ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus PublicationsGöttingen, Germany10.5194/acp-17-13559-2017Aerosol trends as a potential driver of regional climate in the central
United States: evidence from observationsCusworthDaniel H.dcusworth@fas.harvard.eduhttps://orcid.org/0000-0003-0158-977XMickleyLoretta J.LeibenspergerEric M.https://orcid.org/0000-0002-1906-2688IaconoMichael J.Department of Earth and Planetary Sciences, Harvard University,
Cambridge, 02138, USASchool of Engineering and Applied Sciences, Harvard University,
Cambridge, 02138, USACenter for Earth and Environmental Science, State University of New
York at Plattsburgh, Plattsburgh, 12901, USAAtmospheric and Environmental Research, Lexington, 02421, USADaniel H. Cusworth (dcusworth@fas.harvard.edu)15November2017172213559135727March201729March20176October201710October2017This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/This article is available from https://acp.copernicus.org/articles/17/13559/2017/acp-17-13559-2017.htmlThe full text article is available as a PDF file from https://acp.copernicus.org/articles/17/13559/2017/acp-17-13559-2017.pdf
In situ surface observations show that downward surface solar radiation
(SWdn) over the central and southeastern United States (US) has increased
by 0.58–1.0 Wm-2 a-1 over the 2000–2014 time frame, simultaneously
with reductions in US aerosol optical depth (AOD) of
3.3–5.0 × 10-3 a-1. Establishing a link between these two trends,
however, is challenging due to complex interactions between aerosols, clouds,
and radiation. Here we investigate the clear-sky aerosol–radiation effects
of decreasing US aerosols on SWdn and other surface variables by applying a
one-dimensional radiative transfer to 2000–2014 measurements of AOD at two
Surface Radiation Budget Network (SURFRAD) sites in the central and
southeastern United States. Observations characterized as “clear-sky” may
in fact include the effects of thin cirrus clouds, and we consider these
effects by imposing satellite data from the Clouds and Earth's Radiant Energy
System (CERES) into the radiative transfer model. The model predicts that
2000–2014 trends in aerosols may have driven clear-sky SWdn trends of +1.35 Wm-2 a-1 at Goodwin Creek, MS, and +0.93 Wm-2 a-1 at
Bondville, IL. While these results are consistent in sign with observed
trends, a cross-validated multivariate regression analysis shows that AOD
reproduces 20–26 % of the seasonal (June–September, JJAS) variability in
clear-sky direct and diffuse SWdn at Bondville, IL, but none of the JJAS
variability at Goodwin Creek, MS. Using in situ soil and surface
flux measurements from the Ameriflux network and Illinois Climate Network
(ICN) together with assimilated meteorology from the North American Land Data
Assimilation System (NLDAS), we find that sunnier summers tend to coincide
with increased surface air temperature and soil moisture deficits in the
central US. The 1990–2015 trends in the NLDAS SWdn over the central US
are also of a similar magnitude to our modeled 2000–2014 clear-sky trends.
Taken together, these results suggest that climate and regional hydrology in
the central US are sensitive to the recent reductions in aerosol
concentrations. Our work has implications for severely polluted regions
outside the US, where improvements in air quality due to reductions in the
aerosol burden could inadvertently pose an enhanced climate risk.
Introduction
From 1930 to 2004, the eastern and central US experienced significant
cooling of as much as -0.12 K a-1 (Kumar et al., 2013). This phenomenon
is known as the “warming hole,” as the temperature trend differs in sign
from expected greenhouse gas warming (Pan et al., 2004). More recent
observations from this region show average annual temperatures increased by
0.6–0.8 K between 1901–1960 and 1991–2012, signaling a reversal of the
warming hole trend (Melillo et al., 2014). The causes of the warming hole
and its subsequent reversal are uncertain. Previous studies have linked the
US warming hole to changing patterns in sea surface temperatures (SSTs)
such as the Atlantic Multidecadal Oscillation (AMO; Kumar et al., 2013;
Zhang et al., 2013) or to trends in anthropogenic aerosols, which may
influence meteorology by interacting with solar radiation or clouds
(Leibensperger et al., 2012b; Booth et al., 2012; Yu et al., 2014). Banerjee
et al. (2017) concluded that while aerosols may have contributed to the
warming hole, much of the observed cooling arose from unforced internal
variability. Most of these studies relied on global or regional climate
models, which are inherently uncertain. In this study, we use recent
observations and simple models to better constrain the influence of
aerosol–radiation interactions on US regional meteorology. In response to
tightening air quality regulations, emissions of aerosol sources are
expected to decline worldwide over the 21st century (Westervelt et al.,
2015), and so our results could have significance for regional climate
elsewhere.
