Ocean acidification, 1998–2016

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Creative Commons Attribution 4.0 International

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4904
58
Added
14 Oct 2017

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

The pH of New Zealand subantarctic waters is calculated from pCO2 (dissolved carbon dioxide) and alkalinity measurements using refitted Mehrbach constants (see Mehrbach et al, 1973; Dickson & Millero, 1987), and in-situ temperature taken from the Munida time-series transect off the Otago coast. Measurements of pCO2 are taken every two months.
The Munida transect, in the subantarctic waters off Otago, is the Southern Hemisphere’s longest-running record of pH measurements (NIWA, 2015).
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 89461
Data type Table
Row count 660
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Trends in ocean acidification, 1998–2016

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4043
20
Added
14 Oct 2017

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

The pH of New Zealand subantarctic waters is calculated from pCO2 (dissolved carbon dioxide) and alkalinity measurements using refitted Mehrbach constants (see Mehrbach et al, 1973; Dickson & Millero, 1987), and in-situ temperature taken from the Munida time-series transect off the Otago coast. Measurements of pCO2 are taken every two months.
The Munida transect, in the subantarctic waters off Otago, is the Southern Hemisphere’s longest-running record of pH measurements (NIWA, 2015).
Trends were assessed using linear regression 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 89462
Data type Table
Row count 3
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Lightning strikes, 2001–2016

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Creative Commons Attribution 4.0 International

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4213
129
Added
16 Oct 2017

This dataset was first added to MfE Data Service on 16 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.
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 89470
Data type Table
Row count 2903389
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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3798
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

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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4022
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

Melanoma registration rates, by age, 1996–2015

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Creative Commons Attribution 4.0 International

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3536
10
Added
18 Oct 2017

This dataset was first added to MfE Data Service on 18 Oct 2017.

This csv reports melanoma registration rates, per 100,000 population, by age. Age is grouped in 5 year segments (eg 0–4 years old, 5–9 years old).
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 89482
Data type Table
Row count 60
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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3882
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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Creative Commons Attribution 4.0 International

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3918
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

Annual ozone concentrations, 1979–2016

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Creative Commons Attribution 4.0 International

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3852
14
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 89463
Data type Table
Row count 114
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Coastal sea level rise, 1891–2015

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Creative Commons Attribution 4.0 International

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5017
90
Added
14 Oct 2017

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

Sea-level rise is a consequence of climate change. Increased global temperatures lead to rising sea-levels because warmer waters take up more space and glaciers and polar ice sheets melt into the ocean. Sea-level varies naturally from place to place due to local ocean circulation and temperatures and the movement of the land relative to the sea. For example, earthquakes can lift or drop the land.
Linear trends were provided by NIWA and Emeritus Professor John Hannah (previously University of Otago). Ideally, linear trends in sea level would be reported if there are at least 50 years of data to account for climate variability from climate oscillations such as the 20–30 year Interdecadal Pacific Oscillation (IPO) and the shorter ENSO cycle. Such climate variability can be seen in the increase in annual mean sea level in 1999–2000, when the IPO across the entire Pacific Ocean changed to a negative phase. While the Moturiki data cover 43 years, it was considered appropriate to apply a linear trend to further extend the number of reported sites. Further detail on the data processing (including adjustments for historic datum changes) and methods used for the trend analysis can be found in Hannah (1990), Hannah (2004), and Hannah and Bell (2012).
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 89454
Data type Table
Row count 533
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed
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