African Climate Change Flashcards
CCV
Clausius-Clapeyron = 1C increase in air temp = 7% more water vapour
energetic constraint = 1C increase in temp = 1-3% increase in precipitation rates (Held and Soden, 2006)
‘wet-get-wetter’ and ‘dry-get-drier’ (Held and Sodon, 2006)
amplification of current patterns = more moisture convergence in tropics but less moisture convergence in subtropics
Upped ante mechanism/ ‘rich-get-richer’ (Neelin et al., 2006)
margins of convection will get drier while regions of high convection get wetter -> because more moisture is required to sustain convection
Africa is very likely to warm ~1.5x global mean warming in W, E, and S (IPCC, 2007)
Drying in N Africa
Wetting in E Africa
Drying in S. Africa (localised due to orographic influence)
(IPCC, 2007)
African tropical rain belt -> shifts seasonally = local changes in precipitation (IPCC, 2007)
Spatially confined convection and precipitation, associated with ITCZ
Single rainy season in poleward edges of the tropical region, but double rainy season in equatorial areas (Giannini et al., 2008)
East Africa precipitation
MAM ‘long rains’ -> 2mm/day and OND ‘short rains’ -> tend to be weaker (Yang et al., 2015)
East Africa Variability (1)
Somali Jet -> supplies moisture for precipitation except for J-A-S = jet reverses for IOM and J-F = as moisture exported to C. Africa and S. Africa (Yang et al., 2015)
East Africa Variability (2)
Turkana Jet -> between Kenyan and Ethiopian Highland = water vapour funnels through -> divergence in tunnel and upper atmospheric convergence = regional aridity (Nicholson, 2016; Vizy and Cook, 2019)
- strong jet = 15-16m/s moisture carried away from Kenya
- weak jet = precipitation across Kenya
reanalysis = underpredicts the jet
East Africa Variability -> short rain (Nicholson et al., 2015)
Indian Ocean Dipole
IOD+ = wet -> increased SSTs off horn of Africa + westerlies
IOD- = dry -> decreased SSTs off the horn of Africa = weaker westerlies
- Strongest IOD+ in 40 years -> very high SSTs in western Indian Ocean -> led to 2019 flooding (Wainwright et al., 2021).
East Africa Variability -> long rains
March-May La Niña = westerly wind anomalies produced-> influence moisture flux (Nicholson and Kim, 1998)
The MJO (Pohl and Camberlin, 2006) or cyclones over the I.O. (Finney et al., 2019) alter moisture flux
observed changes - East Africa = decline in long rains and more variability in short rains
East African Climate Paradox -> CMIP5 models imply increase in precipitation but decrease in observed record (Wainwright et al., 2019) + HadGEM3-G2 model (James et al., 2018) + CMIP3 (Cook and Vizy, 2012)
convective parameterisation = early onset biases of short rains as it increases moist static energy and alters long rains = CMIP5 models undergo parameterisation (Wainwright et al., 2021)
causes for wet biases in the short rains = Equatorial Indian Ocean winds simulated poorly -> observations highlight a low-level westerly flow during the short rains, but models depict an easterly flow at the equator -> decreases confidence in models (Hirons et al., 2018) -> 50% of models unable to capture the easterlies (Hirons and Turner, 2018).
models are temporally poor -> overestimation at short rains and underestimate the long rains (Yang et al., 2014)
GCMs -> better at simulating the E. African climate but imply short rains and long rains = same intensity (Wainwright et al., 2021)
Future Changes to E. Africa in CMIP
wetting in E. Africa -> uncertain as complex topography not represented well in GCMs (Giannini, 2019)
Future wetting = SSTs alter regions of convection (Rowell and Chadwick, 2019) -> found to be unlikely when examined as I.O. SST increases on specific humidity unlikely.
Thermodynamic changes = more intense precipitation (Kendon et al., 2019)
Future Changes to E. Africa -> convection permitting-models
CP4 -> regional model to analyse convection -> 4km resolution -> predicts increased precipitation during the two rainy seasons -> long rains will start earlier + short rains start later but will exceed long rains (Wainwright et al., 2021)
Future Changes to E. Africa -> 21C model
regional model -> short rains start later but increase in precipitation rates + long rains start later but decrease in precipitation rate (Cook and Vizy, 2013).
