Frost Trends of Wine Growing Regions in New Zealand

Directed Individual Study

SCIE 306

Written By: D. Erin Sullivan

I.D: 300282251

Frost Trends of Wine Growing Regions in New Zealand

Table of Contents

1. Abstract

2. Introduction

3. Background

Research Area

New Zealand Climate

Southern Annular Mode

El Nino Southern Oscillation (ENSO) cycle and Southern Oscillation Index (SOI)

4. Methods

Climate Data

Southern Oscillation Index (SOI)

Southern Annular Mode (SAM)

Kidson Regimes

5. Results

Mean Minimum Temperature

Minimum Temperature Extreme

Frost Frequency

Southern Oscillation Index (SOI)

Southern Annular Mode (SAM)

Kidson Regimes

6. Discussion

7. Conclusion

8. Acknowledgements

9. Appendices

10. References

1. Abstract

Trends in minimum temperature values and frost frequency are described for wine growing regions

in New Zealand. Frosts can be detrimental in the viticulture industry where damage to crops can

result in a loss in production. A period ranging from 1970-2013 has been examined to look for trends

in minimum temperature values and frost occurrence in response to the IPCC’s fifth assessment

findings that the globally averaged combined land and ocean temperature shows a warming of

about 0.72ºC for the period of 1951-2012.

Significant trends are apparent in mean minimum temperature records which show an increase in

temperature over time in most wine growing regions. The frost frequency response shows a

decrease in the number of frost days per winter, although some anomalies show an increase in frost

days and a decrease in minimum temperature values. Orographic effects are proposed to be the

cause of the anomalies, while the remaining trends follow that of regional warming in response to

climate change.

Relationships were examined to see minimum temperature values were affected by the El Nino-

Southern Oscillation phenomenon or Southern Annular Mode phases. No significant relationship

were found, although weather station locations were based on the leeward side of mountain ranges

running through the middle of New Zealand. It is proposed that the mountain ranges create an

orographic effect that protects wine growing regions from the strength and north-south location

changes of prevailing westerly winds.

Finally large scale synoptic weather patterns during the study period have been grouped into three

Kidson regimes: blocking, zonal and trough. Each regimes influence on minimum temperature and

frost frequency was investigated to look for relationships. No evidence was presented that blocking

regimes influence an increase in frost occurrence, however it follows that a significant trend can be

observed with trough regimes and a decrease in mean minimum temperature across all regions.

2. Introduction

Understanding the relationship between agricultural activities and the atmosphere has become

increasingly important because the threat of global warming may require agricultural systems to

adapt to changing regional climate conditions (Sturman & Tapper, 2007). In viticulture: the process

of cultivating grapevines (Collins, 2015), frosts can have a direct impact on production volume and

quality of the crops (Sturman & Clark, 2009).

Frost can form in two ways: air or ground frosts. Air frosts occur when the air temperature falls to or

below the freezing point of water (Met Office, 2013). The air temperature is measured in a special

screen (called a Stevenson screen: Figure 1) and at a specific height (1.3 metres or 4.3 feet) above

ground level (Meteorological Service of New Zealand, n.d). Ground frosts occur when the ground

temperature drops below zero, allowing the formation of ice. A ground frost can occur without an

air frost (Met Office, 2013), normally the ground is significantly colder, as shown in Figure 1.

Figure 1: A Stevenson Screen

A Stevenson screen is designed to allow the thermometer inside to reach equilibrium with air temperature,

while being shielded against rain and allowing free air flow. This is image illustrates a Stevenson screen and the

temperature difference between ground and air temperatures.

(Meteorological Service of New Zealand, 2007)

In viticulture, significant effort is made to match vineyard design and the trellis system to the site-

specific factors that influence potential growth (Dokoozlian, 2003). Trellis wire heights can vary

among commercial vineyards in New Zealand, wire heights can range from 0.7m-2.0m. This height

allows crops to be at a similar height to that of a Stevenson screen thermometer and above ground

level. This permits ground frost data to be excluded from the study.

There are two types of frosts: advective and radiation. Advective frosts occur when a cold front

sweeps into an area as a part of a broader weather system (Chemung, 2001) while radiation frosts

occur where clear skies and calm evenings create heat loss from the ground to the atmosphere

(Sturman & Clark, 2009). In New Zealand, advection frosts are relatively rare.

