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CHAPTER 14: CLIMATE
PHENOMENA AND THEIR
RELEVANCE FOR FUTURE
REGIONAL CLIMATE CHANGE
Christensen, J.H., K. Krishna Kumar, E. Aldrian, S.-I. An, I.F.A. Cavalcanti, M. de Castro, W.
Dong, P. Goswami, A. Hall, J.K. Kanyanga, A. Kitoh, J. Kossin, N.-C. Lau, J. Renwick, D.B.
Stephenson, S.-P. Xie and T. Zhou, 2013: Climate Phenomena and their Relevance for
Future Regional Climate Change. In: Climate Change 2013: The Physical Science Basis.
Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental
Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J.
Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press,
Cambridge, United Kingdom and New York, NY, USA.
Amanda Sheffield
December 8, 2014
Table of Contents
“This chapter assesses the scientific literature on projected changes
in major climate phenomena and more specifically their relevance
for future change in regional climate, contingence on global mean
temperatures continue to rise.”
“The dynamics of regional climates are determined by local
weather systems that control the net transport of heat, moisture and
momentum into a region.”
 14.1 Introduction
 14.2 Monsoon Systems
 14.3 Tropical Phenomena
 14.4 El Nino-Southern Oscillation
 14.5 Annular and Dipolar Modes
 14.6 Large-scale Storm Systems
 14.7 Additional Phenomena of Relevance
 14.8 Future Regional Climate Change
3 Main Classes of Phenomena


“The following large-scale phenomena are increasingly well simulated by
climate models and so provide a scientific basis for understanding and
developing credibility in future regional climate change.”
Monsoons and Tropical Convergence Zones (i.e. seasonal movement of
convergence zones over land, convergence over tropical oceans, leading to
profound seasonal changes in local hydrological cycles)
Modes of Climate Variability (i.e. ENSO, NAO/NAM, SAM, PNA, PDO,
AMO).






No Change - the modes will continue to behave as they have done in the recent
past
Index Changes - the probability distributions of the mode indices may change
Spatial Changes – the climate patterns associated with the modes may change
spatially or the local amplitudes of the climate patterns may change
Structural Changes – the types and number of modes and their mutual
dependencies may change; completely new modes could in principle emerge.
Tropical and Extratropical Cyclones
No focus on local feedback processes
Page 1224
Monsoon Systems
Global Monsoon System




Very Likely Very
Likely
Likely
Onset early,
retreat delayed




Global Monsoon Total
Precipitation (GMP)
Global Monsoon Area
(GMA)
Global Monsoon Intensity
(GMI = GMP/GMA)
Standard Dev of Interannual
Variability in Seasonal Avg
Precipitation (PsD)
Simple Daily Precipitation
Intensity (SDII) (GMP/# days
> 1 mm)
Seasonal Maximum 5-day
Precipitation Total (R5d)
Seasonal Maximum
Consecutive Dry Days (CDD)
Monsoon Season Duration
(DUR)
Fig. 14.1: Upper: GMA: GPCP Observed (black contour), CMIP5 History Sim (blue), RCP8.5 (orange)
Lower: (2080-2099) relative to (1986-2005) for the RCP scenarios
CMIP5 Simulated Anomalies
(relative to 1986-2005)




Lower-troposphere wind
convergence (dynamical
factor) decrease [d] with
increased moisture results
in increase moisture flux
convergence [c].
Surface evaporation
increase [b] with warmer
SSTs
GMP [a] increases due to
increase in [c] and [b]
despite a weakened
monsoon circulation
Source of uncertainty:
aerosol loading (direct
effect) as aerosol forcing
differs among models
Fig. 14.2 : Historical (Grey), RCP2.6 (Dark Blue), RCP4.5 (Light Blue), RCP6.0 (Orange), RCP8.5 (Red)
Regional Land Monsoon Domain
AsianAustralian
Monsoon
(AAM)
(incl. WNP)
Fig. 14.3: N. America Monsoon System (NAMS), N. Africa (NAF), S. Asia (SAS), E.
Asia (EAS), S. America Monsoon System (SAMS), S. Africa (SAF), AustralianMaritime Continent (AUSMC)



Model
agreement low
Fig. 14.4 (similar to fig. 14.2)
Present day
average in
average
precipitation (Pav)
Monsoon onset
date (ONS)
Monsoon retreat
date (RET)
Monsoon Circulation
(JJA, SLP difference)
(JJA, 850 hPa zonal wind avg)
(JJA, 850 hPa zonal wind avg)
(DJF, 850 hPa zonal wind avg)
Fig. 14.5: Summer Monsoon Indices (21 year running
mean) relative to (1986-2005)
Decrease
Unchanged
Limited by
ability to
capture
mesoscale
squall lies
Monsoon Systems: Executive Summary




