Weather and climate forecasting data services

We can deliver forecasts using API, GIS and web interfaces, all underpinned by our data analytics expertise.

Obtain forecast data from NIWA

About NIWA environmental forecast products

Short-term, ultra-high resolution weather forecasting, New Zealand Convective Scale Model (NZCSM): The NZCSM is NIWA’s highest resolution, short-term (48-hour) weather model. Updated four times a day, the model is run at a 1.5km resolution, which enables highly detailed outputs of things like rain, temperature, wind, and much more at a town-by-town level.

Integrated medium-range forecasting, Optimal Seamless Forecast (OSF): OSF is a model that seamlessly stitches together NIWA’s weather modelling out 10 days into the future. The underlying model selects the best-performing model at the different time scales to offer NIWA’s best overall weather outlook.

High resolution probabilistic forecasting, New Zealand Ensemble System (NZENS): NZENS is an ensemble system or a group of 18 different model members run 5 days into the future. Although traditional weather forecasts are often based on a single model, by having multiple model members, forecast information can be considered in a probabilistic sense, which is beneficial toward understanding forecast confidence, the chance of threshold exceedance, and the likely location of a weather event.

Monthly forecast trends (sub-seasonal), NIWA35: NIWA35 is a sub-seasonal model, best used to identify forecast themes, trends, and anomalies 5 weeks into the future. Unlike a weather forecast, its utility is in identifying long-range regional patterns, such as rainfall being above or below normal. NIWA35 produces daily-to-weekly rainfall, soil moisture, and drought forecasts 35 days into the future and can be used to inform longer-term decisions.

Seasonal forecast trends, Seasonal Climate Outlook: NIWA has produced seasonal climate outlooks since 1999, which provide indications of rainfall, temperature, and hydrological conditions three months into the future. The models that underpin the seasonal climate outlook are sourced from Global Producing Centres and their data is translated into a New Zealand context.

Preparing for our future climate, Climate change projections: NIWA’s climate change scenario data can help different sectors plan and prepare for New Zealand’s future climate. Future climate pathways can provide an indication of the likely changes in seasonal temperature, rainfall, and wind patterns across the country through the end of the 21st century.

Technical details of data

 Spatial resolution Temporal resolution Period 
NZCSM 1.5km 30 minutes 48 hrs 
OSF 1.5km 1 hour 10 days 
NZENS 4.5km 1 hour 120 hrs 
NIWA35 5km Daily 35 days 
Seasonal Climate Outlook 100 km Monthly 6 months 
Climate change 5 km Average parameters for 20 years  To the year 2120 

Core parameters for NZCSM, OSF, NZENS and Seasonal Climate Outlook (not all parameters apply to all models):

  • Air Temperature 
  • Relative Humidity 
  • Rainfall 
  • Wind  
  • Air Pressure 
  • Solar radiation/sunshine

Forecasts by API 

NIWA can deliver forecasts by API (application programming interface) so you integrate our data feeds directly into your own systems.

Web interfaces and custom solutions

Alternately we also have several web interfaces you can use to access our forecast model data – or we can work with you to build custom solutions. 

Forecasting as a GIS service

Another mode of delivery for our forecasts is using GIS. By overlaying your own assets, infrastructure maps or areas of interest with NIWA weather data, you will have access to the best information to make the best decisions. 

You can define the asset-specific weather conditions you’re most interested in and use these to generate alerts and warnings in a geo-temporal context using dashboards and other applications.

Our web-based dashboard helps you to: 

  • assess the potential risks faced by your assets, infrastructure or operations
  • forecast hazards that may impact your assets, infrastructure or operations
  • schedule environmental condition-dependent operations
  • prepare for significant weather.

Data analytics

With expertise and experience in data analytics and machine learning, we can leverage our wealth of weather and climate data (high-resolution modelling, climate database and historic weather data) to develop predictive analytics to inform your business needs. For instance, how does weather impact your sales or how has it affected modes of transportation?