Global Pollen Data -  Historical | Real-Time | Forecast | Climatology product image in hero

Global Pollen Data - Historical | Real-Time | Forecast | Climatology

Ambee
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timestamp
Risk.grass_pollen
Risk.tree_pollen
Risk.weed_pollen
Count.grass_pollen
Count.tree_pollen
Count.weed_pollen
Species.Grass.Grass / Poaceae
Species.Others
Species.Tree.Ash
Species.Tree.Birch
Species.Tree.Cypress / Juniper / Cedar
Species.Tree.Elm
Species.Tree.Maple
Species.Tree.Mulberry
Species.Tree.Oak
Species.Tree.Pine
Species.Tree.Poplar / Cottonwood
Species.Weed.Ragweed
SpeciesRisk.Ash
SpeciesRisk.Birch
SpeciesRisk.Cypress / Juniper / Cedar
SpeciesRisk.Elm
SpeciesRisk.Grass / Poaceae
SpeciesRisk.Maple
SpeciesRisk.Mulberry
SpeciesRisk.Oak
SpeciesRisk.Pine
SpeciesRisk.Poplar / Cottonwood
SpeciesRisk.Ragweed
lat
lng
xxxxxxxxxx Xxxxxxxxx xxxxxx xxxxxxxxxx Xxxxx Xxxxxx Xxxxxxxxxx Xxxxxx Xxxxxxxxx Xxxxxxxxxx xxxxxxxxx Xxxxxxxxx xxxxxxxxx Xxxxxxx xxxxxx Xxxxx xxxxxxxxxx xxxxxx Xxxxxxxxxx xxxxxx Xxxxx Xxxxxx xxxxx xxxxxxxx xxxxxxx Xxxxx Xxxxxxxx xxxxxxxxxx xxxxxx Xxxxxxxxx xxxxxx Xxxxxxxxx
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Xxxxxx Xxxxxxxxx xxxxxxx Xxxxxxxx xxxxx xxxxx Xxxxxxxxxx Xxxxxxx Xxxxxxxx Xxxxxxx xxxxx xxxxxxx Xxxxx xxxxxxxxxx Xxxxxxxxxx xxxxxxx Xxxxx xxxxxxxxx xxxxxxxx Xxxxxxxx xxxxxxxx Xxxxxxx Xxxxxx Xxxxxxxxx Xxxxxxxx Xxxxxxxxxx Xxxxxxx Xxxxxx Xxxxxxxxxx xxxxxxxxxx xxxxxxxxxx Xxxxxxx
Xxxxx Xxxxx Xxxxx Xxxxxxx xxxxx xxxxxxxxx xxxxxxx Xxxxxxx xxxxxx xxxxxxxxxx xxxxxxxxxx Xxxxxxx xxxxxxxxx Xxxxx xxxxxxx Xxxxxx Xxxxx xxxxxxxxxx xxxxxxxxx Xxxxxxxxxx Xxxxxxxxx Xxxxxxxx xxxxxxxxx Xxxxxxx Xxxxxxx Xxxxx xxxxxxxxxx Xxxxxxxxx Xxxxxxx Xxxxxxx xxxxxxxx xxxxx
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Volume
30
days of forecast
Avail. Formats
.csv, .geojson, and .json
File
Coverage
250
Countries
History
9
years

Data Dictionary

[Sample] Pollen Latest
Attribute Type Example Mapping
timestamp
DateTime 2025-07-04T06:00:00+00:00
Risk.grass_pollen
String Low
Risk.tree_pollen
String Low
Risk.weed_pollen
String Low
Count.grass_pollen
Integer 8
Count.tree_pollen
Integer 2
Count.weed_pollen
Integer 8
Species.Grass.Grass / Poaceae
Integer 8
Species.Others
Integer 2
Species.Tree.Ash
Integer 0
Species.Tree.Birch
Integer 0
Species.Tree.Cypress / Juniper / Cedar
Integer 0
Species.Tree.Elm
Integer 0
Species.Tree.Maple
Integer 0
Species.Tree.Mulberry
Integer 0
Species.Tree.Oak
Integer 0
Species.Tree.Pine
Integer 0
Species.Tree.Poplar / Cottonwood
Integer 0
Species.Weed.Ragweed
Integer 8
SpeciesRisk.Ash
String Low
SpeciesRisk.Birch
String Low
SpeciesRisk.Cypress / Juniper / Cedar
String Low
SpeciesRisk.Elm
String Low
SpeciesRisk.Grass / Poaceae
String Low
SpeciesRisk.Maple
String Low
SpeciesRisk.Mulberry
String Low
SpeciesRisk.Oak
String Low
SpeciesRisk.Pine
String Low
SpeciesRisk.Poplar / Cottonwood
String Low
SpeciesRisk.Ragweed
String Low
lat
Float 40.7128
lng
Float -74.006