There is growing evidence of improved skill of climate models in reproducing climatological features of the
global monsoon.
The global monsoon is likely to strengthen in the 21st c. with increases in its area and intensity, while the
monsoon circulation weakens. Monsoon onset dates are likely to become earlier or not change much and
monsoon retreat dates are likely to delay, resulting in lengthening of the monsoon season in many regions.
Future increase in precipitation extremes related to the monsoon is very likely in S. America, Africa, East
Asia, S. Asia, SE Asia, and Australia. Lesser model agreement results in medium confidence that the
monsoon-related interannual precipitation variability will increase in the future.
There is medium confidence that overall precipitation associated with the AAM will increase but with a N-S
asymmetry:






Indian and EAS monsoon precipitation is projected to increase
Australian summer monsoon precipitation changes are small
There is medium confidence that the Indian summer monsoon circulation will weaken, but yet has increased
precipitation due increased moisture convergence. For the summer EAS, both the monsoon circulation and
precipitation are projected to increase.
There is medium confidence that the increase of the Indian summer monsoon rainfall and its extremes
throughout the 21st c. will be the largest among all monsoons.
There is low confidence in projections of changes in precipitation amounts for the NAMS and SAMS, but
medium confidence that the NAMS will arrive and persist later in the annual cycle, and high confidence in
expansion of the SAMS area.
There is low confidence in projections of a small delay in the development of the W. African rainy season
and intensification of late-season rains. Model limitation in representing central features of the W. African
monsoon result in low confidence in future projections.
Tropical Phenomena




“Tropical convection over the oceans, averaged for a month or longer, is organized into long
and narrow convergence zones, often anchored by SST structures. Latent heat release in
convection drives atmospheric circulation and affects global climate.”
“…studies since AR4 show that such changes [i.e. changes to tropical convection] in a warmer
climate also depend on the spatial pattern of SST warming.”
“In CMIP3/5 model projections, annual rainfall change over tropical oceans follows a
‘warmer-get-wetter’ pattern, increasing where the SST warming exceeds the tropical mean
and vice versa.”
Greater warming in the Northern Hemisphere than the Southern Hemisphere
Fig. 14.8: Annual mean precipitation percentage change (grey-green shading)
and relative SST change to the tropical mean warming in RCP8.5.
Intertropical Convergence Zone (ITCZ)



Over the Atlantic and eastern
half of the Pacific, the ITCZ is
displaced north of the equator
due to ocean-atmosphere
interaction and extratropical
influences
Many models show an unrealistic
double-ITCZ pattern over the
tropical Pacific and Atlantic
In CMIP5, seasonal mean
rainfall is projected to increase
on the equatorward flank of the
ITCZ
Indian Ocean Modes





Indian Ocean Basin (IOB) mode
featuring a basin-wide structure
SST of the same sign
Indian Ocean Dipole (IOD) mode
with largest amplitude in SST in
the eastern Indian Ocean off
Indonesia, and weaker anomalies
of the opposite over the rest of
the basin
Both are correlated with ENSO
and model simulated well
Equatorial Indian Ocean include
easterly wind anomalies, a
shoaling thermocline, and reduced
SST warming in the east
IOD variability in SST remains
nearly unchanged in the future
projections despite the easterly
wind change that lifts the
thermocline
Fig 14.10: Sept. to Nov. changes in CMIP5 ensemble [(2081-2100) – 19862005)]. (a) SST (grey-green) and precipitation and (b) surface wind velocity
and sea surface height deviation from the global mean (contours)
Pre-Industrial
RCP8.5
Fig. 14.10: CMIP5 multi-model ensemble mean standard deviation of
interannual variability for Sept.-Nov.
Other Phenomena

South Pacific Convergence Zone (SPCZ)




South Atlantic Convergence Zone (SACZ)




Extends from the Amazon through southwest Brazil towards the Atlantic during austral summer
CMIP3/5 suggests southward displacement and intensification of the southern center of the
precipitation dipole (increase in precipitation in SE S. America, south of 25S)
Consistent with the southward displacement of the Atlantic subtropical high and southward expansion of
the Hadley Cell
Madden-Julian Oscillation (MJO)




