Google Air Quality Data

import requests
import numpy as np
import pandas as pd
import xarray as xr
from tqdm import tqdm
import matplotlib.pyplot as plt
import dask
from dask.distributed import Client, LocalCluster

if "key" in locals():
    pass
else:
    key = input("Enter your key: ")

url = f"https://airquality.googleapis.com/v1/history:lookup?key={key}"
url

'https://airquality.googleapis.com/v1/history:lookup?key=AIzaSyA9ytSec31of_INkpuB3TZ6vLR1nzme9iQ'

if "client" in locals():
    print(client)
else:
    cluster = LocalCluster(n_workers=54, threads_per_worker=1)
    client = Client(cluster)
    print(client)

<Client: 'tcp://127.0.0.1:36239' processes=54 threads=54, memory=503.73 GiB>

payload = {
    "hours": 24 * 30,
    "pageSize": 168,
    "pageToken": "",
    "location": {"latitude": 28.636429, "longitude": 77.201067},
    "extraComputations": ["POLLUTANT_CONCENTRATION", "LOCAL_AQI"],
}

headers = {"Content-Type": "application/json"}

response = requests.post(url, json=payload, headers=headers)

res = response.json()

24 * 30

720

len(res["hoursInfo"])

168

ts = []
codes = []
pm25 = []
df = pd.DataFrame(columns=["timestamp", "value", "code"])

for each in res["hoursInfo"]:
    ts.append(each["dateTime"])
    codes.append(each["pollutants"][4]["code"])
    pm25.append(each["pollutants"][4]["concentration"]["value"])

df["timestamp"] = ts
df["value"] = pm25
df["code"] = codes
df["timestamp"] = pd.to_datetime(df["timestamp"])
df.head(20)

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
Cell In[5], line 9
      7     ts.append(each["dateTime"])
      8     codes.append(each["pollutants"][4]["code"])
----> 9     pm25.append(each["pollutants"][4]["concentration"]["value"])
     11 df["timestamp"] = ts
     12 df["value"] = pm25

KeyError: 'concentration'

sensor_data = pd.read_excel(
    "/home/patel_zeel/blog/posts/site_12220230831125207.xlsx", skiprows=16
)
sensor_data["From Date"] = pd.to_datetime(
    sensor_data["From Date"], format="%d-%m-%Y %H:%M"
)
sensor_data["To Date"] = pd.to_datetime(sensor_data["To Date"], format="%d-%m-%Y %H:%M")
sensor_data["mean_time"] = sensor_data[["From Date", "To Date"]].mean(axis=1)
sensor_data["utc_time"] = sensor_data["mean_time"] - pd.Timedelta(hours=5, minutes=30)

fig, ax = plt.subplots(figsize=(15, 4))
sensor_data.plot(x="utc_time", y="PM2.5", ax=ax, label="sensor")
df.plot(x="timestamp", y="value", ax=ax, label="google")

Request at a grid.

from aqmsp_data.data import load_camx

camx = load_camx(years=2022, months=1, days=1, variables="P25")
camx

/home/patel_zeel/miniconda3/lib/python3.9/site-packages/xarray/core/indexing.py:1443: PerformanceWarning: Slicing is producing a large chunk. To accept the large
chunk and silence this warning, set the option
    >>> with dask.config.set(**{'array.slicing.split_large_chunks': False}):
    ...     array[indexer]

To avoid creating the large chunks, set the option
    >>> with dask.config.set(**{'array.slicing.split_large_chunks': True}):
    ...     array[indexer]
  return self.array[key]

<xarray.Dataset>
Dimensions:    (time: 24, latitude: 80, longitude: 80)
Coordinates:
  * longitude  (longitude) float64 76.85 76.86 76.87 76.88 ... 77.62 77.63 77.64
  * latitude   (latitude) float64 28.2 28.21 28.22 28.23 ... 28.97 28.98 28.99
  * time       (time) datetime64[ns] 2022-01-01T00:30:00 ... 2022-01-01T23:30:00
Data variables:
    P25        (time, latitude, longitude) float32 dask.array<chunksize=(24, 80, 80), meta=np.ndarray>
Attributes: (12/34)
    CDATE:          2023126
    CTIME:          95909
    EXEC_ID:        ????????????????                                         ...
    FILEDESC:       I/O API formatted CAMx AVRG output                       ...
    FTYPE:          1
    GDNAM:          ????????????????
    ...             ...
    XCELL:          0.009999999776482582
    XCENT:          0.0
    XORIG:          76.8499984741211
    YCELL:          0.009999999776482582
    YCENT:          0.0
    YORIG:          28.200000762939453

xarray.Dataset

• Dimensions:
  • time: 24
  • latitude: 80
  • longitude: 80
• Coordinates: (3)
  • longitude
    (longitude)
    float64
    76.85 76.86 76.87 ... 77.63 77.64

    array([76.85, 76.86, 76.87, 76.88, 76.89, 76.9 , 76.91, 76.92, 76.93, 76.94,
           76.95, 76.96, 76.97, 76.98, 76.99, 77.  , 77.01, 77.02, 77.03, 77.04,
           77.05, 77.06, 77.07, 77.08, 77.09, 77.1 , 77.11, 77.12, 77.13, 77.14,
           77.15, 77.16, 77.17, 77.18, 77.19, 77.2 , 77.21, 77.22, 77.23, 77.24,
           77.25, 77.26, 77.27, 77.28, 77.29, 77.3 , 77.31, 77.32, 77.33, 77.34,
           77.35, 77.36, 77.37, 77.38, 77.39, 77.4 , 77.41, 77.42, 77.43, 77.44,
           77.45, 77.46, 77.47, 77.48, 77.49, 77.5 , 77.51, 77.52, 77.53, 77.54,
           77.55, 77.56, 77.57, 77.58, 77.59, 77.6 , 77.61, 77.62, 77.63, 77.64])

  • latitude
    (latitude)
    float64
    28.2 28.21 28.22 ... 28.98 28.99

    array([28.2 , 28.21, 28.22, 28.23, 28.24, 28.25, 28.26, 28.27, 28.28, 28.29,
           28.3 , 28.31, 28.32, 28.33, 28.34, 28.35, 28.36, 28.37, 28.38, 28.39,
           28.4 , 28.41, 28.42, 28.43, 28.44, 28.45, 28.46, 28.47, 28.48, 28.49,
           28.5 , 28.51, 28.52, 28.53, 28.54, 28.55, 28.56, 28.57, 28.58, 28.59,
           28.6 , 28.61, 28.62, 28.63, 28.64, 28.65, 28.66, 28.67, 28.68, 28.69,
           28.7 , 28.71, 28.72, 28.73, 28.74, 28.75, 28.76, 28.77, 28.78, 28.79,
           28.8 , 28.81, 28.82, 28.83, 28.84, 28.85, 28.86, 28.87, 28.88, 28.89,
           28.9 , 28.91, 28.92, 28.93, 28.94, 28.95, 28.96, 28.97, 28.98, 28.99])

  • time
    (time)
    datetime64[ns]
    2022-01-01T00:30:00 ... 2022-01-...

