Rainfall Intensity, 1960–2016

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Creative Commons Attribution 4.0 International

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5950
83
Added
13 Oct 2017

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

Two measures of rainfall intensity - percent of annual precipitation in the 95th percentile (r95ptot) and annual maximum one-day rainfall (rx1day).
Intense rainfall can result in flash floods or land slips that damage homes and property, disrupt transportation, and endanger lives. It can also interfere with recreation and increase erosion. Changes to the frequency of intense rainfall events can alter biodiversity.
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 89435
Data type Table
Row count 1710
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

New Zealand's greenhouse gas emissions, 1990 - 2018

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Creative Commons Attribution 4.0 International

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2337
35
Added
14 Oct 2020

This dataset was first added to MfE Data Service on 14 Oct 2020.

DATA SOURCE: Ministry for the Environment

Adapted by Ministry for the Environment and Statistics New Zealand to provide for environmental reporting transparency

Dataset used to develop the "New Zealand's greenhouse gas emissions" indicator [available at www.stats.govtnz/indicators/new-zealanads-greenhou...]

This indicator measures New Zealand’s greenhouse gas (GHG) emissions in carbon dioxide equivalent (CO-e) units from 1990 to 2018.

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 105058
Data type Table
Row count 252938
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Monthly average peak UV index value, 1981–2017

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Creative Commons Attribution 4.0 International

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9427
33
Added
14 Oct 2017

This dataset was first added to MfE Data Service on 14 Oct 2017.

Monthly average peak UV index values at Invercargill, Lauder (Otago region), Christchurch, Paraparaumu (Wellington region), and Leigh (Auckland region). The strength of UV light is expressed as a solar UV index, starting from 0 (no UV) to 11+ (extreme).
Exposure to the sun's ultraviolet (UV) light helps our bodies make vitamin D, which we need for healthy bones and muscles. However, too much exposure to UV light can cause skin cancer. New Zealand has naturally high UV levels, and monitoring UV levels helps us understand the occurrence of skin cancer.
Ozone in the upper atmosphere absorbs some of the sun’s UV light, protecting us from harmful levels. The amount of UV radiation reaching the ground varies in relation to changes in the atmospheric ozone concentrations. The Antarctic ozone hole lies well to the south of New Zealand and does not have a large effect on New Zealand’s ozone concentrations.
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 89467
Data type Table
Row count 65
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Extreme wind, 1972 - 2019, trend

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Creative Commons Attribution 4.0 International

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1819
5
Added
14 Oct 2020

This dataset was first added to MfE Data Service on 14 Oct 2020.

DATA SOURCE: National Institute for Water and Atmospheric Research (NIWA)
[Technical report available at www.mfe.govt.nz/publications/environmental-reporti...]

Adapted by Ministry for the Environment and Statistics New Zealand to provide for environmental reporting transparency

Dataset used to develop the "Extreme wind indicator [available at www.stats.govt.nz/indicators/extreme-wind]

This indicator measures the strength of extreme wind and how often extreme wind events (measured as a gust that is extreme for that location) happen at 30 sites across New Zealand from 1972 to 2019, although not all sites start at 1972. We report windiness using the annual average of the daily maximum wind gust. We report wind strength using the annual maximum wind gust. We use the number of days per year with a maximum wind gust in the 99th percentile to report how often extreme wind events occur for a location (on average, the 99th percentile daily maximum wind gust will be exceeded on 3.6 days per year). We also present trends for all three of these measures.

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 105049
Data type Table
Row count 84
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Trends in maximum highest annual wind gust, 1972–2016

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Creative Commons Attribution 4.0 International

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5502
17
Added
12 Oct 2017

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

Trends in maximum highest annual wind gust, 1972–2016. 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.
Trend direction was assessed using the Theil-Sen estimator and the Two One-Sided Test (TOST) for equivalence at the 95% confidence level.
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 89424
Data type Table
Row count 30
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Oceanic sea surface temperature trends, 1993–2016

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Creative Commons Attribution 4.0 International

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6451
11
Added
12 Oct 2017

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

We used NIWA’s sea-surface temperature archive, which is derived from the Advanced Very High Resolution Radiometer (AVHRR) satellite data it receives from the US National Oceanic and Atmospheric Administration. The archive provides high spatial (approximately 1km) and high temporal (approximately six-hourly in cloud-free locations) resolution estimates of sea-surface temperatures over the New Zealand region, dating from January 1993. Uddstrom & Oien (1999) and Uddstrom (2003) describe the methods used to derive and validate the data.
Our data extends from about 30°S to 55°S, and from 160°E to 170°W and is grouped into five areas: the exclusive economic zone (EEZ), the Chatham Rise, northern subtropical waters, subantarctic waters, and the Tasman Sea.
Trend direction was assessed using the Theil-Sen estimator and the Two One-Sided Test (TOST) for equivalence at the 95% confidence level.
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 89407
Data type Table
Row count 4
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Spring rainfall trends, 1960–2016

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Creative Commons Attribution 4.0 International

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5392
12
Added
12 Oct 2017

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

Spring rainfall trends 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.
Trend direction was assessed using the Theil-Sen estimator and the Two One-Sided Test (TOST) for equivalence at the 95% confidence level.
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 89403
Data type Table
Row count 30
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Summer rainfall trends, 1960–2016

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Creative Commons Attribution 4.0 International

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5483
15
Added
12 Oct 2017

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

Summer rainfall trends 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.
Trend direction was assessed using the Theil-Sen estimator and the Two One-Sided Test (TOST) for equivalence at the 95% confidence level.
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 89404
Data type Table
Row count 30
Services Web Feature Service (WFS), 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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7650
74
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

Annual growing degree days

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Creative Commons Attribution 3.0 New Zealand

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10489
121
Added
01 Oct 2015

This dataset was first added to MfE Data Service on 01 Oct 2015.

Growing degree days (GDD) is the measure of how much warmth is available for plant and insect growth during a growing season. GDD information helps horticulturists and farmers predict plant growth and stock development. The GDD value changes in response to climate variations, such as El Niño. Long-term changes in GDD are a measure of changing climate conditions.
Further information can be found in:
Tait, A, Macara, G, & Paul, V. (2014) Preparation of climate datasets for the 2015 Environmental Synthesis Report: Temperature, Rainfall, Wind, Sunshine and Soil Moisture. Prepared for Ministry for the Environment. Available at data.mfe.govt.nz/x/Fwn9AL on the Ministry for the Environment dataservice (data.mfe.govt.nz/).
This dataset relates to the "Growing degree days" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52574
Data type Table
Row count 12168
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed
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