Highlights:
- The tropical lower stratosphere water vapour (SWV) experiences a
drying process during 1984-2020 in both linear and nonlinear
perspectives.
- The Indo-Pacific warm pool (IPWP) is the main factor in such drying of
the tropical stratosphere.
- IPWP leads the coldest point region cooler modulating tropical SWV
entry by enhancing equatorial waves.
ABSTRACT
A decreasing trend in the tropical (30°S~30°N)
stratospheric water vapour (SWV) entry in recent four decades (from 1984
to 2020) is detected based on the Stratospheric Water and OzOne
Satellite Homogenized (SWOOSH) measurements and the ERA5 reanalysis
dataset using linear regression and Ensemble Empirical Mode
Decomposition (EEMD) analysis. With the concurrent warming of the SST,
the Indo-Pacific warm pool (IPWP)
appears to be the most significant region among the tropical oceans
based on correlation analysis. More than 43% of the decreasing tropical
lower SWV trend is likely to be related to the IPWP sea surface
temperature (SST) warming. To validate this relationship, two groups of
idealized runs are carried out with version 4 of the Whole Atmosphere
Community Climate Model (WACCM4) and version 5 of the Community
Atmosphere Model (CAM5). Both simulations agree with the
observational-based linkage. The IPWP-SST-warming forced simulations
show that the temperature in the tropical tropopause has decreased at
the rate of around 0.318 K per decade in the coldest point region, as
the tropical convection over the IPWP has become more vigorous and
excited stronger equatorial waves
to produce adiabatic cooling around tropopause. This cooling tropical
tropopause leads to a dehydrating tropical lower stratosphere at the
rate of 0.025 ppmv per decade, as expected by the freeze-drying
mechanism. These results imply the substantial warming trend of IPWP is
an important factor for the long-term trend of the tropical SWV entry
under climate change, and a better representation of this relationship
in the model is critical for the SWV projection under future climate
scenarios.
Keywords: Stratospheric water vapour; Indo-Pacific warm pool;
Trend; Tropopause; Coldest point region
Introduction
The stratospheric water vapour (SWV) mainly originates from the
troposphere: the moist air parcels at the bottom of the troposphere
ascend, reaching the tropical tropopause layer (TTL) between 14–18.5
km, experiencing a severe dehydration process at the TTL (because the
TTL has the coldest temperature in the lower atmosphere) (Gettelman and
Forster 2002; Fueglistaler et al. 2009), then arriving in the
stratosphere. The SWV is suggested to contribute significantly to global
climate change by altering the infrared opacity of the atmosphere (e.g.,
Soden and Held 2006), providing a strong positive feedback at +0.3
W/(m2·K) to global warming (Dessler et al. 2013). When
the SWV increases, it subsequently leads to warming in the troposphere
and cooling in the stratosphere, and the warmer troposphere will, in
turn, increase the SWV (Rind and Lonergan 1995; de F. Forster and Shine
1999; Solomon et al. 2010; Dessler et al. 2013; Fu et al. 2015), and by
this positive feedback, the increase of the SWV will accelerate the rate
of increase in global surface temperature and vice versa. Meanwhile, the
SWV participates in stratospheric chemical processes as the primary
source of stratospheric hydrogen oxide radicals. For example, it
strongly affects heterogeneous chemistry on cold sulfate aerosol and the
formation of polar stratospheric clouds, which promote chlorine
activation and polar ozone loss (Evans et al. 1998; Shindell 2001;
Stenke and Grewe 2005; Tian et al. 2009). So, it is critical to
understand the decadal and long-term SWV variability and the relevant
physical processes.
Previous studies have already documented that the TTL temperature is
very important for SWV variability.
