Forest carbon stocks, 1990–2015

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Creative Commons Attribution 4.0 International

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5450
30
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

Trends in PED, 1972/3–2015/6

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Creative Commons Attribution 4.0 International

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5463
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

Water physical stocks for selected measures (1995–2014)

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Creative Commons Attribution 3.0 New Zealand

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5413
28
Added
15 Oct 2015

This dataset was first added to MfE Data Service on 15 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.
Variables: Abstraction for Hydrogeneration, Change in Ice, Change in Lakes, Change in Snow, Change in Soil Moisture, Discharge by Hydrogeneration, Evapotranspiration, Inflow from other regions, Outflow to other regions, Outflow to sea, Precipitation, Total.

Table ID 52596
Data type Table
Row count 240
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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5410
10
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

Trends in ozone concentrations, 1978–2017

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Creative Commons Attribution 4.0 International

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5411
5
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.
The trend 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 89465
Data type Table
Row count 3
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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5400
11
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

Frost and warm days, 1972–2016

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Creative Commons Attribution 4.0 International

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5367
32
Added
12 Oct 2017

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

The number of frost and warm days changes from year to year in response to climate variation, such as the warming pattern induced by El Niño. Climate models project we may experience fewer cold and more warm extremes in the future. Changes in the number of frost and warm days can affect agriculture, recreation, and our behaviour, for example, what we do to keep safe on icy roads or whether to use air conditioning to keep cool.
A frost day is when the minimum temperature recorded is below 0 degrees Celsius. It refers to a temperature measured in an instrument screen 1.2 m above the ground rather than a ‘ground frost’. We define a warm day as having a maximum recorded temperature above 25 degrees Celsius. The threshold of 25 degrees Celsius is chosen to represent days where action might be taken to keep cool (eg turn air conditioning on).
This dataset gives the number of frost and warm days per month and calendar year for New Zealand, the North and South Islands, and all 30 sites.
For frost days we have used calendar years. For warm days we have used growing season (July 1 – June 30 of the following 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 89387
Data type Table
Row count 32667
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Global and New Zealand temperatures, five year running average (1911–2010)

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Creative Commons Attribution 3.0 New Zealand

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5326
41
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 aim of the datasets is to provide a tool to show average New Zealand and global temperatures compared to a reference temperature in order to compare this with expected global climate change in response to mechanisms such as atmospheric carbon dioxide, volcanic aerosols, and solar irradiance changes. 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 52573
Data type Table
Row count 929
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Melanoma registration rates, 1948–2015

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Creative Commons Attribution 4.0 International

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You must attribute the creator in your own works.

5350
12
Added
14 Oct 2017

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

New Zealand and Australia have the world’s highest rates of melanoma, the most serious type of skin cancer. Melanoma is mainly caused by exposure to ultraviolet (UV) light, usually from the sun. New Zealand has naturally high UV levels, especially during summer.
The risk of developing melanoma is affected by factors such as skin colour and type, family history, and the amount of sun exposure. Melanoma can affect people at any age, but the chance of developing a melanoma increases with age. We report on age-standardised rates of melanoma to account for the increasing proportion of older people in our population.
Our data on melanoma registrations come from the New Zealand Cancer Registry and the Ministry of Health's Mortality Collection. The passing of the Cancer Registry Act 1993 and Cancer Registry Regulations 1994 led to significant improvements in data quality and coverage (Ministry of Health, 2013). A sharp increase in registrations after 1993 is likely to have been related to these legislative and regulatory changes; for this reason we have only analysed data from 1996.
2014–15 data are provisional and subject to change.
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 89458
Data type Table
Row count 204
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Average daily ozone concentrations, 1979–2016

Licence

Creative Commons Attribution 4.0 International

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5330
19
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
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