Some previous model studies have linked the emergence of a warming hole with
changes in SST patterns or large-scale circulation. Pan et al. (2004) found
that enhanced greenhouse gases produced a circulation response that
increased the frequency of the southerly low-level jet over the southern
Great Plains in late summer, which in turn replenished soil moisture and
suppressed temperature extremes. They concluded this mechanism could induce
a warming hole. Using a climate model forced with observed SSTs, Meehl et al. (2012) linked the warming hole cooling trend to the Interdecadal Pacific
Oscillation (IPO). Kumar et al. (2013) found that among 22 climate models,
those that had the best representation of the AMO also best reproduced the
warming hole, although even these models show large discrepancies with the
observed trend.
Alternative explanations for the warming hole involve the influence of
aerosol trends on regional meteorology, which may include the impact of
changing aerosols on SSTs. Over much of the United States, anthropogenic
aerosols are dominated by light-colored, highly reflective species such as
sulfate. Such aerosols have adverse health effects, and since the 1970s the
US EPA has worked to reduce their sources. Between 1990–2010, the Clean
Air Act of 1970 and its amendments cut SO2 emissions by 75 % (USEPA,
2012), and this reduction may have affected regional climate. Focusing on
June–July–August (JJA) during 2000–2011 across the United States, Yu et al. (2014) found positive correlations between monthly mean satellite
observations of aerosol optical depth (AOD) and cloud optical depth (COD, r= 0.76) and between AOD
and shortwave cloud forcing (SWCF, r= 0.84), as well as negative
correlations between SWCF and maximum surface air temperatures (r=-0.67).
They thus attribute the 20th century warming hole to aerosol–cloud
interactions that lead to surface cooling. To quantify aerosol–radiation
interactions, Gan et al. (2014) analyzed a sparse network of surface
observations from the Surface Radiation Budget Network (SURFRAD) during
1995–2010, and found increasing trends in annual mean downward surface solar radiation (SWdn) accompanying
decreases in AOD, especially among eastern US
sites. However, that study also detected an increase in clear-sky diffuse
radiation, which is perplexing, given that declining aerosol would be
expected to decrease such radiation. In contrast, Eshel (2016) diagnosed
1998–2014 surface observations at a site in upstate New York, and inferred
that improved air quality has led to a strong increase in JJA SWdn there.
The Eshel (2016) result is similar to European studies that have tied
aerosol reductions to enhanced SWdn (Philipona et al., 2009; Ruckstuhl et
al., 2008). Tosca et al. (2017) compared the observed +0.54 ± 0.52 K
decade-1 summertime temperature trend in the southeast US to the
-0.05 decade-1 satellite retrieved AOD trend. The authors conclude that
aerosols reductions enhanced surface temperature through aerosol–radiation
interactions, but their study did not consider the covariability between
observed clear-sky SWdn and AOD measurements, which we argue should exist
for aerosol–radiation interactions.
In a modeling framework, Mickley et al. (2012) found that simple removal of
US aerosols exerted a top-of-atmosphere (TOA) radiative forcing of as much
as +4–5 Wm-2 over the central and eastern US. This forcing produced
a positive feedback in which increases in SWdn
enhanced surface fluxes of sensible heat in late summer, drying out soils
and reducing cloud cover, which further enhanced SWdn. To understand the
climate response of a more realistic representation of US aerosols,
Leibensperger et al. (2012a) forced a global climate model using simulated
historical aerosols, and found that high aerosol loading during 1970–1990s
increased cloud cover and soil moisture by as much as 5 % in the central
and eastern US. The study also found that aerosol outflow to the Atlantic
Ocean in this time frame may have cooled SSTs and increased mean JJA 850 hPa
geopotential heights in the region of the Bermuda High (BH), a
semipermanent high-pressure system. Booth et al. (2012) found that stronger
aerosol influence on surface forcing in a climate model could better
reproduce Atlantic SSTs. Zhang et al. (2013)
contested this result, pointing to mismatches between the Booth et al. (2012) model results and observations of North Atlantic upper ocean heat
content and salinity. They proposed instead that variations in the Atlantic
Multidecadal Overturning Circulation have driven recent changes in Atlantic
SSTs. Mascioli et al. (2016) found competing effects on US temperature
extremes by changing aerosols and greenhouse gases over the 20th century, as
expected, but temperature in the southeast responded only weakly to aerosols
in their simulation. Finally, using 50–member ensembles, Banerjee et al. (2017) simulated aerosol–radiation interactions and the cloud albedo effect
on US climate, but not the cloud lifetime effect. They found that aerosol
forcing could not entirely explain the 1951–1975 decreasing JJA trend in
southeastern US temperatures.
Nearly all these studies on the origin of the US warming hole relied on
climate or chemistry–climate models with their many uncertainties. For
example, the response of soil moisture or low cloud cover to changing SWdn
in such models may not be well captured (Soden and Held, 2006), and with few
observations, aerosol concentrations in the early warming hole years are not
well constrained. Aerosol composition is also not well known in the 1950s
and 1960s, with black carbon emissions likely uncertain by at least a factor
of 2 (Bond et al., 2007). The meteorological response to black carbon could
be very different to that of sulfate (Koch and Del Genio, 2010; Bond et al., 2013),
the most abundant anthropogenic aerosol in more recent decades.
