ArcGIS Pro says that NetCDF file has NaN NoData
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07-25-2023 11:56 AM
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I want to add a multidimensional voxel layer to ArcGIS Pro. When I do so, I'm getting this error:
I'm not sure why this happens.
First, when I print out the netCDF4 Dataset in Python, I get this, where none of the fill values (marked FV) are NaN.
<class 'netCDF4._netCDF4.Dataset'>
root group (NETCDF4 data model, file format HDF5):
HDFEOSVersion: HDFEOS_V2.18
identifier_product_doi: 10.5067/UO3Q64CTTS1U
identifier_product_doi_authority: http://dx.doi.org/
ascending._FV_TotalCounts_A: -9999.0
ascending._FV_SurfPres_Forecast_A: -9999.0
ascending._FV_SurfPres_Forecast_A_ct: -9999.0
ascending._FV_SurfPres_Forecast_A_sdev: -9999.0
ascending._FV_SurfSkinTemp_A: -9999.0
ascending._FV_SurfSkinTemp_A_ct: -9999.0
ascending._FV_SurfSkinTemp_A_sdev: -9999.0
ascending._FV_EmisIR_A: -9999.0
ascending._FV_EmisIR_A_ct: -9999.0
ascending._FV_EmisIR_A_sdev: -9999.0
ascending._FV_Temperature_A: -9999.0
ascending._FV_Temperature_A_ct: -9999.0
ascending._FV_Temperature_A_sdev: -9999.0
ascending._FV_SurfAirTemp_A: -9999.0
ascending._FV_SurfAirTemp_A_ct: -9999.0
ascending._FV_SurfAirTemp_A_sdev: -9999.0
ascending._FV_TropPres_A: -9999.0
ascending._FV_TropPres_A_ct: -9999.0
ascending._FV_TropPres_A_sdev: -9999.0
ascending._FV_TropTemp_A: -9999.0
ascending._FV_TropTemp_A_ct: -9999.0
ascending._FV_TropTemp_A_sdev: -9999.0
ascending._FV_TotH2OVap_A: -9999.0
ascending._FV_TotH2OVap_A_ct: -9999.0
ascending._FV_TotH2OVap_A_sdev: -9999.0
ascending._FV_H2O_MMR_Lyr_A: -9999.0
ascending._FV_H2O_MMR_Lyr_A_ct: -9999.0
ascending._FV_H2O_MMR_Lyr_A_sdev: -9999.0
ascending._FV_H2O_MMR_A: -9999.0
ascending._FV_H2O_MMR_A_ct: -9999.0
ascending._FV_H2O_MMR_A_sdev: -9999.0
ascending._FV_H2O_MMR_Surf_A: -9999.0
ascending._FV_H2O_MMR_Surf_A_ct: -9999.0
ascending._FV_H2O_MMR_Surf_A_sdev: -9999.0
ascending._FV_RelHum_A: -9999.0
ascending._FV_RelHum_A_ct: -9999.0
ascending._FV_RelHum_A_sdev: -9999.0
ascending._FV_RelHumSurf_A: -9999.0
ascending._FV_RelHumSurf_A_ct: -9999.0
ascending._FV_RelHumSurf_A_sdev: -9999.0
ascending._FV_RelHum_liquid_A: -9999.0
ascending._FV_RelHum_liquid_A_ct: -9999.0
ascending._FV_RelHum_liquid_A_sdev: -9999.0
ascending._FV_RelHumSurf_liquid_A: -9999.0
ascending._FV_RelHumSurf_liquid_A_ct: -9999.0
ascending._FV_RelHumSurf_liquid_A_sdev: -9999.0
ascending._FV_TropHeight_A: -9999.0
ascending._FV_TropHeight_A_ct: -9999.0
ascending._FV_TropHeight_A_sdev: -9999.0
ascending._FV_GPHeight_A: -9999.0
ascending._FV_GPHeight_A_ct: -9999.0
ascending._FV_GPHeight_A_sdev: -9999.0
[...] (everything between here has a FV of -9999.0)
