Fieldwork Suggestions for Independent Investigations

Some ideas, data sources and guidance for students wishing to include weather measurements in their NEA or EPQ.

Updated November 2022

A guide to collecting weather data

https://www.rgs.org/CMSPages/GetFile.aspx?nodeguid=59f46632-ae51-4ea7-ab94-a0c537eb3c71&lang=en-GB

Passage of a depression

https://www.metlink.org/wp-content/uploads/2020/12/depression_wow_teacher_Eva.pdf
Data source:

http://wow.metoffice.gov.uk

Weather and Health/ Behaviour

Data source: http://wow.metoffice.gov.uk

Urban Climates

Using Wow data to look at urban heat islands https://www.metlink.org/resource/using-wow-to-illustrate-the-urban-heat-island-effect/

Urban winds: fieldwork guidance can be found on https://www.metlink.org/fieldwork-resource/fieldwork-in-geography/

Urban temperature https://www.metlink.org/fieldwork-resource/urban-heat-island-introduction/
Data source: http://wow.metoffice.gov.uk

Community resilience to extreme weather

Local microclimate

https://www.metlink.org/fieldwork-resource/using-usb-temperature-dataloggers/

https://www.rgs.org/schools/teaching-resources/quick-and-easy-ideas/

Data source: http://wow.metoffice.gov.uk

Factors affecting rainfall:


https://www.manchester.ac.uk/discover/news/tuesday-wettest-day-of-week-suggests-new-analysis/
https://rmets.onlinelibrary.wiley.com/doi/10.1002/joc.2321

Orographic rainfall https://www.metlink.org/resource/orographic-relief-rainfall-and-the-foehn-effect/

 

Red Sky at Night


https://www.metlink.org/resource/red-sky-teachers/ with an introductory concept cartoon from the ASE 
https://www.metlink.org/blog/folklore/weather-folklore/

Snow

 https://www.metlink.org/blog/extreme-weather/when-will-it-snow/

Sky Colour


https://www.exploringoverland.com/constantapprentice/2021/8/10/making-a-cyanometer-to-measure-sky-moisture-through-color with https://uk-air.defra.gov.uk/interactive-map pollution forecast and pollen forecast http://www.metoffice.gov.uk/health/public/pollen-forecast

Weather and Flooding


Data source: National River Flow Archive http://nrfa.ceh.ac.uk/ and https://environment.data.gov.uk/hydrology/index.html#/landing

Sea level

http://www.coolgeography.co.uk/GCSE/AQA/Coastal%20Zone/Sea%20level%20rise/Sea%20level%20rise.htm

Land and Sea breezes, sea breeze front

Data source: http://wow.metoffice.gov.uk

Air Masses


https://earth.nullschool.net/
http://www1.wetter3.de/Archiv/archiv_ukmet.html
various links on https://www.metlink.org/teaching-resources/?_sft_topic=air-masses
including https://www.metlink.org/resource/pressure-and-rainfall/
Data source: http://wow.metoffice.gov.uk

General resources


https://www.metlink.org/fieldwork-resource/instruments-and-fieldwork/


https://www.rgs.org/schools/teaching-resources/key-stage-five/extreme-weather/


https://www.metlink.org/fieldwork/


https://www.rgs.org/schools/teaching-resources/a-student-guide-to-the-a-level-independent-investi/


https://www.field-studies-council.org/resources/16-18-geography/route-to-enquiry/

IPCC 2021 – Extreme Heat in Urban Africa

Climate change has increased heat waves (high confidence) and drought (medium confidence) on land, and doubled the probability of marine heatwaves around most of Africa.

Heat waves on land, in lakes and in the ocean will increase considerably in magnitude and duration with increasing global warming.

Most African countries will enter unprecedented high temperature climates earlier in this century than generally wealthier, higher latitude countries, emphasising the urgency of adaptation measures in Africa.

IPCC 2021 – Wildfire

Wildfire: Causes, Impacts and Responses

Wildfire is a natural and essential part of many forest, woodland and grassland ecosystems, killing pests, releasing plant seeds to sprout, thinning out small trees and serving other functions essential for ecosystem health. Excessive wildfire, however, can kill people, the smoke can cause breathing illnesses, destroy homes and damage ecosystems.

Anthropogenic climate change increases wildfire by exacerbating its three principal driving factors: heat (by drying out vegetation and accelerating burning), fuel and ignition. Non-climatic factors also contribute to wildfires—in tropical areas, fires are set intentionally to clear forest for agricultural fields and livestock pastures.

Urban areas and roads create ignition hazards. Governments in many temperate-zone countries implement policies to suppress fires, even natural ones, producing unnatural accumulations of fuel in the form of coarse woody debris and high densities of small trees. The fuel accumulations cause particularly severe fires that burn upwards into tree crowns.

Globally, 4.2 million km2 of land per year burned on average from 2002 to 2016, with the highest fire frequencies in the Amazon rainforest, deciduous forests and savannas in Africa and deciduous forests in northern Australia.

Across the western USA, increases in vegetation aridity due to higher temperatures from anthropogenic climate change doubled burned area from 1984 to 2015 over what would have burned due to non-climate factors including unnatural fuel accumulation from fire suppression, with the burned area attributed to climate change accounting for 49%  of cumulative burned area.

Anthropogenic climate change doubled the severity of a southwest North American drought from 2000 to 2020 that has reduced soil moisture to its lowest levels since the 1500s, driving half of the increase in burned area. In British Columbia, Canada, the increased maximum temperatures due to anthropogenic climate change increased burned area in 2017 to its highest extent in the 1950–2017 record, seven to eleven times the area that would have burned without climate change.

In Alaska, USA, the high maximum temperatures and extremely low relative humidity due to anthropogenic climate change accounted for 33–60% of the probability of wildfire in 2015, when the area burned was the second highest in the 1940–2015 record.

In National Parks and other protected areas of Canada and the USA, climate factors (temperature, precipitation, relative humidity and evapotranspiration) accounted for 60% of burned area from local human and natural ignitions from 1984 to 2014, outweighing local human factors (population density, roads and built area).

In summary, field evidence shows that anthropogenic climate change has increased the area burned by wildfire above natural levels across western North America in the period 1984–2017, at Global Mean Surface Temperature increases of 0.6°C–0.9°C, increasing burned area up to 11 times in one extreme year and doubling it (over natural levels) in a 32-year period.

Regarding global terrestrial area as a whole, from 1900 to 2000, fire frequency increased on one-third of global land, mainly from burning for agricultural clearing in Africa, Asia and South America.

Where the global average burned area has decreased in the past two decades, higher correlations of rates of change in burning to human population density, cropland area and livestock density than to precipitation indicate that agricultural expansion and intensification were the main causes.  The fire-reducing effect of reduced vegetation cover following expansion of agriculture and livestock herding can counteract the fire-increasing effect of the increased heat and drying associated with climate change.

The human influence on fire ignition can be seen through the decrease documented on holy days (Sundays and Fridays) and traditional religious days of rest. Overall, human land use exerts an influence on wildfire trends for global terrestrial area as a whole that can be stronger than climate change.

In the Amazon, deforestation for agricultural expansion and the degradation of forests adjacent to deforested areas cause wildfire in moist humid tropical forests not adapted to fire. Roads facilitate deforestation, fragmenting the rainforest and increasing the dryness and flammability of vegetation.

In the extreme fire year 2019, 85% of the area burned in the Amazon occurred in areas deforested in 2018. In the Amazon, deforestation exerts an influence on wildfire that can be stronger than climate change.

Overall, burned area has increased in the Amazon, Arctic, Australia and parts of Africa and Asia, consistent with, but not formally attributed to, anthropogenic climate change.

Deforestation, peat draining, agricultural expansion or abandonment, fire suppression and inter-decadal climate cycles exert a stronger influence than climate change on wildfire trends in numerous regions outside of North America.

The global increases in temperature from anthropogenic climate change have increased aridity and drought, lengthening the fire weather season (the annual period with a heat and aridity index greater than half of its annual range) on one-quarter of global vegetated area and increasing the average fire season length by one-fifth from 1979 to 2013.

Climate change has contributed to increases in the fire weather season or the probability of fire weather conditions in the Amazon, Australia, Canada, central Asia, East Africa and North America

In non-forest areas, the burned area correlates with high precipitation in the previous year, which can produce high grass fuel loads.

Globally, fire has contributed to biome shifts and tree mortality attributed to anthropogenic climate change. Through increased temperature and aridity, anthropogenic climate change has driven post-fire changes in plant regeneration and species composition in South Africa – in the fynbos vegetation of the Cape Floristic Region, South Africa, post-fire heat and drought and the legacy effects of exotic plant species reduced the regeneration of native plant species, decreasing species richness by 12% from 1966 to 2010

Continued climate change under high-emission scenarios that increase global temperature ~4°C by 2100 could increase global burned area by 50% to 70% and global mean fire frequency by ~30%. Lower emissions that would limit the global temperature increase to <2°C would reduce projected increases of global burned area to 30% to 35% and projected increases of fire frequency to ~20%.

Increased wildfire increases risks of tree mortality, biome shifts and carbon emissions as well as high risks from invasive species. Wildfire risks to people include death and destruction of their homes, respiratory illnesses from smoke, post-fire flooding from areas exposed by vegetation loss and degraded water quality due to increased sediment flow. Increased wildfire under continued climate change increases the probability of human exposure to fire and risks to public health.

Regions identified as being at a high risk of increased burned area, fire frequency and fire weather include: the Amazon, Mediterranean Europe, the Arctic tundra, Western Australia and the western USA.  Moreover, increased fire, deforestation and drought, acting via vegetation–atmosphere feedbacks, increase the risk of extensive forest dieback and potential biome shifts of up to half of the Amazon rainforest to grassland, a tipping point that could release an amount of carbon that would substantially increase global emissions.

In the Arctic tundra, boreal forests and northern peatlands, including permafrost areas, climate change under the scenario of a 4°C temperature increase could triple the burned area in Canada, double the number of fires in Finland and double the burned area in Alaska. Thawing of Arctic permafrost due to wildfires could release 11–200 Gt Carbon which could substantially exacerbate climate change.

In Venezuela, Brazil and Guyana, Indigenous knowledge systems have led to a lower incidence of wildfires, reducing the risk of rising temperatures and droughts.

The Tasmanian Wilderness World Heritage Area has a high concentration of plant species which are restricted to living in cool, wet climates and fire-free environments, but recent wildfires have burnt substantial stands that are unlikely to recover. Most of the area is managed as a wilderness zone and is currently carried out in a manner that allows natural processes to predominate. There has been a realisation that this ‘hands off’ approach will not be sufficient.  After the wildfires in 2016 caused extensive damage, significant efforts and resources were spent trying to protect the remaining stands of pencil pine during the 2019 fires, using new approaches including the strategic application of long-term fire retardant and the installation of kilometres of sprinkler lines.  However, there is concern that these interventions may have adverse effects if applied widely. Increasingly, there is an acknowledgment that the cessation of traditional fire use has led to changes in vegetation and there are calls to incorporate Aboriginal burning knowledge into fire management.

Wildfires pose a significant threat to electricity systems in dry conditions and arid regions.  Solar PV generation is reduced by clouds and is less efficient under extreme heat, dust storms, and wildfires.

Severe impacts on railway infrastructure and operations can arise from the occurrence of temperatures below freezing, excess precipitation, storms and wildfires.

Adaptation for natural forests includes conservation, protection and restoration measures.

Restoring natural forests and drained peatlands and improving sustainability of managed forests generally enhances the resilience of carbon stocks and sinks.

In managed forests, adaptation options include sustainable forest management, diversifying and adjusting tree species compositions to build resilience, and managing increased risks from pests and diseases and wildfires.

Successful forest adaptation requires cooperation, inclusive decision making with local communities, and recognition of the inherent rights of indigenous people.

Ecosystem-based adaptation measures can reduce climatic risks to people, for example restoring natural vegetation cover and wildfire regimes can reduce risks to people from catastrophic fires.

A case study to illustrate the innovativeness of indigenous adaptation is the Bedouin pastoralists of Israel, where wildfires are a major cause of deforestation. Competing land use has reshaped the landscape with pine monocultures and cattle farming, reducing the availability of land suitable for herding goats the indigenous way, across the original landscape of shrubland or maquis (consisting mostly of oak and Pistacia). In addition, since 1950, plant protection legislation has decreased Bedouin forest pastoralism by defining indigenous black goats as an environmental threat. This has led to nature reserves where no human interference is allowed and shrubland regeneration, which is susceptible to wildfires.

In 2019, many severe wildfires occurred in Israel due to extreme heatwaves and, in response, plant protection legislation was repealed, allowing Bedouin pastoralists to graze their goats in these areas once more. The amount of combustible undergrowth subsequently decreased, reducing the risk for wildfire whilst also facilitating indigenous food sovereignty among the Bedouin.

Modelling of the interactions between climate-induced vegetation shifts, wildfire and human activities can provide keys to how people may be able to adapt to climate change.