Influences South Pacific Island nations, most pronounced during DJF
Often simulated lying east-west, missing the southeastward orientation and creating the ‘double ITCZ’
pattern
CMIP3/5 simulate much more frequent zonally oriented SPCZ events in the future due to reduction in
near-equatorial meridional SST gradient -> longer dry spells in the southwest Pacific
Possible changes in the MJO in future warmer climate only just beginning to be explored
Sensitive to the spatial pattern of SST
“In light of the low skill in simulating the MJO, and its sensitive to SST warming pattern, which in itself is
subject to large uncertainties, it is currently not possible to assess how the MJO will change in a warmer
climate.”
Atlantic Ocean Modes

“The biases severely limit model skill in simulating modes of Atlantic climate variability and in
projecting future climate change in the Atlantic sector. In depth analysis of the CMIP5 projections of
Atlantic Ocean Modes has not yet been fully explored…”
Tropical Systems: Executive Summary


Based on models’ ability to reproduce general features of the Indian Ocean Dipole
and agreement on future projections, the tropical Indian Ocean is likely to feature a
zonal pattern of change in the future with reduced warming and decreased
precipitation in the east, and increased warming and increased precipitation in the
west, directly influencing East Africa and Southeast Asia precipitation.
A newly identified robust feature in model simulations of tropical precipitation over
oceans gives medium confidence that annual precipitation change follows a
‘warmer-get-wetter’ pattern, increasing where warming of SST exceeds the tropical
mean and vice versa.





Medium confidence in projections showing an increase in seasonal mean precipitation on
the equatorial flank of the ITCZ affecting parts of Central America, the Caribbean, S.
America, Africa and W. Asia, despite shortcomings in many models simulating the ITCZ
Medium confidence that the frequency of zonally oriented SPCZ events will increase, with
SPCZ lying well to the NE of its average position, resulting in reduced precipitation over
many S. pacific island nations.
Medium confidence that the SACZ will shift southwards leading to an increase in
precipitation over SE S. America and reduction immediately north thereof
Low confidence in projections of future changes in the MJO owing to poor ability of models
simulation.
Low confidence in the projections of future changes for the tropical Atlantic, because of
systematic errors in model simulations of current climate. Future changes to Atlantic
hurricanes and tropical S. American and W. African precipitation are uncertain.
El Nino-Southern Oscillation (ENSO)
Fig. 14.13: Intensities for the last 60 years, Nino3 = E. Eq. Pac., Nino4 = Central Eq.
Pac.



Fig. 14.14: Standard Dev. In CMIP5 ensemble of SST
over the Nino3 region for pre-industrial (PI), 20th c.,
RCP4.5, RCP8.5.
Little consensus as to whether the decadal modulations of ENSO (amplitude and
spatial pattern) during recent decades are due to anthropogenic effects of natural
variability.
Because the change in tropical mean conditions in a warming climate is model
dependent, changes in ENSO intensity for the 21st century is uncertain.
There is little improvement in the CMIP5 ensemble relative to CMIP3 in the
amplitude and spatial correlation metrics of precipitation teleconnections in
response to ENSO, in particular within regions of strong observed precipitation
teleconnections.
ENSO: Executive Summary


The realism of the representation
of ENSO in climate models is
increasing and models simulate
ongoing ENSO variability in the
future. Therefore there is high
confidence that ENSO very likely
remains as the dominant mode of
interannual variability in the future
and due to increased moisture
availability on regional scales
likely intensifies.
Natural modulations of the
variance and spatial pattern of
ENSO are so large in models that
confidence in any specific
projected change in its variability
in the 21st century remains low.
Fig. 14.12: Warmer World: Trade winds weaken, the thermocline flattens and shoals, the
upwelling is reduced although the mean vertical temperature gradient is increased, and SSTs
(shown as anomalies w.r.t. the mean tropical–wide warming) increase more on the equator than
off. Absolute SST fields are on the left, SST anomalies on the right (blue colors indicate a
warming smaller than the basin mean, not a cooling)
Annular and Dipolar Modes



Models are generally able to
simulate gross features of annual
and dipolar modes
Model agreement in projections
indicates that future boreal
wintertime North Atlantic
Oscillation (NAO) is very likely to
exhibit large natural variations
and trend of similar magnitude to
that observed in the past and is
likely to become slightly more
positive on average, with some,
but not well documented,
implications for winter conditions in
the Arctic, N. America, and
Eurasia.
The austral summer/autumn
positive trend in Southern Annular
Mode (SAM) is likely to weaken Fig. 14.16: DJF mean SLP indices for historical and RCP4.5 scenarios. (top) Time
series of ensemble mean, (bottom) 2081-2100 vs 1986-2005 time means
considerably as stratospheric
ozone recovers through the mid21st c. with some, but not well
documented, implications for S.
America, Africa, Australia, New
Zealand, and Antarctica.
Large Scale Storm Systems


Tropical Cyclones:

It is likely that the global frequency of occurrences of TCs will either decrease or remain essentially unchanged,
concurrent with a likely increase in both global mean TC maximum wind speed and precipitation rates. The future
influence of climate change on TCs is likely to vary by region, but the specific characteristics of the changes are
not yet well quantified and there is low confidence in region-specific projections of frequency and intensity.