The Intergovernmental Panel on Climate Change (2013) has established strong evidence that

warming has led to changes in temperature extremes; it is found that warm days and nights have

increased and cold days and nights has decreased for most regions of the globe. Salinger and

Griffiths (2001) report significant increases in minimum temperatures during 1951-1998 in New

Zealand and Sturman & Clark (2009) found “evidence of a national warming trend as the number of

frosts was found to be decreasing since 1972.”

This study uses extreme and mean minimum temperature data alongside frost frequency data,

collected from weather stations located in wine growing regions to examine trends in frost

occurrence in response to climate change within New Zealand.

In conjunction with the weather station data, a supplementary dataset has been compiled using the

El Nino Southern Oscillation Index and the Southern Annular Mode indices to examine relationships,

if any, between New Zealand’s large scale climate system and the weather station data.

Finally, a dataset was created to investigate if a relationship exists between a particular synoptic

weather type and the influence it has on temperature or frost frequency values using Kidson

regimes. Three Kidson regimes exist: blocking, trough and zonal. Certain regimes have been

associated with variations in temperature in many regions in New Zealand. It is the aim of this paper

to distinguish if low temperature values or frost frequency favour a particular Kidson regime.

A single weather station representing each region may not be representative for an entire wine

growing district, especially considering the variations in orography and altitude of different

vineyards. Depending on whether a vineyard is planted on a hillside or valley can have considerable

differences in how the climate is affected. However for the purpose of this study, trends in the

climate data have been inferred to represent an entire region.

Figure 2: Wine Growing Regions in New Zealand

Wine growing regions in New Zealand. Northland and Auckland were excluded from the study. Data from

Tauranga was used for the Bay of Plenty location, Martinborough was used for the Wellington location and

Blenheim was used for the Marlborough location.

Source: (Drake, 2013)

3. Background

Research Area

New Zealand’s land mass spans the latitudes of 34°S to 47°S. The far north is subtropical, while the

far south has a cool, temperate climate (Walrond, 2013). Isolated in the south west Pacific Ocean,

New Zealand enjoys a mid-latitude maritime climate while “mountain chains extending the length of

New Zealand provide a barrier for the prevailing westerly winds, dividing the country into

dramatically different climate regions” (Mackintosh, 2001).

Growing regions in New Zealand stretch from 36°S in the north (Northland), to 45°S on the South

Island (Central Otago). They have developed in the east, on the leeward side of mountain chains

shadowed from the prevailing moisture laden winds of the west (NZWINE, 2015). There is largely ten

major wine growing regions where wine is produced in New Zealand: Northland, Auckland, Waikato,

Gisborne, Hawkes Bay, Martinborough, Marlborough, Canterbury and Central Otago. In these

regions a common enemy of viticulturists is frost. Frost is a significant hazard to grape production in

many parts of New Zealand (Trought, Howell, & Cherry, 1999).

Frosts are rare in the far north of New Zealand, in Auckland the screen minimum thermometer has

registered below 0°C only once in 65 years, while favourable sites in coastal areas of Northland are

free of frost ( (Meteorological Service of New Zealand, n.d). Due to this, the Auckland and Northland

growing regions have been excluded from this study. This study focuses on the remaining four wine

growing regions in the North Island and four growing regions in the South Island.

New Zealand Climate

The New Zealand climate is naturally variable, both regionally and temporally (Office of the Chief

Science Advisor, 2013). Seasonal changes occur throughout the year with summer taking place

during the months of December, January, February and winter during June, July and August. Year to

year variability in New Zealand is influenced by a number of components of the large scale climate

system (Renwick, Mladeno, Purdie, McKercha, & Jamieson, 2010). The El Nino-Southern Oscillation

(ENSO) cycle, Southern Annular Mode (SAM) and Interdecadal Pacific Oscillation (IPO) cycle all

influence the country’s climate.

The dataset used in this study ranges from 1970-2013, “the IPO affects the climate of the Pacific

region on a time frame of one to three decades” (Sturman & Tapper, 2007). Due to the relatively

short timescale of the dataset on a decadal scale, the IPO has been omitted from the study. The

remaining components of New Zealand’s climate system will be analysed in conjunction with trends

that the Intergovernmental Panel on Climate Change (2013) identifies as an unequivocal rise in

global average surface temperatures.