Fire management plans and programmes are increasingly being developed, even in parts of Europe where wildfires are less common.

There is growing recognition of the need to shift fire management and suppression activities to co-exist with more fire on the landscape, particularly in North America. This includes widespread use of prescribed fire across landscapes to increase ecological and community-based resilience.

Climate-informed post-fire ecosystem recovery measures (e.g., strategic seeding, planting, natural regeneration), restoration of habitat connectivity and managing for carbon sequestration (e.g., soil conservation through erosion control, preservation of old growth forests, sustainable agroforestry) are critical to maximise long-term adaptation potential and reduce future risk through co-benefits with carbon mitigation. Prescribed fire and thinning approaches, including the use of indigenous practices, are receiving a new level of awareness.

Enhanced coordination between the health sector and fire suppression agencies can also reduce the health impacts of wildfire smoke via improving communication, weather forecasting, mapping, fire shelters and coordinating decision making.

All text and diagrams adapted from the WGII and WGIII reports of the IPCC Sixth Assessment Report https://www.ipcc.ch/report/ar6/wg3/ and https://www.ipcc.ch/report/ar6/wg2

Beast from the East

Broad General Education (BGE)

Second Level: People, Place and the Environment

I can describe the physical processes of a natural disaster (extreme weather event)
and discuss its impact on people and the landscape
.

  • Describes the causes of a natural disaster such as a volcano, earthquake or extreme weather event.
  • Describes the impact of the natural disaster giving at least three examples for people and one for the landscape. Impact can be positive or negative.

Depressions: Case Study Template and Storm Eunice Example

Download editable worksheet.
This can be used to create a case study of a named depression in the UK. Below, we have given an example of how the worksheet could be used to create a case study of Storm Eunice.
Depressions are low pressure weather systems which bring rain, wind and sometimes snow to the UK. They are responsible for much of our extreme weather.   A depression is easily recognisable on weather charts and satellite images. It has low pressure in the centre with warm, cold and occluded fronts and a hook shaped cloud.
Storm Eunice cloud and wind

In the UK, storms have been given names since 2015. A storm is named if it is likely to have a significant impact on the UK or Ireland.

  1. Write down the names of any recent storms you can remember. Eunice
  2. Use the Met Office storm centre index to discover the date that one of those storms had an impact on the UK/ Ireland (if your storm isn’t in the current year, scroll to the bottom of the page to the Related Links section for previous years).

Storm Name: Eunice Date: 18th February 2022

Now download the weather charts for the storm. 

In the bottom left of the page, where is says ‘Archiv – Basistermin, enter the date of the storm in the format day – month – year

3) Copy and paste the weather map onto this document.

4) Put a red circle around the centre of the storm. This is marked by a cross and the pressure value at the centre of the storm is given.

Now use the single forward arrow to advance the chart by 6 hours.

5) Copy and paste the weather map onto this document.

6) Put a red circle around the centre of the storm

Storm Eunice

Now use the single forward arrow to advance the chart by 6 hours.

7) Copy and paste the weather map onto this document.

8) Put a red circle around the centre of the storm

9) Now complete the table using information from your three weather maps:

Eunice centre data

Winds rotate around a depression in an anticlockwise direction, following the pressure contours. 

10) Use ‘insert’ and ‘shapes’ to add arrows showing the wind direction around the storm to the first of your weather maps.

In addition to naming storms, sometimes colour coded weather warnings are given. The colour of the warning depends on a combination of how much damage the storm is expected to do, and how likely that damage is. So a storm that is very likely to cause a lot of damage is given a red warning, but a yellow warning could mean that a storm is either very likely to cause a bit of damage, or unlikely to cause a lot of damage.

weather warning matrix

11) Go back to the Met Office storm centre https://www.metoffice.gov.uk/weather/warnings-and-advice/uk-storm-centre/index and click on your storm’s name – this should give you a summary sheet about your storm. Scroll through it – were any weather warnings issued? List them below, or write ‘none’.

Eunice warnings

Extension

Use the Met Office summary sheet you just opened, or BBC news https://www.bbc.co.uk/news to write a paragraph about the impacts of your storm.

Storm Eunice had significant impacts, including four fatalities and significant wind damage. However, with weather warnings issued almost a week in advance, the precautionary measures people were able to take, for example closing schools, meant that damage was minimised. 

