CAIT Country greenhouse gas emissions, 1990–2013

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Creative Commons Attribution 4.0 International

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2495
9
Added
13 Oct 2017

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

Emissions data are from the Climate Analysis Indicators Tool (CAIT) version 2.0 produced by the World Resources Institute (WRI). WRI compiles country-level emissions data from governmental sources, complemented by non-governmental sources “based on criteria such as completeness and relative accuracy and country datasets are produced by applying a consistent methodology.” For detailed information see World Resources Institute (2015).
Data compiled are obtained from government reporting and complemented by a variety of non-governmental data sources.
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 89443
Data type Table
Row count 90240
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 (1909–2013)

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Creative Commons Attribution 3.0 New Zealand

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2479
20
Added
01 Oct 2015

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

El Niño Southern Oscillation (ENSO). It is an important predictor of how tropical oceans and climate might influence New Zealand’s climate. Being able to predict the timing and intensity of an El Niño or La Niña climate phase is important in predicting and preparing for extreme climatic conditions, such as strong winds, heavy rain, or drought. Such extreme conditions can impact on our environment, industries, and recreational activities. ENSO is commonly measured using the Southern Oscillation Index (SOI).
In New Zealand, an El Niño phase can cause colder winters. In summer it can result in more rain in the west and drought in the east. A La Niña phase can cause warmer temperatures, more rain in the north-east, and less rain in the south and south-west.
This dataset relates to the "El Niño Southern Oscillation" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52590
Data type Table
Row count 105
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Estimated global production of major ozone-depleting substances (1986–2013)

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Creative Commons Attribution 3.0 New Zealand

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2461
11
Added
01 Oct 2015

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

Ozone in the stratosphere is destroyed in a catalytic reaction with a range of chemical species (mainly CFCs) that are emitted through human activities. The emission of these ozone-depleting substances (ODSs) is closely related to the amount of the chemicals that are produced. The ozone layer absorbs most of the sun's harmful ultraviolet (UV) radiation. Monitoring global ODS production helps us track how much pressure these substances put on the atmosphere.
In accordance with article 7 of the Montreal Protocol – Parties are required to report data on the production, import and export of specified ozone depleting substances covered in the original protocol and the amendments ratified by that Party. The United Nations Environment Programme (UNEP) Ozone Secretariat data centre is the source of the information reported.
This dataset relates to the "global emissions of ozone-depleting substances" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52566
Data type Table
Row count 4428
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Ski field operating days (2003–14)

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Creative Commons Attribution 3.0 New Zealand

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2421
25
Added
01 Oct 2015

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

The climate can affect ski-field operations. Warm temperatures can result in less snow or shorter ski seasons. Extreme weather events such as storms can close fields. Monitoring the season length of ski fields and the percentage of days they are closed may indicate the extent of any effects of climate change. We assessed the season length and percentage of days closed for three South Island ski fields from 2003 to 2014.
This dataset relates to the "Ski-field operating days" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52571
Data type Table
Row count 180
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Annual ground and sea lightning strikes (2001–14)

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Creative Commons Attribution 3.0 New Zealand

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2425
16
Added
01 Oct 2015

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

Lightning is the discharge of electricity from thunderstorms. Ground strikes can cause significant damage to property and infrastructure, and injure or kill people and livestock. Lightning is often associated with other severe weather events, such as strong wind gusts. Thunderstorms may increase in frequency and intensity with climate change.
This dataset relates to the "Lightning" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52587
Data type Table
Row count 15
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Growing degree days trend assessment, for New Zealand, the North Island, and the South Island, 1972/3–2015/6

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Creative Commons Attribution 4.0 International

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2430
11
Added
17 Oct 2017

This dataset was first added to MfE Data Service on 17 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 New Zealand and the North and South Islands.
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 89476
Data type Table
Row count 3
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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2400
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

Frost and warm days, 1972–2016

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Creative Commons Attribution 4.0 International

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2382
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

Global and New Zealand temperature anomalies, 1909–2016

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Creative Commons Attribution 4.0 International

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2380
9
Added
14 Oct 2017

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

This dataset compares temperatures anomalies from NIWA's 'seven-station' temperature series with three global temperature series.
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 89452
Data type Table
Row count 855
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Annual and Daily column ozone Dobson spectrophotometer measurements (1987–2013)

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Creative Commons Attribution 3.0 New Zealand

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2365
8
Added
01 Oct 2015

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

Ozone (O3) is a gas that is of interest in two regions of Earth’s atmosphere – at ground level and in the upper atmosphere (stratosphere). Stratospheric ozone absorbs ultraviolet (UV) rays from the sun and protects Earth from harmful levels of UV. Exposure to these UV rays has been linked to skin cancer. Monitoring variations in stratospheric ozone concentrations is important in New Zealand as we have high rates of skin cancers.
This ozone data for Lauder was taken with Dobson spectrophotometer (72) from 1987 to 2013. Measurements are in Dobson units (DU). One DU represents the amount of ozone molecules needed to produce a 0.01mm layer of pure ozone. These datasets contain annual measurements by DOY and DOY statistics of mean, standard deviation, minimum and maximum.
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 "Ozone concentrations" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52562
Data type Table
Row count 6389
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed
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