Essentially, climate change brings the prospect of reduced frost risk because of the global process of

warming. The globally averaged combined land and ocean surface temperature shows a warming of

about 0.72°C over the period of 1951-2012 (IPCC, 2013). Increases in southern hemisphere mean

temperatures are also associated with the positive phase of the ENSO cycle, and contributes to a

negative phase of the SAM (Cai & Wang, 2013).

The ENSO phenomenon “accounts for less than 25% of the year to year variance in seasonal rainfall

and temperature” (National Institute of Atmospheric Research, 2013) in New Zealand, while the

SAM is the pervasive mode of climate variability that affects the atmosphere and ocean at mid- and

high–latitudes over a wide range of time scales (Gupta & England, 2006).

Southern Annular Mode

The SAM describes the north-south movement of the westerly winds circling Antarctica. In its

positive phase, the SAM has stronger than normal westerly winds that move south and contract

closer to Antarctica. While in the negative phase, the SAM brings westerly winds northward, closer

to the equator. This results in stronger than normal westerly winds over most of New Zealand

(Bureau of Meteorology, 2015).

In recent years, several papers have reported a trend in the SAM towards more periods of the

positive phase, with a tendency towards stronger westerlies over Antarctica and relatively low winds

over the mid latitudes (Renwick & Thompson, 2006).

As discussed, radiation frosts favour clear skies and low winds, while advective frosts are caused by a

cold front moving into a region. Relationships will be examined to determine if there is a significant

statistical relationship between a positive SAM phase and an increase in frosts, or any other

correlation relationships using both positive and negative SAM indices.

El Nino Southern Oscillation (ENSO) cycle & Southern Oscillation Index (SOI)

The El Nino-Southern Oscillation is a coupled ocean-atmosphere phenomenon where climatic

conditions are influenced by changes in sea surface temperatures. It is one of the major climate

drivers influencing inter-annual climate variations in New Zealand and the globe. It is used to

describe the oscillation between the El Nino and La Nina conditions (Bureau of Meteorology, 2015).

During an El Nino event, the prevailing trade winds weaken, altering ocean currents such that the

sea surface temperatures warm, further weakening the trade winds (IPCC, 2013). Warmer

temperatures are generally associated with an El Nino episode across Asia and the west Pacific

(Nicholls, et al., 2005). In New Zealand, stronger and more frequent winds from the west occur in

the summer and winds tend to be more from the south in the winter, bringer colder conditions to

both the land and surrounding sea (National Institute of Atmospheric Research, 2013).

Sea surface temperatures become colder during a La Nina event, as trade winds strengthen in the

western Pacific. In New Zealand warmer than normal temperatures typically occur over much of the

country (National Institute of Atmospheric Research, 2013) and winds tend to be north easterly

flowing. Variations in sea level barometric pressure between phases is quantified by the Southern

Oscillation Index (SOI).

The SOI is a standardised index based on the observed sea level pressure differences between Tahiti

and Darwin, Australia (National Oceanic and Atmospheric Administration, 2005). Low SOI values

correspond to El Nino conditions, while high SOI values coincide with La Nina (National Oceanic and

Atmospheric Administration, 2005). Prolonged negative SOI values correspond with warm sea

surface temperatures and El Nino episodes. Prolonged positive SOI values correspond with cold

ocean waters across the eastern tropical pacific typical of La Nina episodes (National Oceanic and

Atmospheric Administration, 2005).

Using SOI data, this study aims to examine if a relationship exists between low temperatures, frost

occurrence and the ENSO phenomenon.

4. Methods

Climate Data

Climate data collected in this study was accessed through New Zealand’s National Climate Database

using the CliFlo web system. Three climate records were used: Number of frost days, Mean

minimum temperature and minimum temperature extreme values that were accessed from weather

station archives.

The data set was collected from weather stations at 8 locations spanning a 43-year period (1970-

2013). A continuous monthly record of climate data over this period only occurred at three weather

stations, Napier (Nelson Park) Blenheim (Aerodrome) and Christchurch (Aerodrome). The remaining

regions used multiple weather stations to represent each region’s climate over the specified time

frame. Weather station closures or relocation were among the reasons for discontinuous station

records.

To calculate a continuous dataset for the remaining locations; differences in temperature and frost

days were calculated using overlapping months where two stations had data for the same date. The

difference was then averaged to get a remaining factor. If a weather station had been closed or

relocated this adjustment was applied to the new weather station data to support a relatively

consistent climate record to avoid sharp spikes in the data.

