Ambient Weather Network: Real-Time Weather Data - Africa - Refreshed Every 5 Minutes
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Verified Data Provider
Verified Data Provider|
PASSKEY
|
DATEUTC
|
WINDDIR
|
WINDSPEEDMPH
|
WINDGUSTMPH
|
MAXDAILYGUST
|
WINDGUSTDIR
|
WINDSPDMPH_AVG2M
|
WINDDIR_AVG2M
|
WINDSPDMPH_AVG10M
|
WINDDIR_AVG10M
|
HUMIDITY
|
HUMIDITY1
|
HUMIDITY2
|
HUMIDITY3
|
HUMIDITY4
|
HUMIDITY5
|
HUMIDITY6
|
HUMIDITY7
|
HUMIDITY8
|
HUMIDITY9
|
HUMIDITY10
|
HUMIDITYIN
|
HUMIDITYKESTREL
|
TEMPF
|
TEMPFKESTREL
|
TEMP1F
|
TEMP2F
|
TEMP3F
|
TEMP4F
|
TEMP5F
|
TEMP6F
|
TEMP7F
|
TEMP8F
|
TEMP9F
|
TEMP10F
|
FEELSLIKE
|
FEELSLIKE1
|
FEELSLIKE2
|
FEELSLIKE3
|
FEELSLIKE4
|
FEELSLIKE5
|
FEELSLIKE6
|
FEELSLIKE7
|
FEELSLIKE8
|
FEELSLIKE9
|
FEELSLIKE10
|
FEELSLIKEIN
|
DEWPOINT
|
DEWPOINT1
|
DEWPOINT2
|
DEWPOINT3
|
DEWPOINT4
|
DEWPOINT5
|
DEWPOINT6
|
DEWPOINT7
|
DEWPOINT8
|
DEWPOINT9
|
DEWPOINT10
|
DEWPOINTIN
|
SOILTEMP1
|
SOILTEMP2
|
SOILTEMP3
|
SOILTEMP4
|
SOILTEMP5
|
SOILTEMP6
|
SOILTEMP7
|
SOILTEMP8
|
SOILTEMP9
|
SOILTEMP10
|
SOILHUM1
|
SOILHUM2
|
SOILHUM3
|
SOILHUM4
|
SOILHUM5
|
SOILHUM6
|
SOILHUM7
|
SOILHUM8
|
SOILHUM9
|
SOILHUM10
|
TEMPINF
|
HOURLYRAININ
|
DAILYRAININ
|
WEEKLYRAININ
|
MONTHLYRAININ
|
YEARLYRAININ
|
EVENTRAININ
|
TOTALRAININ
|
BAROMRELIN
|
BAROMABSIN
|
UV
|
SOLARRADIATION
|
CO2
|
RELAY1
|
RELAY2
|
RELAY3
|
RELAY4
|
RELAY5
|
RELAY6
|
RELAY7
|
RELAY8
|
RELAY9
|
RELAY10
|
PM25
|
PM25_24H
|
PM25_IN
|
PM25_IN_24H
|
PM25_IN_AQIN
|
PM25_IN_24H_AQIN
|
PM10_IN_AQIN
|
PM10_IN_24H_AQIN
|
CO2_IN_AQIN
|
CO2_IN_24H_AQIN
|
PM_IN_TEMP_AQIN
|
PM_IN_HUMIDITY_AQIN
|
AQI_PM25_AQIN
|
AQI_PM25_24H_AQIN
|
AQI_PM10_AQIN
|
AQI_PM10_24H_AQIN
|
AQI_PM25
|
AQI_PM25_24H
|
AQI_PM25_IN
|
AQI_PM25_IN_24H
|
BATTOUT
|
BATTIN
|
BATT1
|
BATT2
|
BATT3
|
BATT4
|
BATT5
|
BATT6
|
BATT7
|
BATT8
|
BATT9
|
BATT10
|
BATTR1
|
BATTR2
|
BATTR3
|
BATTR4
|
BATTR5
|
BATTR6
|
BATTR7
|
BATTR8
|
BATTR9
|
BATTR10
|
BATT_25
|
BATT_25IN
|
BATLEAK1
|
BATLEAK2
|
BATLEAK3
|
BATLEAK4
|
BATT_LIGHTNING
|
BATTSM1
|
BATTSM2
|
BATTSM3
|
BATTSM4
|
BATT_CO2
|
BATT_CELLGATEWAY
|
BATTVOLTS
|
BATT1VOLTS
|
BATT3VOLTS
|
LEAK1
|
LEAK2
|
LEAK3
|
LEAK4
|
LIGHTNING_DAY
|
LIGHTNING_HOUR
|
LIGHTNING_DISTANCE
|
LIGHTNING_TIME
|
CO2_IN
|
CO2_IN_24H
|
SOLARRADDAY
|
LEAFWET1X
|
LEAFWETSUM
|
LEAFWETNESS1
|
LEAFWETNESS2
|
LEAFWETNESS3
|
LEAFWETNESS4
|
LEAFWETNESS5
|
LEAFWETNESS6
|
LEAFWETNESS7
|
LEAFWETNESS8
|
SOILTENS1
|
SOILTENS2
|
SOILTENS3
|
SOILTENS4
|
GDD
|
ETOS
|
ETRS
|
WBGTF
|
HEATINDEXF
|
BLACKGLOBEF
|
WETBULBF
|
NAWBF
|
PIG
|
DISCHARGEFT3S
|
GAUGEHEIGHTFT
|
WATERMEASPH
|
WATERNITRATESMGL
|
EVAPRATELBFT3HR
|
TWLWM2
|
DENSITYALTITUDEFT
|
CROSSWINDMPH
|
HEADWINDMPH
|
AHLU1