In this paper, we turn to observational datasets to try to reconcile the
apparently conflicting hypotheses of previous studies (e.g., Leibensperger
et al., 2012b; Kumar et al., 2013; Gan et al., 2014; Yu et al., 2014). We
extend previous analyses of SURFRAD trends (Long et al., 2009; Augustine and
Dutton, 2013; Gan et al., 2014) by using more recent observations and by
focusing on two central and eastern US sites, where emission controls have
had the largest influence on AOD. To gain knowledge of the potential
influence of changing AOD on regional meteorology, we apply the observed AOD
and cirrus cloud variables to a radiative transfer model and a simple
statistical model. We further study regional meteorology during summers with
enhanced SWdn to better understand how potential trends in SWdn could
influence climate and soil hydrology, especially if the warming hole
reversal continues, as suggested by some modeling studies (Leibensperger et
al., 2012b). Our work has special relevance for developing countries that
currently experience heavy aerosol loading but are planning emission
reduction strategies (e.g., Lu et al., 2011).
Data and methods
We obtain surface SWdn observations from the SURFRAD Network, which consists
of seven sites across the US (Augustine et al., 2000). Although sparse,
the network provides some of the longest in situ solar radiance measurements
in the US, broken into diffuse and direct components. In this study we
focus on 2000–2014 data from sites in Bondville, Illinois, and Goodwin
Creek, Mississippi, as these sites are located in the central and eastern
US and have experienced AOD reductions in the recent past (Gan et al.,
2014). We exclude the SURFRAD Penn State site from this study, as the record
is incomplete for much of 2009–2014. SURFRAD solar diffuse radiation is
measured through a shaded Eppley Black and White Pyranometer, and direct
solar radiation is measured with an Eppley Normal Incidence Pyrheliometer
(NIP). Diffuse and direct measurements are summed to produce all-sky
shortwave radiation fluxes. All broadband radiation measurements have a
3 min temporal resolution, taken as an average of 1 s samples.
There are uncertainties of 3 and 6 % (4 and 20 Wm-2) associated
with the direct and diffuse measurements, respectively (Stoffel, 2005),
where uncertainty is derived from the 95 % confidence interval. SURFRAD
stations also measure AOD in five spectral channels using a multifilter
shadowband radiometer. The AOD data are also available as 3 min
averages, but only under cloud-free conditions. Both SURFRAD sites are
located away from urban sources, so we expect them to be representative of
the larger region. To verify consistency of SURFRAD trends against trends
across the broader region, we compare the SURFRAD SWdn radiance data with
pyranometer measurements from the US Climate Reference Network (USCRN; Diamond et al., 2013), but consider only those USCRN sites that have 10+
years of data, starting as early as 2003. We also compare SURFRAD SWdn to in
situ pyranometer measurements from the Cary Institute of Ecosystem Studies
(CIES; http://www.caryinstitute.org), located near Millbrook, New York, from
1990 to 2015.
SURFRAD also provides estimates of total clear-sky radiance using the
all-sky observations, following the methods in Long and Ackerman (2000).
Briefly, a power law model (Y=A×cos(θ)b) is fit,
where the initial guess for Y is all-sky SWdn, θ is the solar zenith
angle, and A and b are the fitted coefficients. After eliminating cloudy
measurements using various selection criteria, the power law model is refit
following an iterative process until its coefficients converge, giving an
estimate of clear-sky fluxes. A weakness of this fitting algorithm is that
it may not remove the influence of thin cirrus clouds on the clear-sky flux
(Long et al., 2009), and trends in cirrus cloud cover may potentially
influence estimates of trends in clear-sky SWdn.
We use the column version of the rapid radiative transfer model for general
circulation models (RRTMG_SW) to relate SURFRAD radiances to
changes in AOD at the two sites (Iacono et al., 2008). RRTMG_SW relies on a correlated-k approach to approximate radiative fluxes and
heating rates (Clough et al., 2005); multiple scattering is calculated
through a two-stream approximation. We apply monthly mean profiles of
atmospheric temperature, pressure, and ozone and water mixing ratios from
the MERRA-2 reanalysis (Rienecker et al., 2011) while keeping all other
chemical profiles (e.g., CO2 and N2O) fixed to climatological
means. The MERRA-2 ozone product is derived from a simple production and
loss chemical scheme (Suarez et al., 2008), assimilated with measurements
from the Ozone Monitoring Instrument and the Microwave Limb Sounder. MERRA-2
ozone fields below 260 hPa are not as reliable. We also apply MERRA-2
surface emissivities to the RRTMG_SW bands in the infrared
part of the spectrum (820–4000 cm-1), and one minus the observed
SURFRAD SW reflectance in the RRTMG_SW bands in the shortwave
region (4000–50000 cm-1).
We drive the model with observed monthly mean AOD from SURFRAD. For single
scattering albedo and asymmetry parameters of the aerosol, we rely on
measurements from two long-term AERONET sites located close to the SURFRAD
sites: Bondville, IL, and Huntsville, AL (Dubovik and King, 2000). Gan et al. (2014) found
close agreement between AOD measurements at the Bondville
SURFRAD site and nearby AERONET sites, so we assume that AERONET aerosol
properties represent those at SURFRAD. For information on thin cirrus
clouds, we rely on cloud fraction, cloud water path, and ice and liquid
radius data retrieved from the CERES instrument onboard the Terra and Aqua
satellites (Minnis et al., 2011). CERES thin cirrus cloud optical depths have
been shown to those retrieved by the Cloud–Aerosol Lidar and Infrared
Pathfinder Satellite (launched in 2006) over land (r= 0.65). More detailed
information about the cirrus retrieval uncertainty is currently being
explored (Minnis, P., personal communication, 2017). Since we are interested in
total column extinction and surface radiation values, we assume all aerosols
are concentrated in the surface layer and fix cirrus fractional cloudiness
at 300 hPa. In a sensitivity simulation, we find that whether we fix the
aerosols at the surface layer or distribute the aerosol through the lower
troposphere has little effect on modeled surface SWdn. Since the CERES Level
3 retrieval is available only since 2000, we perform all monthly radiative
transfer simulations over the 2000–2014 period. Our model setup is similar
to the approach of Ruiz-Arias et al. (2013), who performed Weather Research
and Forecasting (WRF) model simulations using RRTMG_SW driven
by AERONET AOD and aerosol parameters during 1–3 October 2011. The authors
found close agreement between 10 min modeled and observed total, direct,
and diffuse SWdn at SURFRAD and Atmospheric Radiation Measurement (ARM)
sites, though they did not perform simulations for Goodwin Creek. We perform
simulations with monthly mean data to avoid gaps in the AOD and CERES
record. Missing daily observations at Goodwin Creek and Bondville range from
43 to 49 %.
To assess the regional climate impacts of variations in SWdn at Bondville,
we use tower data from the nearby Ameriflux site, also in Bondville, and
Illinois Climate Network (ICN) sites (WARM, 2014). The Ameriflux site
provides 9 years (1998–2007) of continuous observations of summertime
radiation, temperature, heat flux, and soil moisture. The tower is located
within an active corn and/or soybean agriculture field, but experiences little
irrigation (Meyers, T., personal communication, 2016), which could influence the
microclimate. The Bondville ICN tower sits in a non-irrigated grass field.
Between 1983–2002, semimonthly soil moisture measurements were made at the
tower, using a neutron probe instrument. Since 2003, the station has taken
hourly soil moisture measurements using a hydraprobe sensor. The ICN site
also provides shortwave global radiation, temperature, and soil temperature
data from 1990 to the present.
We compare Ameriflux and ICN tower data with the estimates from the NASA
Land Data Assimilation System (NLDAS) over North America (Mitchell et al.,
2004). The goal of the NLDAS project is to construct high-quality,
consistent datasets for use in land surface models (LSMs). NLDAS utilizes a
combination of gauge-based precipitation and meteorological data from the
NCEP North American Regional Reanalysis (NARR) to drive an ensemble of LSMs,
yielding estimates of soil moisture and surface energy fluxes. Version 2 of
NLDAS also uses bias-corrected SWdn data from the University of Maryland
Surface Radiation Budget dataset, which is based on GOES-8 satellite data
(Pinker et al., 2003). Here we analyze the output from three LSMs in the
NLDAS project: Mosaic, Variable Infiltration Capacity (VIC), and Noah (Xia
et al., 2012; Koster and Suarez, 1994; Wood et al., 1997). Each LSM has a
different treatment of land–atmosphere coupling, but all require that
incoming solar radiation balance the sum of outgoing thermal radiation,
latent and sensible heat losses, and diffusion of energy into the soil
(Overgaard and Rosbjerg, 2011). Spatial resolution of these models is
1/8∘×1/8∘.
We calculate annual trends in observations using monthly mean anomalies. For
the SURFRAD dataset, we first find the mean diurnal profile for each month
during 2000–2014. We then calculate monthly mean SWdn by averaging these
diurnal profiles over daylight hours. We compute the monthly climatology
over the 2000–2014 period and subtract that from each year's monthly means
to arrive at monthly SWdn anomalies. Trends for other data measured with
hourly or daily frequency are computed using the same method. Radiative
transfer simulations in RRTMG_SW are performed with monthly
average AOD and other environmental variables. As with the observations, we
find monthly anomalies in RRTMG_SW by first calculating the
2000–2014 monthly climatology for each simulation and subtracting that from
the corresponding time series of monthly means. We use least-squares
regression to estimate the slopes of the time series of both observed and
modeled monthly anomalies. To test for statistical significance, we follow
the method described by Weatherhead et al. (2008), a method also utilized
by Gan et al. (2014). This method determines the significance of a
least-squares trend based on variance of the noise (i.e., the residual from
the straight-line fit), the autocorrelation of the noise, and the number of
data points used to determine the trend. In this study, we set p< 0.05 as the threshold for statistical significance.