Because the TTL is the main area
where air enters the stratosphere, changes in SWV are largely related to
the tropical SWV entry and the TTL temperature largely determines the
SWV entry values (Brewer 1949; Randel et al. 1998; Scaife et al. 2003;
Fueglistaler et al. 2005; Rosenlof and Reid 2008; Schoeberl and Dessler
2011; Grise and Thompson 2012; Dessler et al. 2013). Therefore, the
multi-timescale variations of the SWV ranging from daily to decadal
timescales (e.g., Randel et al. 2004; Fueglistaler and Haynes 2005;
Fujiwara et al. 2010; Hegglin et al. 2014) can be traced to TTL
temperature variations (e.g., Randel et al. 2007; Rosenlof and Reid
2008; Randel 2010; Fueglistaler et al. 2013; Randel and Jensen 2013). As
a layer between the stratosphere and troposphere at about 14–18.5 km
(Fueglistaler et al. 2009), the TTL temperature is affected by both the
stratospheric (top-down) and tropospheric (bottom-up) processes,
including variability of the Brewer-Dobson circulation (BDC, a
stratospheric mean meridional circulation), the quasi-biennial
oscillation (QBO), and tropical convection (bottom-up). Because the TTL
temperature and SWV entry values are generally the results of the
interplay between the top-down and bottom-up processes, the SWV’s
interpretation (e.g., Hegglin et al. 2014) and prediction (e.g.,
Gettelman et al. 2010) are complex. In the tropical troposphere,
anomalous deep convection induces upward motion near the tropopause and
thereby results in a cooling of the TTL (Highwood and Hoskins 1998). And
deep convection is usually associated with the El Nino Southern
Oscillation (ENSO), Asian Monsoon, and Madden-Julian Oscillation exert
tropical planetary waves including the equatorial Rossby wave and Kelvin
wave. In the stratosphere, the acceleration of the BDC causes the
adiabatic cooling of the TTL through the enhanced large-scale vertical
ascending motions, and vice versa (Holton et al. 1995; Thompson and
Solomon 2005). Fu et al. (2010) also documented that the strength of the
BDC is a main factor driving the seasonal variability of the TTL
temperature. In short, the TTL temperature variability is driven by both
the tropospheric (bottom-up) processes and the stratospheric (top-down)
(Kumar et al. 2014).
By using balloon-borne water vapour profiles above Washington DC and
Boulder, Oltmans et al. (2000) observed an increase of lower SWV by
about 1% per year during the 1960s and 1990s. This agrees with the
Third Assessment Report of the IPCC, which reported water vapour in the
lower stratosphere is likely to have increased by about 10% per decade
since the beginning of the observational record. Dessler et al. (2013)
showed observational evidence for stratospheric water vapour
feedback—a warmer climate increases stratospheric water vapour, and
because stratospheric water vapour is itself a greenhouse gas, this
leads to further warming. Lin et al. (2017) found that the tropical
tropopause layer will become warmer in response to carbon dioxide
increase and surface warming. A few numerical studies reported that a
moist stratosphere occurs under global warming scenario by using the
forcing of quadrupling CO2 in different general circulation models
(Zhang and Huang 2014; Banerjee et al. 2019; Li and Newman 2020; Wang
and Huang 2020; Xia et al. 2021b). Keeble et al. (2021) suggested that
CMIP6 multi-model mean SWV mixing ratios in the tropical lower
stratosphere have increased by ∼0.5 ppmv from the pre-industrial to the
present-day period and are projected to increase further by the end of
the 21st century. Keeble et al. (2021) further pointed out that the
largest SWV increases (∼2 ppmv) are simulated under the future scenarios
with the highest assumed forcing pathway (e.g., SSP5-8.5).
However, the increasing trend of the SWV seems stopped or becomes
blurred after the 1990s. Although the SWV above Boulder is reported to
increase during the periods of 1992 to 2002 in the balloon water vapour
data (Randel et al. 2004). This increasing trend is not reproduced well
by satellite data. Randel et al. (2004) also documented that the SWV
near Boulder, Colorado (40°N) and the tropical mean (60°S-60°N) SWV have
no significant trend in 1992-2002 based on the HALOE data. Besides, the
Fifth Assessment Report of the IPCC (IPCC5, 2014) documented that the
near-global satellite measurements of SWV show substantial variability
but small net changes for 1992-2011, i.e., the satellite data show no
clear trends for the SWV. Randel et al. (2006) even reported that the
near-global SWV after 2001 decreased (or had persistent low values
beginning in 2001), and this near-global SWV decrease is attributed to
the enhanced tropical upwelling after 2001. Hurst et al. (2011) analyzed
the balloon-borne SWV over Boulder, Colorado, then reported the
multi-decadal variability of the SWV: the SWV increased by an average of
1.0 ± 0.2 ppmv (27 ± 6%) during 1980-2010, but in 2001-2005, it has an
opposite trend to other periods. Recently, another strong drop is
reported in the tropical SWV (10°S-10°N, similar to the SWV drop
observed in the year ~2000) was observed in 2011-2012
(Urban et al. 2014). Hegglin et al. (2014) using observation data
revised by transfer function found a negative trend in the lower and
mid-stratosphere. Dessler et al. (2014) revealed that water vapour
entering the stratosphere has no firm evidence of trend.