- Drying in long rains = Somali Jet weakens so less moisture enters for the long rains -> controlled by the heat low across the Arabian Peninsula (Cook and Vizy, 2013)
issues with modelling in E. Africa
need convective permitting models
Needed to represent the Turkana Jet -> important for moisture transport -> poor simulation = wet bias (Munday et al., 2021).
Imply wetting -> due to increased easterly moisture transport from I.O -> increased precipitation (Finney et al., 2020)
Process-based analysis is important
analyses the accuracy of model simulations to analyse whether projection outcomes are likely (James et al., 2018)
Central Africa precipitation
Bimodal precipitation -> MAM (long rains) and SON (short rains) -> different rates between NH and SH w/ SH drier during the dry phase (Cook and Vizy, 2022).
- Short rains are less intense = form simultaneously with the Saharan heat low which causes moisture divergence = reduced precipitation rates (Cook and Vizy, 2022).
Central Africa observations
Poor observational coverage -> in 2012 only 3 observation sites collecting data (Creese and Washington, 2016) -> means cannot challenge model simulations
Central Africa MCSs -> 70% total rainfall, but their dynamics in the Congo Basin are unknown -> high lightning strike activity (Jackson et al., 2009) -> high CAPE over the Congo Basin
MCS formation occurs over: Ethiopian Highlands, Mount Cameroon, Lake Victoria and west of the Congo Basin due to African easterly jets (Jackson et al., 2009).
- MCSs are represented poorly in GCMs w/ regional component (James et al., 2018)
Central Africa Variability - Models
High spread of variability across stations -> ensemble mean precipitation does not agree with a single model (Creese and Washington, 2016) -> greatest variability in models in November while smallest variability in July (Creese and Washington, 2016)
Central Africa Variability
Formation of wet seasons -> controlled by zonal convergence associated with warm Atlantic SSTs and cool I.O. SSTs (Pokam et al., 2012)
Congo Basin Walker Circulation -> connected to E. Atlantic Cold Tongue -> forms during alternative periods to precipitation though (Cook and Vizy, 2016)
Central Africa Projections -> models imply wetting but observations imply drying
Central Africa Projections -> Cook et al. (2020) -> model identified a decrease in precipitation from 1979-2017 due to anthropogenic climate change impacting the Saharan and Angolan Heat Lows (SHL and AL)
C.C. -> thermal lows shift poleward = convergence N and S. of the Congo Basin -> reduction in moisture convergence across C. Basin (Cook and Vizy, 2019)
process-based analysis -> confirmed convergence = meridional wind convergence at 800-500hPa = precipitation across the Congo Basin and changes to this convergence = reduction in precipitation (Cook and Vizy, 2022)
Central Africa Observations
clear drying trend -> Climate Research Unit N. Congo Basin = 3% reduction/decade and S. Congo Basin = 2% reduction/decade (Cook and Vizy, 2020) -> caused by C.C. on SHL and AL
Central Africa -> process-based analysis on SON (short rains) -> CMIP5 = wetting across N. Central Africa (Creese et al., 2019)
Wetting trends -> had SST biases across Eastern Tropical Atlantic = moisture flux through westerlies overemphasised (Creese et al., 2019).
Models tend to depict these westerlies as yearly but they are seasonal -> overstimulates moisture into southern and eastern Africa (James et al., 2018).
½ models from CMIP and some from CORDEX did actually indicate drying trends (Haensler et al., 2013).
Central Africa -> process-based analysis on Congo Basin
increase in short rains (SON) as N and S African easterly jets and Tropical Easterly Jet form leading to enhanced MCS forming (Jackson et al., 2009; Haensler et al., 2013) -> tend to be underrepresented in models which predict drying -> correct simulation would imply wetting as C.C. would weaken the S african easterly jet -> more moisture taken out the region (Creese et al., 2019)