Once a record was derived for each location; the data was processed by calculating the average of

mean minimum temperature over the summer (December, January, and February) and winter

months (June, July, August). This reduced noise in the data to give a smoother looking line graph.

The number of frost days in the winter months were added together to give a frost frequency value

for each year. Summer frost days were excluded due to the small amount of frost days that

occurred in most regions during the summer, resulting in a discontinuous data set.

The extreme minimum temperature value was determined by selecting the lowest temperature

value of each month in the summer/winter for each year. Again this was done to reduce noise in the

data.

Southern Oscillation Index (SOI)

The Southern Oscillation Index gives an indication of the intensity of ENSO events in the Pacific

Ocean (Bureau of Meteorology, 2015). Monthly SOI data was collected from the Bureau of

Meteorology’s (2015) archives for the period of January 1970- December 2013.

The data was then processed the same way as the mean minimum temperature data, whereby an

average SOI was worked out for the summer months beginning 1971 and winter months beginning

from 1970. It was then tabulated alongside the temperature and frost frequency data.

Southern Annular Mode (SAM)

Gong and Wang (1999) proposed a definition of the SAM to be “the difference between normalised

zonal mean pressure between 40°S and 65°S” (Ho, Kiem, & Verdon-Kidd, 2012, p. 969). Marshall

(2003) created an updated SAM index where the Gong and Wang definition is adjusted based on the

mean of six station records near each of the two latitudes. The SAM values used in this study were

collected from an observation-based Southern Hemisphere Annular Mode Index developed by the

British Antarctic Survey (2015) using the same methodology outlined in Marshall (2003).

The monthly SAM data was then processed so a mean SAM value was calculated for summer and

winter months, using the same technique employed with the mean minimum temperature and SOI

values and tabulated with the rest of the dataset.

Kidson Regimes

Kidson (2000) defined 12 synoptic weather types over New Zealand and group them into 3 regimes

that predominantly describe unsettled conditions (trough regime), westerly flow over New Zealand

(zonal regime) or a blocking regime which involves settled conditions (Renwick, 2011).

Renwick (2011) found that Kidson regimes are also associated to the phase of the ENSO cycle and

SAM phases. More zonal flow occurs during El Nino, while more blocking types during a La Nina.

Positive SAM phases go with blocking types and negative SAM phases go with trough types.

For the period of 1970-2013 each day’s weather map was assigned a synoptic type and entered into

one of the three regimes. Then each regimes percentage for the year was worked out and the

results were tabulated alongside the climate data.

5. Results

Mean Minimum Temperature

The mean minimum temperature data was plotted against time, the result was the mean minimum

temperatures have increased at all locations in the North Island during summer months (Figure 3).

All locations display a positive linear relationship. Tauranga displays a moderate strength

relationship, while the remaining locations in the North Island display a weak linear relationship.

Figure 3: North Island Summer and Winter Months

Changes in mean minimum temperature for the North Island summer and winter for the period of 1970-2013.

The R² value expresses the strength of the correlation coefficient.

R² = 0.1137

0.0

5.0

10.0

15.0

20.0

1970 1980 1990 2000 2010

Tem

per

atu

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)

Year

Gisborne Mean Minimum TemperatureSummer

Mean MinimumTemperature

The mean minimum temperature has increased in the north and north-east of the North Island

during the winter months (Figure 3). Tauranga and Gisborne display a moderate positive linear

relationship and Napier displays a weak relationship. Martinborough shows a weak negative linear

relationship presenting a trend opposite to the IPCC’s (2015) findings that cold days and nights are

decreasing, but the relationship is not significant.

In the northern regions of the South Island, Nelson and Blenheim display an increase in mean

minimum temperatures during summer. A weak positive linear relationship is observed in these

wine growing regions, while in the lower South Island wine growing regions a decrease in mean

minimum temperature is observed. A weak negative linear relationship exists in Central Otago and

Christchurch but they are not statistically significant (Figure 4).

Figure 4: South Island Summer months

Changes in mean minimum temperature for the South Island summer for the period of 1970-2013. The R² value

expresses the strength of the correlation coefficient. Any value less than 0.3 is considered a weak linear

relationship and values below 0.1 are considered not statistically significant.

In the winter months, a positive linear relationship is again observed in the northern South Island

and in Central Otago. A positive linear relationship is observed in the Nelson region, while Blenheim

and central Otago display a positive linear relationship but it is not statistically significant.

Christchurch again displays a decrease in mean minimum temperatures but it is also not statistically

significant (Figure 5).