    array(['2022-01-01T00:30:00.000000000', '2022-01-01T01:30:00.000000000',
           '2022-01-01T02:30:00.000000000', '2022-01-01T03:30:00.000000000',
           '2022-01-01T04:30:00.000000000', '2022-01-01T05:30:00.000000000',
           '2022-01-01T06:30:00.000000000', '2022-01-01T07:30:00.000000000',
           '2022-01-01T08:30:00.000000000', '2022-01-01T09:30:00.000000000',
           '2022-01-01T10:30:00.000000000', '2022-01-01T11:30:00.000000000',
           '2022-01-01T12:30:00.000000000', '2022-01-01T13:30:00.000000000',
           '2022-01-01T14:30:00.000000000', '2022-01-01T15:30:00.000000000',
           '2022-01-01T16:30:00.000000000', '2022-01-01T17:30:00.000000000',
           '2022-01-01T18:30:00.000000000', '2022-01-01T19:30:00.000000000',
           '2022-01-01T20:30:00.000000000', '2022-01-01T21:30:00.000000000',
           '2022-01-01T22:30:00.000000000', '2022-01-01T23:30:00.000000000'],
          dtype='datetime64[ns]')

• Data variables: (1)
  • P25
    (time, latitude, longitude)
    float32
    dask.array<chunksize=(24, 80, 80), meta=np.ndarray>

    long_name :

    FPRM

    units :

    micrograms/m**3

    var_desc :

    VARIABLE FPRM

    Array Chunk Bytes 600.00 kiB 600.00 kiB Shape (24, 80, 80) (24, 80, 80) Dask graph 1 chunks in 11 graph layers Data type float32 numpy.ndarray

• Indexes: (3)
  • longitude
    PandasIndex

    PandasIndex(Index([            76.85,             76.86, 76.86999999999999,
                       76.88,             76.89, 76.89999999999999,
                       76.91, 76.91999999999999, 76.92999999999999,
                       76.94, 76.94999999999999,             76.96,
                       76.97, 76.97999999999999,             76.99,
                        77.0, 77.00999999999999,             77.02,
                       77.03, 77.03999999999999,             77.05,
           77.05999999999999,             77.07,             77.08,
           77.08999999999999,              77.1,             77.11,
           77.11999999999999,             77.13,             77.14,
           77.14999999999999,             77.16, 77.16999999999999,
           77.17999999999999,             77.19, 77.19999999999999,
                       77.21,             77.22, 77.22999999999999,
                       77.24,             77.25, 77.25999999999999,
                       77.27,             77.28, 77.28999999999999,
                        77.3, 77.30999999999999,             77.32,
                       77.33, 77.33999999999999,             77.35,
                       77.36, 77.36999999999999,             77.38,
                       77.39, 77.39999999999999,             77.41,
           77.41999999999999, 77.42999999999999,             77.44,
           77.44999999999999,             77.46,             77.47,
           77.47999999999999,             77.49,              77.5,
           77.50999999999999,             77.52,             77.53,
           77.53999999999999,             77.55, 77.55999999999999,
                       77.57,             77.58, 77.58999999999999,
                        77.6,             77.61, 77.61999999999999,
                       77.63,             77.64],
          dtype='float64', name='longitude'))

  • latitude
    PandasIndex

    PandasIndex(Index([              28.2,              28.21,              28.22,
                        28.23,              28.24,              28.25,
           28.259999999999998,              28.27, 28.279999999999998,
                        28.29,               28.3,              28.31,
                        28.32,              28.33,              28.34,
           28.349999999999998,              28.36,              28.37,
                        28.38,              28.39,               28.4,
                        28.41, 28.419999999999998,              28.43,
           28.439999999999998,              28.45,              28.46,
                        28.47,              28.48,              28.49,
                         28.5, 28.509999999999998,              28.52,
           28.529999999999998,              28.54,              28.55,
                        28.56,              28.57,              28.58,
                        28.59, 28.599999999999998,              28.61,
                        28.62,              28.63,              28.64,
                        28.65,              28.66, 28.669999999999998,
                        28.68, 28.689999999999998,               28.7,
                        28.71,              28.72,              28.73,
                        28.74,              28.75, 28.759999999999998,
                        28.77, 28.779999999999998,              28.79,
                         28.8,              28.81,              28.82,
                        28.83,              28.84, 28.849999999999998,
                        28.86,              28.87,              28.88,
                        28.89,               28.9,              28.91,
           28.919999999999998,              28.93, 28.939999999999998,
                        28.95,              28.96,              28.97,
                        28.98,              28.99],
          dtype='float64', name='latitude'))

  • time
    PandasIndex

    PandasIndex(DatetimeIndex(['2022-01-01 00:30:00', '2022-01-01 01:30:00',
                   '2022-01-01 02:30:00', '2022-01-01 03:30:00',
                   '2022-01-01 04:30:00', '2022-01-01 05:30:00',
                   '2022-01-01 06:30:00', '2022-01-01 07:30:00',
                   '2022-01-01 08:30:00', '2022-01-01 09:30:00',
                   '2022-01-01 10:30:00', '2022-01-01 11:30:00',
                   '2022-01-01 12:30:00', '2022-01-01 13:30:00',
                   '2022-01-01 14:30:00', '2022-01-01 15:30:00',
                   '2022-01-01 16:30:00', '2022-01-01 17:30:00',
                   '2022-01-01 18:30:00', '2022-01-01 19:30:00',
                   '2022-01-01 20:30:00', '2022-01-01 21:30:00',
                   '2022-01-01 22:30:00', '2022-01-01 23:30:00'],
                  dtype='datetime64[ns]', name='time', freq=None))

• Attributes: (34)

  CDATE :

  2023126

  CTIME :

  95909

  EXEC_ID :

  ????????????????

  FILEDESC :

  I/O API formatted CAMx AVRG output

  FTYPE :

  1

  GDNAM :

  ????????????????

  GDTYP :

  1

  HISTORY :

  Sun May 7 09:57:07 2023: ncrcat camxout.2023.05.06.nc camxout.2023.05.07.nc camxout.2023.05.08.nc camxout.2023.05.09.nc camxout.2023.05.10.nc camx120hr.nc

  IOAPI_VERSION :

  $Id: @(#) ioapi library version 3.0 $

  NCO :

  netCDF Operators version 4.9.1 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco)

  NCOLS :

  80

  NLAYS :

  1

  NROWS :

  80

  NTHIK :

  1

  NVARS :

  2

  P_ALP :

  0.0

  P_BET :

  0.0

  P_GAM :

  0.0

  SDATE :

  2023126

  STIME :

  0

  TSTEP :

  10000

  UPNAM :

  CAMXMETOU

  VAR-LIST :

  P10 P25

  VGLVLS :

  [0. 0.]

