Try this notebook in 
.
[1]:
!test -f syn_new.bufr || wget https://get.ecmwf.int/repository/test-data/pdbufr/test-data/syn_new.bufr
Synop: overview
[2]:
import pdbufr
The input BUFR data contains three Synop observations. In this notebook we will read this file with the synop reader, which uses pre-defined parameters instead of the ecCodes BUFR keys. Parameter is a high-level concept in pdbufr enabling data extraction without knowing the actual BUFR encoding and allowing more tailor-made access to specific data types.
The default settings
By default the “stnid”, “lat”, “lon”, “elevation”, “time” (see station parameters for details) and the default observed parameters are extracted.
[3]:
df = pdbufr.read_bufr("syn_new.bufr", reader="synop")
[4]:
df.T
[4]:
| 0 | 1 | 2 | |
|---|---|---|---|
| stnid | 91948 | 11766 | 56257 |
| lat | -23.13017 | 49.77722 | 30.0 |
| lon | -134.96533 | 17.54194 | 100.27 |
| elevation | 91.0 | 748.1 | 3950.0 |
| time | 2020-03-15 00:00:00 | 2020-03-15 00:00:00 | 2020-03-15 00:00:00 |
| t2m | 300.45 | 269.25 | 276.35 |
| rh2m | 73 | 65 | 37 |
| td2m | 295.15 | 263.55 | 263.05 |
| wind10m_speed | 1.6 | 4.0 | 2.5 |
| wind10m_dir | 100 | 60 | 229 |
| max_wgust_speed_10min | 5.3 | NaN | NaN |
| max_wgust_dir_10min | 110.0 | NaN | NaN |
| max_wgust_speed_60min | 5.3 | NaN | NaN |
| max_wgust_dir_60min | 110.0 | NaN | NaN |
| max_wgust_speed_360min | 7.6 | NaN | NaN |
| max_wgust_dir_360min | 130.0 | NaN | NaN |
| max_wgust_speed_nan | NaN | NaN | NaN |
| max_wgust_dir_nan | NaN | NaN | NaN |
| max_wgust_speed_720min | NaN | NaN | 8.9 |
| max_wgust_dir_720min | NaN | NaN | 193.0 |
| present_weather | 2 | 508 | 0 |
| past_weather_1_1h | 0.0 | NaN | NaN |
| past_weather_2_1h | 0.0 | NaN | NaN |
| past_weather_1_6h | 0.0 | 10.0 | NaN |
| past_weather_2_6h | 0.0 | 10.0 | NaN |
| past_weather_1_12h | NaN | NaN | 0.0 |
| past_weather_2_12h | NaN | NaN | 0.0 |
| precipitation_1h | 0.0 | 0.0 | NaN |
| precipitation_3h | 0.0 | NaN | NaN |
| precipitation_6h | 0.0 | 0.0 | 0.0 |
| precipitation_12h | 0.0 | NaN | 0.0 |
| precipitation_24h | 0.0 | NaN | 0.0 |
| min_t2m_60min | NaN | NaN | NaN |
| min_t2m_0h | 296.45 | NaN | 272.65 |
| max_t2m_60min | 300.75 | NaN | NaN |
| max_t2m_nan | NaN | NaN | NaN |
| max_t2m_0h | NaN | NaN | 288.35 |
| mslp | 101320.0 | NaN | 100440.0 |
| pressure | 100310.0 | 93680.0 | 63030.0 |
| cloud_cover | 25.0 | NaN | 0.0 |
| snow_depth | NaN | NaN | 0.0 |
| visibility | NaN | 30000.0 | 30000.0 |
Using parameter groups
[5]:
df = pdbufr.read_bufr("syn_new.bufr", reader="synop", columns="station")
[6]:
df.T
[6]:
| 0 | 1 | 2 | |
|---|---|---|---|