Figure 5: South Island Winter months

Changes in mean minimum temperature for the South Island winter months during the period of 1970-2013.

The R² value expresses the strength of the correlation coefficient.

Minimum Temperature Extreme

The minimum temperature extreme data displays similar trends to the mean minimum temperature

data. In the North Island, all locations display a positive linear trend during both summer and winter

months (see appendix 1).

In the South Island, the northern wine growing regions Nelson and Blenheim show an increase in

minimum temperature extreme values, while the lower South Island regions show a decrease in the

minimum temperature extreme values, giving a negative linear trend, although the strength of the

relationship is weak (see appendix 2).

Frost Frequency

The frequency of frost days per winter were added up for each year during the period of 1970-2013.

The data was then plotted on a histogram; a trend-line and R² value were added to distinguish

trends in frost occurrence and the strength (if any) of the relationships.

Figure 6: Frost Frequency of North and South Island’s in winter

Histogram of frost frequencies during the winter over the period of 1970-2013. The number of frost days was

calculated by summing up the number of frost days of June, July, and August per year. R² values were added to

the charts to distinguish the strength of relationships.

In the North Island, the number of frost days is decreasing in Tauranga, Gisborne and Napier and are

all statistically significant, displaying a weak linear relationship. In Martinborough however, the

number of frost days during the winter is increasing, this follows a similar trend to that of the mean

minimum temperature and minimum temperature extreme data.

In the South Island, the northern regions show a decreasing number of frost days over time, while

the lower South Island regions display that the number of frost days is increasing slightly, although

the R² values indicate that the strength of the relationship is not statistically significant.

Southern Oscillation Index

Mean minimum temperature and frost frequency values were plotted against the SOI data in scatter

diagrams to identify if a relationship exists between the ENSO phenomenon and low temperature

anomalies or frost occurrence.

The result was no statistically significant relationship exists between the summer or winter SOI data

and the climate records used in this study.

Southern Annular Mode

Mean minimum temperature and frost frequency values were again plotted against SAM data in

scatter diagrams to identify if a relationship exists between different phases of the SAM and

temperature variations or frost occurrence.

Kidson Regimes

The three Kidson regimes were plotted in scatter diagrams against frost frequency and mean

minimum temperature to examine if any correlation occurred between the regime and the climate

records.

The settled conditions of a blocking regime provide the right conditions for radiation frosts to occur,

however the scatter diagrams of frost frequency vs Kidson blocking regime did not show a significant

linear relationship (see appendix 3). Weak linear relationships were evident when plotted against

winter mean minimum temperature and no relationship was apparent when plotted against summer

mean minimum temperatures on both islands.

A trough regime is associated with unsettled conditions over New Zealand. A linear relationship

exists when the Kidson trough regime percentage was plotted against mean minimum temperature

values, especially in the South Island. Appendix 4 illustrates the downward trend where lower mean

minimum temperature values are linked with a higher percentage of trough regimes during the

winter. A similar downward trend was seen when summer mean minimum temperatures were

plotted against trough regime percentage, however the relationship was significantly weaker.

Frost frequency was plotted on a scatter diagram against Kidson trough regime percentage and a

positive linear trend was evident across all locations. A relationship exists where higher trough

regime percentage result in more frost days per year (see appendix 5).

A zonal regime has intense anticyclone north of 40ºS and strong westerlies to the south of the

country (Kidson, 2000). No statistically significant trends were evident in the North Island during

both the summer and winter when the mean minimum temperature was plotted against the zonal

regime percentage. While a very weak positive linear trend was present in the South Island during

the summer and winter except for the Christchurch (winter). A weak relationship exists where more

zonal regimes go with higher temperatures (see appendix 6).

The frost frequency scatter diagrams did not show any significant relationships during the summer

when plotted against the zonal regime percentage in the North Island. While in the South Island

Nelson, Blenheim and Central Otago all display a trend where less frost days occur with more zonal

regime percentage. Conversely in Christchurch, a weak relationship is seen where more frost days

occur with increasing zonal regime. Although this relationship is not statistically significant (see

appendix 7).

6. Discussion

The number of winter frost days for most wine growing regions in New Zealand are decreasing,

while the minimum temperature values are increasing. This reflects regional warming where land

and sea surface temperatures are warming in response to climate change. The IPCC’s fifth

assessment report (2013) outlines that continued decreases in frost frequency are expected and

temperatures in New Zealand will continue to rise. Yet anomalies exist in Martinborough,

Christchurch and Central Otago.

