The annual SOI compared with New Zealand's detrended temperature series, 1908/9–2015/6

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4649
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

Influenza hospitalisations, 2000–16

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Creative Commons Attribution 4.0 International

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4650
8
Added
14 Oct 2017

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

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 can occur all year round, incidence generally peaks in winter and spring in New Zealand. Some studies suggest this is because the virus can survive longer outside the body in periods of colder weather and low humidity (dry conditions).
Influenza infections may decline as our climate changes. Warmer projected temperatures and higher humidity during winter and spring may contribute to reduced annual influenza rates. However, influenza infection is also affected by factors besides temperature and humidity.
These data are reported in an annual surveillance report by the Institute of Environmental Science and Research. See the 2015 report for more information (Institute of Environmental Science and Research, 2016).
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 89457
Data type Table
Row count 17
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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4642
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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4627
9
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

New Zealand greenhouse gas emissions trends, 1990–2015

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Creative Commons Attribution 4.0 International

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4598
10
Added
13 Oct 2017

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

Greenhouse gases (GHGs) absorb heat from Earth’s surface, warming the atmosphere and changing our climate. New Zealand’s share of GHG emissions is very small, but our gross emissions per person are high. Emissions mainly come from combustion of fossil fuels that emit carbon dioxide (CO2), and agriculture which emits methane (CH4) and nitrous oxide (N2O). Carbon dioxide remains in the atmosphere much longer than other major GHGs. Because of this, today’s global CO2 emissions will continue to influence atmospheric CO2 concentrations for a very long time. Methane and N2O trap heat better than CO2 but leave the atmosphere faster. Reducing emissions of CH4 and N2O will decrease concentrations in the atmosphere more quickly. Greenhouse gases (GHGs) absorb heat from Earth’s surface, warming the atmosphere and changing our climate. New Zealand’s share of GHG emissions is very small, but our gross emissions per person are high. Emissions mainly come from combustion of fossil fuels that emit carbon dioxide (CO2), and agriculture which emits methane (CH4) and nitrous oxide (N2O). Carbon dioxide remains in the atmosphere much longer than other major GHGs. Because of this, today’s global CO2 emissions will continue to influence atmospheric CO2 concentrations for a very long time. Methane and N2O trap heat better than CO2 but leave the atmosphere faster. Reducing emissions of CH4 and N2O will decrease concentrations in the atmosphere more quickly.
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 89432
Data type Table
Row count 2
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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4589
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

Trends in ozone concentrations, 1978–2017

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Creative Commons Attribution 4.0 International

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4590
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

Average daily ozone concentrations, 1979–2016

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4568
18
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

Annual glacier ice volumes (1978–2014)

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Creative Commons Attribution 3.0 New Zealand

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4523
32
Added
01 Oct 2015

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

A glacier is a body of slow-moving ice, at least one hectare in area that has persisted for two decades or longer. Glacier volume is strongly influenced by climate factors, such as temperature and precipitation. Changes in glacier ice volumes give some indication of changing climate conditions in New Zealand.
This dataset relates to the "Change in glacier ice volume" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52579
Data type Table
Row count 37
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Global greenhouse gas emissions (1990–2011)

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Creative Commons Attribution 3.0 New Zealand

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4511
35
Added
01 Oct 2015

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

Greenhouse gas (GHG) emissions from human activities increase the concentrations of these gases in the atmosphere. GHGs absorb some of the heat radiating from the Earth’s surface and warm the atmosphere. In turn, this warming changes our climate. Some GHG emissions are removed, primarily by forests. For this reason, we use net emission rather than gross emission values to represent the total amount of gas contributed to the atmosphere.
This data is compiled from two sources. The UNFCCC (United Nations) GHG data and CAIT 2.0 (World Resources Institute, climate analysis indicators tool 2014).
This dataset relates to the "Global greenhouse gas emissions" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52564
Data type Table
Row count 5258
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed
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