Long-term trends in surface SWdn
Observed 500 nm AOD decreases significantly at both Bondville (-0.047) and
Goodwin Creek (-0.052) during the 2000–2014 time frame (Fig. 1),
providing evidence of the success of strengthening US air quality
regulations. In Fig. 2 we show the corresponding trends in observed SWdn
for all-sky and clear-sky conditions at the two sites. Both stations show
significant increases in total (diffuse + direct) all-sky as well as
clear-sky SWdn, as would be expected from the changes in AOD. However,
diffuse SWdn is the dominant contributor to these clear-sky trends in both
cases, a finding that is discussed further in this section and Sect. 4.
Figure 2 also shows the modeled trends in SWdn. At Bondville, the
aerosol-only simulated trend in clear-sky SWdn agrees in magnitude and sign
(+0.93 ± 0.22 Wm-2 a-1) with that observed (+0.85 ± 0.13 Wm-2 a-1). Breaking down the total SWdn into its direct and
diffuse components, the aerosol-only simulation shows a result consistent
with aerosol reductions, specifically large increases in direct SWdn
accompanied by a decrease in diffuse SWdn. However, this result differs from
clear-sky observations, which show both direct and diffuse SWdn increasing
(+0.41 ± 0.16 and +0.44 ± 0.11 Wm-2 a-1).
Trends in monthly anomalies of 500 nm aerosol optical
depth (AOD) at Bondville, IL, and Goodwin Creek, MS, during 2000–2014. All
trend lines pass the significance threshold (p < 0.05).
As noted above, thin cirrus clouds may influence SWdn even under apparently
clear-sky conditions. Figure 3 shows spatial trends in cirrus ice cloud
fraction over 2000–2014 from CERES. Cirrus cloud fraction increases as much
as +0.5 % a-1 over parts of the eastern US, with a +0.21 % a-1 increase over Bondville. Trends in two other cirrus cloud
properties – cloud water path and cloud particle radius – are not as
spatially coherent as those of cirrus cloud fraction, and we do not discuss
these further. Incorporating the cirrus cloud fraction and the other two cloud
parameters into the aerosol–cirrus simulation still yields an increasing
trend in total clear-sky SWdn as shown in Fig. 2 (+0.40 ± 0.29 Wm-2 a-1), but with a magnitude only about half that observed.
Diffuse SWdn in this simulation is roughly a third of the observed clear-sky
trend, and this match comes at the expense of direct SWdn, which now shows a
decreasing trend, in contradiction to the observations. Neither the direct
nor diffuse SWdn trends in the aerosol–cirrus simulation are statistically
significant.
At Goodwin Creek, the modeled aerosol-only simulation trend in clear-sky
SWdn is +1.35 ± 0.25 Wm-2 a-1, more than double the
observed clear-sky trend (+0.52 ± 0.14 Wm-2 a-1). As at
Bondville, the diffuse component of the observed clear-sky SWdn at Goodwin
Creek also exhibits an increasing trend (+0.34 ± 0.11 Wm-2 a-1), even though cirrus cloud fraction shows no significant
trend there (Fig. 3). In fact, the diffuse SWdn trend in the
aerosol–cirrus simulation at Goodwin Creek is still negative, though more
positive than the aerosol-only simulation. This result contrasts with that
in Bondville, where consideration of the large cirrus trend changed the sign
and significance of direct and diffuse SWdn trends.
Reconciling the observed trends in diffuse, direct, and total SWdn at the
two sites is challenging. In their analysis of SURFRAD data, Gan et al. (2014) also found increasing trends in clear-sky diffuse SWdn averaged over
seven sites across the US from 1995 to 2010. That study hypothesized that
trends in this variable could be traced to increasing air traffic and
enhanced thin cirrus cloud formation. The effect of aircraft contrails on
total cirrus cloud fraction is uncertain. Analyzing trends in upper-atmosphere humidity and cirrus cloud cover, Minnis et al. (2004) determined
that the observed 1971–1995 +1.0 % per decade (+0.1 % a-1)
increase in cirrus cloud fraction over the US was indeed caused by
increased air traffic. The magnitude of this trend is similar to what we
observe in Fig. 3. Consistent with Minnis et al. (2004), Travis et al. (2004) found the diurnal temperature range (DTR) over the entire US
increased by 1.0 K compared to the 1971–2000 climatological mean after the
3-day suspension of nearly all air traffic following the events on 11 September
2001, with especially large increases (1–2 standard deviations above the
climatological mean) in regions such as Illinois that favor the formation of
aircraft contrails at high altitudes. The conclusions of the Minnis et al. (2004) finding, although controversial (Hong et al., 2008), suggest a strong
influence of contrails on the surface energy budget. At the two SURFRAD
sites, we do not find evidence in the diffuse SWdn record of a response to
the abrupt halt to air traffic in September 2001 (Fig. S1 in the Supplement). At Bondville,
a slight enhancement in diffuse radiation occurred 1 day after 11 September
which then decayed to the 1995–2000 average after 2 weeks.