In a study on observed variability and change in climate, (Salinger, et al., 1996) found that inland

South Island areas had an increase in frost frequency, and lighter winds and less winter cloud cover

leading to more radiation frosts. This result can be inferred for Central Otago and Christchurch

although the South Island anomalies in this paper do not have a significant statistical relationship.

Martinborough was the only growing region in the North Island that displayed an increase in frost

days and decrease in minimum temperature data. Martinborough is located in the rain shadow

created by the Tararua and Rimutaka Ranges (Wines from Martinborough, n.d) which allows

moisture in the air (clouds) to evaporate. This provides the clear skies favourable for radiation frosts

to occur. During overcast nights, clouds act like a blanket trapping radiant heat from the ground,

however clear skies and calm winds allow radiant heat from the Earth to rise to the upper layers of

the atmosphere (Chemung, 2001). An inversion layer develops where a layer of warm air traps

cooler air near the surface of the Earth, preventing the normal rising of surface air (Collins, 2015).

Scatter diagrams using the SOI and SAM and climate data were noisy and did not show any

significant relationships. As the SAM describes the north-south movement and strength of westerly

winds, it could be assumed that because all the wine growing regions used in this paper have been

developed in the east, on the leeward side of a “mountain chain extending the length of New

Zealand” (Mackintosh, 2001) they are sheltered from prevailing westerly winds and therefore

unaffected by the phases of the SAM. As the air descends on the leeward side of the mountains it

becomes compressed and warmed and therefore has no effect on the climate in the growing

regions.

The same goes for the SOI, where the strengthening and weakening of trade winds influence warmer

or colder conditions in New Zealand. During a La Nina event warmer temperatures occur over the

country and winds tend to be north easterly flowing. Winds coming from this direction do not have a

mountain barrier to contend with, however no significant trends were seen with positive SOI values

and warmer temperatures when plotted on a scatter diagram. Frost frequency was also plotted on a

scatter diagram with SOI values. Cooler conditions occur over New Zealand during an El Nino event,

trends were investigated to see if there was a correlation with negative SOI values and an increase in

frost frequency but no relationship was evident. The phases of ENSO are also associated in

dynamically reasonable ways to the Kidson regimes (Renwick J. , 2011).

The 3 Kidson regimes were plotted against mean minimum temperature and frost frequency values.

No significant relationship was observed when climate data was plotted against the blocking regime

percentage. This indicates that the blocking regime does not go with the colder nights which was

unexpected considering the blocking regime provides favourable conditions for radiation frosts to

occur.

A relationship exists when the climate records were plotted against the Kidson trough regime, it is

associated with colder nights in the winter. As the trough regime percentage increases the mean

minimum temperatures decrease at all locations (North and South). This in-turn increase the amount

of frost days per year across all locations (see appendix 5).

Kidson (2000) found that the trough group includes synoptic weather patterns which would bring

wet, cool and cloudy conditions to much of the country, while (Renwick J. , 2011) outlines that

cloudy nights associated with the trough regime have more of an effect on minimum temperatures

in winter than they do during shorter summer nights. This trend is consistent with those displayed in

appendix 4.

Kidson’s zonal regime brings warmer temperatures to the north, with stronger westerlies in the

southwest of the South Island. (Kidson, 2000) Also found that the zonal regime brings below normal

precipitation to the north-east and mild conditions in the south. No relationship was evident in the

North Island when zonal regime percentage was plotted against mean minimum temperatures

during both summer and winter.

However, a weak linear relationship was present in the South Island during the winter months (see

appendix 6). Mean minimum temperatures increase in Nelson, Blenheim and Central Otago as the

zonal regime percentage increased. This in-turn resulted in the number of frost days decreasing as

the zonal percentage increased (as seen in appendix 7). An inverse relationship exists in

Christchurch, where the mean minimum temperature is decreasing as the zonal percentage

increases, which results in an increase in the number of frost days. Trends in Christchurch display a

decrease in mean minimum temperatures across all three Kidson regimes.

7. Conclusion

Trends seen in minimum temperature records and frost occurrence in wine growing regions are

relatively consistent with the IPCC’s fifth assessment report (2013) where temperatures will

continue to rise over New Zealand and a continued decrease in frost frequency. Anomalies exist in

the regions of Christchurch, Central Otago and Martinborough (winter) where mean minimum

temperatures are decreasing resulting in an increase in the number of frost days. It follows that the

minimum temperature extreme data followed the same trends to that of the mean minimum

temperature data in all locations.