| stnid | 91948 | 11766 | 56257 |
| lat | -23.13017 | 49.77722 | 30.0 |
| lon | -134.96533 | 17.54194 | 100.27 |
| elevation | 91.0 | 748.1 | 3950.0 |
| time | 2020-03-15 00:00:00 | 2020-03-15 00:00:00 | 2020-03-15 00:00:00 |
[7]:
df = pdbufr.read_bufr("syn_new.bufr", reader="synop", columns="location")
[8]:
df.T
[8]:
| 0 | 1 | 2 | |
|---|---|---|---|
| lat | -23.13017 | 49.77722 | 30.00 |
| lon | -134.96533 | 17.54194 | 100.27 |
[9]:
df = pdbufr.read_bufr("syn_new.bufr", reader="synop", columns="geometry")
[10]:
df.T
[10]:
| 0 | 1 | 2 | |
|---|---|---|---|
| lat | -23.13017 | 49.77722 | 30.00 |
| lon | -134.96533 | 17.54194 | 100.27 |
| elevation | 91.00000 | 748.10000 | 3950.00 |
Using individual parameters
[11]:
df = pdbufr.read_bufr("syn_new.bufr", reader="synop", columns="t2m")
[12]:
df.T
[12]:
| 0 | 1 | 2 | |
|---|---|---|---|
| t2m | 300.45 | 269.25 | 276.35 |
[13]:
df = pdbufr.read_bufr("syn_new.bufr", reader="synop", columns=["station", "t2m", "td2m", "total_sunshine"])
[14]:
df.T
[14]:
| 0 | 1 | 2 | |
|---|---|---|---|
| stnid | 91948 | 11766 | 56257 |
| lat | -23.13017 | 49.77722 | 30.0 |
| lon | -134.96533 | 17.54194 | 100.27 |
| elevation | 91.0 | 748.1 | 3950.0 |
| time | 2020-03-15 00:00:00 | 2020-03-15 00:00:00 | 2020-03-15 00:00:00 |
| t2m | 300.45 | 269.25 | 276.35 |
| td2m | 295.15 | 263.55 | 263.05 |
| total_sunshine_1h | 39.0 | NaN | NaN |
| total_sunshine_24h | 535.0 | 486.0 | NaN |
Adding level columns
[15]:
df = pdbufr.read_bufr("syn_new.bufr", reader="synop",
columns=["station", "t2m", "td2m"],
level_columns=True)
[16]:
df.T
[16]:
| 0 | 1 | 2 | |
|---|---|---|---|
| stnid | 91948 | 11766 | 56257 |
| lat | -23.13017 | 49.77722 | 30.0 |
| lon | -134.96533 | 17.54194 | 100.27 |
| elevation | 91.0 | 748.1 | 3950.0 |
| time | 2020-03-15 00:00:00 | 2020-03-15 00:00:00 | 2020-03-15 00:00:00 |
| t2m | 300.45 | 269.25 | 276.35 |
| t2m_level | 1.5 | 2.0 | 1.5 |
| td2m | 295.15 | 263.55 | 263.05 |
| td2m_level | 1.5 | 2.0 | 1.5 |
Adding units columns
[17]:
df = pdbufr.read_bufr("syn_new.bufr", reader="synop",
columns=["station", "t2m", "td2m"],
units_columns=True)
[18]:
df.T
[18]:
| 0 | 1 | 2 | |
|---|---|---|---|
| stnid | 91948 | 11766 | 56257 |
| lat | -23.13017 | 49.77722 | 30.0 |
| lat_units | deg | deg | deg |
| lon | -134.96533 | 17.54194 | 100.27 |
| lon_units | deg | deg | deg |
| elevation | 91.0 | 748.1 | 3950.0 |
| elevation_units | m | m | m |
| time | 2020-03-15 00:00:00 | 2020-03-15 00:00:00 | 2020-03-15 00:00:00 |
| t2m | 300.45 | 269.25 | 276.35 |
| t2m_units | K | K | K |
| td2m | 295.15 | 263.55 | 263.05 |
| td2m_units | K | K | K |
[ ]: