Future climate change in Northern Ireland: From downscaling to dissertations

1. Future climate change in Northern Ireland: From downscaling to dissertations Thomas Crawford and David Favis-Mortlock Environmental Change Research Cluster

2. Get reading! If you’re doing your dissertation on climate change in NI, there are several texts that are essential to have read. You’re simply asking for trouble if you haven’t read them. 1. The SNIFFER report (QUB, DFM editor, Dr Betts climate section, agriculture section…) (available to download) 2. The EHS climate change indicators for NI report (available to download) 3. Soil and Environment Northern Ireland (QUB, climate and agriculture sections…) 4. Northern Ireland: Environment and Natural Resources (QUB, as above…) 5. EHS website To get ‘up to speed’ with ideas about climate change in the UK / Ireland, see: 1. UKCIP reports / website 2. Met Office / Met Éireann websites 3. IPCC reports (global…)

3. Who can you believe? The future climate projections presented here consist of two basic components: 1. General Circulation Model (GCM) global projections. These are created by leading atmospheric physics centres across the globe (e.g. Met Office). These are fully referenced in the published literature and form part of the IPCC future climate change assessments. There is nothing we can do to change / modify these. They are they best tools currently available for projecting global scale climate change. However, different models create different projections… 2. Downscaled scenarios for NI. Created at QUB as part of Ph.D. research. The highest resolution climate change scenarios currently available for NI. Created using well-established downscaling techniques. Methodology has strengths and weaknesses, but represents a replicable, defensible regional impacts modelling approach.

4. The current rainfall regime in NI

6. The ‘big picture’ To get an idea about the ‘big picture’ of future climate change in NI, we must look at ‘grid square’ scale changes. This tells us about the general changes in seasonal / monthly temperature and rainfall. We must look at a range of GCM predictions – uncertainty.

7. Making global predictions relevant at the regional scale Evidently we need to make large scale projections relevant for a land area that is small and heterogeneous – NI. You do not need to know about the details of the techniques used to achieve this. The suite of methods are referred to as ‘downscaling techniques’. The information you will see today was created using ‘delta change’ and ‘statistical downscaling’ approaches. Other, more general information is available for the UK as a whole – UKCIP reports.

8. The ‘big picture’ – changes predicted for NI as a whole

9. General statements N.B. Uncertainty – models / scenarios / different sites / time periods So, if you’re making general statements, pick a time period and model(s) etc. All months are likely to experience a temperature increase, the severity of this increase is model dependent Winter rainfall is likely to increase. This may be manifested as a combination of more frequent wet days and more precipitation on those wet days. Summer rainfall is likely to decrease. Combined with temperature increase, this will place pressure on water resources. There may be an increase in late summer / early autumn rainfall associated with increased convectional activity.

10. The ‘big picture’ – changes predicted for NI as a whole (2060s) The general, monthly changes can be applied to a gridded climatology (5km), to help appreciate the spatial aspects of change. This makes comparative statements possible.

11. The ‘big picture’ – changes predicted for NI as a whole Comparative statements: ‘By the 2060s, the ECHAM GCM predicts that the Comber / Hillsborough area of County Down will have the same mean daily precipitation in January that is currently experienced by the lower slopes of the Mournes’ ‘By the 2060s, the HAD GCM predicts that parts of the upland Sperrins will receive the same mean daily precipitation in July that is currently experienced by their lower slopes bordering Lough Neagh’ However, these only refer to changes in rainfall – be careful with your statements. Comparative statements should be created with your audience in mind i.e. the type of person to be answering your questionnaire / something that they will be able to appreciate etc.

12. Seasonality of rainfall receipt In terms of annual rainfall amount, no statistically significant long-term trend is evident. However, an increasing trend towards contrasting behaviour of winter and summer precipitation is evident. Thus, when discussing changes in rainfall, it is necessary to look at sub-annual time scales e.g. seasonal / monthly This is a function of: A marked decrease in summer rainfall (mean daily) A moderate increase in winter rainfall (more frequent wet days and more precipitation in those wet days) Think of the potential impacts for farmers – wet winter following a dry summer?

