Trends in number of days with a maximum gust in the 99th percentile, 1972–2016

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3889
6
Added
12 Oct 2017

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

Trends in number of days with a maximum gust in the 99th percentile, 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 89423
Data type Table
Row count 30
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

You may use this work for commercial purposes.

You must attribute the creator in your own works.

3711
11
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

Trends in greenhouse gas concentrations at Baring Head, 1972–2016

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Creative Commons Attribution 4.0 International

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3200
4
Added
12 Oct 2017

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

We report on GHG concentrations in ‘clean air’ measured at Baring Head, near Wellington. These measurements give us a good idea of global concentrations and help us infer long-term impacts on ocean acidity, temperature, sea level and glaciers.
Trends were 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 89413
Data type Table
Row count 3
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Trends in global production of ozone depleting substances, 1986–2015

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Creative Commons Attribution 4.0 International

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3769
2
Added
13 Oct 2017

This dataset was first added to MfE Data Service on 13 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.
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 89450
Data type Table
Row count 9
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Trends in global and New Zealand temperature anomalies, 1909–2016

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Creative Commons Attribution 4.0 International

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3000
10
Added
14 Oct 2017

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

This dataset contains trends in temperatures anomalies from NIWA's 'seven-station' temperature series and three global temperature series.
Trends were assessed using linear regression 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 89455
Data type Table
Row count 4
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Trends in annual maximum one–day rainfall (rx1day), 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.

3764
8
Added
13 Oct 2017

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

Trends in annual maximum one-day rainfall (rx1day), 1960–2016.
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.
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 89433
Data type Table
Row count 30
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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You must attribute the creator in your own works.

4295
46
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

Total column ozone, Lauder, assimilated series (1978-2013)

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Creative Commons Attribution 3.0 New Zealand

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2751
4
Added
01 Oct 2015

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

Ozone (O3) is a gas that is of interest in two regions of Earth’s atmosphere – at ground level and in the upper atmosphere (stratosphere). Stratospheric ozone absorbs ultraviolet (UV) rays from the sun and protects Earth from harmful levels of UV. Exposure to these UV rays has been linked to skin cancer. Monitoring variations in stratospheric ozone concentrations is important in New Zealand as we have high rates of skin cancers.
Ozone data for Lauder have been supplied in two forms: Measurements taken with Dobson spectrophotometer (number 72) and data assimilated from satellite measurements recalibrated against the global Dobson network. The Dobson spectrophotometer has been in operation at Lauder since January 1987. The timeseries for interpolated satellite data is available from 1978. Both timeseries are provided until 2013.
This dataset is the assimilated dataset which is available from 1978 to 2013. Measurements are in Dobson units (DU). One DU represents the amount of ozone molecules needed to produce a 0.01mm layer of pure ozone.
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 "Ozone concentrations" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52557
Data type Table
Row count 12643
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

The annual SOI compared with New Zealand's detrended temperature series, 1908/9–2015/6

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Creative Commons Attribution 4.0 International

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3741
9
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 annual ENSO and detrended temperature data.
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 89380
Data type Table
Row count 216
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

The annual SOI compared with New Zealand's detrended temperature series (1909–2013)

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Creative Commons Attribution 3.0 New Zealand

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You must attribute the creator in your own works.

3565
20
Added
01 Oct 2015

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

El Niño Southern Oscillation (ENSO). It is an important predictor of how tropical oceans and climate might influence New Zealand’s climate. Being able to predict the timing and intensity of an El Niño or La Niña climate phase is important in predicting and preparing for extreme climatic conditions, such as strong winds, heavy rain, or drought. Such extreme conditions can impact on our environment, industries, and recreational activities. ENSO is commonly measured using the Southern Oscillation Index (SOI).
In New Zealand, an El Niño phase can cause colder winters. In summer it can result in more rain in the west and drought in the east. A La Niña phase can cause warmer temperatures, more rain in the north-east, and less rain in the south and south-west.
This dataset relates to the "El Niño Southern Oscillation" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52590
Data type Table
Row count 105
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed
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