Spring 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.

2832
7
Added
12 Oct 2017

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

Spring 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 89403
Data type Table
Row count 30
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Autumn rainfall trends, 1960–2016

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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.

3021
11
Added
12 Oct 2017

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

Autumn 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 89402
Data type Table
Row count 30
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Rainfall, 1960–2016

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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.

3724
144
Added
12 Oct 2017

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

Daily rainfall values 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.
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 89401
Data type Table
Row count 617808
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Annual rainfall trends, 1960–2016

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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.

3230
36
Added
12 Oct 2017

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

Annual 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 89400
Data type Table
Row count 30
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Annual glacier ice volumes trend, 1977–2016

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Creative Commons Attribution 4.0 International

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You must attribute the creator in your own works.

3065
16
Added
12 Oct 2017

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

A glacier is a body of slow-moving ice, at least 1 hectare in area that has persisted for two decades or longer. New Zealand has 3,144 glaciers. Most are located along the Southern Alps on the South Island, although Mount Ruapehu on the North Island supports 18 glaciers. New Zealand’s large glaciers are noteworthy for their large debris cover. The exceptions, Franz Joseph and Fox glaciers, are rare examples of glaciers that terminate in a rainforest.
Glacier volume is strongly influenced by climate factors, such as temperature and precipitation, which scientists expect to be affected by the warming climate. Glacial ice is an important water resource. Changes to ice storage and melting can affect ecological and hydropower resources downstream, as well as important cultural values and tourism.
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 89397
Data type Table
Row count 1
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Growing degree days annual growing season averages and totals, 1972/3–2015/6

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Creative Commons Attribution 4.0 International

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3326
19
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 average number of GDD over growing seasons (July 1 – June 30 of the following year) for New Zealand, the North and South Islands, and 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 89393
Data type Table
Row count 1389
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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You must attribute the creator in your own works.

3135
23
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

Frost and warm days trend assessment, 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.

2860
14
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 1.2m 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 trend in frost and warm days for New Zealand, the North and South Islands, and for 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).
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 89388
Data type Table
Row count 60
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Frost and warm days, 1972–2016

Licence

Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

2525
17
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

Campylobacteriosis, cryptosporidiosis, and salmonellosis notifications, 1997–2016

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Creative Commons Attribution 4.0 International

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2539
3
Added
12 Oct 2017

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

Bacteria and parasites are influenced by climate variables, and infection rates may increase in response to climate change and rising temperatures. Campylobacter, Cryptosporidium, and Salmonella are three such organisms that can contaminate our food and water, leading to serious illness. Monitoring the incidence rates of illnesses can help us assess the health risks related to climate change and better prepare for disease outbreaks.
The numbers of notified cases of infection are sourced from EpiSurv, New Zealand’s national notifiable disease surveillance system. Various factors influence disease notification, and therefore the calculation of notifiable disease rates. For example, people are less likely to consult a medical practitioner when an illness is not severe (ESR, 2016a). The number of notified cases vary greatly from year to year due to New Zealand’s small population and low number of cases for some diseases (Environmental Science and Research, 2016). The August 2016 Camplylobacter outbreak in Havelock provides an example of this variation (ESR, 2016b).
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 89386
Data type Table
Row count 816
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed
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