Average annual rainfall, 1972–2013

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Creative Commons Attribution 3.0 New Zealand

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You must attribute the creator in your own works.

10865
370
Added
18 Feb 2016

This dataset was first added to MfE Data Service on 18 Feb 2016.

Annual rainfall is the total accumulated rain over one year. Rain is vital for life, including plant growth, drinking water, river ecosystem health, and sanitation. Floods and droughts affect our environment, economy, and recreational opportunities.

This dataset shows annual average rainfall across New Zealand for years 1972 to 2013. Annual rainfall is estimated from the daily rainfall estimates of the Virtual Climate Station Network (NIWA).

This dataset relates to the "Annual average rainfall" measure on the Environmental Indicators, Te taiao Aotearoa website.

Geometry: raster catalogue
Unit: mm/yr

Layer ID 53314
Data type Grid
Resolution 5110.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

Rainfall, 1960–2016

Licence

Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

5502
204
Added
12 Oct 2017

This dataset was first added to MfE Data Service on 12 Oct 2017.

Daily rainfall values for 30 representative sites from 1960–2016.
Rain is vital for life – it supplies the water we need to drink and to grow our food, keeps our ecosystems healthy, and supplies our electricity. New Zealand’s mountainous terrain and location in the roaring forties mean rainfall varies across the country. Changes in rainfall amount or timing can significantly affect agriculture, energy, recreation, and the environment. For example, an increase or decrease of rainfall in spring can have marked effects on crops or fish populations.
More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Table ID 89401
Data type Table
Row count 617808
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Average annual rainfall, 2016

Licence

Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

5951
116
Added
12 Oct 2017

This dataset was first added to MfE Data Service on 12 Oct 2017.

Rain is vital for life – it supplies the water we need to drink and to grow our food, keeps our ecosystems healthy, and supplies our electricity. New Zealand’s mountainous terrain and location in the roaring forties mean rainfall varies across the country. Changes in rainfall amount or timing can significantly affect agriculture, energy, recreation, and the environment. For example, an increase or decrease of rainfall in spring can have marked effects on crops or fish populations.
More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Layer ID 89420
Data type Grid
Resolution 5110.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

Monthly El Niño Southern Oscillation Index, 1986–2016

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Creative Commons Attribution 4.0 International

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You must attribute the creator in your own works.

4985
65
Added
12 Oct 2017

This dataset was first added to MfE Data Service on 12 Oct 2017.

The El Niño Southern Oscillation (ENSO) is the movement of warm equatorial water across the Pacific Ocean and the atmospheric response. It occurs every 2–7 years, typically lasting 6–18 months. ENSO has three phases: neutral, El Niño and La Niña. In New Zealand an El Niño phase in summer can bring increased westerly winds, more rain in the west, and drought in the east; in winter it can lead to more cool southerly winds. During a La Niña phase we may experience more north-easterly winds, wetter conditions in the north and east, and higher sea levels.
This dataset relates to monthly ENSO values.
More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Table ID 89381
Data type Table
Row count 372
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Extreme wind, 1972–2016

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Creative Commons Attribution 4.0 International

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You must attribute the creator in your own works.

4286
54
Added
12 Oct 2017

This dataset was first added to MfE Data Service on 12 Oct 2017.

Extreme wind annual statistics for 30 regionally representative sites. The number of days with a maximum gust in the 99th percentile provides information on the frequency of extreme wind events. Percentiles are obtained from all available daily maximum wind gust data. On average, the 99th percentile daily maximum wind gust will be exceeded on approximately 3.6 days per year. Therefore, annual counts higher than this indicate more days than usual with very strong wind gusts recorded; annual counts lower than 3.6 indicate fewer strong wind gust days than usual. By using a percentile threshold we can identify events that are extreme for a particular location. Some places are naturally subject to stronger winds than others, so vegetation can become ‘wind-hardened’ and may have a higher tolerance to high wind gusts (eg a 100 km/hr wind gust may be damaging at one location, but not at another). Using a relative threshold accounts for these differences and better captures extreme wind gust occurrences. The highest maximum gust per year and the average annual highest maximum wind gust both provide information on the magnitude of extreme wind events.
Steady wind can be an important resource, but strong gusts can damage property, topple trees, and disrupt transportation, communications, and electricity. Extreme wind events can occur with frontal weather systems, around strong convective storms such as thunderstorms, and with ex-tropical cyclones. Projections indicate climate change may alter the occurrence of extreme wind events, with the strength of extreme winds expected to increase over the southern half of the North Island and the South Island, especially east of the Southern Alps, and decrease from Northland to Bay of Plenty. Monitoring can help us gauge the potential of, and prepare for, such events.
More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Table ID 89425
Data type Table
Row count 1327
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Lightning strike density, 2000–14

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Creative Commons Attribution 3.0 New Zealand

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You must attribute the creator in your own works.

4336
29
Added
10 Feb 2016

This dataset was first added to MfE Data Service on 10 Feb 2016.

Lightning is the discharge of electricity, from thunderstorms, that equalises areas of positive and negative charge, for example, between a storm cloud and the ground. Thunderstorms form as a result of rapidly rising air with a high moisture content (humidity). On average, 1 in 10 lightning discharges strikes the ground (or sea) (Metservice, 2015). Lightning (and therefore thunderstorms) are also often associated with other severe weather events, such as strong wind gusts, and in extreme cases tornadoes.

By international standards, lightning does not occur frequently around New Zealand. However, thunderstorms, and thus lightning, can cause injury and damage (Ministry of Civil Defence and Emergency Management, 2010), and may increase in frequency and intensity with climate change (Mullen et. al., 2011).