  VGTOP :

  -9.998999757492232e+36

  VGTYP :

  -9999

  WDATE :

  2023126

  WTIME :

  95909

  XCELL :

  0.009999999776482582

  XCENT :

  0.0

  XORIG :

  76.8499984741211

  YCELL :

  0.009999999776482582

  YCENT :

  0.0

  YORIG :

  28.200000762939453

lat_grid, lon_grid = np.meshgrid(camx.latitude, camx.longitude)
lat_lon_grid = np.vstack([lat_grid.ravel(), lon_grid.ravel()]).T
print(lat_lon_grid.shape)

session = requests.Session()
delayed_fn = dask.delayed(session.post)
responses = []
for lat, lon in tqdm(lat_lon_grid):
    payload = {
        "hours": 1,
        "pageSize": 200,
        "pageToken": "",
        "location": {"latitude": lat, "longitude": lon},
        "extraComputations": ["POLLUTANT_CONCENTRATION"],
    }

    headers = {"Content-Type": "application/json"}

    response = delayed_fn(url, json=payload, headers=headers)
    responses.append(response)

all_res = dask.compute(*responses)

(6400, 2)

100%|██████████| 6400/6400 [00:01<00:00, 5981.06it/s]

---------------------------------------------------------------------------
KeyboardInterrupt                         Traceback (most recent call last)
Cell In[7], line 22
     19     response = delayed_fn(url, json=payload, headers=headers)
     20     responses.append(response)
---> 22 all_res = dask.compute(*responses)

File ~/miniconda3/lib/python3.9/site-packages/dask/base.py:666, in compute(traverse, optimize_graph, scheduler, get, *args, **kwargs)
    663     keys.append(x.__dask_keys__())
    664     postcomputes.append(x.__dask_postcompute__())
--> 666 results = schedule(dsk, keys, **kwargs)
    667 return repack([f(r, *a) for r, (f, a) in zip(results, postcomputes)])

File ~/miniconda3/lib/python3.9/site-packages/dask/threaded.py:89, in get(dsk, keys, cache, num_workers, pool, **kwargs)
     86     elif isinstance(pool, multiprocessing.pool.Pool):
     87         pool = MultiprocessingPoolExecutor(pool)
---> 89 results = get_async(
     90     pool.submit,
     91     pool._max_workers,
     92     dsk,
     93     keys,
     94     cache=cache,
     95     get_id=_thread_get_id,
     96     pack_exception=pack_exception,
     97     **kwargs,
     98 )
    100 # Cleanup pools associated to dead threads
    101 with pools_lock:

File ~/miniconda3/lib/python3.9/site-packages/dask/local.py:500, in get_async(submit, num_workers, dsk, result, cache, get_id, rerun_exceptions_locally, pack_exception, raise_exception, callbacks, dumps, loads, chunksize, **kwargs)
    498 while state["waiting"] or state["ready"] or state["running"]:
    499     fire_tasks(chunksize)
--> 500     for key, res_info, failed in queue_get(queue).result():
    501         if failed:
    502             exc, tb = loads(res_info)

File ~/miniconda3/lib/python3.9/site-packages/dask/local.py:137, in queue_get(q)
    136 def queue_get(q):
--> 137     return q.get()

File ~/miniconda3/lib/python3.9/queue.py:171, in Queue.get(self, block, timeout)
    169 elif timeout is None:
    170     while not self._qsize():
--> 171         self.not_empty.wait()
    172 elif timeout < 0:
    173     raise ValueError("'timeout' must be a non-negative number")

File ~/miniconda3/lib/python3.9/threading.py:312, in Condition.wait(self, timeout)
    310 try:    # restore state no matter what (e.g., KeyboardInterrupt)
    311     if timeout is None:
--> 312         waiter.acquire()
    313         gotit = True
    314     else:

KeyboardInterrupt: 

dfs = []
for res, (lat, lon) in tqdm(zip(all_res, lat_lon_grid)):
    res = res.json()
    df = pd.DataFrame(columns=["timestamp", "value", "code"])
    ts = []
    codes = []
    pm25 = []
    for each in res["hoursInfo"]:
        ts.append(each["dateTime"])
        codes.append(each["pollutants"][4]["code"])
        try:
            pm25.append(each["pollutants"][4]["concentration"]["value"])
        except KeyError:
            pm25.append(np.nan)

    df["timestamp"] = ts
    df["value"] = pm25
    df["code"] = codes
    df["lat"] = lat
    df["lon"] = lon
    df["timestamp"] = pd.to_datetime(df["timestamp"])
    dfs.append(df)
master_df = pd.concat(dfs)
assert master_df["code"].nunique() == 1 and master_df["code"].unique()[0] == "pm25"

ds = master_df.set_index(["lat", "lon", "timestamp"]).to_xarray()
ds.isel(timestamp=0)["value"].plot(x="lon", y="lat", cmap="RdYlGn_r")

0it [00:00, ?it/s]6400it [00:12, 497.91it/s]

Appendix

import xarray as xr

global_date = "2023-07-26"
ds_met = xr.open_dataset(
    f'../../sarath_auto_download/data/camxmet2d.delhi.{global_date.replace("-","")}.96hours.nc'
)
ds_aq = xr.open_dataset(
    f'../../sarath_auto_download/data/camx120hr_merged_{global_date.replace("-","")}.nc'
)
ds_met

<xarray.Dataset>
Dimensions:     (TSTEP: 96, VAR: 14, DATE-TIME: 2, LAY: 1, ROW: 80, COL: 80)
Dimensions without coordinates: TSTEP, VAR, DATE-TIME, LAY, ROW, COL
Data variables: (12/15)
    TFLAG       (TSTEP, VAR, DATE-TIME) int32 ...
    TSURF_K     (TSTEP, LAY, ROW, COL) float32 ...
    SNOWEW_M    (TSTEP, LAY, ROW, COL) float32 ...
    SNOWAGE_HR  (TSTEP, LAY, ROW, COL) float32 ...
    PRATE_MMpH  (TSTEP, LAY, ROW, COL) float32 ...
    CLOUD_OD    (TSTEP, LAY, ROW, COL) float32 ...
    ...          ...
    SWSFC_WpM2  (TSTEP, LAY, ROW, COL) float32 ...
    SOLM_M3pM3  (TSTEP, LAY, ROW, COL) float32 ...
    CLDTOP_KM   (TSTEP, LAY, ROW, COL) float32 ...
    CAPE        (TSTEP, LAY, ROW, COL) float32 ...
    PBL_WRF_M   (TSTEP, LAY, ROW, COL) float32 ...
    PBL_YSU_M   (TSTEP, LAY, ROW, COL) float32 ...
Attributes: (12/33)
    IOAPI_VERSION:  $Id: @(#) ioapi library version 3.0 $                    ...
    EXEC_ID:        ????????????????                                         ...
    FTYPE:          1
    CDATE:          2023207
    CTIME:          72116
    WDATE:          2023207
    ...             ...
    VGLVLS:         [0. 0.]
    GDNAM:          ????????????????
    UPNAM:          CAMx2IOAPI      
    VAR-LIST:       TSURF_K         SNOWEW_M        SNOWAGE_HR      PRATE_MMp...
    FILEDESC:       I/O API formatted CAMx AVRG output                       ...
    HISTORY:        

xarray.Dataset

• Dimensions:
  • TSTEP: 96
  • VAR: 14
  • DATE-TIME: 2
  • LAY: 1
  • ROW: 80
  • COL: 80
• Coordinates: (0)
• Data variables: (15)
  • TFLAG
    (TSTEP, VAR, DATE-TIME)
    int32
    ...

