Annual sea surface temperature difference from normal, 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.

6848
18
Added
12 Oct 2017

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

The oceans store most of the excess energy accumulated due to increased greenhouse gases in the atmosphere warming the surface layer. These long-term increases in temperature caused by climate change are in addition to natural variability where ocean temperatures change in response to climate oscillations like the El Niño Southern Oscillation.
Changes in sea-surface temperatures can affect marine processes, environments, and species. Some species may shift range or find it hard to survive in changing environmental conditions. Warmer water also takes up more space, which contributes to sea-level rise.
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.

Layer ID 89396
Data type Grid
Resolution About 4548.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

Annual sea surface temperature difference from normal, 2015

Licence

Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

5707
9
Added
12 Oct 2017

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

The oceans store most of the excess energy accumulated due to increased greenhouse gases in the atmosphere warming the surface layer. These long-term increases in temperature caused by climate change are in addition to natural variability where ocean temperatures change in response to climate oscillations like the El Niño Southern Oscillation.
Changes in sea-surface temperatures can affect marine processes, environments, and species. Some species may shift range or find it hard to survive in changing environmental conditions. Warmer water also takes up more space, which contributes to sea-level rise.
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.

Layer ID 89395
Data type Grid
Resolution About 4548.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

Annual sea surface temperature difference from normal, 2014

Licence

Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

5606
7
Added
12 Oct 2017

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

The oceans store most of the excess energy accumulated due to increased greenhouse gases in the atmosphere warming the surface layer. These long-term increases in temperature caused by climate change are in addition to natural variability where ocean temperatures change in response to climate oscillations like the El Niño Southern Oscillation.
Changes in sea-surface temperatures can affect marine processes, environments, and species. Some species may shift range or find it hard to survive in changing environmental conditions. Warmer water also takes up more space, which contributes to sea-level rise.
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.

Layer ID 89394
Data type Grid
Resolution About 4548.000m
Services Raster Query API, 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

You may use this work for commercial purposes.

You must attribute the creator in your own works.

9113
39
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

Licence

Creative Commons Attribution 4.0 International

You may use this work for commercial purposes.

You must attribute the creator in your own works.

7827
45
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

You may use this work for commercial purposes.

You must attribute the creator in your own works.

6627
19
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.

7060
40
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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You must attribute the creator in your own works.

6553
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

Southern Annular Mode trend assessment, 1860–2016

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Creative Commons Attribution 4.0 International

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You must attribute the creator in your own works.

8174
14
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.
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 89385
Data type Table
Row count 7
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Southern Annular Mode monthly values, January 1979–December 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.

7737
31
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 89384
Data type Table
Row count 456
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed
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