Historical precipitation data is useful for agriculture, insurance, transportation, construction, event analysis, research, and many other weather-sensitive applications.
Visual Crossing provides historical precipitation data through the Visual Crossing Weather API and interactive Weather Data tools.
You can retrieve precipitation for a specific location and date, a range of dates, or a longer historical period.
To use the Weather API, sign up for a free Visual Crossing account and obtain your API key.
What historical precipitation data is available?
The Timeline Weather API includes several precipitation-related fields.
Precipitation amount (precip)
The precip field is the amount of precipitation that fell during the requested period.
It includes the liquid-equivalent amount of rain, snow, freezing precipitation, and other precipitation.
For example:
{
"datetime": "2026-08-20",
"precip": 12.4
}
When using metric units, precipitation is reported in millimeters.
When using US units, precipitation is reported in inches.
For daily records, precip represents the precipitation accumulated during that day.
Precipitation coverage (precipcover)
The precipcover field indicates the percentage of the reporting period during which measurable precipitation occurred.
For example, if precipitation was recorded during 6 hours of a 24-hour day:
6 / 24 × 100 = 25%
the daily precipitation coverage would be approximately:
25
This can help distinguish between a short heavy rainfall event and precipitation that continued for much of the day.
Historical precipitation coverage is particularly useful when the total precipitation amount alone does not describe how the precipitation was distributed through the period.
Precipitation type (preciptype)
The preciptype field identifies the type or types of precipitation that occurred.
Possible values can include:
rain
snow
freezingrain
ice
A daily record can contain more than one precipitation type if different types occurred during the day.
Snow (snow)
The snow field represents the amount of new snow that fell during the period.
This is different from precipitation because precip reports the liquid-equivalent amount of precipitation, while snow reports the depth of newly fallen snow.
Snow depth (snowdepth)
The snowdepth field represents the amount of snow on the ground.
Snow depth can remain above zero long after snow has stopped falling because existing snow can remain on the ground until it melts, compacts, or is removed.
This means:
snow = 0
snowdepth > 0
is completely normal.
It means no new snow fell during the period, but snow was still present on the ground.
Precipitation probability (precipprob)
The precipprob field represents the probability of measurable precipitation and is primarily a forecast value.
For example:
precipprob = 70
means there is a 70% probability of measurable precipitation during the forecast period.
Do not confuse precipitation probability with historical precipitation amount.
For historical analysis, the most important fields are generally:
precip
precipcover
preciptype
snow
snowdepth
What units are used?
The units depend on the unitGroup parameter.
For example:
unitGroup=us
uses US units.
unitGroup=metric
uses metric units.
Typical precipitation-related units are:
| Field | US | Metric |
|---|---|---|
precip | inches | mm |
snow | inches | cm |
snowdepth | inches | cm |
precipcover | % | % |
precipprob | % | % |
For a complete reference, see Weather API Unit Groups and Measurement Units.
Find historical precipitation using Weather Data
If you want to look up precipitation without writing code, use Visual Crossing Weather Data.
Enter:
- The location.
- The historical date or date range.
- The weather elements you want to view.
You can then inspect the results and download the weather data for additional analysis.
The Query Builder is useful when you want to select specific fields such as:
precip
precipcover
preciptype
snow
snowdepth
and export the results in a tabular format.
Find historical precipitation using the Weather API
For automated access, use the Timeline Weather API.
The general request structure is:
/timeline/[location]/[date1]/[date2]
For example, to retrieve historical weather for London from July 1 through July 7, 2026:
https://weather.visualcrossing.com/VisualCrossingWebServices/rest/services/timeline/London,UK/2026-07-01/2026-07-07?unitGroup=metric&key=YOUR_API_KEY
To request only precipitation-related fields:
https://weather.visualcrossing.com/VisualCrossingWebServices/rest/services/timeline/London,UK/2026-07-01/2026-07-07?unitGroup=metric&include=days&elements=datetime,precip,precipcover,preciptype,snow,snowdepth&key=YOUR_API_KEY
JSON example
A simplified response might look like:
{
"resolvedAddress": "London, England, United Kingdom",
"days": [
{
"datetime": "2026-07-01",
"precip": 2.4,
"precipcover": 16.67,
"preciptype": [
"rain"
],
"snow": 0,
"snowdepth": 0
}
]
}
Retrieve hourly precipitation
Daily precipitation is useful for summaries, but hourly data can show when the precipitation actually occurred.
Use:
include=hours
For example:
https://weather.visualcrossing.com/VisualCrossingWebServices/rest/services/timeline/London,UK/2026-07-01?unitGroup=metric&include=hours&elements=datetime,precip,preciptype&key=YOUR_API_KEY
The returned hourly records can help answer questions such as:
- What time did the rain begin?
- How long did precipitation continue?
- Which hour had the most precipitation?
- Was precipitation concentrated in one short event or spread through the day?
Retrieve sub-hourly precipitation
For applications requiring higher time resolution, the Timeline Weather API also supports sub-hourly weather data using:
include=minutes
Sub-hourly availability and resolution depend on the location, period, and available observation sources.
For more information, see Requesting Sub-Hourly Data in the Timeline Weather API.
Historical precipitation from radar
Some precipitation information can also be derived from radar or other remote observation sources.
The Timeline Weather API includes remote precipitation information such as radar-estimated precipitation where available.
This can be useful when station observations are sparse or when radar provides additional spatial information about a precipitation event.
For details about remote observation data, see Using Remote Data Sources in the Weather API.
Historical precipitation versus precipitation probability
It is important to distinguish between these two concepts:
precip
is the amount of precipitation that occurred or is predicted to occur.
precipprob
is the probability that measurable precipitation will occur in a forecast period.
For historical analysis, use the actual precipitation measurements rather than forecast probability.
Precipitation and snow are not the same measurement
When snow falls, the precip value represents the equivalent amount of liquid water contained in that snow.
The snow field represents the depth of newly fallen snow.
For example, a weather record could contain:
precip = 10 mm
snow = 8 cm
Those values represent different physical measurements and should not be directly compared as though they were the same unit.
Historical precipitation data quality
Historical precipitation can come from multiple observational and remote data sources.
The availability and quality of precipitation measurements can vary depending on:
- Location
- Time period
- Nearby weather stations
- Radar or remote observation coverage
- Reporting frequency
- The weather elements available from individual sources
Visual Crossing processes available sources to produce historical weather data for the requested location.
For detailed source analysis, you can also inspect station and remote-observation information available through the Timeline Weather API.
Hail data
Hail is different from the normal precipitation fields described above.
Hail reports are better treated as weather events rather than as a simple continuous precipitation measurement.
If you need historical hail information, see Weather and Environmental Events in the Weather API.
Common uses for historical precipitation data
Historical precipitation data is commonly used for:
- Agriculture
- Insurance
- Flood and storm analysis
- Construction
- Transportation
- Logistics
- Retail analysis
- Energy
- Environmental research
- Event analysis
- Academic research
- Machine learning
Daily precipitation is often sufficient for long-term analysis, while hourly or sub-hourly data can be useful when the exact timing of an event matters.
Summary
Historical precipitation data can be retrieved using the Visual Crossing Weather Data tools or programmatically through the Timeline Weather API.
The most important historical precipitation fields include:
precip
precipcover
preciptype
snow
snowdepth
Use daily data for summarized precipitation totals, hourly data to analyze the timing of precipitation, and sub-hourly data when finer time resolution is required.
For a complete introduction to the API, see Getting Started with the Weather API.
For the complete weather-element definitions, see Weather Data Documentation.