 

Core Maths – Extreme Weather

Resource produced in collaboration with MEI

Brief overview of session ‘logic’

  • Do reports of extreme cold weather provide evidence that global warming is not happening?
  • Show the New York Times graphs of summer temperature distributions for the Northern Hemisphere for different periods.
  • Interrogate/critique these graphs
  • The distributions of temperatures are approximately Normal distributions and the mean and standard deviation both increase as the time period becomes more recent.
  • Use the dynamic bell curve to calculate probabilities of different temperatures in different time periods.
  • Despite the mean temperature increasing, the standard deviation also increasing means that the probability of extreme low temperatures increases.
  • Normal distributions and bell curves can explain a higher frequency of extreme cold weather despite global warming.

Mathematical opportunities offered

  • Interpretation of data, statistics, graphs, infographics in context
  • Critiquing graphs
  • Reading scales
  • Using standard form to write very large or very small numbers
  • Fitting a Normal distribution or bell curve to a graph
  • Exploring the effect of adjusting mean and standard deviation on a bell curve
  • Understanding that probabilities can be represented and calculated using areas
  • Analysing and comparing data in order to develop and present a conclusion.

Key Stage 3 – Extreme Weather

Resource produced in collaboration with MEI

Brief overview of session ‘logic’

  • Do reports of extreme cold weather provide evidence that global warming is not happening?
  • Show the New York Times graphs of summer temperature distributions for the Northern Hemisphere for different periods.
  • Interrogate/critique these graphs
  • The distributions of temperatures are approximately Normal distributions and the mean and standard deviation both increase as the time period becomes more recent.
  • Use the dynamic bell curve to calculate probabilities of different temperatures in different time periods.
  • Despite the mean temperature increasing, the standard deviation also increasing means that the probability of extreme low temperatures increases.
  • Normal distributions and bell curves can explain a higher frequency of extreme cold weather despite global warming.

Mathematical opportunities offered

  • Interpretation of data, statistics, graphs, infographics in context
  • Critiquing graphs
  • Reading scales
  • Using standard form to write very large or very small numbers
  • Fitting a Normal distribution or bell curve to a graph
  • Exploring the effect of adjusting mean and standard deviation on a bell curve
  • Understanding that probabilities can be represented and calculated using areas
  • Analysing and comparing data in order to develop and present a conclusion

IPCC 2021 – Which Regions have been affected the most by climate change?

“A.3 Human-induced climate change is already affecting many weather and climate extremes in every region across the globe. Evidence of observed changes in extremes such as heatwaves, heavy precipitation, droughts, and tropical cyclones, and, in particular, their attribution to human influence, has strengthened since AR5”1

Consider the three following maps with your students, or alternatively focus in on one of the maps.

Heavy Precipitation

“A.3.2 The frequency and intensity of heavy precipitation events have increased since the 1950s over most land area for which observational data are sufficient for trend analysis (high confidence), and human-induced climate change is likely the main driver. Human-induced climate change has contributed to increases in agricultural and ecological droughts in some regions due to increased land evapotranspiration (medium confidence).”1

IPCC precipitation

Source: Adjusted from IPCC 1

  1. Study carefully the map above which shows an assessment of the observed change in heavy precipitation across the globe.
  2. How many of the regions showing on the map have experienced an increase in heavy precipitation?                                                                                                                                                            
  3. How many of the regions shown on the map have experienced a decrease in heavy precipitation?                                                                                                                                                            
  4. What is the situation in the region where you live with regards to changes in heavy precipitation?                                                                                                                                                            
  5. Identify the region where there is high confidence in the human contribution to the observed change.                                                                                                                                                            
  6. Use TEA (Trend, Evidence, Anomoly) to describe the patterns shown on the map above. Which regions have had an increase in observed heavy precipitation? Which regions have limited evidence?                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               
  7. Suggest what impacts an increase in heavy precipitation might have.                                                                                                                                                                                                                                                                                                                                                                                                                        
  8. Look closely at the areas that have limited data and/or literature. Can you suggest reasons why these areas have limited data and literature in relation to heavy precipitation?                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    

Hot Extremes

“A.3.1 It is virtually certain that hot extremes (including heatwaves) have become more frequent and more intense across most land regions since the 1950s, while cold extremes (including cold waves) have become less frequent and less severe, with high confidence that human-induced climate change is the main driver14 of these changes. Some recent hot extremes observed over the past decade would have been extremely unlikely to occur without human influence on the climate system. Marine heatwaves have approximately doubled in frequency since the 1980s (high confidence), and human influence has very likely contributed to most of them since at least 2006.” 1