Enhancements of similar magnitude occur previous to 11 September so
excursions from the mean may be typical for diffuse SWdn at Bondville.
Diffuse SWdn at Goodwin Creek site exhibits a jump on 11 September above the
1995–2000 climatology, but mostly stays within 1 standard deviation of
the 1995–2000 average afterward. These jumps in diffuse SWdn around
11 September would seem to contradict an influence of contrails on surface
SWdn observations. However, it is also possible that the sites are simply
not representative of the larger domain during this short time frame.
However, since we do not see strong evidence of aircraft influencing the
diffuse clear-sky SWdn at Bondville during 11–13 September, we are cautious in
ascribing the increasing diffuse clear-sky SWdn trends simulated at
Bondville (Fig. 2) to aircraft contrails. The increasing trend in CERES
cirrus cloud fraction (Fig. 3) may be due to other factors that are
outside the scope of this paper.
Annual trends in downward surface solar radiation (SWdn)
during 2000–2014 at Bondville, IL (a), and Goodwin Creek, MS (b).
Trends are determined from daytime data (10:00–23:00 UTC). Trends in observed
all-sky SWdn from the SURFRAD network are shown in light blue; observed
trends in clear-sky SWdn are in dark blue. Modeled trends in clear-sky SWdn
are shown for an aerosol-only simulation (light red) and for a simulation
with both aerosols and cirrus clouds included (dark red). Error bars are the
standard error of the slope estimated from a linear regression fit.
Asterisks above the bars indicate statistical significance (p < 0.05).
Annual trends in cirrus ice cloud fraction as retrieved
from Clouds and Earth's Radiant Energy System (CERES) for 2000–2014. Black
circles represent the locations of the SURFRAD stations (B = Bondville,
IL; G = Goodwin Creek, MS). White indicates regions where trends are not
statistically significant (p > 0.05).
Short-term variability in SWdn
The 2000–2014 trends in total observed and modeled clear-sky SWdn are
positive at both Bondville and Goodwin Creek, implying a link between
aerosols and SWdn. However, surface clear-sky SWdn would be expected to
respond rapidly to changes in overhead aerosol, and here we check whether
changes in aerosols and/or cirrus clouds can explain the monthly variability
of clear-sky SWdn observations. Figure 4 shows the time series of observed
and standardized monthly mean SWdn anomalies at Bondville and Goodwin Creek,
together with SWdn results from the aerosol-only and aerosol–cirrus
radiative transfer simulations. The standardized time series is constructed
by differencing each month's value with the long-term monthly mean and then
dividing by the monthly standard deviation. The Bondville aerosol-only
simulations show greater correlation with observations (e.g., r= 0.49 for
total SWdn) than that for the aerosol–cirrus simulations (r= 0.29). At
Goodwin Creek, results from neither monthly simulation are significantly
correlated with monthly observations.
Time series of monthly mean anomalies (standardized by
mean and standard deviation) in surface solar radiation (shortwave down or
SWdn) at Bondville, IL, and Goodwin Creek, MS, from 2000 to 2014. Blue curves
denote observations, light red shows model results with observed aerosol
optical depths (AOD) taken into account, and dark red shows results when
both AOD and observed cirrus cloud fraction are included. Thick lines
represent a 3-year locally weighted scatter-plot smoothing (lowess). The
correlations R between the non-smoothed model simulations and observations
are shown inset. All the correlations at Bondville are significant (p < 0.05), and no correlations at Goodwin Creek are significant.
For AOD to be a controlling factor of clear-sky SWdn, we would expect
covariability between variables. To check whether this connection is robust,
we develop a statistical model to predict surface monthly mean clear-sky
SWdn anomalies based on AOD and cirrus cloud properties using multivariable
linear regression (MLR) with no lag. We perform MLR for
June–July–August–September (JJAS). Aerosol load is generally highest in
the US during these months (Malm et al., 2004), the incoming solar flux is
large, and feedbacks can extend the aerosol influence into late summer
(Mickley et al., 2012). We find the optimal coefficients of the MLR by
individually fitting independent models across all combinations of predictor
variables. For predictor variables, we use AOD and the same cirrus cloud
parameters used to drive RRTMG_SW aerosol–cirrus simulations
– cirrus cloud liquid water path (LWP), cirrus cloud ice water path (IWP),
cirrus cloud liquid radius (RL), cirrus cloud ice radius (RI), and
cirrus cloud fraction (Cf). We also include monthly average column
ozone (pressure weighted) as a predictor. We optimize coefficients for each
individual MLR fit using leave-one-out cross-validation. For each MLR fit,
we calculate the Bayesian information criterion (BIC), which scores the MLR
based on its goodness of fit and penalizes based on the number of
parameters included in the regression (Posada and Buckley, 2004). Thus, we
seek solutions that explain clear-sky SWdn using the fewest number of terms,
so as to avoid over-fitting. Both clear-sky SWdn and the predictors are
detrended, deseasonalized, and standardized before the MLR is fit.