    units :

    <YYYYDDD,HHMMSS>

    long_name :

    TFLAG

    var_desc :

    Timestep-valid flags: (1) YYYYDDD or (2) HHMMSS

    [2688 values with dtype=int32]

  • TSURF_K
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    TSURF_K

    units :

    ppmV

    var_desc :

    VARIABLE TSURF_K

    [614400 values with dtype=float32]

  • SNOWEW_M
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    SNOWEW_M

    units :

    ppmV

    var_desc :

    VARIABLE SNOWEW_M

    [614400 values with dtype=float32]

  • SNOWAGE_HR
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    SNOWAGE_HR

    units :

    ppmV

    var_desc :

    VARIABLE SNOWAGE_HR

    [614400 values with dtype=float32]

  • PRATE_MMpH
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    PRATE_MMpH

    units :

    ppmV

    var_desc :

    VARIABLE PRATE_MMpH

    [614400 values with dtype=float32]

  • CLOUD_OD
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    CLOUD_OD

    units :

    ppmV

    var_desc :

    VARIABLE CLOUD_OD

    [614400 values with dtype=float32]

  • U10_MpS
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    U10_MpS

    units :

    ppmV

    var_desc :

    VARIABLE U10_MpS

    [614400 values with dtype=float32]

  • V10_MpS
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    V10_MpS

    units :

    ppmV

    var_desc :

    VARIABLE V10_MpS

    [614400 values with dtype=float32]

  • T2_K
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    T2_K

    units :

    ppmV

    var_desc :

    VARIABLE T2_K

    [614400 values with dtype=float32]

  • SWSFC_WpM2
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    SWSFC_WpM2

    units :

    ppmV

    var_desc :

    VARIABLE SWSFC_WpM2

    [614400 values with dtype=float32]

  • SOLM_M3pM3
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    SOLM_M3pM3

    units :

    ppmV

    var_desc :

    VARIABLE SOLM_M3pM3

    [614400 values with dtype=float32]

  • CLDTOP_KM
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    CLDTOP_KM

    units :

    ppmV

    var_desc :

    VARIABLE CLDTOP_KM

    [614400 values with dtype=float32]

  • CAPE
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    CAPE

    units :

    ppmV

    var_desc :

    VARIABLE CAPE

    [614400 values with dtype=float32]

  • PBL_WRF_M
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    PBL_WRF_M

    units :

    ppmV

    var_desc :

    VARIABLE PBL_WRF_M

    [614400 values with dtype=float32]

  • PBL_YSU_M
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    PBL_YSU_M

    units :

    ppmV

    var_desc :

    VARIABLE PBL_YSU_M

    [614400 values with dtype=float32]

• Indexes: (0)
• Attributes: (33)

  IOAPI_VERSION :

  $Id: @(#) ioapi library version 3.0 $

  EXEC_ID :

  ????????????????

  FTYPE :

  1

  CDATE :

  2023207

  CTIME :

  72116

  WDATE :

  2023207

  WTIME :

  72116

  SDATE :

  2023207

  STIME :

  0

  TSTEP :

  10000

  NTHIK :

  1

  NCOLS :

  80

  NROWS :

  80

  NLAYS :

  1

  NVARS :

  14

  GDTYP :

  1

  P_ALP :

  0.0

  P_BET :

  0.0

  P_GAM :

  0.0

  XCENT :

  0.0

  YCENT :

  0.0

  XORIG :

  76.8499984741211

  YORIG :

  28.200000762939453

  XCELL :

  0.009999999776482582

  YCELL :

  0.009999999776482582

  VGTYP :

  -9999

  VGTOP :

  -9.999e+36

  VGLVLS :

  [0. 0.]

  GDNAM :

  ????????????????

  UPNAM :

  CAMx2IOAPI

  VAR-LIST :

  TSURF_K SNOWEW_M SNOWAGE_HR PRATE_MMpH CLOUD_OD U10_MpS V10_MpS T2_K SWSFC_WpM2 SOLM_M3pM3 CLDTOP_KM CAPE PBL_WRF_M PBL_YSU_M

  FILEDESC :

  I/O API formatted CAMx AVRG output

  HISTORY :

plt.figure(figsize=(15, 3))
ds_met["PBL_WRF_M"].isel(LAY=0).mean(dim=["ROW", "COL"]).plot()
twin_x = plt.gca().twinx()
ds_aq["P25"].isel(LAY=0, TSTEP=range(24, 120)).mean(dim=["ROW", "COL"]).plot(
    ax=twin_x, color="r"
)
# set ylabel color as red
twin_x.set_ylabel("PM2.5", color="r")
# set yticks color as red
twin_x.tick_params(axis="y", colors="r")
twin_x.set_xlabel("Time")

Text(0.5, 0, 'Time')

ds_met

<xarray.Dataset>
Dimensions:     (TSTEP: 96, VAR: 14, DATE-TIME: 2, LAY: 1, ROW: 80, COL: 80)
Dimensions without coordinates: TSTEP, VAR, DATE-TIME, LAY, ROW, COL
Data variables: (12/15)
    TFLAG       (TSTEP, VAR, DATE-TIME) int32 ...
    TSURF_K     (TSTEP, LAY, ROW, COL) float32 ...
    SNOWEW_M    (TSTEP, LAY, ROW, COL) float32 ...
    SNOWAGE_HR  (TSTEP, LAY, ROW, COL) float32 ...
    PRATE_MMpH  (TSTEP, LAY, ROW, COL) float32 ...
    CLOUD_OD    (TSTEP, LAY, ROW, COL) float32 ...
    ...          ...
    SWSFC_WpM2  (TSTEP, LAY, ROW, COL) float32 ...
    SOLM_M3pM3  (TSTEP, LAY, ROW, COL) float32 ...
    CLDTOP_KM   (TSTEP, LAY, ROW, COL) float32 ...
    CAPE        (TSTEP, LAY, ROW, COL) float32 ...
    PBL_WRF_M   (TSTEP, LAY, ROW, COL) float32 ...
    PBL_YSU_M   (TSTEP, LAY, ROW, COL) float32 ...
Attributes: (12/33)
    IOAPI_VERSION:  $Id: @(#) ioapi library version 3.0 $                    ...
    EXEC_ID:        ????????????????                                         ...
    FTYPE:          1
    CDATE:          2023207
    CTIME:          72116
    WDATE:          2023207
    ...             ...
    VGLVLS:         [0. 0.]
    GDNAM:          ????????????????
    UPNAM:          CAMx2IOAPI      
    VAR-LIST:       TSURF_K         SNOWEW_M        SNOWAGE_HR      PRATE_MMp...
    FILEDESC:       I/O API formatted CAMx AVRG output                       ...
    HISTORY:        

xarray.Dataset

• Dimensions:
  • TSTEP: 96
  • VAR: 14
  • DATE-TIME: 2
  • LAY: 1
  • ROW: 80
  • COL: 80
• Coordinates: (0)
• Data variables: (15)
  • TFLAG
    (TSTEP, VAR, DATE-TIME)
    int32
    ...