IPCC hot extremes

Source: Adjusted from IPCC 1

The IPCC define an extreme weather event as “an event that is rare at a particular place and time of year. Definitions of rare vary, but an extreme weather event would normally be as rare as or rarer” than the top or bottom 10% of observed events. Therefore, for hot extremes these would be periods where temperatures are in the top 10% for that region. 1

  1. Study the map above carefully which shows an assessment of the observed change in hot extremes across the globe.
  2. How many of the regions showing on the map have experienced an increase in hot extremes?                                                                                                                                                                                                                                                                                                                        
  3. How many of the regions shown on the map have experienced a decrease in hot extremes?                                                                                                                                                                                                                                                                                                                        
  4. What is the situation in the region where you live with regards to changes in hot extremes?                                                                                                                                                                                                                                                                                                                        
  5. Identify the region where there is high confidence in the human contribution to the observed change.                                                                                                                                                            
  6. Describe the patterns shown in the regions that have had an increase in observed hot extremes.                                                                                                                                                                                                                                                                                                            
  7. Suggest what impacts an increase in hot extremes might have.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                
  8. Look closely at the areas that have limited data and/or literature on both the hot extremes and heavy precipitation maps. There are more regions with limited data on the heavy precipitation map.  Can you suggest reasons why?                                                                                                                                                                                                                                                                                                                                                                                                                 

Agricultural and Ecological Drought

“A.3.5 Human influence has likely increased the chance of compound extreme events18 since the 1950s. This includes increases in the frequency of concurrent heatwaves and droughts on the global scale (high confidence)”1

IPCC drought

Image source: Adjusted from IPCC 1

The IPCC define Drought as “A period of abnormally dry weather long enough to cause a serious hydrological (water) imbalance.”1 This would mean that the amount of rain that falls is not sufficient to meet agricultural (farming) or ecological (the plants and animals in a region) needs and during the growing season impinges on crop production or ecosystem function.

  1. How many of the regions showing on the map have experienced an increase in agricultural and ecological drought?                                                                                                                                                            
  2. How many of the regions shown on the map have experienced a decrease in agricultural and ecological drought?                                                                                                                                                            
  3. Identify the two regions where there is medium confidence in the human contribution to the observed change.                                                                                                                                                                                                                                                                                                                        
  4. What is the situation in the region where you live with regards to changes in agricultural and ecological drought?                                                                                                                                                                                                                                                                                                                                                                                                                                                
  5. Describe the patterns shown in the regions that have had an increase in observed agricultural and ecological drought.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
  6. Suggest what impacts an increase in agricultural and ecological drought might have.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            
  7. Look closely at the areas that have limited data and/or literature. Can you suggest reasons why these areas have limited data and literature in relation to agricultural and ecological drought?                                                                                                                                                                                                                                                                                                                                                                                                                                                                        

Overview – Which Regions have been Affected the Most?

IPCC extreme weather overview
Source: Adjusted from IPCC 1
  1. Using the graphic above identify three places but are affected negatively by all three situations [hot extremes, heavy precipitation, and agricultural and ecological drought]
    1.                                                                       
    2.                                                                       
    3.                                                                       
  2. Using the graphic identify an area that that is affected by fewest of the situations?                                                                                                                                                            
  3. Which areas on the map should be a priority for further research into the effects of climate change? Explain your answer.                                                                                                                                                                                                                                                                                                
  4. Which of the three situations have affected most regions of the world? Use evidence from the maps to support your answer.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
  5. Write a letter to your local MP, use evidence from the graphic to justify the need for action on climate change. You should focus upon the urgent need for action and how that can be implemented (done) locally.

Geographical information systems activity

Visit the website below, it is the Intergovernmental Panel on Climate Change’s Interactive Atlas. IPCC WGI Interactive Atlas Click on the regional information button, it will bring up an interactive map. Complete the table below using information from the map. You will need to use the menu tools above the map, changing the variable and scenario. Complete this for the Near Term. If you finish, you could repeat for the Long Term on a new sheet and then compare results.
IPCC extreme weather table

Overall what does the table and map show you about global climates in the future?                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        

Note 

  • SSP1-2.6: Global CO2 emissions are cut severely, but not as fast, reaching net-zero after 2050. Temperatures stabilize around 1.8°C higher by the end of the century.
  • SSP5-8.5: Current CO2 emissions levels roughly double by 2050. The global economy grows quickly, but this growth is fuelled by exploiting fossil fuels and energy-intensive lifestyles. By 2100, the average global temperature is a scorching 4.4°C higher.