Medium confidence that precipitation will be more extreme near the centers of TCs making landfall in N. and
Central America, E. Africa, W., E., S. and SE. Asia as well as in Australia and many Pacific Islands

The frequency of the most intense storms will more likely than not increase substantially in some basins.
Extratropical Cyclones:

Despite systematic biases in simulating storm tracks, most models and studies are in agreement on the future
changes in the number of ETCs. The global number of ETCs is unlikely to decrease by more than a few percent. A
small poleward shift is likely in the S. Hemisphere storm track.

More likely than not, based on projections with medium confidence, that the N. Pacific storm track will shift
poleward.

Unlikely that the response of the N Atlantic storm track is a simple poleward shift.

There is low confidence in the magnitude of regional storm track changes, and the impact of such changes on
regional surface climate.

It is very likely that increases in Arctic, N. European, N. American and SH winter precipitation by the end of the
21st c. (2081-2100) will result from more precipitation in ETCs associated with enhanced extremes of stormrelated precipitation.
Future Regional Climate Change




External
forcings vary
regionally
Surface
conditions vary
spatially
Weather
systems and
ocean currents
redistribute
heat and
moisture from
one region to
another
See Annex 1
for more
specific
regional
figures
Arctic


Arctic climate is affected by
three modes of variability:
NAO, PDO, and AMO. ETCs
are mainly responsible for
winter precipitation in the
region.
It is likely Arctic surface
temperature changes will be
strongly influenced by
anthropogenic forcing over
the coming decades
dominating the natural
variability such as induced
by NAO. It is likely the panArctic region will experience
a significant increase in
precipitation by mid-century
due mostly to enhanced
precipitation in ETCs.
Fig. AI.10 & AI.11: Time series relative change to 1986-2005 for the RCP
scenarios
North America


Climate affected by
NAO, ENSO, PNA,
PDO, NAMS, TCs and
ETCs
It is very likely that by
mid-century the
anthropogenic warming
signal will be large
compared to natural
variability…in all NA
regions throughout the
year. It is likely that the
northern half of NA
will experience an
increase in
precipitation over the
21st c., due in large
part to precipitation
increase within ETCs.
Fig. 14.18: Precipitation changes from (2080-2099) compared to
(1986-2005)
Central America and Caribbean


Climate affected by
ITCZ, NAMS, ENSO,
and TCs
Owing to model
agreement on
projections and the
degree of consistency
with observed trends, it
is likely warm-season
precipitation will
decrease in the
Caribbean region,
over the coming
century. However, there
is only medium
confidence that Central
America will
experience a decrease
in precipitation.
Fig. 14.19: Precipitation changes from (2080-2099) compared to
(1986-2005)
South America



Climate affected by ENSO, Atlantic
Ocean modes, SAMS, SACZ, Atlantic ITCZ,
teleconnections such as the PSA, SAM,
ETCs, and IOD.
It is very likely temperatures will increase
over the whole continent, with greatest
warming projected in southern Amazonia.
It is likely there will be an increase
(reduction) in the frequency of warm
(cold) nights in most regions.
It is very likely precipitation will increase
in the southern sector of SE and NW SA,
and decrease in Central Chile and
extreme north of the continent. It is very
likely that less rainfall will occur in E
Amazonia, NE and E Brazil during the dry
season. However, in the rainy season there
is medium confidence in the precipitation
changes over these regions. There is high
confidence in an increase of precipitation
extremes.
Fig. 14.20: Precipitation changes from (2080-2099)
compared to (1986-2005)
Europe and Mediterranean



Climate affected by NAO, ETCs,
blocking, AMO, and others in
limited sectors of the region
There is high confidence in model
projections of mean temperature
in this region. It is very likely that
temperatures will continue to
increase through the 21st c. over
all of EUR and the MED region. It
is likely that winter mean
temperature will rise more in NEU
than in CEU or MED, whereas
summer warming will likely be
more intense in MED and CEU
than in NEU. The length,
frequency, and/or intensity of
warm spells or heat waves are
assessed to be very likely to
increase throughout the whole
region.
There is medium confidence in an
annual mean precipitation
increase in NEU and CEU, while a
decrease is likely in MED summer
mean precipitation.
Fig. 14.22: Precipitation changes from (2080-2099)
compared to (1986-2005)
Africa




