Lecture vii - Reasons for Uncertainties of Predicting Climate Change

Question 1

What are some reasons for uncertainty surrounding present and future impacts of contemporary climate change?

Answer 1

• Lack of full understanding of physical processes
• incomplete in-situ data on vast expanse of ocean, desert, polar region
• intrinsic measurement error in current climate data
• uncertainty over future greenhouse gas emis n

Question 2

Explain lack of full understanding of physical processes

Answer 2

• earth’s climate system is complex, involve interact n btw atmos, ocean, land surface, ice sheet, many eco
• regional variability exists (spatial variat n) ie some areas may experience more pronounced climate changes than others
• temporal variability: climate oso naturally vary over time (temporal variat n) due to factors eg volcanic erupt n, solar cycles & ocean currents. Distinguish btw natural variability & human-induced CC need long-term data, sophisticated modelling techniques
  eg
  feedback mechanism - melt ice cap reduce albedo, cause furthehr warming while increased evaporat n can enhance cloud form n & may hv cooling effect (so, these 2 differing feedback mechanisms clearly reflect difficulty in determine exact nature, timing, strength of feedback mechanisms)
  eg
  ocean processes
• even difficult to identify ‘tipping points’ in climatic system

Question 3

Explain incomplete in-situ data on vast expanses of oceans, deserts and polar regions

Answer 3

• pose signifi challenge for accurate monitor, understand CC due to:

1. harsh environ condit n
   - scorch heat, sandstorm in desert, extreme cold, freezing temp w strong wind in polar region can damage tracking equipment, hamper data collect n effort
   - many remote region esp in polar area, oni accessible for limited period of year due to ice cover, extreme weather condit n, restrict ability collect continuous, year round data
2. sparse pop n density
   - desert, polar region usually low pop n density as extreme weather condit n , harsh terrain less hospitable for human settlement
   - more challenging establish, maintain observational network, monitoring stations for accurate data collect n over time
3. Limited monitoring infra
   - data collect n in remote, inaccessible region require vv challenging logistics eg transport to gain access to such area AND incur vv high installat n, maintain costs for building weather, data collect n stations, ocean buoys, other observational instruments

Question 4

Explain intrinsic measurement errors in current climate data

Answer 4

• can b deterring factor in full understanding of past, present, future climate condit n. Some main source error include:

1. sampling biases
   - if monitor, data collect n station unevenly distributed across region, any gap in observational coverage can cause spatial, temporal sampling biases
   => could cause under-representat n, over-representat n of climatic data collected at certain stations, time periods, affect accuracy of analysis
   eg
   placemt weather station near urban area, heat source eg buildings, pavements can cause artificial elevated temp reading aka urban heat island effect
2. inaccurate, unreliable measurements
   - issues related to instrument poor calibrat n, malfunct n, sensor drift can all contribute to inaccurate data measuremt
   - error oso can b introduced during data processing eg data filter, interpolat n, mistake in data entry, inconsistency in data format, impact reliability of climate datasets
   - change in measuremt technique over time, station relocat , instrument upgrades can oso affect data comparability, consistency, continuity; so, more difficult predict climatic condit n
3. modelling limit n
   - climat models r essential tools to project future CC, but hv limitat n due to simplificat n of complex climate processes, inaccuracies in input data, computational constraints
   => make such models unreliable, ongoing challenge in climate science

Question 5

Explain uncertainty over future greenhouse gas emissions

Answer 5

1. pop n growth, associated consumpt n pattern
   - large pop n size, greater rcs, energy consump n, cause more ghg emis n
   - indiv, societal behaviour including consump n pattern (eg prefer meat so more cattle ranching), choice transport (private car, planes), waste mgment practices affect ghg emis n
   - uncertainty in future pop n project n & associated behavioural change add complexity to emis n project n
2. econ, tech dvlopmt
   - transit n fr FF to renewable energy source, deploymt low-carbon tech eg solar, wind, nuclear pwr highly dependent on pace of econ growth w direct impact on dvlopmt of tech to harness such renewable energy source at affordable price
   - BUT, such transit n uncertain bcos not all countries hv same capacity dvlop economically, techonologically, so difficult predict future ghg emis n
3. national, international policies, regulat n
   - implementat n, effectiveness, stringency of climate policy, & potential shift in political priorities over time can play crucial role in shape ghg emis n tracjectory
   eg
   change in landuse w afforestat n or deforestat n can affect ghg emis n through carbon sequestrat n, release stored carbon respectively. BUT, future land-use decision, policy, natural disturbances (eg wildfire)
   - oso, many challenge still exist to ascertain lvl international coop needed among competing needs of various countries & geopolitical tension cld affect emis n reduct n effort
   eg
   LDCs (china, brazil) support industrial econ, so large ghg emis n but not legally bound by targets set.
   US withdrew fr Paris agreement in 2020 but rejoin in 2021
4. socio-econ factor
   - extent of future climate impact oso depend on societal response to CC, (adapt n measure, mitigat n strategy)
   - uncertainty stem fr effectiveness, timing of responses & societal vulnerability & adaptive capacity

Question 6

What can be done to address uncertainties in predicting climate change?

Answer 6

-> multi-faceted nature of CC, & uncertainty in natural, human systems, make accurate predict present, future impact more difficult
-> addressing uncertainties require:
- continued rigorous research, keen, detailed observ n
- collab across scientific discipline, & both national, international stakeholders
- improved understand of socio-econ drivers, tech innovat n, policy dynamics can oso help reduce uncertainty, facilitate climate mitigat n strategy, adapt n plan