Precipitation#

An introduction to Synoptic’s Precipitation service using SynopticPy.

[2]:

from datetime import datetime, timedelta

import matplotlib.dates as mdates
import matplotlib.pyplot as plt
import polars as pl

from synoptic.services import Precipitation

Daily Precipitation#

Let’s get the daily precipitation at a single station for August 2024 and plot the daily accumulation with a running total for the month.

[3]:

df = Precipitation(
    stid="wbb",
    start=datetime(2024, 8, 1),
    end=datetime(2024, 9, 1),
    pmode="intervals",
    units="english",
    interval="day",
).df()

# Calculate cumulative precipitation for the time period
df = df.with_columns(cum_sum=pl.col("total").cum_sum())
df

🚚💨 Speedy delivery from Synoptic precipitation service.
📦 Received data from 1 stations.

[3]:

shape: (31, 21)

total	first_report	last_report	count	interval	report_type	units	id	stid	name	elevation	latitude	longitude	mnet_id	state	timezone	elev_dem	period_of_record	is_restricted	is_active	cum_sum
f64	datetime[μs, UTC]	datetime[μs, UTC]	i64	i64	str	str	u32	str	str	f64	f64	f64	u32	str	str	f64	struct[2]	bool	bool	f64
0.0	2024-08-01 00:00:00 UTC	2024-08-02 00:00:00 UTC	1440	1	"precip_accum_one_minute"	"Inches"	1	"WBB"	"U of U William Browning Buildi…	4806.0	40.76623	-111.84755	153	"UT"	"America/Denver"	4727.7	{"1997-01-01T00:00:00Z","2024-10-17T05:50:00Z"}	false	true	0.0
0.0	2024-08-02 00:00:00 UTC	2024-08-03 00:00:00 UTC	1440	2	"precip_accum_one_minute"	"Inches"	1	"WBB"	"U of U William Browning Buildi…	4806.0	40.76623	-111.84755	153	"UT"	"America/Denver"	4727.7	{"1997-01-01T00:00:00Z","2024-10-17T05:50:00Z"}	false	true	0.0
0.0	2024-08-03 00:00:00 UTC	2024-08-04 00:00:00 UTC	1440	3	"precip_accum_one_minute"	"Inches"	1	"WBB"	"U of U William Browning Buildi…	4806.0	40.76623	-111.84755	153	"UT"	"America/Denver"	4727.7	{"1997-01-01T00:00:00Z","2024-10-17T05:50:00Z"}	false	true	0.0
0.0	2024-08-04 00:00:00 UTC	2024-08-05 00:00:00 UTC	1440	4	"precip_accum_one_minute"	"Inches"	1	"WBB"	"U of U William Browning Buildi…	4806.0	40.76623	-111.84755	153	"UT"	"America/Denver"	4727.7	{"1997-01-01T00:00:00Z","2024-10-17T05:50:00Z"}	false	true	0.0
0.0	2024-08-05 00:00:00 UTC	2024-08-06 00:00:00 UTC	1440	5	"precip_accum_one_minute"	"Inches"	1	"WBB"	"U of U William Browning Buildi…	4806.0	40.76623	-111.84755	153	"UT"	"America/Denver"	4727.7	{"1997-01-01T00:00:00Z","2024-10-17T05:50:00Z"}	false	true	0.0
…	…	…	…	…	…	…	…	…	…	…	…	…	…	…	…	…	…	…	…	…
0.0	2024-08-27 00:00:00 UTC	2024-08-28 00:00:00 UTC	1440	27	"precip_accum_one_minute"	"Inches"	1	"WBB"	"U of U William Browning Buildi…	4806.0	40.76623	-111.84755	153	"UT"	"America/Denver"	4727.7	{"1997-01-01T00:00:00Z","2024-10-17T05:50:00Z"}	false	true	1.15
0.0	2024-08-28 00:00:00 UTC	2024-08-29 00:00:00 UTC	1406	28	"precip_accum_one_minute"	"Inches"	1	"WBB"	"U of U William Browning Buildi…	4806.0	40.76623	-111.84755	153	"UT"	"America/Denver"	4727.7	{"1997-01-01T00:00:00Z","2024-10-17T05:50:00Z"}	false	true	1.15
0.0	2024-08-29 00:00:00 UTC	2024-08-30 00:00:00 UTC	1440	29	"precip_accum_one_minute"	"Inches"	1	"WBB"	"U of U William Browning Buildi…	4806.0	40.76623	-111.84755	153	"UT"	"America/Denver"	4727.7	{"1997-01-01T00:00:00Z","2024-10-17T05:50:00Z"}	false	true	1.15
0.0	2024-08-30 00:00:00 UTC	2024-08-31 00:00:00 UTC	1440	30	"precip_accum_one_minute"	"Inches"	1	"WBB"	"U of U William Browning Buildi…	4806.0	40.76623	-111.84755	153	"UT"	"America/Denver"	4727.7	{"1997-01-01T00:00:00Z","2024-10-17T05:50:00Z"}	false	true	1.15
0.0	2024-08-31 00:00:00 UTC	2024-09-01 00:00:00 UTC	1440	31	"precip_accum_one_minute"	"Inches"	1	"WBB"	"U of U William Browning Buildi…	4806.0	40.76623	-111.84755	153	"UT"	"America/Denver"	4727.7	{"1997-01-01T00:00:00Z","2024-10-17T05:50:00Z"}	false	true	1.15