Sources:

  • IPCC, 2021: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press. In Press. P.11. Accessed 28th November 2021 at Sixth Assessment Report (ipcc.ch)

How often will a heatwave hit the UK?

Royal Geographical Society

This resource links to Figure 11.12 in the IPCC report of 2021. The aim of this resource is to answer the question how often will a heatwave hit the UK?

It was written with the Royal Geographical Society with IBG

Box and whisker plots

Figure 11.12 (see Appendix B) is a box and whisker plot. The graph highlights that extreme temperature events are forecast to increase in the twenty-first century. Extreme temperature events are defined as the daily maximum temperatures that were exceeded once during a 10-year (or 50-year) period.

The dataset for Figure 11.12 is from the paper Changes in Annual Extremes of Daily Temperature and Precipitation in CMIP6 Models by Li et al., 2020. An extract of the data is shown below in Table 1 in Appendix A. The numbers in parenthesis ( ) and square brackets [ ] show respectively the central 66% and 90% uncertainty ranges of the estimated changes in annual maximum temperature, from identified warming level ‘windows’.

The warming of annual maximum temperature events is more uniform over land and increases linearly with global warming. There is high confidence that the magnitude of temperatures extremes will continue to increase more strongly than global mean temperature.

2021 heatwave

Figure 1 the European heatwave of 2021, heat is becoming more extreme and more frequent © University of Maine

The temperature at which an event is classed as a hot extreme is going up (faster than the mean temperature). In the mid-latitudes (between 30° and 60° north and south) the strongest warming is expected in the warm season, with an increase of up to 3°C for 1.5°C of global warming. This has led to events such as the ‘merciless’ temperature spike in Russia, and the ‘heat dome’ over North America in June 2021. The highest increase of temperature in the ‘hottest days’ is projected for some mid-latitude countries and semi-arid regions, such as in North America.

  1. The frequency with which hot events occur is also going up. Study Table 1 in Appendix A. Using Relative frequency change for a 1.5°C, 2°C and a 4°C future, draw a box and whisker plot for global land, with 90% uncertainty ranges. Use the following steps to draw your graph.

a. Draw an x axis and label Global warming above 1850-1900 (°C).

b. Draw the y axis and label Relative frequency change (for one in a 50-year events).

c. Identify the median (the middle) of the data set (which is given to you).

d. Use the 66% uncertainty data (parenthesis brackets) for each box plot.

e. Use the 90% uncertainty data [square bracket] for the whiskers.

In Europe the evidence predicts an increase in the frequency and intensity of hot extremes (warm days, warm nights, heat waves) and, in reverse, a decrease in the frequency and intensity of cold extremes. Heat wave increases will be greater over the south Mediterranean and Scandinavia with southern European cities expected to suffer the biggest increases in maximum heat wave temperatures.

Figure 2 extreme heat is afflicting Europe more regularly © Fabian Keller Unsplashed

2. Why do cities experience extreme heat more frequently?

3. Now repeat the same activity, graphing Relative frequency change, for the ocean dataset.

Whilst heatwaves will increase across Europe and in the UK, there will still be extreme cold in the future. It is a common misconception to think that, as the climate changes, we will only experience warm weather and extreme heat in the twenty-first century. In fact, the climate distribution will change. Extreme cold will still happen, just less frequently. Figure 3 below illustrates this misconception with a probability curve showing climate likelihood and temperature and, underneath, the change from our previous climate to a warmer one. Both the the threshold temperature for an event to be considered extreme, and the frequency of high temperatures, rise in a warming climate. 

temperature pdf
changing temperature pdf

Figure 3 climate graphs © The Royal Meteorological Society Weather and Climate: A Teachers’ Guide

Further work

Exam-style question 

Using all the work you have completed answer the final question below. The instruction is to assess the likelihood that heat wave frequency will increase in the UK. This means you must consider the different arguments, likelihoods, and levels of certainty, after weighing them up, to come to a conclusion. 