Konopka et al. (2022) suggested
that the stratosphere has become wetter after 2000. Tao et al. (2023)
found that SWV has a robust multi-decadal variation and short-term
trends in SWV are closely related to this multi-decadal variation. These
imply that there are great uncertainties in the trends of SWV and the
trends are sensitive to the period focused on.
Many studies have suggested that tropical oceans have a crucial effect
on the stratosphere (e.g., Hu et al. 2014; Hu and Guan 2018; Xie et al.
2020b; Xie et al. 2020a; Xia et al. 2021a). As an important component of
the stratosphere, the SWV is no exception. Scaife et al. (2003) have
pointed out that a positive trend in water vapour of around 0.1% per
year and ENSO effects appear to explain no more than about one-tenth of
the long-term trend by using model and observational data. Tropical SST
variability, especially ENSO, has been known to be an important factor
in determining the amount of water vapour being uplifted to the upper
tropospheric region and the lower stratosphere by altering tropical
convection (Su et al. 2006; Rosenlof and Reid 2008; Liang et al. 2011;
Xie et al. 2012; Garfinkel et al. 2013a; Garfinkel et al. 2013b; Avery
et al. 2017; Su et al. 2020). The tropical SST has been suggested to
contribute to the drop of the lower stratospheric water vapour during
2000 (Brinkop et al. 2016; Ding and Fu 2018).
The Indo-Pacific Warm Pool (IPWP)
has been also documented as a vital region that affects the stratosphere
and tropical lower SWV (Xie et al. 2014; Xie et al. 2018; Zhou et al.
2018). The warm phase of IPWP causes a drier lower stratosphere and vice
versa. Zhou et al. (2021) further pointed out that such impact has
seasonality and hemispheric differences. Almost the entire tropical
ocean shows a warming long-term trend in SST over the last century
(Deser et al. 2010). The tropical western Pacific is warm faster than
the eastern Pacific in observations (Cane et al. 1997; Kanamitsu et al.
2002; Compo and Sardeshmukh 2010; Zhang et al. 2010; Li et al. 2017).
There is widespread warming across the tropical Indian Ocean basin and
SSTs have reached 28°C in the western Indian Ocean, which has expanded
the Indo-Pacific warm pool region defined by the 28°C isotherm westward
(Roxy et al. 2015). It is quite possible that the zonally asymmetric
warming trend of tropical oceans will further influence the SWV entry
and provide the principal source for its decadal trend. Previous studies
have shown the impact of IPWP on interannual variability of tropical
lower SWV and discussed its seasonal and hemispheric differences.
However, the impact of IPWP on tropical SWV entry over longer time
periods is unclear, especially when the IPWP is substantially warming in
the past forty years. Therefore, in this study, we seek to understand
the impact of IPWP continuous warming on tropical SWV entry in recent
decades.
In short, the decadal or long-term changes of the tropical SWV during
the past decades seem not to strictly follow the presumed long-term
increasing trend under global warming. So, we try to revisit and
interpret the decadal or long-term change of the SWV with longer
observations for the period 1984-2020 and explore the potential impact
of IPWP warming on it. The remainder of the paper is arranged as
follows. The data, model, and methods we used are presented in Section
2. In section 3, we revisit the long-term trend of SWV for the period
1984-2020, then focus on its link with the warming of IPWP. Section 4 is
a summary of the principal findings.