descending_MW_only._FV_GPHeight_MW_D: -9999.0
descending_MW_only._FV_GPHeight_MW_D_ct: -9999.0
descending_MW_only._FV_GPHeight_MW_D_sdev: -9999.0
descending_MW_only._FV_TotCldLiqH2O_MW_D: -9999.0
descending_MW_only._FV_TotCldLiqH2O_MW_D_ct: -9999.0
descending_MW_only._FV_TotCldLiqH2O_MW_D_sdev: -9999.0
location._FV_Latitude: -9999.0
location._FV_Longitude: -9999.0
location._FV_LandSeaMask: 0
location._FV_Topography: -9999.0
location.Year: 2023
location.Month: 7
location.Day: 6
location.NumOfDays: 1
location.AscendingGridStartTimeUTC: 2023-07-06T01:30:00.000000Z
location.AscendingGridEndTimeUTC: 2023-07-07T01:29:59.999999Z
location.DescendingGridStartTimeUTC: 2023-07-05T13:30:00.000000Z
location.DescendingGridEndTimeUTC: 2023-07-06T13:29:59.999999Z
location.StdPressureLev: 1000.0
location.H2OPressureLev: 1000.0
location.H2OPressureLay: 961.7692
location.EmisFreqIR: 832.0
location.EmisFreqMW: 23.8
location.CoarseCloudLayer: 865.0
location.FineCloudLayer: 1018.0
history: 2023-07-24 18:38:32 GMT Hyrax-1.16.3 https://acdisc.gesdisc.eosdis.nasa.gov /opendap/Aqua_AIRS_Level3/AIRS3STD.7.0/2023/AIRS.2023.07.06.L3.RetStd_IR001.v7.0.7.0.G23188155256.hdf.nc4?CO_VMR_A[0:23][50:52][101:105],StdPressureLev[0:23],Latitude[50:52],Longitude[101:105]
dimensions(sizes): time(1), Longitude(5), Latitude(3), StdPressureLev(24)
variables(dimensions): float64 Longitude(Longitude), float64 Latitude(Latitude), float32 StdPressureLev(StdPressureLev), int32 time(time), float64 CO(time, StdPressureLev, Latitude, Longitude)
groups: Now below is the dataset at the variable I'm interested in. Second, the fill_value that I hard-coded into the dataset is 4.65079211e-08, which you see in the first entry of the first three sub-arrays. Third, the fill_value you see at the bottom is 1e+20. Neither of those are NaN.
masked_array(
data=[[[[4.65079211e-08, 1.05414074e-07, 1.01281330e-07,
1.01164915e-07, 1.04249921e-07],
[4.65079211e-08, 1.05646905e-07, 1.24564394e-07,
1.13388523e-07, 1.09313987e-07],
[4.65079211e-08, 1.02561899e-07, 1.08266249e-07,
1.05996151e-07, 1.12049747e-07]],
[[1.03667844e-07, 1.04249921e-07, 1.00524630e-07,
9.90694389e-08, 1.01979822e-07],
[1.06403604e-07, 1.01805199e-07, 1.20257027e-07,
1.10187102e-07, 1.06985681e-07],
[1.01339538e-07, 1.00058969e-07, 1.04715582e-07,
1.02911144e-07, 1.09372195e-07]],
[[1.01223122e-07, 1.01397745e-07, 9.83127393e-08,
9.72650014e-08, 1.00058969e-07],
[1.03726052e-07, 9.95351002e-08, 1.16357114e-07,
1.07218511e-07, 1.05006620e-07],
[9.94186848e-08, 9.77306627e-08, 1.01455953e-07,
1.00233592e-07, 1.07102096e-07]],
[[9.74978320e-08, 9.70903784e-08, 9.54605639e-08,
9.54605639e-08, 9.80217010e-08],