Table 1 summarizes the coefficients of the optimal MLR fits to clear-sky
SWdn. At Bondville, we find the optimal clear-sky total SWdn MLR model is
driven by AOD and overhead ozone, explaining 15 % of the variance. Direct
SWdn is best explained (20 %) by AOD alone. The MLR model with AOD and
cirrus LWP best fits the observed variability in clear-sky diffuse SWdn,
explaining 26 % of the variance. The magnitude of the fitted AOD
coefficients are of similar magnitude and opposite sign for direct and
diffuse SWdn, consistent with the expectation for aerosol–radiation
interactions. The coefficients of determination (R2) in Table 1 are
similar in magnitude to the correlations between observed SWdn fluxes and
those calculated by the radiative transfer model (Fig. 4), showing a
consistency between the two methods to interpret the influence of AOD on
SWdn.
At Goodwin Creek, neither observed AOD nor any property of cirrus clouds can
explain the variability in direct or diffuse SWdn, casting doubt on these
variables as influences on SWdn at this site. That two separate sites with
similar 2000–2014 AOD reductions could have different MLR results
underscores the possible multiplicity of drivers of SWdn and the uncertainty
in resolving local radiation budgets. RRTMG_SW simulations
driven by AOD have been shown to capture SWdn fluxes at SURFRAD sites well
(Ruiz-Arias et al., 2013). However, Ruiz-Arias et al. (2016) found a 4 %
reduction in monthly mean AOD compared to daily AOD in fine aerosol regimes.
(Ruiz-Arias et al. segregate aerosol regimes using the Angstrom exponent,
which is a direct function of the average size of the aerosol mixture.)
Among the Bondville and Goodwin Creek AOD time series and the CERES
retrievals, nearly half the days are missing coincident observations, hence
the need to bin the daily data into monthly observations.
Fitted regression coefficients to downward surface
shortwave radiation (SWdn) at Bondville, IL, from 2000 to 2014. Fits represent
the optimal multivariate regression model chosen using the Bayesian
Information Criterion (BIC) and fit to column–averaged ozone, aerosol
optical depth (AOD), cirrus cloud liquid water path (LWP), cirrus cloud ice
water path (IWP), cirrus cloud liquid radius (RL), cirrus cloud ice
radius (RI), and cirrus cloud fraction (Cf).
* Predictor variables were detrended, deseasonalized, and normalized by their
mean and standard deviation before being fitted to SWdn anomalies.
Meteorological impacts from enhanced SWdn in late summer
Previous work has suggested that the land–atmosphere coupled response to
increased SWdn involves a cascade of meteorological phenomena (Shindell et
al., 2003; Budyko, 1969). Gu et al. (2006) saw evidence of coupling between
net radiation, heat fluxes, and soil moisture using Ameriflux observations
during the 2005 growing season in Missouri. The model study of Mickley et al. (2012) found that US aerosol reductions lead to enhanced latent heat
fluxes in early summer, which transition to enhanced sensible heat fluxes by
late summer–early fall. We probe the observational record for evidence of
these feedbacks by first analyzing 1998–2007 tower data from the Ameriflux
site at Bondville. We classify the data for each year into either a sunny or
cloudy regime depending on whether the JJAS mean SWdn for that year is above
or below the climatological JJAS median. We chose JJAS as the time frame of
reference due to the large summer to early fall SWdn response from reduced
aerosols seen in Mickley et al. (2012). We then compare the responses in
monthly mean surface fluxes for these two regimes (Fig. 5). We do not
consider aerosols directly here, as the short time series of the Ameriflux
data limits the ability to assess long-term trends, but we can use our
results to understand the regional sensitivity of the land–atmosphere system
to SWdn changes driven by AOD trends. We also do not consider microclimate
feedbacks from irrigation at the Ameriflux station. Although irrigation has
been shown in other studies to suppress extreme temperatures in the Midwest
(Mueller et al., 2016), we find that the monthly-average temperatures
recorded at the Ameriflux Bondville site nearly match the temperature
readings at the nearest airport in Champaign, IL (not shown). Also, since
the Ameriflux temperatures and SWdn data correspond closely to these value
in the 1/8∘ NLDAS dataset (Fig. S2), we assume that the effect of
microscale irrigation is small.