|
AHLU2
|
AHLU3
|
HUMIDITYRATIOGPLB
|
AIRDENSITYLBFT3
|
RELATIVEAIRDENSITY
|
ALTITUDEFT
|
DELTAF
|
AIRFLOWCFM
|
WINDCHILLF
|
THINRC
|
THIYOUSEF
|
LEAFWETDAY
|
24HOURRAININ
|
WBGTFLAGZONE
|
LAT
|
LON
|
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| Xxxxx | xxxxxxxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxx | xxxxx | Xxxxx | Xxxxxxxx | xxxxx | Xxxxxxxx | Xxxxxx | xxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxxx | xxxxx | xxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxx | xxxxxxxxx | xxxxxx | Xxxxx | xxxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxx | xxxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxx | xxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxx | Xxxxxxx | xxxxxxxx | xxxxx | xxxxxxxxxx | Xxxxx | xxxxx | xxxxxxxxxx | xxxxxxx | xxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxx | xxxxxx | xxxxx | Xxxxxxx | xxxxxx | xxxxx | Xxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | xxxxx | xxxxxxxxxx | Xxxxx | xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxx | Xxxxx | xxxxx | xxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxxx | Xxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx | xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxx | xxxxxxx | xxxxxxxxx | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxx | xxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | Xxxxx | xxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxx | xxxxxx | xxxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxx | xxxxxx | xxxxx | Xxxxxxx | xxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxx |
| xxxxxx | xxxxxx | xxxxxxxxxx | xxxxxx | xxxxx | Xxxxxxx | Xxxxxxxxx | xxxxx | xxxxxxx | xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxx | Xxxxxx | xxxxxxxx | xxxxxx | Xxxxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxx | Xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxx | xxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxx | xxxxxxxxx | xxxxx | xxxxxxxxx | xxxxxxx | xxxxx | xxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxx | xxxxxxx | Xxxxxxxxx | xxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxx | Xxxxxxxxxx | xxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxx | Xxxxxxx | xxxxxx | xxxxxx | xxxxxx | xxxxxxx | xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxx | xxxxx | xxxxx | xxxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | xxxxx | xxxxx | xxxxxx | Xxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxx | Xxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxx | Xxxxxxxx | Xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxx | xxxxx | xxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxx | xxxxxxxx | Xxxxx | Xxxxx | Xxxxxxxxxx | Xxxxxxxxxx | xxxxxx | xxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxx | xxxxx | xxxxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | Xxxxxxxxxx |
| Xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxx | Xxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxxx | xxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxxxx | xxxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxx | Xxxxxx | xxxxxx | Xxxxx | xxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxx | xxxxxx | Xxxxxx | Xxxxxxxx | xxxxxxx | xxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxx | xxxxx | Xxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxx | Xxxxx | xxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxx | xxxxx | Xxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxx | xxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxx | xxxxxx | Xxxxxxx | Xxxxx | Xxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxx | Xxxxx | Xxxxx | Xxxxxxxxxx | xxxxxxx | xxxxxxx | xxxxxxxx | xxxxxxx | xxxxxxx | Xxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | xxxxxxxx | xxxxxx | xxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxx | xxxxxxx | Xxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxx | xxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxx | Xxxxxxxxx | xxxxxxx | xxxxxx | Xxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxx | xxxxxxx | Xxxxxxxxxx | xxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxxxx | xxxxxxx | xxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxx |
Volume
175K
Weather Stations
Avail. Formats
.json, .csv, and .xls
File
Coverage
58
Countries
History
8
years
Data Dictionary
[Sample] Awn Real Time Weather Data
| Attribute | Type | Example | Mapping |
|---|---|---|---|
|
PASSKEY
|
String | 6772e5e9513a3f08fdd6dfd34bf5b087 | |
|
DATEUTC
|
Integer | 1749105840000 | |
|
WINDDIR
|
Integer | 119 | |
|
WINDSPEEDMPH
|
Integer | 0 | |
|
WINDGUSTMPH
|
Integer | 4 | |
|
MAXDAILYGUST
|
Integer | 6 | |
|
WINDGUSTDIR
|
|||
|
WINDSPDMPH_AVG2M
|
|||
|
WINDDIR_AVG2M
|
|||
|
WINDSPDMPH_AVG10M
|
Integer | 2 | |
|
WINDDIR_AVG10M
|
Integer | 116 | |
|
HUMIDITY
|
Integer | 93 | |
|
HUMIDITY1
|
|||
|
HUMIDITY2
|
|||
|
HUMIDITY3
|
|||
|
HUMIDITY4
|
|||
|
HUMIDITY5
|
|||
|
HUMIDITY6
|
|||
|
HUMIDITY7
|
|||
|
HUMIDITY8
|
|||
|
HUMIDITY9
|
|||
|
HUMIDITY10
|
|||
|
HUMIDITYIN
|
|||
|
HUMIDITYKESTREL
|
|||
|
TEMPF
|
Integer | 68 | |
|
TEMPFKESTREL
|
|||
|
TEMP1F
|
|||
|
TEMP2F
|
|||
|
TEMP3F
|
|||
|
TEMP4F
|
|||
|
TEMP5F
|
|||
|
TEMP6F
|
|||
|
TEMP7F
|
|||
|
TEMP8F
|
|||
|
TEMP9F
|
|||
|
TEMP10F
|
|||
|
FEELSLIKE
|
