Interdecadal Pacific Oscillation, 1871–2016

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Creative Commons Attribution 4.0 International

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3190
49
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

Daily peak, noon, and SED UV (UVM dataset)

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Creative Commons Attribution 3.0 New Zealand

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3208
35
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 most reliable data on solar UV irradiance in New Zealand are from spectroradiometers developed and operated by NIWA at Lauder since summer 1989/90. The dataset supplied begins in 1993, and measurements includee 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 52583
Data type Table
Row count 7530
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Southern Annular Mode annual values, 1887–2016

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Creative Commons Attribution 4.0 International

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3184
22
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 89383
Data type Table
Row count 168
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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3166
18
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

Water physical stocks by region (1995–2014)

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Creative Commons Attribution 3.0 New Zealand

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3110
36
Added
01 Oct 2015

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

New Zealand is a water-rich country. Water is found in a network of waterways and lakes, as ground water, in glaciers, and in the soil and plants. Changes in temperature and precipitation patterns affect our water stocks, for example leading to low flows or floods. Water physical stocks show how climate changes can impact on our environment, its ecosystems, and ultimately our lifestyles.
Further information can be found in:
Collins, D, Zammit, C, Willsman, A & Henderson, R (2015) Surface water components of New Zealand’s National WaterAccounts, 1995-2014. Prepared for Ministry for the Environment May 2015. Available at data.mfe.govt.nz/x/Tebsax on the Ministry for the Environment dataservice (data.mfe.govt.nz/).
This dataset relates to the "Water physical stocks: precipitation and evapotranspiration" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52578
Data type Table
Row count 3520
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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3117
23
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

Extreme wind, 1972–2016

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Creative Commons Attribution 4.0 International

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3101
44
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

Number of frost days for selected sites (1975–2013)

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Creative Commons Attribution 3.0 New Zealand

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3086
36
Added
01 Oct 2015

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

The number of frost and hot days we experience each year can change in response to many climate factors, such as the warming pattern induced by El Niño. These numbers indicate the variations in our climate and are an important consideration in agriculture. They also affect our behaviour, for example, what we do to keep safe on icy roads or whether to use air conditioning to keep cool.
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 "Frost and hot days" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52575
Data type Table
Row count 12194
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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3051
60
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

Winter rainfall trends, 1960–2016

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Creative Commons Attribution 4.0 International

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3088
17
Added
12 Oct 2017

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

Winter 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 89405
Data type Table
Row count 30
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed
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