[9.97097231e-08, 9.66247171e-08, 1.09837856e-07,
1.02969352e-07, 1.02794729e-07],
[9.71485861e-08, 9.45874490e-08, 9.63336788e-08,
9.64500941e-08, 1.04075298e-07]],
[[9.65665095e-08, 9.56351869e-08, 9.49949026e-08,
9.56351869e-08, 9.80217010e-08],
[9.84873623e-08, 9.61008482e-08, 1.06228981e-07,
1.01164915e-07, 1.02561899e-07],
[9.72067937e-08, 9.39471647e-08, 9.41217877e-08,
9.53441486e-08, 1.03085767e-07]],
[[9.66829248e-08, 9.49949026e-08, 9.55187716e-08,
9.67411324e-08, 9.88948159e-08],
[9.82545316e-08, 9.65665095e-08, 1.02678314e-07,
9.98261385e-08, 1.02561899e-07],
[9.81963240e-08, 9.42382030e-08, 9.26083885e-08,
9.51113179e-08, 1.02212653e-07]],
[[9.66829248e-08, 9.42382030e-08, 9.57516022e-08,
9.73814167e-08, 9.90694389e-08],
[9.77306627e-08, 9.67993401e-08, 9.76724550e-08,
9.74978320e-08, 1.01048499e-07],
[9.90694389e-08, 9.45874490e-08, 9.08621587e-08,
9.44710337e-08, 9.96515155e-08]],
[[9.34232958e-08, 9.03964974e-08, 9.23755579e-08,
9.38889571e-08, 9.47620720e-08],
[9.38889571e-08, 9.37143341e-08, 8.84174369e-08,
9.08039510e-08, 9.41799954e-08],
[9.62172635e-08, 9.19098966e-08, 8.63801688e-08,
9.01054591e-08, 9.19681042e-08]],
[[8.83592293e-08, 8.52742232e-08, 8.71950760e-08,
8.83592293e-08, 8.88248906e-08],
[8.85338522e-08, 8.86502676e-08, 8.09086487e-08,
8.42264853e-08, 8.69622454e-08],
[9.10367817e-08, 8.72532837e-08, 8.13161023e-08,
8.44011083e-08, 8.45175236e-08]],
[[7.94534571e-08, 7.67176971e-08, 7.82310963e-08,
7.89295882e-08, 7.91042112e-08],
[7.94534571e-08, 7.96862878e-08, 7.08969310e-08,
7.44475983e-08, 7.63102435e-08],
[8.16653483e-08, 7.87549652e-08, 7.30506144e-08,
7.50878826e-08, 7.39819370e-08]],
[[6.61239028e-08, 6.40284270e-08, 6.49597496e-08,
6.51925802e-08, 6.51925802e-08],
[6.60656951e-08, 6.62403181e-08, 5.80330379e-08,
6.11762516e-08, 6.21075742e-08],
[6.76373020e-08, 6.56582415e-08, 6.10016286e-08,
6.18747436e-08, 6.01285137e-08]],
[[4.86325007e-08, 4.73810360e-08, 4.76429705e-08,
4.75847628e-08, 4.75556590e-08],
[4.86033969e-08, 4.85451892e-08, 4.26080078e-08,
4.46743798e-08, 4.46743798e-08],
[4.92145773e-08, 4.82832547e-08, 4.53146640e-08,
4.51109372e-08, 4.32773959e-08]],
[[3.70491762e-08, 3.63797881e-08, 3.62633727e-08,
3.61178536e-08, 3.60887498e-08],
[3.70782800e-08, 3.68745532e-08, 3.27709131e-08,
3.40223778e-08, 3.34403012e-08],
[3.71364877e-08, 3.67290340e-08, 3.48663889e-08,
3.40514816e-08, 3.23925633e-08]],
[[2.95549398e-08, 2.91620381e-08, 2.88855517e-08,
2.87400326e-08, 2.87109287e-08],
[2.95840437e-08, 2.93366611e-08, 2.64408300e-08,
2.71829776e-08, 2.63971742e-08],
[2.94094207e-08, 2.92493496e-08, 2.80560926e-08,
2.70374585e-08, 2.55968189e-08]],
[[2.25554686e-08, 2.23662937e-08, 2.20898073e-08,
