Specifications

TEAM Climate Monitoring Protocol 3.1
5
1 I
I
N
N
T
T
R
R
O
O
D
D
U
U
C
C
T
T
I
I
O
O
N
N
A
A
N
N
D
D
S
S
C
C
O
O
P
P
E
E
Climate change has been identified as one of the main threats to humanity and to the long-term
persistence of the living world in general (IPCC 2007, Wright 2005, Malhi et al. 2008, Rockström et
al. 2009). Only 15 out of 50,000 long-term time series of biological and bioclimatic variables come
out of tropical areas (less than 0.03%) (IPCC 2007). The lack of a long-term, continuous, reliable
climate data stream coming from tropical areas (Clark and Clark 1994; Root and Schneider 1995;
IPCC 2007; Enquist 2002) is compounded by the fact that most surface climate measurements are
collected in populated areas (e.g. airports, cities, towns), which experience local climates that may not
be representative of natural forested areas (Malhi and Wright 2004). Additionally, many of these
measurements although useful for meteorological services (e.g. local weather forecasts), are not
adequate to estimate long-term trends in climatic variables over long periods of time, because of a
lack of consistency between most surface weather stations in instrumentation, sensor calibration
protocols and data quality control (among others).
The expected effects of climate change on tropical forest ecosystems are still unknown. For example,
Phillips et al. (1998) describe how forests could be carbon sinks, increasing forest biomass
accumulation as CO
2
levels increase. However, during unusually dry spells, which are more frequent
due to climate change, increased temperature could cause tropical forests to become sources of CO
2
,
thus further aggravating the problem (Clark 2002, Kenneth et al. 2007, Phillips et al. 2009).
A global network collecting continuous and reliable climate data throughout tropical forests is badly
needed. The foundation of this network should be the application of a single consistent climate
protocol for setup, instrumentation, data collection, calibration, maintenance, and data quality control.
Since changes in climate are so gradual and small (e.g. increase in temperature ~ 0.6 ºC in the last
two decades), it is imperative to remove the confounding effects differences in methods produce in
order to measure climate across sites and to detect these changes with an adequate level of precision.
The World Meteorological Organization and the National Research Council at the National Academy
of Sciences (NRC 1999, WMO 2003) propose a minimum set of guidelines for climate observing
networks to ensure adequate scientific rigor and maximize the use of data and its applications
(summarized):
1
1
.
.
M
M
a
a
n
n
a
a
g
g
e
e
m
m
e
e
n
n
t
t
o
o
f
f
N
N
e
e
t
t
w
w
o
o
r
r
k
k
C
C
h
h
a
a
n
n
g
g
e
e
:
:
Assess the effects of change in the observing network
on current and future climatological observations, particularly with respect to climate change
and variability.
2
2
.
.
P
P
a
a
r
r
a
a
l
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l
l
e
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l
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T
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e
s
s
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g
g
: Simultaneous operation of old systems with new systems over a sufficiently
long period that captures the full range of variation in the data.
3. M
M
e
e
t
t
a
a
d
d
a
a
t
t
a
a
: Full documentation of climate observing systems and procedures. This includes,
among others, instrumentation, instrument sampling time, calibration, validation, climate
station location, local environmental conditions, and detailed algorithm descriptions.
4. D
D
a
a
t
t
a
a
Q
Q
u
u
a
a
l
l
i
i
t
t
y
y
a
a
n
n
d
d
C
C
o
o
n
n
t
t
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n
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u
u
i
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y
y
: Assessment of data quality and continuity as part of the
routine data collection process.
5. I
I
n
n
t
t
e
e
g
g
r
r
a
a
t
t
e
e
d
d
E
E
n
n
v
v
i
i
r
r
o
o
n
n
m
m
e
e
n
n
t
t
a
a
l
l
A
A
s
s
s
s
e
e
s
s
s
s
m
m
e
e
n
n
t
t
: Anticipate the use of the data in the development
of environmental assessments such as climate change and its effects on other systems.
6
6
.
.
H
H
i
i
s
s
t
t
o
o
r
r
i
i
c
c
a
a
l
l
S
S
i
i
g
g
n
n
i
i
f
f
i
i
c
c
a
a
n
n
c
c
e
e
:
:
Strive to maintain climate observing systems that have been
operating for long time frames (decades, century) and maintain high quality data.