    units :

    <YYYYDDD,HHMMSS>

    long_name :

    TFLAG

    var_desc :

    Timestep-valid flags: (1) YYYYDDD or (2) HHMMSS

    [2688 values with dtype=int32]

  • TSURF_K
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    TSURF_K

    units :

    ppmV

    var_desc :

    VARIABLE TSURF_K

    [614400 values with dtype=float32]

  • SNOWEW_M
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    SNOWEW_M

    units :

    ppmV

    var_desc :

    VARIABLE SNOWEW_M

    [614400 values with dtype=float32]

  • SNOWAGE_HR
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    SNOWAGE_HR

    units :

    ppmV

    var_desc :

    VARIABLE SNOWAGE_HR

    [614400 values with dtype=float32]

  • PRATE_MMpH
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    PRATE_MMpH

    units :

    ppmV

    var_desc :

    VARIABLE PRATE_MMpH

    [614400 values with dtype=float32]

  • CLOUD_OD
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    CLOUD_OD

    units :

    ppmV

    var_desc :

    VARIABLE CLOUD_OD

    [614400 values with dtype=float32]

  • U10_MpS
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    U10_MpS

    units :

    ppmV

    var_desc :

    VARIABLE U10_MpS

    [614400 values with dtype=float32]

  • V10_MpS
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    V10_MpS

    units :

    ppmV

    var_desc :

    VARIABLE V10_MpS

    [614400 values with dtype=float32]

  • T2_K
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    T2_K

    units :

    ppmV

    var_desc :

    VARIABLE T2_K

    [614400 values with dtype=float32]

  • SWSFC_WpM2
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    SWSFC_WpM2

    units :

    ppmV

    var_desc :

    VARIABLE SWSFC_WpM2

    [614400 values with dtype=float32]

  • SOLM_M3pM3
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    SOLM_M3pM3

    units :

    ppmV

    var_desc :

    VARIABLE SOLM_M3pM3

    [614400 values with dtype=float32]

  • CLDTOP_KM
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    CLDTOP_KM

    units :

    ppmV

    var_desc :

    VARIABLE CLDTOP_KM

    [614400 values with dtype=float32]

  • CAPE
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    CAPE

    units :

    ppmV

    var_desc :

    VARIABLE CAPE

    [614400 values with dtype=float32]

  • PBL_WRF_M
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    PBL_WRF_M

    units :

    ppmV

    var_desc :

    VARIABLE PBL_WRF_M

    [614400 values with dtype=float32]

  • PBL_YSU_M
    (TSTEP, LAY, ROW, COL)
    float32
    ...

    long_name :

    PBL_YSU_M

    units :

    ppmV

    var_desc :

    VARIABLE PBL_YSU_M

    [614400 values with dtype=float32]

• Indexes: (0)
• Attributes: (33)

  IOAPI_VERSION :

  $Id: @(#) ioapi library version 3.0 $

  EXEC_ID :

  ????????????????

  FTYPE :

  1

  CDATE :

  2023207

  CTIME :

  72116

  WDATE :

  2023207

  WTIME :

  72116

  SDATE :

  2023207

  STIME :

  0

  TSTEP :

  10000

  NTHIK :

  1

  NCOLS :

  80

  NROWS :

  80

  NLAYS :

  1

  NVARS :

  14

  GDTYP :

  1

  P_ALP :

  0.0

  P_BET :

  0.0

  P_GAM :

  0.0

  XCENT :

  0.0

  YCENT :

  0.0

  XORIG :

  76.8499984741211

  YORIG :

  28.200000762939453

  XCELL :

  0.009999999776482582

  YCELL :

  0.009999999776482582

  VGTYP :

  -9999

  VGTOP :

  -9.999e+36

  VGLVLS :

  [0. 0.]

  GDNAM :

  ????????????????

  UPNAM :

  CAMx2IOAPI

  VAR-LIST :

  TSURF_K SNOWEW_M SNOWAGE_HR PRATE_MMpH CLOUD_OD U10_MpS V10_MpS T2_K SWSFC_WpM2 SOLM_M3pM3 CLDTOP_KM CAPE PBL_WRF_M PBL_YSU_M

  FILEDESC :

  I/O API formatted CAMx AVRG output

  HISTORY :

np.array([1, 2, 3])[:]

array([1, 2, 3])

import numpy as np
import pandas as pd

df = pd.DataFrame(columns=["lag"], index=list(ds_met.data_vars)[1:])

for lag in range(-24, 24):
    for var in list(ds_met.data_vars)[1:]:
        if lag == 0:
            met_series = ds_met[var].isel(LAY=0).mean(dim=["ROW", "COL"]).values
            aq_series = (
                ds_aq["P25"]
                .isel(LAY=0, TSTEP=range(24, 120))
                .mean(dim=["ROW", "COL"])
                .values
            )
        elif lag > 0:
            met_series = ds_met[var].isel(LAY=0).mean(dim=["ROW", "COL"]).values[lag:]
            aq_series = (
                ds_aq["P25"]
                .isel(LAY=0, TSTEP=range(24, 120))
                .mean(dim=["ROW", "COL"])
                .values[:-lag]
            )
        else:
            met_series = ds_met[var].isel(LAY=0).mean(dim=["ROW", "COL"]).values[:lag]
            aq_series = (
                ds_aq["P25"]
                .isel(LAY=0, TSTEP=range(24, 120))
                .mean(dim=["ROW", "COL"])
                .values[-lag:]
            )
        # print(f"{var}: {np.corrcoef(met_series, aq_series)[0, 1]}")
        df.loc[var, lag] = np.corrcoef(met_series, aq_series)[0, 1]

/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2897: RuntimeWarning: invalid value encountered in divide
  c /= stddev[:, None]
/home/patel_zeel/miniconda3/lib/python3.9/site-packages/numpy/lib/function_base.py:2898: RuntimeWarning: invalid value encountered in divide
  c /= stddev[None, :]

df.index.values

array(['TSURF_K', 'SNOWEW_M', 'SNOWAGE_HR', 'PRATE_MMpH', 'CLOUD_OD',
       'U10_MpS', 'V10_MpS', 'T2_K', 'SWSFC_WpM2', 'SOLM_M3pM3',
       'CLDTOP_KM', 'CAPE', 'PBL_WRF_M', 'PBL_YSU_M'], dtype=object)

import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation

plt.figure(figsize=(6, 3))
for var in ["TSURF_K", "T2_K", "SWSFC_WpM2", "PBL_WRF_M", "PBL_YSU_M"]:
    df.loc[var].plot(label=var)
for var in ["CLOUD_OD", "V10_MpS"]:
    df.loc[var].plot(label=var, linestyle="--")

plt.legend(bbox_to_anchor=(1, 1))
plt.ylabel("Correlation with P25 from CAMx")
plt.tight_layout()
plt.savefig("lag.pdf")

plt.rcParams["animation.html"] = "jshtml"
fig, ax = plt.subplots(figsize=(15, 4))
mappable = (
    ds_met["PBL_WRF_M"]
    .isel(TSTEP=1, LAY=0)
    .plot(
        x="COL", y="ROW", cmap="RdYlGn_r", ax=ax, vmin=0, vmax=2000, add_colorbar=False
    )
)
fig.colorbar(mappable)


def plot_it(t):
    ax.cla()
    tmp = ds_met["PBL_WRF_M"].isel(TSTEP=t, LAY=0)
    tmp.plot(
        x="COL", y="ROW", cmap="RdYlGn_r", ax=ax, vmin=0, vmax=2000, add_colorbar=False
    )
    ax.set_xlabel("Longitude")
    ax.set_ylabel("Latitude")
    ax.set_title(f"Mean PBLH: {tmp.mean().values:.2f} m")


anim = FuncAnimation(fig, plot_it, frames=range(1, 13), interval=500)
plt.close()
anim