Integer | 68 | |
|
FEELSLIKE1
|
|||
|
FEELSLIKE2
|
|||
|
FEELSLIKE3
|
|||
|
FEELSLIKE4
|
|||
|
FEELSLIKE5
|
|||
|
FEELSLIKE6
|
|||
|
FEELSLIKE7
|
|||
|
FEELSLIKE8
|
|||
|
FEELSLIKE9
|
|||
|
FEELSLIKE10
|
|||
|
FEELSLIKEIN
|
|||
|
DEWPOINT
|
|||
|
DEWPOINT1
|
|||
|
DEWPOINT2
|
|||
|
DEWPOINT3
|
|||
|
DEWPOINT4
|
|||
|
DEWPOINT5
|
|||
|
DEWPOINT6
|
|||
|
DEWPOINT7
|
|||
|
DEWPOINT8
|
|||
|
DEWPOINT9
|
|||
|
DEWPOINT10
|
|||
|
DEWPOINTIN
|
|||
|
SOILTEMP1
|
|||
|
SOILTEMP2
|
|||
|
SOILTEMP3
|
|||
|
SOILTEMP4
|
|||
|
SOILTEMP5
|
|||
|
SOILTEMP6
|
|||
|
SOILTEMP7
|
|||
|
SOILTEMP8
|
|||
|
SOILTEMP9
|
|||
|
SOILTEMP10
|
|||
|
SOILHUM1
|
|||
|
SOILHUM2
|
|||
|
SOILHUM3
|
|||
|
SOILHUM4
|
|||
|
SOILHUM5
|
|||
|
SOILHUM6
|
|||
|
SOILHUM7
|
|||
|
SOILHUM8
|
|||
|
SOILHUM9
|
|||
|
SOILHUM10
|
|||
|
TEMPINF
|
|||
|
HOURLYRAININ
|
Integer | 0 | |
|
DAILYRAININ
|
Integer | 0 | |
|
WEEKLYRAININ
|
Integer | 0 | |
|
MONTHLYRAININ
|
Integer | 0 | |
|
YEARLYRAININ
|
Integer | 18 | |
|
EVENTRAININ
|
Integer | 0 | |
|
TOTALRAININ
|
|||
|
BAROMRELIN
|
Integer | 30 | |
|
BAROMABSIN
|
Integer | 30 | |
|
UV
|
Integer | 0 | |
|
SOLARRADIATION
|
Integer | 0 | |
|
CO2
|
|||
|
RELAY1
|
|||
|
RELAY2
|
|||
|
RELAY3
|
|||
|
RELAY4
|
|||
|
RELAY5
|
|||
|
RELAY6
|
|||
|
RELAY7
|
|||
|
RELAY8
|
|||
|
RELAY9
|
|||
|
RELAY10
|
|||
|
PM25
|
|||
|
PM25_24H
|
|||
|
PM25_IN
|
|||
|
PM25_IN_24H
|
|||
|
PM25_IN_AQIN
|
|||
|
PM25_IN_24H_AQIN
|
|||
|
PM10_IN_AQIN
|
|||
|
PM10_IN_24H_AQIN
|
|||
|
CO2_IN_AQIN
|
|||
|
CO2_IN_24H_AQIN
|
|||
|
PM_IN_TEMP_AQIN
|
|||
|
PM_IN_HUMIDITY_AQIN
|
|||
|
AQI_PM25_AQIN
|
|||
|
AQI_PM25_24H_AQIN
|
|||
|
AQI_PM10_AQIN
|
|||
|
AQI_PM10_24H_AQIN
|
|||
|
AQI_PM25
|
|||
|
AQI_PM25_24H
|
|||
|
AQI_PM25_IN
|
|||
|
AQI_PM25_IN_24H
|
|||
|
BATTOUT
|
|||
|
BATTIN
|
|||
|
BATT1
|
|||
|
BATT2
|
|||
|
BATT3
|
|||
|
BATT4
|
|||
|
BATT5
|
|||
|
BATT6
|
|||
|
BATT7
|
|||
|
BATT8
|
|||
|
BATT9
|
|||
|
BATT10
|
|||
|
BATTR1
|
|||
|
BATTR2
|
|||
|
BATTR3
|
|||
|
BATTR4
|
|||
|
BATTR5
|
|||
|
BATTR6
|
|||
|
BATTR7
|
|||
|
BATTR8
|
|||
|
BATTR9
|
|||
|
BATTR10
|
|||
|
BATT_25
|
|||
|
BATT_25IN
|
|||
|
BATLEAK1
|
|||
|
BATLEAK2
|
|||
|
BATLEAK3
|
|||
|
BATLEAK4
|
|||
|
BATT_LIGHTNING
|
|||
|
BATTSM1
|
|||
|
BATTSM2
|
|||
|
BATTSM3
|
|||
|
BATTSM4
|
|||
|
BATT_CO2
|
|||
|
BATT_CELLGATEWAY
|
|||
|
BATTVOLTS
|
|||
|
BATT1VOLTS
|
|||
|
BATT3VOLTS
|
|||
|
LEAK1
|
|||
|
LEAK2
|
|||
|
LEAK3
|
|||
|
LEAK4
|
|||
|
LIGHTNING_DAY
|
|||
|
LIGHTNING_HOUR
|
|||
|
LIGHTNING_DISTANCE
|
|||
|
LIGHTNING_TIME
|
|||
|
CO2_IN
|
|||
|
CO2_IN_24H
|
|||
|
SOLARRADDAY
|
|||
|
LEAFWET1X
|
|||
|
LEAFWETSUM
|
|||
|
LEAFWETNESS1
|
|||
|
LEAFWETNESS2
|
|||
|
LEAFWETNESS3
|
|||
|
LEAFWETNESS4
