.OSOAA()

for idx, wa in enumerate(wavelength):
    i_ray, q_ray, u_ray = GenRayleighLUT(s, wa, taur[idx], wind_speed, senz, solz, phi)

   # Save
   results = {
        "taur": {
            "data": taur[idx],
            "attrs": {
                "long_name": "Optical Thickness",
                "slope": 1.0,
                "intercept": 0.0,
                "units": "dimensionless",
            },
        },
        "depol": {
            "data": depol[idx],
            "attrs": {
                "long_name": "Depolarization Factor",
                "slope": 1.0,
                "intercept": 0.0,
                "units": "dimensionless",
            },
        },
        "senz": {
            "data": senz,
            "attrs": {
                "long_name": "Sensor Zenith Angles",
                "slope": 1.0,
                "intercept": 0.0,
                "units": "degrees",
            },
        },
        "solz": {
            "data": solz,
            "attrs": {
                "long_name": "Solar Zenith Angles",
                "slope": 1.0,
                "intercept": 0.0,
                "units": "degrees",
            },
        },
        "sigma": {
            "data": sigma,
            "attrs": {
                "long_name": "Sigma of Wind Speed",
                "slope": 1.0,
                "intercept": 0.0,
                "units": "sqrt(m/s)",
            },
        },
        "i_ray": {
            "data": i_ray,
            "attrs": {
                "long_name": "Rayleigh Reflectance Coefficitnts for I-component",
                "slope": 1.0,
                "intercept": 0.0,
                "units": "dimensionless",
            },
        },
        "q_ray": {
            "data": q_ray,
            "attrs": {
                "long_name": "Rayleigh Reflectance Coefficitnts for Q-component",
                "slope": 1.0,
                "intercept": 0.0,
                "units": "dimensionless",
            },
        },
        "u_ray": {
            "data": u_ray,
            "attrs": {
                "long_name": "Rayleigh Reflectance Coefficitnts for U-component",
                "slope": 1.0,
                "intercept": 0.0,
                "units": "dimensionless",
            },
        },
    }
    with h5py.File(f"rayleigh_goci_{wa}_iqu.h5", mode="w") as f:
        for k, v in results.items():
            dataset = f.create_dataset(k, data=v["data"])
            dataset.attrs["long_name"] = v["attrs"]["long_name"]
            dataset.attrs["slope"] = v["attrs"]["slope"]
            dataset.attrs["intercept"] = v["attrs"]["intercept"]
            dataset.attrs["units"] = v["attrs"]["units"]

using LUT

The usage is the same as the SeaDAS lookup table method.

If there are any issues, feel free to reach out.

Best regards.