zhanshi1997
commented
4 months ago Attached are two wrf output files. I got large values in Aug 16_00 file, while Aug 16_03 is good: https://drive.google.com/drive/folders/1o2JtpElNSTTM68dDx_3QxijfEx9afc27?usp=sharing
Here's the list of my package in this environment:
Name Version Build Channel
asttokens 2.4.1 pyhd8ed1ab_0 conda-forge blas 1.0 mkl bottleneck 1.3.7 py310h9128911_0 brotli 1.0.9 h2bbff1b_7 brotli-bin 1.0.9 h2bbff1b_7 bzip2 1.0.8 hcfcfb64_5 conda-forge ca-certificates 2024.2.2 h56e8100_0 conda-forge cartopy 0.22.0 py310h4748b25_0 certifi 2024.2.2 py310haa95532_0 cftime 1.6.2 py310h9128911_0 colorama 0.4.6 pyhd8ed1ab_0 conda-forge comm 0.2.1 pyhd8ed1ab_0 conda-forge contourpy 1.2.0 py310h59b6b97_0 cycler 0.11.0 pyhd3eb1b0_0 debugpy 1.8.1 py310h00ffb61_0 conda-forge decorator 5.1.1 pyhd8ed1ab_0 conda-forge exceptiongroup 1.2.0 pyhd8ed1ab_2 conda-forge executing 2.0.1 pyhd8ed1ab_0 conda-forge fonttools 4.25.0 pyhd3eb1b0_0 freetype 2.12.1 ha860e81_0 geos 3.8.0 h33f27b4_0 hdf4 4.2.13 h712560f_2 hdf5 1.12.1 h51c971a_3 icc_rt 2022.1.0 h6049295_2 importlib-metadata 7.0.1 pyha770c72_0 conda-forge importlib_metadata 7.0.1 hd8ed1ab_0 conda-forge intel-openmp 2023.1.0 h59b6b97_46320 ipykernel 6.29.2 pyha63f2e9_0 conda-forge ipython 8.22.0 pyh7428d3b_0 conda-forge jedi 0.19.1 pyhd8ed1ab_0 conda-forge jpeg 9e h2bbff1b_1 jupyter_client 8.6.0 pyhd8ed1ab_0 conda-forge jupyter_core 5.7.1 py310h5588dad_0 conda-forge kiwisolver 1.4.4 py310hd77b12b_0 lerc 3.0 hd77b12b_0 libbrotlicommon 1.0.9 h2bbff1b_7 libbrotlidec 1.0.9 h2bbff1b_7 libbrotlienc 1.0.9 h2bbff1b_7 libcurl 8.5.0 h86230a5_0 libdeflate 1.17 h2bbff1b_1 libffi 3.4.4 hd77b12b_0 libnetcdf 4.8.1 h6685c40_4 libpng 1.6.39 h8cc25b3_0 libsodium 1.0.18 h8d14728_1 conda-forge libsqlite 3.45.1 hcfcfb64_0 conda-forge libssh2 1.10.0 he2ea4bf_2 libtiff 4.5.1 hd77b12b_0 libwebp-base 1.3.2 h2bbff1b_0 libzip 1.8.0 h289538f_1 libzlib 1.2.13 hcfcfb64_5 conda-forge lz4-c 1.9.4 h2bbff1b_0 m2w64-gcc-libgfortran 5.3.0 6 conda-forge m2w64-gcc-libs 5.3.0 7 conda-forge m2w64-gcc-libs-core 5.3.0 7 conda-forge m2w64-gmp 6.1.0 2 conda-forge m2w64-libwinpthread-git 5.0.0.4634.697f757 2 matplotlib-base 3.8.0 py310h4ed8f06_0 matplotlib-inline 0.1.6 pyhd8ed1ab_0 conda-forge mkl 2023.1.0 h6b88ed4_46358 mkl-service 2.4.0 py310h2bbff1b_1 mkl_fft 1.3.8 py310h2bbff1b_0 mkl_random 1.2.4 py310h59b6b97_0 msys2-conda-epoch 20160418 1 munkres 1.1.4 py_0 nest-asyncio 1.6.0 pyhd8ed1ab_0 