Description

High-resolution global pollen data built for precision health, allergy forecasting, and demand modeling. Hourly updates, species-level insights, and region-optimized models.
Ambee’s global pollen dataset provides precision-level environmental intelligence on allergenic activity, built for real-world decision systems across healthcare, consumer health, retail, and analytics platforms. The dataset is powered by a blend of environmental signals and proprietary modeling techniques, designed to reflect real-world conditions with high spatial and temporal accuracy. Pollen outputs are available at both category level (tree, grass, weed) and species level, with hourly updates and validated forecast windows extending up to 30 days in advance. Every forecast is benchmarked against seasonal cycles and adjusted by geography for local accuracy. Ambee maintains a pristine historical pollen archive spanning more than a decade, supporting long-term analysis, demand modeling, and climate-aware planning. All data is spatially and temporally complete, queryable at lat-lon resolution or mapped to ZIP codes, postcodes, DMAs, and custom geographies. Core variables include: • Pollen count and risk by species • Category-level breakdowns: tree, grass, weed • Hourly and daily forecast feeds • Historical pollen records spanning multiple decades Built for integration into platforms where environmental triggers impact behavior, outcomes, or demand, Ambee’s pollen data supports everything from personalized digital health recommendations to allergy season inventory forecasting.

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
Asia (51)
Afghanistan
Armenia
Azerbaijan
Bahrain
Bangladesh
Bhutan
Brunei Darussalam
Cambodia
China
Cyprus
Georgia
Hong Kong
India
Indonesia
Iran (Islamic Republic of)
Iraq
Israel
Japan
Jordan
Kazakhstan
Korea (Democratic People's Republic of)
Korea (Republic of)
Kuwait
Kyrgyzstan
Lao People's Democratic Republic
Lebanon
Macao
Malaysia
Maldives
Mongolia
Myanmar
Nepal
Oman
Pakistan
Palestine, State of
Philippines
Qatar
Saudi Arabia
Singapore
Sri Lanka
Syrian Arab Republic
Taiwan
Tajikistan
Thailand
Timor-Leste
Turkey
Turkmenistan
United Arab Emirates
Uzbekistan
Vietnam
Yemen
Europe (52)
Albania
Andorra
Austria
Belarus
Belgium
Bosnia and Herzegovina
Bulgaria
Croatia
Czech Republic
Denmark
Estonia
Faroe Islands
Finland
France
Germany
Gibraltar
Greece
Guernsey
Holy See
Hungary
Iceland
Ireland
Isle of Man
Italy
Jersey
Kosovo
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia (the former Yugoslav Republic of)
Malta
Moldova (Republic of)
Monaco
Montenegro
Netherlands
Norway
Poland
Portugal
Romania
Russian Federation
San Marino
Serbia
Slovakia
Slovenia
Spain
Svalbard and Jan Mayen
Sweden
Switzerland
Ukraine
United Kingdom
Åland Islands
North America (13)
Belize
Bermuda
Canada
Costa Rica
El Salvador
Greenland
Guatemala
Honduras
Mexico
Nicaragua
Panama
Saint Pierre and Miquelon
United States of America
Oceania (25)
American Samoa
Australia
Cook Islands
Fiji
French Polynesia
Guam
Kiribati
Marshall Islands
Micronesia (Federated States of)
Nauru
New Caledonia
New Zealand
Niue
Norfolk Island
Northern Mariana Islands
Palau
Papua New Guinea
Pitcairn
Samoa
Solomon Islands
Tokelau
Tonga
Tuvalu
Vanuatu
Wallis and Futuna
Other (9)
Antarctica
Bouvet Island
British Indian Ocean Territory
Christmas Island
Cocos (Keeling) Islands
French Southern Territories
Heard Island and McDonald Islands
South Georgia and the South Sandwich Islands
United States Minor Outlying Islands
South America (42)
Anguilla
Antigua and Barbuda
Argentina
Aruba
Bahamas
Barbados
Bolivia (Plurinational State of)
Bonaire, Sint Eustatius and Saba
Brazil
Cayman Islands
Chile
Colombia
Cuba
Curaçao
Dominica
Dominican Republic
Ecuador
Falkland Islands (Malvinas)
French Guiana
Grenada
Guadeloupe
Guyana
Haiti
Jamaica
Martinique
Montserrat
Paraguay
Peru
Puerto Rico
Saint Barthélemy
Saint Kitts and Nevis
Saint Lucia
Saint Martin (French part)
Saint Vincent and the Grenadines
Sint Maarten (Dutch part)
Suriname
Trinidad and Tobago
Turks and Caicos Islands
Uruguay
Venezuela (Bolivarian Republic of)
Virgin Islands (British)
Virgin Islands (U.S.)