4. Assess the likelihood that heat wave frequency will increase in the UK.

Appendix A

extreme temperature data

Appendix B

IPCC AR6 extreme high temperatures

Figure 4 Projected changes in the intensity of extreme temperature events under 1°C, 1.5°C, 2°C, 3°C, and 4°C global warming levels relative to the 1851-1900 baseline © The IPCC report

Answers

  1. As instructed. Figure 4 Appendix B shows a finished box and whisker plot.
  2. Southern Europe is experiencing extreme heat more frequently because high atmospheric pressure draws hot air from northern Africa, Portugal, and Spain up and across the continent with greater regularity. This raises temperatures and increases humidity. Heatwaves are being enhanced by drier soils, humidity, and low wind speeds making the effects particularly dangerous in urban areas. Changes to the North Atlantic jet stream and increasing instability and changing flow pattern of the Gulf Stream are some of the influences on Eurasian weather.As instructed.
  3. As instructed.
  4. As instructed. 

Using WOW to Illustrate the Urban Heat Island Effect

The Urban Heat Island (UHI) effect makes the centres of towns and cities warmer than the surrounding countryside, especially at night. This is mainly because all the brick, concrete and paving in a city warms up during the day, and then retains its heat for several hours, so helping to keep the city warm as night comes.

The graph below shows temperature over a couple of days in September in the middle of Reading (dark blue) and in a rural village (light blue) about 6km north of Reading.  For this period, the skies were clear and the wind was light, allowing the temperature at Sonning Common to fall quickly after sunset.

However, the Reading city centre temperature fell less rapidly, because of the UHI effect, so that it remained 3 or 4 degrees warmer than Sonning Common during most of the night.

weather station data

On the other hand, the UHI effect is smaller when nights are cloudy and when it is windy. The graph below shows a comparison of temperature the same two places for a couple of very cloudy, rainy, days in October.  Because clouds stop heat escaping from the ground, the temperature doesn’t fall much after sunset, and there is only a degree or so difference between the rural village and the city centre.

weather station data

You can easily make the same sort of comparisons, and shown the UHI effect, using WOW.

The Met Office WOW website http://wow.metoffice.gov.uk is the result of a collaboration between the Met Office and the Royal Meteorological Society, and is a platform for weather observers around the world to upload and share their data.

Aim

  • To use archived weather station data to show the development of an Urban Heat island.
  • To understand when Urban Heat Islands form.

The advantage of using archived data from a site such as WOW is that a date can be selected when weather conditions were appropriate for urban heat island formation, and local data can be found.

Differentiation

Depending on ability, students could be given help choosing locations and/ or dates for the study. More able students could use several sites in and around an urban area.

Background Information for Teachers

Urban Heat Island Introduction

Supporting PowerPoint presentations can be found here and here.

and from MetMatters Urban Heat Islands

Required

Students will require access to the internet.

Choosing locations

Students should select two locations, one in an inner city area and one in a rural area just outside the city.

They might like to make sure that the sites they choose are submitting high quality data (for example, use the ‘filter’ drop down menu to select ‘official observations’ have the best data).

Students could use the satellite view on Google Earth to check the land use of the place where the weather is being recorded.

Advanced students might like to use an OS map to check whether there is a substantial height difference between the sites, and should consider whether this will have an effect on the temperatures recorded.

Choosing a Date and time

The Urban Heat Island is biggest:

  • At night (before sunrise)
  • In the summer
  • When there is little or no wind (<5m/s)
  • When the sky is clear
  • When the weather doesn’t change through the night

How to Use WOW

  • Go to the WOW website wow.metoffice.gov.uk
  • Zoom in to find appropriate pairs of weather stations (perhaps in your area), one urban and one rural within 10km of your urban site. Click on them and make a note of their Site name.
  • Click on the urban weather station.
  • A pop-up box will appear, giving you some information about the site.
  • Click on ‘View Full Observation’ and then on either ‘table’ or ‘graph’.
  • You may like to change the tick boxes under ‘show filters’ such that only Air Temperature is selected, and alter the date range shown to choose a summer period.
weather station data
  • Look for a period of a few days in that month when the temperature difference between night and day is big – this usually means it is clear and with only light winds. In this graph, the 28th August stands out as a time when an UHI might be expected.
  • Select that period in the start and end calendars.
  • Get a graph from the rural station of just those few days
  • Next enter the name of the nearby urban station in the ‘compare to’ box, and update the graph.
  • This should show temperatures at both stations so that you can compare them.
  • Look to see how the difference changes over the course of the days you have selected. Can you see the UHI? What time of day is it biggest? Smallest?

Plenary

Use the second PowerPoint presentation above. 

Ask students to line up across room as a continuum. Students should stand at the left if they think their experiment does provide evidence for an urban heat island, and the right if they think it does not, or somewhere in between.

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