|
|||
|
LEAFWETNESS5
|
|||
|
LEAFWETNESS6
|
|||
|
LEAFWETNESS7
|
|||
|
LEAFWETNESS8
|
|||
|
SOILTENS1
|
|||
|
SOILTENS2
|
|||
|
SOILTENS3
|
|||
|
SOILTENS4
|
|||
|
GDD
|
|||
|
ETOS
|
|||
|
ETRS
|
|||
|
WBGTF
|
|||
|
HEATINDEXF
|
|||
|
BLACKGLOBEF
|
|||
|
WETBULBF
|
|||
|
NAWBF
|
|||
|
PIG
|
|||
|
DISCHARGEFT3S
|
|||
|
GAUGEHEIGHTFT
|
|||
|
WATERMEASPH
|
|||
|
WATERNITRATESMGL
|
|||
|
EVAPRATELBFT3HR
|
|||
|
TWLWM2
|
|||
|
DENSITYALTITUDEFT
|
|||
|
CROSSWINDMPH
|
|||
|
HEADWINDMPH
|
|||
|
AHLU1
|
|||
|
AHLU2
|
|||
|
AHLU3
|
|||
|
HUMIDITYRATIOGPLB
|
|||
|
AIRDENSITYLBFT3
|
|||
|
RELATIVEAIRDENSITY
|
|||
|
ALTITUDEFT
|
|||
|
DELTAF
|
|||
|
AIRFLOWCFM
|
|||
|
WINDCHILLF
|
|||
|
THINRC
|
|||
|
THIYOUSEF
|
|||
|
LEAFWETDAY
|
|||
|
24HOURRAININ
|
|||
|
WBGTFLAGZONE
|
|||
|
LAT
|
Float | 34.31826 | |
|
LON
|
Float | -97.17408 |
Description
Ambient Weather Network Real-Time Weather delivers continuous, high-resolution updates to power businesses, researchers, and agencies with current, precise weather insights. Integrate seamlessly for logistics, agriculture, energy, and public safety efficiency.
The Ambient Weather Network offers real-time, high-resolution weather data designed to empower businesses, researchers, and organizations with actionable insights. This listing provides continuous updates from the last 12 hours, ensuring you have the most current and accurate weather information at your fingertips. Ideal for industries such as logistics, agriculture, energy, and public safety, our data enables seamless integration into analytics workflows for better decision-making and operational efficiency.
Sample Dataset: Real-Time Weather Data (Last 12 Hours)
Coverage:
Global, with hyper-local precision available for specific regions
Data Resolution:
Updates every 15 minutes
Data Types:
Temperature, humidity, precipitation, wind speed and direction, barometric pressure, UV index, and more
Dynamic Sample:
Continuously updated to reflect the last 12 hours of weather data
Key Features:
Real-Time Updates:
Stay informed with up-to-the-minute weather data, refreshed every 5 minutes.
Global Coverage:
Access weather information from locations worldwide, with optional hyper-local granularity.
Wide Data Range:
Includes key parameters such as temperature, wind, precipitation, and more for comprehensive analysis.
Seamless Integration:
Ready-to-use data compatible with Snowflake’s ecosystem, enabling real-time analytics and visualization.
Access and Pricing:
Sample Data:
Real-time weather data for the last 12 hours is available as a free demonstration.
Subscription Plans:
Customizable based on data volume, resolution, and geographic coverage.