conda-forge netcdf4 1.6.2 py310hadf358c_0 numexpr 2.8.7 py310h2cd9be0_0 numpy 1.26.3 py310h055cbcc_0 numpy-base 1.26.3 py310h65a83cf_0 openjpeg 2.4.0 h4fc8c34_0 openssl 3.2.1 hcfcfb64_0 conda-forge packaging 23.2 pyhd8ed1ab_0 conda-forge pandas 2.1.4 py310h4ed8f06_0 parso 0.8.3 pyhd8ed1ab_0 conda-forge pickleshare 0.7.5 py_1003 conda-forge pillow 10.2.0 py310h2bbff1b_0 pip 24.0 pyhd8ed1ab_0 conda-forge platformdirs 4.2.0 pyhd8ed1ab_0 conda-forge proj 9.3.1 ha107b6e_0 prompt-toolkit 3.0.42 pyha770c72_0 conda-forge psutil 5.9.8 py310h8d17308_0 conda-forge pure_eval 0.2.2 pyhd8ed1ab_0 conda-forge pygments 2.17.2 pyhd8ed1ab_0 conda-forge pyparsing 3.0.9 py310haa95532_0 pyproj 3.6.1 py310h8d66fa9_0 pyshp 2.3.1 py310haa95532_0 python 3.10.13 h4de0772_1_cpython conda-forge python-dateutil 2.8.2 pyhd8ed1ab_0 conda-forge python-tzdata 2023.3 pyhd3eb1b0_0 python_abi 3.10 4_cp310 conda-forge pytz 2023.3.post1 py310haa95532_0 pywin32 306 py310h00ffb61_2 conda-forge pyzmq 25.1.2 py310h2849c00_0 conda-forge scipy 1.11.4 py310h309d312_0 setuptools 69.1.0 pyhd8ed1ab_1 conda-forge shapely 2.0.1 py310h6c53999_0 six 1.16.0 pyh6c4a22f_0 conda-forge sqlite 3.45.1 hcfcfb64_0 conda-forge stack_data 0.6.2 pyhd8ed1ab_0 conda-forge tbb 2021.8.0 h59b6b97_0 tk 8.6.13 h5226925_1 conda-forge tornado 6.4 py310h8d17308_0 conda-forge traitlets 5.14.1 pyhd8ed1ab_0 conda-forge typing_extensions 4.9.0 pyha770c72_0 conda-forge tzdata 2024a h0c530f3_0 conda-forge ucrt 10.0.22621.0 h57928b3_0 conda-forge vc 14.3 hcf57466_18 conda-forge vc14_runtime 14.38.33130 h82b7239_18 conda-forge vs2015_runtime 14.38.33130 hcb4865c_18 conda-forge wcwidth 0.2.13 pyhd8ed1ab_0 conda-forge wheel 0.42.0 pyhd8ed1ab_0 conda-forge wrapt 1.14.1 py310h2bbff1b_0 wrf-python 1.3.4.1 py310hf8fe482_2 conda-forge xarray 2023.6.0 py310haa95532_0 xz 5.4.5 h8cc25b3_0 zeromq 4.3.5 h63175ca_0 conda-forge zipp 3.17.0 pyhd8ed1ab_0 conda-forge zlib 1.2.13 hcfcfb64_5 conda-forge zstd 1.5.5 hd43e919_0
Hello, I am wondering if anyone had the same problem or could help me with this. Really appreciate any help.
So I have wrf output files and try to get the sea level pressure by: slp_sim = getvar(wrfout, 'slp') The returned results are around 1040 to 1050 hPa while slp from ERA5 reanalysis is around 1016 hPa. Also, this happens only in a few output files (one time step output per file). For example, when I use an output file of different time, it matches with the reanalysis.