Oceanic sea surface temperature anomaly

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Creative Commons Attribution 3.0 New Zealand

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4078
22
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

Winter rainfall trends, 1960–2016

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Creative Commons Attribution 4.0 International

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4072
24
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

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

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Creative Commons Attribution 3.0 New Zealand

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4057
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

Average daily ozone concentrations, 1979–2016

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Creative Commons Attribution 4.0 International

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4058
16
Added
14 Oct 2017

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

NIWA supplied ozone data in two forms, with different starting dates:
- measurements made using a Dobson spectrophotometer (number 72), from 1987
- data assimilated from satellite measurements recalibrated against the global Dobson network, from 1978.
NIWA takes measurements using the Dobson spectrophotometer 72 under clear-sky, direct sunlight conditions at Lauder in Otago. There are gaps in the time series due to days with cloud, rain, or too much wind. However, over the whole period, each individual calendar day of the year was measured. This allows us to calculate statistics based on the day of the year.
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 89464
Data type Table
Row count 1098
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Forest carbon stocks, 1990–2015

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Creative Commons Attribution 4.0 International

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4051
21
Added
17 Oct 2017

This dataset was first added to MfE Data Service on 17 Oct 2017.

Forest carbon stocks and areas, including stock changes, areas, and deforestation.
New Zealand’s indigenous and exotic forests absorb carbon dioxide (CO2) from the atmosphere through photosynthesis and store the carbon as biomass and in the soil. On average, more than twice as much carbon per hectare is stored in New Zealand’s mature indigenous forests than in exotic forests planted for wood production. Regenerating indigenous forests are also an important store of carbon, adding carbon every year as they grow. Total carbon stored in exotic forests will fluctuate over decades as the forests grow from seedlings to mature trees, are harvested, and replanted. Because CO2 is the major driver of climate change, forests provide important mitigation services and help New Zealand meet its climate change commitments.
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 89475
Data type Table
Row count 1066
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Lightning Trends, 2001–2016

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Creative Commons Attribution 4.0 International

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4078
4
Added
13 Oct 2017

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

Lightning is the discharge of electricity from thunderstorms and can occur within a cloud, between clouds, or between a cloud and the ground. By international standards, lightning does not occur frequently around New Zealand. However, ground strikes can injure or kill people and livestock, damage property and infrastructure, and, although rarely in New Zealand, spark forest fires. Thunderstorms are often associated with other severe weather events, such as strong wind gusts and hail. Thunderstorms may increase in frequency and intensity with climate change.
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 89427
Data type Table
Row count 1
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Average annual rainfall, 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.

3958
115
Added
12 Oct 2017

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

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.
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.

Layer ID 89421
Data type Grid
Resolution 5110.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

Oceanic sea surface temperature trends, 1993–2016

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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.

4052
6
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.
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 89407
Data type Table
Row count 4
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Trends in PED, 1972/3–2015/6

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Creative Commons Attribution 4.0 International

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4036
3
Added
13 Oct 2017

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

Trends in potential evapostranspiration deficit (PED), 1972–2016.
Soil moisture is vital for plant growth. When plants cannot access the water they need, growth is reduced, affecting crops and food for livestock, and native biodiversity. Over a sustained period, a drought can have significant social and economic costs, particularly for rural communities.
Potential evapotranspiration deficit (PED) can be thought of as a drought index. It is the difference between how much water could potentially be lost from the soil through evapotranspiration and how much is actually available. When PED is high, plants do not have the full amount of water available they need for growth. PED is measured in growing seasons (the 12 months from 1 July to 30 June of the following year. Data covers each of the growing seasons from 1 July 1972, with the last growing season in the series ending on 30 June 2016.
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 89438
Data type Table
Row count 30
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

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

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Creative Commons Attribution 4.0 International

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4028
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
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