13. Annual Winter Winter - summer Summer Observed data

14. Seasonality of rainfall receipt – the future? Most GCMs agree that there will be an increased seasonality of rainfall receipt during the 21st century. This can therefore be described as a ‘robust prediction’. In this instance, the winter / summer ratio is used. For example, the Hadley GCM (Met Office) predicts that (for Helen’s Bay): The winter / summer ratio is currently ~ 1.5. By the end of the century, the ratio may be ~ 2.5. There may be some individual years when the ratio is extreme – very dry summer or very wet winter (combinations) Variability is much more pronounced

15. Detailed projections It is possible to make more detailed projections using a method known as ‘statistical downscaling’. It produces future projections of daily rainfall for individual sites. This mean that we can make much more detailed statements about certain areas. In the previous slide, we looked at the general projection for seasonality at Helen’s Bay. However, what will a much more detailed analysis of future projections reveal?

18. Detailed projections So, for many sites in NI, the following may be said: The distribution of daily rainfall is likely to change. For example, whilst there may be a certain change in mean daily rainfall, the more extreme quantiles may change in a complex way. The Q90 level is likely to increase in winter and decrease in summer. The maximum 5 day total may experience dramatic changes in winter. This is particularly important for NI. An increase in the amount of rainfall received during wet spells in winter months will impact upon surface runoff / flooding / harvest and planting times. Peaks over threshold are also likely to increase in winter. This means that individual ‘intense’ rainfall events will become more frequent. This may also mean that these events contribute much more to the overall total of rainfall receipt. Think about the impact of intense rainfall on runoff process / how they will combine with max 5 day totals / what they mean for crops etc.

19. A sample impacts analysis Future climate change will certainly impact, at least in some way, on almost all natural systems. One example impacts analysis in NI is the relationship between future climate change and hydrological regimes. How will future changes in rainfall characteristics change the way rivers in NI behave?

20. A sample impacts analysis In general, changes to mean daily flow follow each GCMs projections of changes to mean daily rainfall. However, projections vary between catchments, and there are dramatic differences between models.

21. A sample impacts analysis Water resource management in NI is primarily concerned with the disposal of excess water. For example, see the current news coverage about water shortages in SE England – rarely a problem here. So, impacts analysis should look at future ‘wet extremes’ – floods etc.

22. A sample impacts analysis Floods in NI are often less of a problem than in other parts of the UK. However, they are still socially and economically severe at the local / regional scale. How might a change in flood frequency impact farmers? See Foresight report.

23. Questionnaire issues In my undergrad dissertation, I investigated the way in which changes in rainfall chemistry may impact upon agricultural practice. Part of this involved talking with farmers / farming groups. Key ideas from questionnaire work: Make sure you ask more than 30 people – think of the stats that you can work with (237 module) A wide spectrum of responses – individuals could appear focussed and certain in their outlook, but there may be no overall consensus within the sample group (despite being from a small area…) Think of controls on response – gender / age / type of farmer / economics… etc. Some farmers may be surprisingly –’up-to-date’ / scientific / critical: “…do you know that I collected 175mm in October this year? That’s nearly three times as much as last October…”

24. Questionnaire issues For the farmers I interviewed, rainfall was evidently a topical issue. However, recent wet months were a potential source of bias in questionnaire response. What would your current feelings on rainfall / climate be if you had just lost a field of crop because of a run of intense rainfall events? Think of including both direct / closed (obvious?) and indirect / open (ambiguous?) questions – this varies the scope for response. Deliberately ambiguous questions can provoke the most interesting answers – reveal what is most important for an individual. Do not underestimate the power of economics for shaping answers. For example, think of recent problems for pig farmers / poultry farmers etc.