Once Loop Reflect

from aqmsp_data.data import load_caaqm

caaqm = load_caaqm(years=2022, months=1, days=1, variables="PM2.5")

import pandas as pd
from glob import glob

files = glob("/home/patel_zeel/aqmsp/aqmsp_data/data/caaqm/raw_2023/*.xlsx")

df = pd.read_excel(
    files[-3],
    header=None,
)
# print(df.head(7))
station = df.iloc[6, 1]
lat = caaqm.sel(station=station).latitude.values.item()
lon = caaqm.sel(station=station).longitude.values.item()
df = df.iloc[16:, :]
# assign first row as column names
df.columns = df.iloc[0].values
# drop first row
df = df.iloc[1:, :]
print(station)
df["time"] = pd.to_datetime(df["From Date"], format="%d-%m-%Y %H:%M") + pd.Timedelta(
    minutes=30
)
df

Vivek Vihar, Delhi - DPCC

	From Date	To Date	PM2.5	PM10	AT	BP	RH	time
17	01-01-2023 00:00	01-01-2023 01:00	141	211	11.95	997.83	78.9	2023-01-01 00:30:00
18	01-01-2023 01:00	01-01-2023 02:00	149	210	11.85	997.47	79.1	2023-01-01 01:30:00
19	01-01-2023 02:00	01-01-2023 03:00	141	186	11.3	997.03	80.25	2023-01-01 02:30:00
20	01-01-2023 03:00	01-01-2023 04:00	138	174	10.3	996.5	83.33	2023-01-01 03:30:00
21	01-01-2023 04:00	01-01-2023 05:00	122	161	10.05	996.38	84.08	2023-01-01 04:30:00
...	...	...	...	...	...	...	...	...
5077	30-07-2023 20:00	30-07-2023 21:00	14	95.75	30.87	972.4	66.17	2023-07-30 20:30:00
5078	30-07-2023 21:00	30-07-2023 22:00	18.25	114.75	30.6	972.42	69.22	2023-07-30 21:30:00
5079	30-07-2023 22:00	30-07-2023 23:00	20.5	100.5	30.48	972.43	72	2023-07-30 22:30:00
5080	30-07-2023 23:00	31-07-2023 00:00	17.75	103	30.42	972.35	71.92	2023-07-30 23:30:00
5081	31-07-2023 00:00	31-07-2023 00:00	23	124	30.4	972.3	71.8	2023-07-31 00:30:00

5065 rows × 8 columns

def process_it(ds, date):
    if ds.TSTEP.size == 120:
        print("120")
        ds = ds.isel(LAY=0, TSTEP=range(24, 48))
    else:
        print("96")
        ds = ds.isel(LAY=0, TSTEP=range(24))
    ds1 = ds.assign(time=("TSTEP", pd.date_range(date, periods=24, freq="H")))
    lats = np.arange(80) * ds1.YCELL + ds1.YORIG
    lons = np.arange(80) * ds1.XCELL + ds1.XORIG
    ds2 = ds1.assign_coords(lat=("ROW", lats), lon=("COL", lons))
    ds3 = ds2.swap_dims({"TSTEP": "time", "ROW": "lat", "COL": "lon"})
    ds3["time"] = ds3["time"] + pd.Timedelta(hours=5, minutes=30)
    return ds3


ds_met_processed = process_it(ds_met, global_date)
ds_met_processed

96

<xarray.Dataset>
Dimensions:     (time: 24, VAR: 14, DATE-TIME: 2, lat: 80, lon: 80)
Coordinates:
  * time        (time) datetime64[ns] 2023-07-26T05:30:00 ... 2023-07-27T04:3...
  * lat         (lat) float64 28.2 28.21 28.22 28.23 ... 28.96 28.97 28.98 28.99
  * lon         (lon) float64 76.85 76.86 76.87 76.88 ... 77.62 77.63 77.64
Dimensions without coordinates: VAR, DATE-TIME
Data variables: (12/15)
    TFLAG       (time, VAR, DATE-TIME) int32 ...
    TSURF_K     (time, lat, lon) float32 ...
    SNOWEW_M    (time, lat, lon) float32 ...
    SNOWAGE_HR  (time, lat, lon) float32 ...
    PRATE_MMpH  (time, lat, lon) float32 ...
    CLOUD_OD    (time, lat, lon) float32 ...
    ...          ...
    SWSFC_WpM2  (time, lat, lon) float32 ...
    SOLM_M3pM3  (time, lat, lon) float32 ...
    CLDTOP_KM   (time, lat, lon) float32 ...
    CAPE        (time, lat, lon) float32 ...
    PBL_WRF_M   (time, lat, lon) float32 ...
    PBL_YSU_M   (time, lat, lon) float32 ...
Attributes: (12/33)
    IOAPI_VERSION:  $Id: @(#) ioapi library version 3.0 $                    ...
    EXEC_ID:        ????????????????                                         ...
    FTYPE:          1
    CDATE:          2023207
    CTIME:          72116
    WDATE:          2023207
    ...             ...
    VGLVLS:         [0. 0.]
    GDNAM:          ????????????????
    UPNAM:          CAMx2IOAPI      
    VAR-LIST:       TSURF_K         SNOWEW_M        SNOWAGE_HR      PRATE_MMp...
    FILEDESC:       I/O API formatted CAMx AVRG output                       ...
    HISTORY:        

xarray.Dataset

• Dimensions:
  • time: 24
  • VAR: 14
  • DATE-TIME: 2
  • lat: 80
  • lon: 80
• Coordinates: (3)
  • time
    (time)
    datetime64[ns]
    2023-07-26T05:30:00 ... 2023-07-...