4 sub-regions: Sahara (SAH), W. Africa
(WAF), E. Africa (EAF), S. Africa (SAF)
Climate affected by insolation (tropical
rainfall regions), monsoons, ENSO, Indian
and Atlantic SSTs (IOD, AMM, AMO),
Walker circulation, TCs, and ETCs
It is very likely that all of Africa will continue
to warm during the 21st c. The SAH, already
very dry, is likely to remain very dry. But
there is low confidence in projection
statements about drying or wetting of WAF.
Owing to models’ ability to capture the
overall monsoonal behavior, there is medium
confidence in projections of a small delay in
the rainy season with an increase at the end
of the season. There is medium confidence in
projections showing little change in mean
precipitation in EAF and reduced
precipitation in Austral winter in SAF, as
models tend to represent Indian Ocean SST
developments with credibility. Likewise,
increasing rainfall in EAF is likely for the
short rainy season, but low confidence exists
in projections regarding drying or wetting of
the long rainy season.
Fig. 14.23: Precipitation changes from (2080-2099)
compared to (1986-2005)
Asia
Fig. 14.24: Precipitation changes from (2080-2099) compared to (1986-2005)
West Asia
Fig. 14.26: Precipitation changes from (2080-2099) compared to (1986-2005)
Asia





Central and N. Asia: All the areas are projected to warm, stronger than global mean warming during
winter. For central Asia, warming magnitude is similar between winter and summer. Precipitation in N. Asia
will very likely increase, whereas the precipitation over central Asia is likely to increase. Extreme
precipitation events will likely increase in both regions.
E. Asia: There is medium confidence that with an intensified E. Asian summer monsoon, summer precipitation
over E. Asia will increase. Under RCP4.5 scenario, precipitation increase is likely over E. Asia during…May
to July, and precipitation extremes are very likely to increase over the E. Asian continent in all seasons and
over Japan in the summer. However, there is only low confidence in more specific details of the projected
changes due to the limited skill of CMIP5 models in simulation monsoon features.
W. Asia: Since AR4 climate models appear to have only modestly improved fidelity in simulating aspects
of large-scale climate phenomena influencing regional climates over W. Asia. Model agreement, however,
indicates that it is very likely that temperatures will continue to increase. But at the same time, model
agreement on projected precipitation changes have reduced, resulting in medium confidence in projections
showing an overall reduction in precipitation.
S. Asia: There is high confidence in projected rise in temperature. There is medium confidence in summer
monsoon precipitation increase in the future over S. Asia. Model projections diverge on smaller regional
scales.
SE Asia: Warming is very likely to continue with substantial sub-regional variations. There is medium
confidence in a moderate increase in rainfall, except on Indonesian islands neighboring the SE Indian
Ocean. Strong regional variations are expected because of the terrain.
Australia and New Zealand



Climate affected by monsoon
circulation, ENSO, SAM, mid-latitude
storm track and transient wave
propagation
It is likely that cool season precipitation
will decrease over S. AUS associated in
part with trends in the SAM, the IOD,
and a poleward shift and expansion of
the subtropical dry zones. It is very likely
that AUS will continue to warm through
the 21st c., at a rate similar to the
global land surface mean. The
frequency of very warm days is very
likely to increase through this century,
across the whole country.
It is very likely that temperatures will
continue to rise over NZ. Precipitation is
likely to increase in W. regions in winter
and spring, but the magnitude of the
change is likely to remain comparable
to that of natural climate variability
through the rest of the century. In
summer and autumn, it is as likely as not
that precipitation amounts will change.
Fig. 14.27: Precipitation changes from (20802099) compared to (1986-2005)
Antarctica


Consistency across CMIP5
projections suggests it is very
likely that Antarctic temperatures
will increase through the rest of
the century, but more slowly than
the global mean rate of
increase. SSTs of the oceans
around Antarctica are likely to
rise more slowly than surface air
temperature over the Antarctic
land mass.
As temperatures rise, it is also
likely that precipitation will
increase, up to 20% or more
over E. Antarctic. However, given
known difficulties associated with
correctly modeling Antarctic
climate, and uncertainties
associated with future SAM and
ENSO trends and the extent of
Antarctic sea ice, precipitation
projections have only medium
confidence.
Fig. AI.77, AI.76, AI.78:
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