Sunshine hours: annual average 1972-2013

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Creative Commons Attribution 3.0 New Zealand

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4214
43
Added
18 Feb 2016

This dataset was first added to MfE Data Service on 18 Feb 2016.

"Sunshine is important for our health and recreation, and for the environment. It is also important for our agriculture-based economy, for example, for plant growth.

This dataset shows average annual sunshine hours across New Zealand for years 1972 to 2013.

The National Institute of Water and Atmospheric Research (NIWA) mapped mean annual sunshine hours from the virtual climate station network data (NIWA) generated from data in its National Climate Database, for the period 1981–2013. It generated the Units: percentage of normal by comparing the annual average to the long-term mean for 1981–2010. Maps were produced using the Virtual Climate Station network data. Data for each year are measured over the calendar year (January–December).

The accuracy of the data source is of high quality.

This dataset relates to the ""Sunshine hours in New Zealand"" measure on the Environmental Indicators, Te taiao Aotearoa website.

Geometry: grid
Unit: hrs/yr"

Layer ID 53313
Data type Grid
Resolution 5110.000m
Services Raster Query API, 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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4015
22
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

Oceanic sea surface temperature, 1993–2016

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Creative Commons Attribution 4.0 International

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3995
33
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.
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 89406
Data type Table
Row count 960
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.

3991
50
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

Water physical stocks by region (1995–2014)

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Creative Commons Attribution 3.0 New Zealand

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3956
37
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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3970
32
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

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

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Creative Commons Attribution 3.0 New Zealand

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3962
37
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

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

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Creative Commons Attribution 3.0 New Zealand

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3899
37
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

Lightning strike density, 2000–14

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Creative Commons Attribution 3.0 New Zealand

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You must attribute the creator in your own works.

3919
27
Added
10 Feb 2016

This dataset was first added to MfE Data Service on 10 Feb 2016.

Lightning is the discharge of electricity, from thunderstorms, that equalises areas of positive and negative charge, for example, between a storm cloud and the ground. Thunderstorms form as a result of rapidly rising air with a high moisture content (humidity). On average, 1 in 10 lightning discharges strikes the ground (or sea) (Metservice, 2015). Lightning (and therefore thunderstorms) are also often associated with other severe weather events, such as strong wind gusts, and in extreme cases tornadoes.

By international standards, lightning does not occur frequently around New Zealand. However, thunderstorms, and thus lightning, can cause injury and damage (Ministry of Civil Defence and Emergency Management, 2010), and may increase in frequency and intensity with climate change (Mullen et. al., 2011).

This data shows the average annual number of lightning strikes per 25km square.

This dataset relates to the "Lightning" measure on the Environmental Indicators, Te taiao Aotearoa website.

Geometry: grid/point

Unit: strikes/25km2/year

Further information can be found in:

MetService (nd). Lightning observation services. Accessed 3 June 2015 from www.metservice.com.

Ministry of Civil Defence and Emergency Management (2010). Thunderstorms. Working from the same page: Consistent messages for CDEM (p3). Available from www.civildefence.govt.nz.

Mullan, B, Carey-Smith, T, Griffiths, G, & Sood, A (2011). Scenarios of storminess and regional wind extremes under climate change. NIWA Client Report: WLG2010-31 (pvii). Available from www.niwa.co.nz.

Layer ID 52851
Data type Grid
Resolution 5000.000m
Services Raster Query API, 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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You must attribute the creator in your own works.

3905
23
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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