History

9 years of historical data

Volume

30 days of forecast

Pricing

Ambee has not published pricing information for this product yet. You can request detailed pricing information below.

Suitable Company Sizes

Small Business
Medium-sized Business
Enterprise

Delivery

Methods
S3 Bucket
SFTP
Email
UI Export
REST API
Compressed File
Snowflake Share
Google BigQuery
Google Cloud Storage
Azure Blob Storage
Databricks Delta Share
Frequency
hourly
daily
weekly
monthly
quarterly
yearly
real-time
on-demand
Format
.csv
.geojson
.json
.parquet
.tiff
.txt
.xls
.xml

Use Cases

Programmatic Advertising Demand Forecasting
Retail Intelligence
Marketing Strategy
Pharmaceutical Research

Categories

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Frequently asked questions

What is Global Pollen Data - Historical Real-Time Forecast Climatology?

High-resolution global pollen data built for precision health, allergy forecasting, and demand modeling. Hourly updates, species-level insights, and region-optimized models.

What is Global Pollen Data - Historical Real-Time Forecast Climatology used for?

This product has 5 key use cases. Ambee recommends using the data for Programmatic Advertising, Demand Forecasting, Retail Intelligence, Marketing Strategy, and Pharmaceutical Research. Global businesses and organizations buy Pollen Data from Ambee to fuel their analytics and enrichment.

Who can use Global Pollen Data - Historical Real-Time Forecast Climatology?

This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Pollen Data. Get in touch with Ambee to see what their data can do for your business and find out which integrations they provide.

How far back does the data in Global Pollen Data - Historical Real-Time Forecast Climatology go?

This product has 9 years of historical coverage. It can be delivered on a hourly, daily, weekly, monthly, quarterly, yearly, real-time, and on-demand basis.

Which countries does Global Pollen Data - Historical Real-Time Forecast Climatology cover?

This product includes data covering 250 countries like USA, China, Japan, Germany, and India. Ambee is headquartered in India.

How much does Global Pollen Data - Historical Real-Time Forecast Climatology cost?

Pricing information for Global Pollen Data - Historical Real-Time Forecast Climatology is available by getting in contact with Ambee. Connect with Ambee to get a quote and arrange custom pricing models based on your data requirements.

How can I get Global Pollen Data - Historical Real-Time Forecast Climatology?

Businesses can buy Pollen Data from Ambee and get the data via S3 Bucket, SFTP, Email, UI Export, REST API, Compressed File, Snowflake Share, Google BigQuery, Google Cloud Storage, Azure Blob Storage, and Databricks Delta Share. Depending on your data requirements and subscription budget, Ambee can deliver this product in .csv, .geojson, .json, .parquet, .tiff, .txt, .xls, and .xml format.

What is the data quality of Global Pollen Data - Historical Real-Time Forecast Climatology?

You can compare and assess the data quality of Ambee using Datarade’s data marketplace.

Pricing available upon request