2.19442882e-08, 2.19442882e-08],
[2.25845724e-08, 2.23662937e-08, 2.05473043e-08,
2.09402060e-08, 2.03581294e-08],
[2.23662937e-08, 2.23226380e-08, 2.16532499e-08,
2.08674464e-08, 1.98342605e-08]],
[[1.97323970e-08, 1.96014298e-08, 1.93831511e-08,
1.92812877e-08, 1.92958396e-08],
[1.97615009e-08, 1.96014298e-08, 1.82335498e-08,
1.85391400e-08, 1.82626536e-08],
[1.96159817e-08, 1.95723260e-08, 1.90921128e-08,
1.86264515e-08, 1.78988557e-08]],
[[1.88592821e-08, 1.87283149e-08, 1.85827957e-08,
1.84809323e-08, 1.84954843e-08],
[1.88883860e-08, 1.87574187e-08, 1.75932655e-08,
1.78697519e-08, 1.77678885e-08],
[1.88010745e-08, 1.87428668e-08, 1.83208613e-08,
1.80443749e-08, 1.74914021e-08]],
[[1.89029379e-08, 1.87719706e-08, 1.86701072e-08,
1.85973477e-08, 1.86118996e-08],
[1.89174898e-08, 1.88301783e-08, 1.78260962e-08,
1.81025825e-08, 1.81607902e-08],
[1.89029379e-08, 1.88301783e-08, 1.84518285e-08,
1.83208613e-08, 1.79425115e-08]],
[[2.00234354e-08, 1.98924681e-08, 1.98051566e-08,
1.97178451e-08, 1.97469490e-08],
[2.00379873e-08, 1.99652277e-08, 1.90339051e-08,
1.92812877e-08, 1.93977030e-08],
[2.00379873e-08, 1.99506758e-08, 1.96014298e-08,
1.94850145e-08, 1.91939762e-08]],
[[2.19297362e-08, 2.17842171e-08, 2.16823537e-08,
2.15950422e-08, 2.16386979e-08],
[2.19442882e-08, 2.18569767e-08, 2.09547579e-08,
2.11875886e-08, 2.12894520e-08],
[2.19297362e-08, 2.18424248e-08, 2.15077307e-08,
2.13476596e-08, 2.10711733e-08]],
[[2.64408300e-08, 2.62953108e-08, 2.61206878e-08,
2.60042725e-08, 2.60770321e-08],
[2.64408300e-08, 2.63244146e-08, 2.54076440e-08,
2.55822670e-08, 2.55822670e-08],
[2.63680704e-08, 2.62807589e-08, 2.59751687e-08,
2.56259227e-08, 2.53057806e-08]],
[[3.15485522e-08, 3.14030331e-08, 3.11702024e-08,
3.09955794e-08, 3.11119948e-08],
[3.15776560e-08, 3.14030331e-08, 3.04135028e-08,
3.05299181e-08, 3.04426067e-08],
[3.14030331e-08, 3.13448254e-08, 3.10246833e-08,
3.05008143e-08, 3.00933607e-08]],
[[3.61469574e-08, 3.60014383e-08, 3.57104000e-08,
3.55066732e-08, 3.56521923e-08],
[3.61760613e-08, 3.59723344e-08, 3.48954927e-08,
3.50119080e-08, 3.48372851e-08],
[3.59723344e-08, 3.58850230e-08, 3.55648808e-08,
3.49245965e-08, 3.44298314e-08]],
[[4.43251338e-08, 4.41214070e-08, 4.37721610e-08,
4.35393304e-08, 4.36848495e-08],
[4.43542376e-08, 4.40923031e-08, 4.28408384e-08,
4.29572538e-08, 4.26953193e-08],
[4.40923031e-08, 4.39758878e-08, 4.35975380e-08,
4.28117346e-08, 4.22296580e-08]]]],
mask=False,
fill_value=1e+20)So why is ArcGIS Pro telling me that my variables have no data and my fill values are NaN?
I haven't been able to find anything on the internet, ArcGIS Pro's docs, or NetCDF's docs about this. I'd really appreciate any help!
