Southern annular mode (1887–2014)

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Creative Commons Attribution 3.0 New Zealand

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6414
31
Added
01 Oct 2015

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

The Southern Annular Mode (SAM) is an index that describes climate variation around the South Pole and Antarctica, as far north as New Zealand. It indicates short-term climate variations that can influence New Zealand’s climate. Such climate variations can impact on our environment, industries, and recreational activities.
The variation is caused by the movement of a low-pressure belt that generates westerly winds. During a negative phase, the low pressure belt moves north, towards the equator. In New Zealand, this can cause increased westerly winds, unsettled weather, and storm activity over most of the country. Over the southern oceans, there are relatively less westerly winds and less storm activity.
During a positive phase, the low pressure belt moves south towards Antarctica. In New Zealand, this can cause relatively light winds and more settled weather. Over the southern oceans, there is increased westerly winds and storm activity.
This dataset relates to the "Southern annular mode" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52592
Data type Table
Row count 128
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Autumn 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.

6425
18
Added
12 Oct 2017

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

Autumn 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 89402
Data type Table
Row count 30
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Primary use and source of consented freshwater takes, 2013–14

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Creative Commons Attribution 3.0 New Zealand

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6303
111
Added
25 Apr 2017

This dataset was first added to MfE Data Service on 25 Apr 2017.

Regional councils issue resource consents for the taking of fresh water for various purposes, including irrigation, drinking, hydroelectricity, and industry. Water can be taken from surface water or groundwater.

The file provides the primary source and primary use of the water take for each consented take.

Table ID 53613
Data type Table
Row count 16154
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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6312
88
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

Mean annual sea-surface temperatures (1993–2013)

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Creative Commons Attribution 3.0 New Zealand

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6353
42
Added
01 Oct 2015

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

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. Sea surface temperature changes with climate drivers such as El Niño, and will change with climate change. The sea surface temperature anomaly provides an indication of the heat change in the ocean.
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.
The oceanic sea surface temperature data comes from the NIWA Sea surface temperature Archive (NSA). There are 2 datasets, NSA Annual Means and NSA Annual Anomolies ,covering the Tasman, subtropical (STW) and Southern Antarctic (SAW) area and the total area. The data is available from 1993 to 2013 and the unit of measure is degrees Celsius .
For more information please see:
Uddstrom, MJ (2015) Sea Surface Temperature Data and Analysis for the 2015 Synthesis Report. For Ministry for the Environment. Available at data.mfe.govt.nz/x/hRbGUJ on the Ministry for the Environment dataservice (data.mfe.govt.nz).
Trend results can be found in the excel file "Sea surface temperature trend statistics" found at data.mfe.govt.nz/x/DGXFS6.
This dataset relates to the "Sea surface temperature" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52581
Data type Table
Row count 84
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Lightning by region

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Creative Commons Attribution 3.0 New Zealand

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6370
21
Added
11 Nov 2016

This dataset was first added to MfE Data Service on 11 Nov 2016.

Lightning is the discharge of electricity from thunderstorms. Ground strikes can cause significant damage to property and infrastructure, and injure or kill people and livestock. Lightning is often associated with other severe weather events, such as strong wind gusts. Thunderstorms may increase in frequency and intensity with climate change.
This dataset relates to the "Lightning" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 53515
Data type Table
Row count 621924
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Emissions from burning wood or coal for home heating 2006 and 2013

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Creative Commons Attribution 3.0 New Zealand

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6353
31
Added
16 Sep 2015

This dataset was first added to MfE Data Service on 16 Sep 2015.

In 2013, 37 percent of homes burned wood and 4 percent burned coal for heating. Burning wood or coal for home heating emits a range of air pollutants. It is the main human-made source of particulate matter and a significant contributor of carbon monoxide. Exposure to these pollutants can damage health, with effects ranging from respiratory irritation to cancer.

The proportions of homes using wood or coal for heating vary around the country. Generally, the use of wood and coal for home heating is greater in the South Island than in the North Island. The West Coast has the highest proportion (72 percent use wood, 56 percent use coal), while in contrast Auckland has lower usage (23 percent use wood and 2 percent use coal). Burning wood or coal for home heating continues to be associated with air quality issues, including high levels of PM10, PM2.5, arsenic, and benzo(a)pyrene at some locations.

This dataset relates to the "Home-heating emissions" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52451
Data type Table
Row count 20
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Annual maximum three-day rainfall totals (1950–2013

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Creative Commons Attribution 3.0 New Zealand

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You must attribute the creator in your own works.

6287
66
Added
01 Oct 2015

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

A three-day rainfall measurement covers a single sustained rain event or a series of shorter events over a three-day period. Such measurements help us understand and prepare for flooding or rain-induced slips that could cause damage.
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 "Annual maximum three-day rainfall" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52580
Data type Table
Row count 1920
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Annual rainfall trends, 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.

6280
63
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

Estimated highly erodible land in North Island, by region, 2012

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Creative Commons Attribution 3.0 New Zealand

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6296
34
Added
28 Sep 2015

This dataset was first added to MfE Data Service on 28 Sep 2015.

Some areas of New Zealand’s North Island are classified as highly erodible land. They have steep slopes and are at high risk of mass soil movement due to the absence of woody vegetation cover with deep roots to hold the soil in place. This can lead to soil erosion. It is important to identify areas of land at risk of severe erosion to inform land use decisions and help prioritise soil conservation work.

This dataset relates to the "Estimated highly erodible land in the North Island" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52481
Data type Table
Row count 280
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed
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