Interdecadal Pacific Oscillation, 1871–2016

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Creative Commons Attribution 4.0 International

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3786
50
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

Total Sunshine Hours, 1972–2016

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Creative Commons Attribution 4.0 International

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3777
42
Added
13 Oct 2017

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

Interpolated total sunshine hours values at 30 regionally representative sites.
Sunshine is essential for our mental and physical well-being and plant growth. It is also important for tourism and recreation.
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 89445
Data type Table
Row count 1350
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Daily peak UV index values, Invercargill, Leigh, Lauder, Paraparaumu and Christchurch (1981–2014)

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Creative Commons Attribution 3.0 New Zealand

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3556
21
Added
01 Oct 2015

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

Too much exposure to the sun's ultraviolet (UV) radiation can cause skin cancer. Ozone absorbs some UV radiation, and UV levels can vary in relation to changes in atmospheric ozone. Monitoring UV levels can help us understand current skin cancer risk.
The Lauder spectroradiometer (UVM dataset) data are used to assure the reliability of broad-band erythermal UV (RB dataset) from five sites. Measurements supplied are daily peak, noon-time mean, and total daily dose of erythemal (skin-reddening) UV.
Further information can be found in:
Liley, B, Querel, B, & McKenzie, R (2014). Measurements of Ozone and UV for New Zealand. Prepared for the Ministry for the Environment, Wellington. Available at data.mfe.govt.nz/x/LoPyPo on the Ministry for the Environment dataservice (data.mfe.govt.nz/).
This dataset relates to the "UV intensity" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52584
Data type Table
Row count 60760
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Growing degree days trend assessment, by site, 1972/3–2015/6

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Creative Commons Attribution 4.0 International

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3716
21
Added
18 Oct 2017

This dataset was first added to MfE Data Service on 18 Oct 2017.

Growing degree days (GDD) measures the amount of warmth available for plant and insect growth and can be used to predict when flowers will bloom and crops and insects will mature. GDD counts the total number of degrees Celsius each day is above a threshold temperature. In this report we used 10 degrees Celsius. Increased GDD means that plants and insects reach maturity faster, provided that other conditions necessary for growth are favourable, such as sufficient moisture and nutrients. As a measure of temperature, GDD experiences short-term changes in response to climate variations, such as El Niño, and in the longer-term is affected by our warming climate.
Growing degree days (GDD) counts the number of days that are warmer than a threshold temperature (Tbase) in a year. GDD is calculated by subtracting the Tbase from the average daily temperature (maximum plus minimum temperature divided by two). If the average daily temperature is less than Tbase the GDD for that day is assigned a value of zero.
This dataset gives the trend in GDD over growing seasons (July 1 – June 30 of the following year) for 30 sites.
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 89481
Data type Table
Row count 30
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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3649
47
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

Growing degree days monthly data by site, 1972–2016

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Creative Commons Attribution 4.0 International

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3646
29
Added
12 Oct 2017

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

Growing degree days (GDD) measures the amount of warmth available for plant and insect growth and can be used to predict when flowers will bloom and crops and insects will mature. GDD counts the total number of degrees Celsius each day is above a threshold temperature. In this report we used 10 degrees Celsius. Increased GDD means that plants and insects reach maturity faster, provided that other conditions necessary for growth are favourable, such as sufficient moisture and nutrients. As a measure of temperature, GDD experiences short-term changes in response to climate variations, such as El Niño, and in the longer-term is affected by our warming climate.
This dataset gives the number of GDD per month and calendar year for all 30 sites.
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 89392
Data type Table
Row count 1290
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Ozone hole (1979–2014)

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Creative Commons Attribution 3.0 New Zealand

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3441
25
Added
01 Oct 2015

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

Ozone protects the Earth from harmful levels of UV radiation. The ozone hole is an area of reduced stratospheric ozone that forms over Antarctica each spring, due to ozone-depleting substance. Reporting on the state of the ozone hole provides important context for the state of ozone concentrations globally.
This dataset relates to the "Ozone hole" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52563
Data type Table
Row count 35
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Annual rainfall trends, 1960–2016

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Creative Commons Attribution 4.0 International

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3549
42
Added
12 Oct 2017

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

Annual 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 89400
Data type Table
Row count 30
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Oceanic sea surface temperature, 1993–2016

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Creative Commons Attribution 4.0 International

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3674
32
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.
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 89406
Data type Table
Row count 960
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Number of extreme weather events identified by ICNZ (1975–2014)

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Creative Commons Attribution 3.0 New Zealand

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3394
46
Added
01 Oct 2015

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

Extreme weather events are weather events that are rare or even statistically unlikely. In New Zealand, such events can be dangerous and costly, both socially and monetarily. They can cause damage that affects productivity and leads to millions of dollars in insurance claims.
This dataset relates to the "Insurance losses for extreme weather events" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52586
Data type Table
Row count 129
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed
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