Southern Annular Mode monthly values, January 1979–December 2016

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Creative Commons Attribution 4.0 International

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1915
16
Added
12 Oct 2017

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

A consistent band of westerly wind flows across the Southern Hemisphere and circles the South Pole. The Southern Annular Mode (SAM) describes how this band moves, either north towards the equator (negative phase) or south towards Antarctica (positive phase). A negative phase typically causes increased westerlies, unsettled weather, and storms in New Zealand. A phase can last several weeks, but changes can be rapid and unpredictable.
The SAM is one of three climate oscillations that affect our weather. The resulting changes in air pressure, sea temperature, and wind direction can last for weeks to decades, depending on the oscillation.
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 89384
Data type Table
Row count 456
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Forest carbon stocks, 1990–2015

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Creative Commons Attribution 4.0 International

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1912
17
Added
17 Oct 2017

This dataset was first added to MfE Data Service on 17 Oct 2017.

Forest carbon stocks and areas, including stock changes, areas, and deforestation.
New Zealand’s indigenous and exotic forests absorb carbon dioxide (CO2) from the atmosphere through photosynthesis and store the carbon as biomass and in the soil. On average, more than twice as much carbon per hectare is stored in New Zealand’s mature indigenous forests than in exotic forests planted for wood production. Regenerating indigenous forests are also an important store of carbon, adding carbon every year as they grow. Total carbon stored in exotic forests will fluctuate over decades as the forests grow from seedlings to mature trees, are harvested, and replanted. Because CO2 is the major driver of climate change, forests provide important mitigation services and help New Zealand meet its climate change commitments.
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 89475
Data type Table
Row count 1066
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Global greenhouse gas emissions (1990–2011)

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Creative Commons Attribution 3.0 New Zealand

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1901
28
Added
01 Oct 2015

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

Greenhouse gas (GHG) emissions from human activities increase the concentrations of these gases in the atmosphere. GHGs absorb some of the heat radiating from the Earth’s surface and warm the atmosphere. In turn, this warming changes our climate. Some GHG emissions are removed, primarily by forests. For this reason, we use net emission rather than gross emission values to represent the total amount of gas contributed to the atmosphere.
This data is compiled from two sources. The UNFCCC (United Nations) GHG data and CAIT 2.0 (World Resources Institute, climate analysis indicators tool 2014).
This dataset relates to the "Global greenhouse gas emissions" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52564
Data type Table
Row count 5258
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Global production of ozone depleting substances, 1986–2015

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Creative Commons Attribution 4.0 International

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1914
5
Added
17 Oct 2017

This dataset was first added to MfE Data Service on 17 Oct 2017.

Ozone in the stratosphere is destroyed in a catalytic reaction with a range of chemical species (mainly CFCs) that are emitted through human activities. The emission of these chemicals is closely related to the amount of the chemicals that are produced. The Montreal protocol helps the UNEP collect information on the production of ozone depleting substances.
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 89474
Data type Table
Row count 9
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Annual ozone concentrations, 1979–2016

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Creative Commons Attribution 4.0 International

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1901
9
Added
14 Oct 2017

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

NIWA supplied ozone data in two forms, with different starting dates:
- measurements made using a Dobson spectrophotometer (number 72), from 1987
- data assimilated from satellite measurements recalibrated against the global Dobson network, from 1978.
NIWA takes measurements using the Dobson spectrophotometer 72 under clear-sky, direct sunlight conditions at Lauder in Otago. There are gaps in the time series due to days with cloud, rain, or too much wind. However, over the whole period, each individual calendar day of the year was measured. This allows us to calculate statistics based on the day of the year.
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 89463
Data type Table
Row count 114
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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You must attribute the creator in your own works.

1897
8
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

Ozone hole (1979–2014)

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Creative Commons Attribution 3.0 New Zealand

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1880
24
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

Trends in total sunshine hours, 1972–2016

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Creative Commons Attribution 4.0 International

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1863
11
Added
13 Oct 2017

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

Trends in total sunshine hours, 1972–2016.
Sunshine is essential for our mental and physical well–being and plant growth. It is also important for tourism and recreation.
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 89444
Data type Table
Row count 30
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Trends in peak UV index value, 1981–2017

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Creative Commons Attribution 4.0 International

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You must attribute the creator in your own works.

1865
5
Added
14 Oct 2017

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

Trends in daily 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.
The trend 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 89469
Data type Table
Row count 5
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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1865
4
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
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