Country Coverage
Africa
(58)
Algeria
Angola
Benin
Botswana
Burkina Faso
Burundi
Cabo Verde
Cameroon
Central African Republic
Chad
Comoros
Congo
Congo (Democratic Republic of the)
Côte d'Ivoire
Djibouti
Egypt
Equatorial Guinea
Eritrea
Ethiopia
Gabon
Gambia
Ghana
Guinea
Guinea-Bissau
Kenya
Lesotho
Liberia
Libya
Madagascar
Malawi
Mali
Mauritania
Mauritius
Mayotte
Morocco
Mozambique
Namibia
Niger
Nigeria
Rwanda
Réunion
Saint Helena, Ascension and Tristan da Cunha
Sao Tome and Principe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
South Sudan
Sudan
Swaziland
Tanzania, United Republic of
Togo
Tunisia
Uganda
Western Sahara
Zambia
Zimbabwe
History
8 years of historical data
Volume
| 175,000 | Weather Stations |
| 50 | TB of Data |
| 8 | Years of Data |
Pricing
| License | Starts at |
|---|---|
| One-off purchase |
$1,000 / purchase |
| Monthly License |
$500 / month |
| Yearly License |
$5,000 / year |
| Usage-based |
$0.01 / per API call (min 50,000 calls) |
Suitable Company Sizes
Small Business
Medium-sized Business
Enterprise
Delivery
Methods
Streaming API
Snowflake Share
Compressed File
Email
S3 Bucket
Databricks Delta Share
Feed API
REST API
Frequency
minutely
hourly
daily
weekly
Format
.json
.csv
.xls
.sql
.jsonl
Use Cases
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Frequently asked questions
What is Ambient Weather Network: Real-Time Weather Data - Africa - Refreshed Every 5 Minutes?
Ambient Weather Network Real-Time Weather delivers continuous, high-resolution updates to power businesses, researchers, and agencies with current, precise weather insights. Integrate seamlessly for logistics, agriculture, energy, and public safety efficiency.
What is Ambient Weather Network: Real-Time Weather Data - Africa - Refreshed Every 5 Minutes used for?
This product has 5 key use cases. Ambient Weather Network recommends using the data for Climate Analytics, purchase behavior analytics, Data Modeling, Retail Intelligence, and Weather Analytics. Global businesses and organizations buy Historical Weather Data from Ambient Weather Network to fuel their analytics and enrichment.
Who can use Ambient Weather Network: Real-Time Weather Data - Africa - Refreshed Every 5 Minutes?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Historical Weather Data. Get in touch with Ambient Weather Network to see what their data can do for your business and find out which integrations they provide.
How far back does the data in Ambient Weather Network: Real-Time Weather Data - Africa - Refreshed Every 5 Minutes go?
This product has 8 years of historical coverage. It can be delivered on a minutely, hourly, daily, and weekly basis.
Which countries does Ambient Weather Network: Real-Time Weather Data - Africa - Refreshed Every 5 Minutes cover?
This product includes data covering 58 countries like Nigeria, South Africa, Egypt, Algeria, and Angola. Ambient Weather Network is headquartered in United States of America.
How much does Ambient Weather Network: Real-Time Weather Data - Africa - Refreshed Every 5 Minutes cost?
Pricing for Ambient Weather Network: Real-Time Weather Data - Africa - Refreshed Every 5 Minutes starts at USD0.01 per per API call (min 50,000 calls). Connect with Ambient Weather Network to get a quote and arrange custom pricing models based on your data requirements.
How can I get Ambient Weather Network: Real-Time Weather Data - Africa - Refreshed Every 5 Minutes?
Businesses can buy Historical Weather Data from Ambient Weather Network and get the data via Streaming API, Snowflake Share, Compressed File, Email, S3 Bucket, Databricks Delta Share, Feed API, and REST API. Depending on your data requirements and subscription budget, Ambient Weather Network can deliver this product in .json, .csv, .xls, .sql, and .jsonl format.
What is the data quality of Ambient Weather Network: Real-Time Weather Data - Africa - Refreshed Every 5 Minutes?
You can compare and assess the data quality of Ambient Weather Network using Datarade’s data marketplace.
What are similar products to Ambient Weather Network: Real-Time Weather Data - Africa - Refreshed Every 5 Minutes?
This product has 3 related products. These alternatives include Ambient Weather Network: Real-Time Weather Data - Refreshed Every 5 Minutes, Global Weather Data - Historical Real-Time Forecast Climatology, and CustomWeather API Severe Weather Data Global Severe Weather Advisories For 85,000 Weather Forecast Locations Storm Data. You can compare the best Historical Weather Data providers and products via Datarade’s data marketplace and get the right data for your use case.