Carbon dioxide concentrations at Baring Head (1972–2013)

Licence

Creative Commons Attribution 3.0 New Zealand

You may use this work for commercial purposes.

You must attribute the creator in your own works.

1458
13
Added
01 Oct 2015

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

Greenhouse gases (GHGS) in the atmosphere absorb heat radiating from Earth, warming the atmosphere. Emissions from human activities increase the concentrations of these gases. Increases in these gases increase ocean acidity and are extremely likely to contribute to increased global temperatures, sea levels, and glacier melt. Monitoring GHG concentrations allows us to infer long-term impacts on ocean acidity, temperature, sea level, and glaciers.
Greenhouse gases are generally well mixed around the globe. We use ‘clean air’ observations from Baring Head, near Wellington, to estimate global concentrations of the greenhouse gases – carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and carbon monoxide (CO). These observations are made only when the air’s trajectory is from the south and away from any likely local sources of gas emissions. This gives an estimate representative of the concentrations over the Southern Ocean.
The observations tell us how the global atmosphere responds to increasing emissions of greenhouse gases, and are an internationally representative measure of global concentrations. However, the Southern Hemisphere has slightly less greenhouse gas concentrations than the Northern Hemisphere, as well as a smaller seasonal variation.
Further information can be found in:
Mikaloff Fletcher, SE, & Nichol, S (2014) Measurements of Trace Gases in Well-mixed Air at Baring Head: Trends in carbon dioxide, methane, nitrous oxide and carbon monoxide. Prepared for Ministry for the Environment. Available at data.mfe.govt.nz/x/cZzREp on the Ministry for the Environment dataservice (data.mfe.govt.nz/).
This dataset relates to the "Greenhouse gas concentrations" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52568
Data type Table
Row count 493
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Southern Annular Mode annual values, 1887–2016

Licence

Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

1450
5
Added
12 Oct 2017

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

A consistent band of westerly wind flows across the Southern Hemisphere and circles the South Pole. The Southern Annular Mode (SAM) describes how this band moves, either north towards the equator (negative phase) or south towards Antarctica (positive phase). A negative phase typically causes increased westerlies, unsettled weather, and storms in New Zealand. A phase can last several weeks, but changes can be rapid and unpredictable.
The SAM is one of three climate oscillations that affect our weather. The resulting changes in air pressure, sea temperature, and wind direction can last for weeks to decades, depending on the oscillation.
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 89383
Data type Table
Row count 168
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Winter rainfall trends, 1960–2016

Licence

Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

1443
10
Added
12 Oct 2017

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

Winter 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 89405
Data type Table
Row count 30
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

Licence

Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

1427
10
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

Daily peak UV index value, 1981–2017

Licence

Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

1415
16
Added
14 Oct 2017

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

Daily peak UV index values at Invercargill, Lauder (Otago region), Christchurch, Paraparaumu (Wellington region), and Leigh (Auckland region). The strength of UV light is expressed as a solar UV index, starting from 0 (no UV) to 11+ (extreme).
Exposure to the sun's ultraviolet (UV) light helps our bodies make vitamin D, which we need for healthy bones and muscles. However, too much exposure to UV light can cause skin cancer. New Zealand has naturally high UV levels, and monitoring UV levels helps us understand the occurrence of skin cancer.
Ozone in the upper atmosphere absorbs some of the sun’s UV light, protecting us from harmful levels. The amount of UV radiation reaching the ground varies in relation to changes in the atmospheric ozone concentrations. The Antarctic ozone hole lies well to the south of New Zealand and does not have a large effect on New Zealand’s ozone concentrations.
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 89468
Data type Table
Row count 38993
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Number of frost days for selected sites (1975–2013)

Licence

Creative Commons Attribution 3.0 New Zealand

You may use this work for commercial purposes.

You must attribute the creator in your own works.

1401
28
Added
01 Oct 2015

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

The number of frost and hot days we experience each year can change in response to many climate factors, such as the warming pattern induced by El Niño. These numbers indicate the variations in our climate and are an important consideration in agriculture. They also affect our behaviour, for example, what we do to keep safe on icy roads or whether to use air conditioning to keep cool.
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 "Frost and hot days" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52575
Data type Table
Row count 12194
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Annual average temperature anomaly (1909–2013)

Licence

Creative Commons Attribution 3.0 New Zealand

You may use this work for commercial purposes.

You must attribute the creator in your own works.

1386
36
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 purpose of the dataset is to provide a long time series which represents the nation-scale state of climate with respect to temperature in New Zealand.
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 52572
Data type Table
Row count 1793
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

Licence

Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

1403
5
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

Trends in PED, 1972/3–2015/6

Licence

Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

1397
2
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

Autumn rainfall trends, 1960–2016

Licence

Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

1384
10
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
Results 21 to 30 of 106