Annual maximum three-day rainfall totals (1950–2013

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Creative Commons Attribution 3.0 New Zealand

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4731
58
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

Oceanic sea surface temperature anomaly

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Creative Commons Attribution 3.0 New Zealand

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4023
23
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, of 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 celcius.
For further 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).
This dataset relates to the "Sea surface temperature" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52582
Data type Table
Row count 84
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Monthly El Niño Southern Oscillation Index, 1986–2016

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Creative Commons Attribution 4.0 International

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4932
69
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 monthly ENSO values.
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 89381
Data type Table
Row count 372
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Rainfall Intensity, 1960–2016

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Creative Commons Attribution 4.0 International

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3974
56
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

Influenza hospital discharges (2000–13)

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Creative Commons Attribution 3.0 New Zealand

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4757
41
Added
01 Oct 2015

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

Influenza is a potentially life-threatening virus that spreads quickly from person to person. It is a significant public health issue in this country, with 10–20 percent of New Zealanders infected every year. While influenza outbreaks can occur all year round, rates peak in winter and spring. This is because the virus can survive longer outside the body in periods of colder weather and low absolute humidity (dry conditions).
This dataset relates to the "Influenza" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52553
Data type Table
Row count 28
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Daily 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.

4354
26
Added
14 Oct 2017

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

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.
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 89468
Data type Table
Row count 38993
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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3719
13
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

El Niño Southern Oscillation Index (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.

4436
73
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 52589
Data type Table
Row count 1729
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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You must attribute the creator in your own works.

3996
55
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

Annual average temperature anomaly (1909–2013)

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Creative Commons Attribution 3.0 New Zealand

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5073
74
Added
01 Oct 2015

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

Temperature change is influenced by changes in atmospheric composition that result from greenhouse gas emissions. It is also linked to atmospheric circulation changes (eg the El Niño southern oscillation). It can have a significant effect on agriculture, energy demand, and recreation. The primary purpose of the dataset is to provide a long time series which represents the nation-scale state of climate with respect to temperature in New Zealand.
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 "National temperature time series" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52572
Data type Table
Row count 1793
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed
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