Data, model and methods
Water vapor data
Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) is a merged
data set that ranges from 1984 to the present containing multiple
satellite data and it not only offers values of SWV but also provides
some ancillary information like standard deviation, number of data
points and others (Davis et al. 2016). In addition, it also supplies a
combined product which is a weighted mean value from the available
satellite measurements mentioned above and it has a fabulous advantage
that when one satellite measurement is missing, others will be filled in
by using different algorithms. SWOOSH has been used in some studies
(Hardiman et al. 2015; Gilford et al. 2016). Our study used this
combined product with 31 pressure levels from 316 to 1 hPa and the
version of SWOOSH is v2.7.
In addition to SWOOSH, water vapour of ERA5 was also analyzed for
comparison. ERA5 which covers the period from 1979 to the present, is
the latest global atmospheric reanalysis product obtained from European
Centre for Medium-Range Weather Forecasts (ECMWF). Based on the 4D-Var
data assimilation scheme and Integrated Forecast System (IFS) CY41R2, it
covers the earth with a 30 km horizontal grid and 137 hybrid
sigma/pressure levels from the surface to 0.01 hPa (Hersbach et al.
2020). And the resolution we used is 0.25° × 0.25° in the horizontal and
37 levels from 1000 hPa to 1 hPa in the vertical. Because ERA5 has a
cold bias in the lower stratosphere during 2000 and 2006, ERA5.1 is
applied in this special time.
Meteorological data
Besides ERA5, the major meteorological data we also used is Japanese
55-year Reanalysis (JRA-55). JRA-55 is conducted by Japan Meteorological
Agency (JMA) and JRA5 is a comprehensive climate dataset with the
applicant of 4D-Var. It covers the period from 1958, coinciding with the
establishment of the global radiosonde observing system. The resolution
we used is 1.25° × 1.25° in the horizontal and 37 levels from 1000 hPa
to 1 hPa in the vertical.
Another relevant meteorological data is sea surface temperature, and
Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) data set was
applied in our study. It is mainly from Met Office Marine Data Bank
(MDB), and it also covers data from Global Telecommunications System
(GTS) since 1982. To enhance the coverage of data, when data from MDB is
missing, the monthly median SSTs for 1871-1995 from the Comprehensive
Ocean-Atmosphere Data Set (COADS) (now ICOADS) are included (Rayner et
al. 2003). And its resolution is 1° × 1°.
Model
The Community Earth System Model version 1 (CESM1), developed by
National Center for Atmosphere Research (NCAR), can simulate the state
of climate from the past to the future. It consists of several
relatively independent component models, including atmosphere, ocean,
land, land ice, sea ice, and so on, and all of them have their own
spatial resolutions. Besides, CESM1 has a central coupler that can
exchange energy and information between different component models
(Hurrell et al. 2013). In our study, we used version 5 of the Community
Atmosphere Model (CAM5) to design experiments, which is one of the vital
component models of CESM1, to simulate global atmosphere activity. CAM5
can not only run as one of the component models of CESM1 but also run as
an independent model. It applies 30 vertical levels from the ground to
3.64 hPa. Version 4 of the Whole Atmosphere Community Climate Model
(WACCM4), a comprehensive numerical model based on CAM, was also used in
the experiment design. It can extend from the surface to the
thermosphere, namely, from the surface to 5.1× 10-6 hPa (about 140
kilometers) with 66 vertical levels. In our study, the finite-volume
dynamical core was applied in both CAM5 and WACCM4. We used the 1.9° ×
2.5° medium resolution version which includes 96 longitude and 144
latitude points.
CAM5 and WACCM4 are employed to investigate how and to what extent SWV
entry changes in response to IPWP warming. WACCM4 can capture the
negative relationship between the IPWP SST anomalies and the tropical
SWV entry (Xie et al. 2018; Zhou et al. 2018). Two groups of experiments
are carried out, which involve a control group forced by observed SST
from 1955 to 2005 (E0, E1) and another forced by the observed SST in the
IPWP region only (E2, E3). Details of transient experiments can be
referred to in Table 1. Due to the limitation of WACCM4, E0 and E2 run
only from 1955 to 2005. So, although CAM5 in E1 and E3 run from 1900 to
2005, we use the same period as WACCM4 in E0 and E2. We evaluate the two
modes using control runs (E0, E1) by comparing them with the
observational data and reanalysis data. Both can represent the
structures in SWV and tropical tropopause temperature, with the pattern
correlations exceeding 0.7 between observed and simulated climatology
(Fig. S1 and Fig. S2).