No relationship was evident relating minimum temperatures and frost frequency to the SOI or SAM.

It was considered that this was due to the location of the wine growing regions where they have

developed on the leeward side of mountain ranges, sheltering the areas from changes in the

strength and north-south location of westerly winds (NZWINE, 2015).

Weak linear relationships were present in some forms when comparing minimum temperature

values to Kidson regime percentages. Frost frequency data followed an inverse relationship to the

same trends, as in, as the minimum temperature values decreased an increase in the number of

frost days occurred and vice versa. The strongest relationship seen was with the trough regime

plotted against mean minimum temperature; decreases occurred in all locations in New Zealand as

the trough regime percentage increased.

Surprisingly, no relationship was present when the blocking regime percentage was plotted against

the minimum temperature values and frost frequency data, despite conditions of the blocking

regime to be favourable for radiation frost’s to occur.

Zonal regime percentages display a weak relationship when plotted against the climate data in most

South Island locations. Nelson, Blenheim and Central Otago all display a weak relationship where the

mean minimum temperature increases as the zonal regime percentage increases. Again it follows

that as the mean minimum temperature increases the number of frost days per year decreases.

This paper has explored relationships associated with frost frequency and minimum temperature

data. Trends in frost occurrence follow that of Sturman & Clark (2009) where results trend toward

higher minimum temperature extremes and fewer frost days or Salinger & Griffiths (2001) paper

where significant increase in minimum temperatures was associated with a decrease in frost day

frequency.

Further investigation involving a control site located on the west coast of the South Island would

help distinguish if minimum temperature and frost frequency can be influenced by the ENSO

phenomenon and SAM phases. Another area for further study involves looking at local scale

processes in relation to neighbouring orography at anomaly sites determined in this study such as

Martinborough and Christchurch. Results in this study are consistent with global trends where it is

certain that global mean surface temperature have increased since the nineteenth century (IPCC,

2013).

8. Acknowledgements

This directed individual study was approved by Rewi Newnham, head of the School of Geography,

Environment and Earth Sciences. My thanks go to Rewi for allowing this paper the go-ahead. Special

thanks also go to James Renwick who was kind enough to supervise this study, providing the initial

idea for the project and continued support and useful comments throughout the duration over the

summer.

Appendix 1: North Island Minimum Temperature Extreme values over time

Summer and Winter Months

Appendix 2: South Island Minimum Temperature Extreme Values over time

Summer and winter months

Appendix 3: Scatter Diagram of Winter Frost Frequency vs Kidson Blocking Regime Percentage

North Island

South Island

Scatter diagram of Blocking Kidson regime percentage vs Frost frequency. No significant relationships

are evident. R² value represents correlation coefficient on some diagrams.

Appendix 4: Scatter Diagram of Winter Mean Minimum Temperature vs Kidson Trough Regime

Percentage

North Island

South Island

Scatter Diagram of Kidson trough regime percentage in New Zealand versus mean minimum temperature data.

R² values represent strength of the correlation coefficient. All locations show a weak linear downward trend.

Appendix 5: Scatter Diagram of Winter Frost Frequency vs Kidson Trough Regime Percentage

North Island

South Island

Scatter Diagrams of Trough regime percentage versus number of frost days. All locations display a positive

linear relationship, providing evidence that as trough synoptic weather types increase more frost days occur in

a year. R² value is the correlation coefficient and indicates the strength of the relationship.

Appendix 6: Scatter Diagram of Mean Minimum Temperature vs Kidson Zonal Regime Percentage

South Island

The Scatter diagrams above show a positive linear trend in all locations except Christchurch. As the percentage

of Zonal regimes increase, the minimum temperature increases in Nelson, Blenheim and Central Otago. In

Christchurch the mean minimum temperature appears to be decreasing as zonal regime percentage increases.

The R² Value indicates the strength of the relationships.

Appendix 7: Scatter Diagram of Frost Frequency vs Kidson Zonal Regime Percentage

South Island

The scatter diagrams above show a positive downward linear trend in Nelson, Blenheim and Central Otago. As

the percentage of zonal Kidson regimes increases the number of frost per year decreases indicating warmer

temperatures. The R² value indicates the strength of the correlation coefficient.

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