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Observations of climate change
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Kevin E Trenberth
NCAR
Global Warming is unequivocal
Since 1970, rise in:
 Global surface temperatures
 Tropospheric temperatures
 Global SSTs, ocean Ts
 Global sea level
 Water vapor
 Rainfall intensity
 Precipitation extratropics
 Hurricane intensity
 Drought
 Extreme high temperatures
 Heat waves
Decrease in:
NH Snow extent
Arctic sea ice
Glaciers
Cold temperatures
IPCC 2007
The climate is changing.
We can and should take mitigating actions
that will slow and eventually stop climate
change.
Meanwhile we must adapt to climate change.
But adapt to what?
We do not have predictions.
We do not have adequate reliable
observations.
We do not have the needed
information system!
Global mean temperatures are rising faster with time
Warmest 12 years:
1998,2005,2003,2002,2004,2006,
2001,1997,1995,1999,1990,2000
Period
25
50
100
150
Rate
0.1770.052
0.1280.026
0.0740.018
0.0450.012
Years /decade
IPCC 2007
Heat waves are increasing: an example
Extreme Heat Wave
Summer 2003
Europe
30,000 deaths
Trend plus variability?
IPCC 2007
Surface
Temperature
1901-2005
It has not warmed uniformly:
More warming over land
Why no warming over SE USA?
Or N Atlantic
IPCC 2007
Drought is increasing most places
The most
Mainly decrease
in rain
over landimportant
in tropicsspatial
and
pattern
(top) of
subtropics,
but enhanced
theatmospheric
monthly
by increased
Drought
demand Palmer
with warming
Severity Index
(PDSI) for 1900
to 2002.
The time series
(below) accounts
for most of the
trend in PDSI.
IPCC 2007
Extremes of
temperature
are changing!
Observed
trends (days)
per decade
for 1951 to
2003:
5th or 95th
percentiles
From Alexander et
al. (2006)
IPCC 2007
Increases in rainfall and cloud counter warming
Drought
Trend in Warm Days 1951-2003
Absence of
warming by day
coincides with
wetter and
cloudier
conditions
IPCC 2007
Regional climate change
Hypothesis: It is impossible to address regional
climate change without fully addressing how patterns
of climate variability (modes) change, and thus how:
ENSO: El Niño Southern Oscillation
NAO/NAM: North Atlantic Oscillation/Northern Annular Mode
SAM: Southern Annular Mode
PDO: Pacific Decadal Oscillation
AMO: Atlantic Multidecadal Oscillation
change!
El Niño - Southern Oscillation
Cooler
SLP
Surface temperature
Wetter
IPCC 2007
Precipitation
Pacific Decadal Oscillation
SST pattern (above) and time
series (lower right) of 1st EOF
of N Pacific SSTs.
NPI index of Aleutian Low
Indian Ocean SST (tropics)
1976/77 climate shift
IPCC 2007
Many observed climate
anomalies can be simulated in
models with specified SSTs
• Sahel drought: Hurrell et al 2004, Giannini et al 2003, Hoerling,
• US Dust Bowl: Schubert et al. 2004, Seager et al. 2005
• Drought (US, Europe, Asia): Hoerling and Kumar 2003
But we can not (yet) simulate the observed
SSTs.
Global increases in SST
are not uniform. Why?
 Coupling with atmosphere
 Tropical Indian Ocean has
warmed to be competitive as
warmest part of global ocean.
 Tropical Pacific gets relief owing
to ENSO?
 Deeper mixing in Atlantic, THC.
This pattern is NOT well simulated
by coupled models!
Relates to ocean uptake of heat,
heat content & transport.
IPCC 2007
IPCC experience on observations
Sorting out the climate signal from
the noise in inadequate observations
from a changing observing system is
an ongoing continual challenge
Space-based observations are a
particular challenge
Temperatures
Issues:
1. Missing data and treatment
2. Quality control
3. Max and Min T much more
sensitive to inhomogeneities
4. Urban heat island
5. Need to continue to pressure
countries to provide high
frequency data (hourly and daily)
IPCC 2007
Annual anomalies of
maximum and minimum
temperatures and
diurnal temperature
range (DTR) (°C)
averaged for the 71%
of global land areas
for 1950 to 2004.
DTR 1979-2004
Precipitation: not a continuous variable
IPCC 2007
Large differences in amounts. Inability to analyze
characteristics: intensity, frequency, duration,
type, as well as amount. Need hourly data!
Tropical rainfall 30N-30S
Land
Total
Issues:
Need much more complete and
better data on all hydrological
variables set in a holistic
framework:
Precipitation: hourly (intensity,
Ocean
frequency,
duration, type,
amount); streamflow, runoff,
Land: systematic offset 3%
evaporation, drought indices,
Ocean: no relationship
soil moisture (incl ice), snow
Total: dominated by ocean
cover depth…
North Atlantic hurricanes have increased with SSTs
N. Atlantic
hurricane
record best
after 1944
Marked
increase
with aircraft
after
1994
surveillance.
(1944-2005)
SST
Global number
and
percentage of
intense
hurricanes
is increasing
Some issues:
Partial reprocessing of ISCCP data has
occurred for tropical storms (Kossin)
Records are far from homogeneous, even
for satellite era
Records/practices are not comparable in
different regions, even now.
We desperately need an internationally
coordinated reprocessing of all satellite
data for hurricanes, to get many
parameters of interest, such as size,
intensity, rainfall, integrated variables
(0-100 km; 0-400 km) etc.
Ivan 2004
Main Issues
• The in situ data are not global and have problems
• Satellites drift in orbit and instruments degrade:
the data generally do not provide a climate
record. They could.
• The satellite record is in jeopardy, especially
from demanifesting several climate instruments
from NPOESS.
• A baseline transfer standard is essential: in situ
super sites (reference radiosonde plus network).
• Regional climate requires attention to modes of
variability and model initialization
Why do we need an integrated
Earth System Analysis?
• We have a lot of observations: from satellites
and other remote sensing.
• The volumes are huge
• We use but a small fraction
• Most are not climate quality
• Inconsistencies exist across variables
• They do not make a climate observing system
• Reprocessing and reanalysis must be part of
system
Goal: Climate Data Records
1. There is a need to better come to grips with the
continually changing observing system.
2. There is no baseline network to anchor the analyses or
space observations.
The radiosonde network is not it!
3. The challenge is to improve continuity and be able to
relate a current set of observations to those taken 20
years ago (or in the future).
4. There is a need for more attention to data synthesis,
reprocessing, analysis and re-analysis of existing data
sets; and
5. There must be a baseline set of measurements:
 Sparse network (30-40) of “reference sondes” for
satellite calibration and climate monitoring, UT water
vapor; co-located with regular sonde sites to replace
them at appropriate times; integrated with ozone sondes
and/or GAW and BSRN = GRUAN?
 GPS Radio Occultation.
The challenge is to better determine:
1)
2)
3)
4)
5)

how the climate system is changing

how the forcings are changing
how these relate to each other (incl. feedbacks) 

attribution of anomalies to causes
what they mean for the immediate and more distant

future (assessment)

6) Validate and improve models
7) seamless predictions on multiple time scales

8) how to use this information for informed planning 
and decision making
9) how to manage the data and reanalyze it routinely 
10) how to disseminate products around the world

11) how to interact with users and stakeholders and add
regional value

From Trenberth et al 2002