25. Sample questions • Start with age / location / gender etc. • How well do you feel that those involved with the agricultural community are informed about environmental issues? • To what extent do you feel at risk from environmental change? • At present, what is the greatest risk to the success of your agricultural practice? • Have you observed any evidence of change to the environmental conditions in the area that you farm? • Do you believe that sources of pollutants are close to your farm or far away? • Would changes in rainfall characteristics (amounts / intensity / seasonality) influence your farming practice? • Which type of agricultural activity will suffer most from future environmental change? • Would you be willing to modify your farming practices in response to changes in environmental conditions? • Make questions flow from more general to more focussed…

26. Questionnaire issues Comments made on evidence of ‘environmental change’: “Unpredictable and unusual weather” “Unseasonal weather” “Changes to the pattern of weather in my lifetime. Weather is much more unseasonal, namely periods of summer in winter and winter in summer” “Rainfall seems to be greater and concentrated into fewer days. Long days of rain instead of odd showers” But also “Changes to the amount of wildlife” “Increase in the number of buildings that don’t fit in with the countryside”

27. The way we think about weather / climate You must also be sympathetic about the way people think about the weather. Climate change in Ireland is nothing new: “That the climate of Ireland has suffered a considerable change, almost within the memory of the present generation, is not only a popular opinion, but is a doctrine held by intelligent and philosophical observors. We are told, that the winters, in this island, have laid aside their ancient horrors, and frequently assume the mildness and vegetative powers of spring; while summer is represented as less favourable than formerly, less genial in promoting vegetation, and less vigorous in advancing to maturity the fruits of the earth“ (Patterson, 1802) “I have seen changes in the pattern of weather in my lifetime. Weather is much more unseasonal, namely periods of summer in winter, and winter in summer” (Mixed cereal farmer, 2002)

28. The way we think about weather / climate Individuals tend to focus on extreme events “There seems to be an inability or an unwillingness to understand that unusual seasons are part and parcel of this country’s – any country’s – climate. We should also be aware that the human memory is a notoriously poor means of recalling weather events. Extremes tend to stick in the memory, so we remember floods and droughts, snowstorms and damaging gales, heatwaves and intense cold. Hot summers like 1959, 1976 and 1995 stick in the memory, as do severe winters such as 1947 and 1963, but we do not retain specific memories of warm winters or poor summers”(Eden, 2003) So, in NI, ‘change’ is the norm, but change is not something that is easily remembered. The memory of events will evolve/erode over time, depending on the individual, type / style of report, or indeed the tendency for tales to grow in the telling!It may often be possible for extremes to be over-represented.

29. Memory and probability Popular understanding of climate science can be hindered by jargon-filled literature. Where this is the case, extreme-event research is likely to be misunderstood by the public. So, make your questions / comments straightforward. Individuals often state an observable change in the frequency of extreme events in their lifetime, but this is often related to complex factors surrounding individual events. In this respect, a full appreciation of the frequency and magnitude of events is vital – emphasis may be placed on ‘one-off’, dramatic events (high magnitude, low frequency), but more common events (high frequency, low magnitude), which may nonetheless have a greater cumulative impact, could well be forgotten.

30. Memory and probability With reference to objective probability, this means that individuals may overestimate the probability of relatively infrequent events such as damaging urban floods, but underestimate the probability of relatively frequent, but less dramatic events such as flooding on agricultural land. Geographical location may well be a controlling factor in the recollection of events. Patt and Schrag (2003) state that, “people’s interpretation of probability descriptors depends on the background frequency of an event”. Mathematically this may provoke a wry smile, as a flood-prone area with a 30% chance of having a flood this winter and a usually ‘dry’ area with a 30% chance have equal probabilities - but in real terms it is understandable that individuals in the flood-prone area will feel at more risk. So, when you ask people questions – be aware of where they come from!

31. Testing memories! It is possible to test (within reason) the accuracy of some memories. One possible example: Q = “Have you observed an increase in extreme rainfall events?” A = “Yes, I have noticed much more heavy winter rainfall during the past five years” Test = Perform statistical analysis on winter rainfall record from the site closest to the farm. If there has been no upward trend, what has conditioned this answer – news / media / economics / crises? However, be careful!

32. General advice for dissertations Attempt a topic that is: Different / interesting Possible to achieve within the time that you have! Involves some type of statistical / data analysis Has a point – the “who cares?” question! That there is at least some other material on Interesting / relevant for you! Do not attempt a topic that is: Investigated every year as a dissertation Irrelevant / of no real importance Has never been studied before / by anyone! Unrealistic given the time / resources that you have