This data shows the average annual number of lightning strikes per 25km square.

This dataset relates to the "Lightning" measure on the Environmental Indicators, Te taiao Aotearoa website.

Geometry: grid/point

Unit: strikes/25km2/year

Further information can be found in:

MetService (nd). Lightning observation services. Accessed 3 June 2015 from www.metservice.com.

Ministry of Civil Defence and Emergency Management (2010). Thunderstorms. Working from the same page: Consistent messages for CDEM (p3). Available from www.civildefence.govt.nz.

Mullan, B, Carey-Smith, T, Griffiths, G, & Sood, A (2011). Scenarios of storminess and regional wind extremes under climate change. NIWA Client Report: WLG2010-31 (pvii). Available from www.niwa.co.nz.

Layer ID 52851
Data type Grid
Resolution 5000.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

Average sea–surface temperature, 1993–2012

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Creative Commons Attribution 3.0 New Zealand

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You must attribute the creator in your own works.

4912
52
Added
18 Feb 2016

This dataset was first added to MfE Data Service on 18 Feb 2016.

The ocean waters surrounding New Zealand vary in temperature from north to south. They interact with heat and moisture in the atmosphere and affect our weather. Long-term changes and short-term variability in sea-surface temperatures can affect marine processes, habitats, and species. Some species may find it hard to survive in changing environmental conditions.

This grid shows average annual sea-surface temperature for years 1993 to 2013.

NIWA’s sea-surface temperature archive is derived from the Advanced Very High Resolution Radiometer (AVHRR) satellite data it receives from the National Oceanic and Atmospheric Administration. The archive provides high spatial (approximately 1km) and high temporal (approximately 6-hourly in cloud-free locations) resolution estimates of sea-surface temperatures over the New Zealand region, dating from January 1993. Uddstrom and Oien (1999) and Uddstrom (2003) describe the methods used to derive and validate the data.

This dataset relates to the "Annual average sea-surface temperature" measure on the Environmental Indicators, Te taiao Aotearoa website.

Further information can be found in:

Uddstrom, MJ (2003). Lessons from high-resolution satellite SSTs. Bulletin of the American Meteorological Society, 84(7), 896–897.

Uddstrom, MJ, & Oien, NA (1999). On the use of high resolution satellite data to describe the spatial and temporal variability of sea surface temperatures in the New Zealand region. Journal of Geophysical Research (Oceans) 104, chapter 9, 20729–20751.

Layer ID 53316
Data type Grid
Resolution 2000.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

Potential evapotranspiration deficit (PED), 1972–2016

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Creative Commons Attribution 4.0 International

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5414
30
Added
13 Oct 2017

This dataset was first added to MfE Data Service on 13 Oct 2017.

Interpolated PED values at 30 regionally representative sites.
Soil moisture is vital for plant growth. When plants cannot access the water they need, growth is reduced, affecting crops and food for livestock, and native biodiversity. Over a sustained period, a drought can have significant social and economic costs, particularly for rural communities.
Potential evapotranspiration deficit (PED) can be thought of as a drought index. It is the difference between how much water could potentially be lost from the soil through evapotranspiration and how much is actually available. When PED is high, plants do not have the full amount of water available they need for growth. PED is measured in growing seasons (the 12 months from 1 July to 30 June of the following year. Data covers each of the growing seasons from 1 July 1972, with the last growing season in the series ending on 30 June 2016. More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Table ID 89437
Data type Table
Row count 1320
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Soil moisture PED annual average 1972-2014

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Creative Commons Attribution 3.0 New Zealand

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You must attribute the creator in your own works.

5028
81
Added
18 Feb 2016

This dataset was first added to MfE Data Service on 18 Feb 2016.

Soil moisture is important for plant growth. A lack of moisture content over a growing season is a good indicator of drought, which can have social, environmental, and economic impacts. Increasing temperatures and changes in rainfall patterns are expected to increase the frequency and intensity of drought in many regions. Growing season soil moisture deficits are estimated by the potential evapotranspiration deficit, the difference between rainfall and evapotranspiration.

This dataset shows annual average soil moisture (potential evapotranspiration deficit (PED)) across New Zealand for years 1972 to 2014.

Evapotranspiration is the loss of water by evaporation and plant transpiration. PED is the difference between estimated evapotranspiration and rainfall.

We produced maps of the annual PED total (in millimetres) for every growing season (calculated as July–June years) from 1972 to 2013. Care should be taken when comparing maps from year to year – days may be missing from the PED GIS data, and data may have been interpolated to complete the dataset. The interpolation accuracy is lowest in areas of high elevation, where there are fewer climate stations and complex terrain affects accuracy. Climate stations may also open and close, affecting the accuracy of the data provided.

This dataset relates to the "Soil moisture and drought" measure on the Environmental Indicators, Te taiao Aotearoa website.

Geometry: raster catalogue
Unit: mm/yr

Layer ID 53315
Data type Grid
Resolution 5096.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

Interdecadal Pacific Oscillation, 1871–2016

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Creative Commons Attribution 4.0 International

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You must attribute the creator in your own works.

5031
58
Added
12 Oct 2017

This dataset was first added to MfE Data Service on 12 Oct 2017.

The Interdecadal Pacific Oscillation (IPO) is a long-term oscillation of sea-surface temperatures in the Pacific Ocean that can last from 20 to 30 years. Its positive and negative phases affect the strength and frequency of El Niño and La Niña. In New Zealand, the positive phase is linked to stronger west to southwest winds and more rain in the west. This trend is reversed during the negative phase.
More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Table ID 89382
Data type Table
Row count 730
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed
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