    array(['2023-07-26T05:30:00.000000000', '2023-07-26T06:30:00.000000000',
           '2023-07-26T07:30:00.000000000', '2023-07-26T08:30:00.000000000',
           '2023-07-26T09:30:00.000000000', '2023-07-26T10:30:00.000000000',
           '2023-07-26T11:30:00.000000000', '2023-07-26T12:30:00.000000000',
           '2023-07-26T13:30:00.000000000', '2023-07-26T14:30:00.000000000',
           '2023-07-26T15:30:00.000000000', '2023-07-26T16:30:00.000000000',
           '2023-07-26T17:30:00.000000000', '2023-07-26T18:30:00.000000000',
           '2023-07-26T19:30:00.000000000', '2023-07-26T20:30:00.000000000',
           '2023-07-26T21:30:00.000000000', '2023-07-26T22:30:00.000000000',
           '2023-07-26T23:30:00.000000000', '2023-07-27T00:30:00.000000000',
           '2023-07-27T01:30:00.000000000', '2023-07-27T02:30:00.000000000',
           '2023-07-27T03:30:00.000000000', '2023-07-27T04:30:00.000000000'],
          dtype='datetime64[ns]')

  • lat
    (lat)
    float64
    28.2 28.21 28.22 ... 28.98 28.99

    array([28.200001, 28.210001, 28.220001, 28.230001, 28.240001, 28.250001,
           28.260001, 28.270001, 28.280001, 28.290001, 28.300001, 28.310001,
           28.320001, 28.330001, 28.340001, 28.350001, 28.360001, 28.370001,
           28.380001, 28.390001, 28.400001, 28.410001, 28.420001, 28.430001,
           28.440001, 28.450001, 28.460001, 28.470001, 28.480001, 28.490001,
           28.500001, 28.510001, 28.520001, 28.530001, 28.540001, 28.550001,
           28.560001, 28.570001, 28.580001, 28.590001, 28.600001, 28.610001,
           28.620001, 28.630001, 28.640001, 28.650001, 28.660001, 28.670001,
           28.680001, 28.690001, 28.700001, 28.710001, 28.720001, 28.730001,
           28.740001, 28.750001, 28.760001, 28.770001, 28.780001, 28.790001,
           28.800001, 28.810001, 28.820001, 28.830001, 28.840001, 28.850001,
           28.860001, 28.870001, 28.880001, 28.890001, 28.900001, 28.910001,
           28.920001, 28.930001, 28.940001, 28.950001, 28.960001, 28.970001,
           28.980001, 28.990001])

  • lon
    (lon)
    float64
    76.85 76.86 76.87 ... 77.63 77.64

    array([76.849998, 76.859998, 76.869998, 76.879998, 76.889998, 76.899998,
           76.909998, 76.919998, 76.929998, 76.939998, 76.949998, 76.959998,
           76.969998, 76.979998, 76.989998, 76.999998, 77.009998, 77.019998,
           77.029998, 77.039998, 77.049998, 77.059998, 77.069998, 77.079998,
           77.089998, 77.099998, 77.109998, 77.119998, 77.129998, 77.139998,
           77.149998, 77.159998, 77.169998, 77.179998, 77.189998, 77.199998,
           77.209998, 77.219998, 77.229998, 77.239998, 77.249998, 77.259998,
           77.269998, 77.279998, 77.289998, 77.299998, 77.309998, 77.319998,
           77.329998, 77.339998, 77.349998, 77.359998, 77.369998, 77.379998,
           77.389998, 77.399998, 77.409998, 77.419998, 77.429998, 77.439998,
           77.449998, 77.459998, 77.469998, 77.479998, 77.489998, 77.499998,
           77.509998, 77.519998, 77.529998, 77.539998, 77.549998, 77.559998,
           77.569998, 77.579998, 77.589998, 77.599998, 77.609998, 77.619998,
           77.629998, 77.639998])

• Data variables: (15)
  • TFLAG
    (time, VAR, DATE-TIME)
    int32
    ...

    units :

    <YYYYDDD,HHMMSS>

    long_name :

    TFLAG

    var_desc :

    Timestep-valid flags: (1) YYYYDDD or (2) HHMMSS

    [672 values with dtype=int32]

  • TSURF_K
    (time, lat, lon)
    float32
    ...

    long_name :

    TSURF_K

    units :

    ppmV

    var_desc :

    VARIABLE TSURF_K

    [153600 values with dtype=float32]

  • SNOWEW_M
    (time, lat, lon)
    float32
    ...

    long_name :

    SNOWEW_M

    units :

    ppmV

    var_desc :

    VARIABLE SNOWEW_M

    [153600 values with dtype=float32]

  • SNOWAGE_HR
    (time, lat, lon)
    float32
    ...

    long_name :

    SNOWAGE_HR

    units :

    ppmV

    var_desc :

    VARIABLE SNOWAGE_HR

    [153600 values with dtype=float32]

  • PRATE_MMpH
    (time, lat, lon)
    float32
    ...

    long_name :

    PRATE_MMpH

    units :

    ppmV

    var_desc :

    VARIABLE PRATE_MMpH

    [153600 values with dtype=float32]

  • CLOUD_OD
    (time, lat, lon)
    float32
    ...

    long_name :

    CLOUD_OD

    units :

    ppmV

    var_desc :

    VARIABLE CLOUD_OD

    [153600 values with dtype=float32]

  • U10_MpS
    (time, lat, lon)
    float32
    ...

    long_name :

    U10_MpS

    units :

    ppmV

    var_desc :

    VARIABLE U10_MpS

    [153600 values with dtype=float32]

  • V10_MpS
    (time, lat, lon)
    float32
    ...

    long_name :

    V10_MpS

    units :

    ppmV

    var_desc :

    VARIABLE V10_MpS

    [153600 values with dtype=float32]

  • T2_K
    (time, lat, lon)
    float32
    ...

    long_name :

    T2_K

    units :

    ppmV

    var_desc :

    VARIABLE T2_K

    [153600 values with dtype=float32]

  • SWSFC_WpM2
    (time, lat, lon)
    float32
    ...

    long_name :

    SWSFC_WpM2

    units :

    ppmV

    var_desc :

    VARIABLE SWSFC_WpM2

    [153600 values with dtype=float32]

  • SOLM_M3pM3
    (time, lat, lon)
    float32
    ...

    long_name :

    SOLM_M3pM3

    units :

    ppmV

    var_desc :

    VARIABLE SOLM_M3pM3

    [153600 values with dtype=float32]

  • CLDTOP_KM
    (time, lat, lon)
    float32
    ...

    long_name :

    CLDTOP_KM

    units :

    ppmV

    var_desc :

    VARIABLE CLDTOP_KM

    [153600 values with dtype=float32]

  • CAPE
    (time, lat, lon)
    float32
    ...

    long_name :

    CAPE

    units :

    ppmV

    var_desc :

    VARIABLE CAPE

    [153600 values with dtype=float32]

  • PBL_WRF_M
    (time, lat, lon)
    float32
    ...

    long_name :

    PBL_WRF_M

    units :

    ppmV

    var_desc :

    VARIABLE PBL_WRF_M

    [153600 values with dtype=float32]

  • PBL_YSU_M
    (time, lat, lon)
    float32
    ...

    long_name :

    PBL_YSU_M

    units :

    ppmV

    var_desc :

    VARIABLE PBL_YSU_M

    [153600 values with dtype=float32]