[4]:

plt.figure(figsize=(10, 5))
ax = plt.gca()

ax.plot(df["last_report"], df["cum_sum"], marker="o", label="Total")
ax.bar(
    df["first_report"],
    df["total"],
    width=timedelta(days=1),
    align="edge",
    edgecolor="w",
    color="tab:green",
    label="Daily",
)
ax.xaxis.set_major_formatter(mdates.DateFormatter("%d %b\n%Y"))
ax.xaxis.set_major_locator(mdates.WeekdayLocator(1))
ax.xaxis.set_minor_locator(mdates.DayLocator())
ax.set_xlim(df["first_report"].min(), df["first_report"].max())

# ---------
# Cosmetics
ax.set_ylabel("Precipitation (inches)")
ax.set_title("August 2024 Precipitation at WBB")
ax.legend()

[4]:

<matplotlib.legend.Legend at 0x7f21a6babbf0>

../../_images/user_guide_services_tutorials_Precipitation_4_1.png

Stations with more than 1 inch precipitation in a week#

[5]:

df = Precipitation(
    state="UT",
    pmode="totals",
    start="2024-06-01",
    end="2024-06-07",
    units="english",
).df()

🚚💨 Speedy delivery from Synoptic precipitation service.
📦 Received data from 1,050 stations.

[6]:

df.filter(pl.col("total") > 1).sort("total")

[6]:

shape: (3, 19)

total	first_report	last_report	count	report_type	units	id	stid	name	elevation	latitude	longitude	mnet_id	state	timezone	elev_dem	period_of_record	is_restricted	is_active
f64	datetime[μs, UTC]	datetime[μs, UTC]	i64	str	str	u32	str	str	f64	f64	f64	u32	str	str	f64	struct[2]	bool	bool
1.1	2024-06-01 00:00:00 UTC	2024-06-07 00:00:00 UTC	144	"precip_accum"	"Inches"	1490	"MCRU1"	"MONTE CRISTO"	8931.0	41.46547	-111.49688	25	"UT"	"America/Denver"	8950.1	{"2000-01-20T00:00:00Z","2024-10-17T04:00:00Z"}	false	true
1.43	2024-06-01 00:00:00 UTC	2024-06-07 00:00:00 UTC	576	"precip_accum_fifteen_minute"	"Inches"	72189	"UCC42"	"Centerfield"	5164.0	39.09943	-111.8077	194	"UT"	"America/Denver"	5164.0	{"2018-09-18T18:04:00Z","2024-10-17T04:45:00Z"}	false	true
3.62	2024-06-01 00:00:00 UTC	2024-06-07 00:00:00 UTC	556	"precip_accum"	"Inches"	2957	"BLKU1"	"BLACKS FORK COMMISSARY NEAR CO…	8845.0	40.96083	-110.57944	106	"UT"	"America/Denver"	8848.4	{"2001-06-06T00:00:00Z","2024-10-17T04:15:00Z"}	false	true