• Indexes: (3)
  • time
    PandasIndex

    PandasIndex(DatetimeIndex(['2023-07-26 05:30:00', '2023-07-26 06:30:00',
                   '2023-07-26 07:30:00', '2023-07-26 08:30:00',
                   '2023-07-26 09:30:00', '2023-07-26 10:30:00',
                   '2023-07-26 11:30:00', '2023-07-26 12:30:00',
                   '2023-07-26 13:30:00', '2023-07-26 14:30:00',
                   '2023-07-26 15:30:00', '2023-07-26 16:30:00',
                   '2023-07-26 17:30:00', '2023-07-26 18:30:00',
                   '2023-07-26 19:30:00', '2023-07-26 20:30:00',
                   '2023-07-26 21:30:00', '2023-07-26 22:30:00',
                   '2023-07-26 23:30:00', '2023-07-27 00:30:00',
                   '2023-07-27 01:30:00', '2023-07-27 02:30:00',
                   '2023-07-27 03:30:00', '2023-07-27 04:30:00'],
                  dtype='datetime64[ns]', name='time', freq=None))

  • lat
    PandasIndex

    PandasIndex(Index([28.200000762939453, 28.210000762715936,  28.22000076249242,
             28.2300007622689, 28.240000762045383, 28.250000761821866,
            28.26000076159835,  28.27000076137483, 28.280000761151314,
           28.290000760927796,  28.30000076070428,  28.31000076048076,
           28.320000760257244, 28.330000760033727,  28.34000075981021,
           28.350000759586692, 28.360000759363174, 28.370000759139657,
            28.38000075891614, 28.390000758692622, 28.400000758469105,
           28.410000758245587,  28.42000075802207, 28.430000757798553,
           28.440000757575035, 28.450000757351518,    28.460000757128,
           28.470000756904483, 28.480000756680965, 28.490000756457448,
            28.50000075623393, 28.510000756010413, 28.520000755786896,
            28.53000075556338,  28.54000075533986, 28.550000755116343,
           28.560000754892826,  28.57000075466931,  28.58000075444579,
           28.590000754222274, 28.600000753998756,  28.61000075377524,
            28.62000075355172, 28.630000753328204, 28.640000753104687,
            28.65000075288117, 28.660000752657652, 28.670000752434134,
           28.680000752210617,   28.6900007519871, 28.700000751763582,
           28.710000751540065, 28.720000751316547,  28.73000075109303,
           28.740000750869513, 28.750000750645995, 28.760000750422478,
            28.77000075019896, 28.780000749975443, 28.790000749751925,
           28.800000749528408,  28.81000074930489, 28.820000749081373,
           28.830000748857856,  28.84000074863434,  28.85000074841082,
           28.860000748187304, 28.870000747963786,  28.88000074774027,
            28.89000074751675, 28.900000747293234, 28.910000747069716,
             28.9200007468462,  28.93000074662268, 28.940000746399164,
           28.950000746175647,  28.96000074595213, 28.970000745728612,
           28.980000745505095, 28.990000745281577],
          dtype='float64', name='lat'))

  • lon
    PandasIndex

    PandasIndex(Index([ 76.8499984741211, 76.85999847389758, 76.86999847367406,
           76.87999847345054, 76.88999847322702,  76.8999984730035,
           76.90999847277999, 76.91999847255647, 76.92999847233295,
           76.93999847210944, 76.94999847188592,  76.9599984716624,
           76.96999847143888, 76.97999847121537, 76.98999847099185,
           76.99999847076833, 77.00999847054482,  77.0199984703213,
           77.02999847009778, 77.03999846987426, 77.04999846965075,
           77.05999846942723, 77.06999846920371,  77.0799984689802,
           77.08999846875668, 77.09999846853316, 77.10999846830964,
           77.11999846808612,  77.1299984678626, 77.13999846763909,
           77.14999846741557, 77.15999846719205, 77.16999846696854,
           77.17999846674502,  77.1899984665215, 77.19999846629798,
           77.20999846607447, 77.21999846585095, 77.22999846562743,
           77.23999846540391,  77.2499984651804, 77.25999846495688,
           77.26999846473336, 77.27999846450984, 77.28999846428633,
           77.29999846406281, 77.30999846383929, 77.31999846361578,
           77.32999846339226, 77.33999846316874, 77.34999846294522,
            77.3599984627217, 77.36999846249819, 77.37999846227467,
           77.38999846205115, 77.39999846182764, 77.40999846160412,
            77.4199984613806, 77.42999846115708, 77.43999846093357,
           77.44999846071005, 77.45999846048653, 77.46999846026301,
            77.4799984600395, 77.48999845981598, 77.49999845959246,
           77.50999845936894, 77.51999845914543, 77.52999845892191,
           77.53999845869839, 77.54999845847487, 77.55999845825136,
           77.56999845802784, 77.57999845780432,  77.5899984575808,
           77.59999845735729, 77.60999845713377, 77.61999845691025,
           77.62999845668674, 77.63999845646322],
          dtype='float64', name='lon'))

• Attributes: (33)

  IOAPI_VERSION :

  $Id: @(#) ioapi library version 3.0 $

  EXEC_ID :

  ????????????????

  FTYPE :

  1

  CDATE :

  2023207

  CTIME :

  72116

  WDATE :

  2023207

  WTIME :

  72116

  SDATE :

  2023207

  STIME :

  0

  TSTEP :

  10000

  NTHIK :

  1

  NCOLS :

  80

  NROWS :

  80

  NLAYS :

  1

  NVARS :

  14

  GDTYP :

  1

  P_ALP :

  0.0

  P_BET :

  0.0

  P_GAM :

  0.0

  XCENT :

  0.0

  YCENT :

  0.0

  XORIG :

  76.8499984741211

  YORIG :

  28.200000762939453

  XCELL :

  0.009999999776482582

  YCELL :

  0.009999999776482582

  VGTYP :

  -9999

  VGTOP :

  -9.999e+36

  VGLVLS :

  [0. 0.]

  GDNAM :

  ????????????????

  UPNAM :

  CAMx2IOAPI

  VAR-LIST :

  TSURF_K SNOWEW_M SNOWAGE_HR PRATE_MMpH CLOUD_OD U10_MpS V10_MpS T2_K SWSFC_WpM2 SOLM_M3pM3 CLDTOP_KM CAPE PBL_WRF_M PBL_YSU_M

  FILEDESC :

  I/O API formatted CAMx AVRG output

  HISTORY :

closest_ds = ds_met_processed.sel(lat=lat, lon=lon, method="nearest")
fig, ax = plt.subplots(figsize=(15, 4))

print(lat, lon)
closest_ds["TSURF_K"].plot(ax=ax, label="TSURF_K")
closest_ds["T2_K"].plot(ax=ax, label="T2_K")
tmp_df = df.set_index("time")
# select data from global_data
tmp_df = tmp_df.loc[closest_ds["time"].values[0] : closest_ds["time"].values[-1]]
tmp_df["AT_K"] = tmp_df["AT"] + 273.15
tmp_df.plot(ax=ax, y="AT_K")
plt.legend()
# tmp_df

28.672342 77.31526