Differences in surface measurements at the Bondville
Ameriflux site (1998–2007) between sunny and non-sunny summers, where
summer is defined as June–July–August–September and a sunny summer is
defined as one with average all-sky downward surface solar radiation (SWdn)
greater than the median 1998–2007 all-sky summer SWdn. Error bars represent
the 95 % confidence interval of the difference.
Figure 5 shows that the difference in all-sky daytime SWdn between these two
regimes during JJAS is +28.1 Wm-2. Enhanced SWdn during sunny years
leads to increased latent heat fluxes in May–June (+5.3 Wm-2), which
transition to increased sensible heat fluxes in August–October (+9.5 Wm-2). Volumetric soil water content follows the latent and sensible
heat fluxes, with greater soil moisture in June (+2.7 %) and drier
conditions in August (-3.5 %). Because of the increased sensible heating
in the sunny regime, we would expect a corresponding change in temperature.
However, the difference in JJAS maximum temperature at this site is slightly
negative (-0.86 K), with cooler temperatures during sunny years. This
negative change in temperature is corroborated by a negative change in
upward surface longwave radiation (LWup) at the nearby SURFRAD site (-5.4 Wm-2). Precipitation at Bondville does not differ significantly between
sunny and cloudy regimes (not shown). Summer 2004, classified as sunny, was
paradoxically the coolest summer in the Ameriflux record, with a mean
maximum temperature 1.7 K cooler than the 1998–2007 average at this site.
Indeed much of the central US experienced cool temperatures that summer
(w2.weather.gov/dtx/2004annualclimatesummary). The surprising result of a
cool but sunny summer in 2004 at the Ameriflux site points to the possible
problem of relying on its short (10 year) record of observations.
We next examine ICN measurements of SWdn and surface variables, including
soil moisture, using the same method of segregating sunny and cloudy
summers. Since the method of measuring ICN soil moisture changed in 2003, we
analyze differences in sunny vs. cloudy regimes within each measurement
period, with PER1 corresponding to 1990–2002, and PER2 corresponding to
2003–2014. Though no sensible or latent heat measurements are available
here, the ICN data include a record of 4 in (10.2 cm) soil temperatures under sod
together with soil moisture and maximum air temperatures (Fig. 6). We see
a similar pattern across the two instrument regime periods, specifically
that sunny JJAS summers (PER1 =+16.3 Wm-2, PER2 =+8.5 Wm-2) favor hotter soils (PER1 =+1.2 K, PER2 =+2.9 K) and
reduced soil volumetric water content (PER1 =-3.0 %, PER2 =-3.4 %).
In both instrument periods, the maximum JJAS temperature increases during
sunny summers (PER1 =+2.0 K, PER2 =+2.5 K), in contrast with the
Ameriflux measurements. In the PER2 ICN data, summer 2004 is categorized as
cloudy, hence its cooler temperature is expected. The LWup change at the
nearby SURFRAD site during PER2 is consistent with the temperature increase
(+4.8 Wm-2). Precipitation again does not differ significantly
between sunny and cloudy regimes for each instrument period (not shown). The
changes in SWdn for both ICN and Ameriflux stations are strongly positive,
with the change during both PER1 and PER2 about half that in the Ameriflux
record.
Differences in surface measurements at the Bondville ICN
site between sunny and non-sunny summers. The technique for measuring soil
moisture changed at this site in 2003, and the panels show differences
separately for the periods before and after this change: period 1 (PER1,
1990–2002) and period 2 (PER2, 2003–2014). As in Fig. 5, summer is
defined as June–July–August–September and a sunny summer is defined as
one with average all-sky downward surface solar radiation (SWdn) greater
than the median all-sky summer SWdn of each respective period. Error bars
represent the 95 % confidence interval of the difference. For clarity,
monthly means for PER1 are slightly offset with respect to the abscissa.
The record of observations at Ameriflux Bondville is relatively short, and
the inconsistent soil instrument record at the ICN station complicates
long-term analysis. Ameriflux and ICN sites yield consistent SWdn and soil
moisture results, but different surface temperature responses, perhaps due
to the short-term measurement record. To investigate long-term
land–atmosphere changes from 1990 to 2015, we use assimilated meteorology and
other variables from the NLDAS dataset. To assure the quality of the NLDAS
driving variables, we compare three of these variables – monthly mean SWdn,
precipitation, and air temperatures – with observations from Ameriflux
stations with at least 5 years of data (11 in total). We also compare NLDAS
SWdn with that from SURFRAD. Figure S2 shows statistically significant
agreement among these datasets, with r ranging from 0.60 to 0.77, depending
on the variable. We find much weaker, but still statistically significant,
agreement between the LSM results and the Ameriflux observations, with r
ranging from 0.24 to 0.47, depending this time on both the variable and
model (Fig. S2). Best matches between models and measurements are obtained
for the sensible heat flux. The relatively weak correlations underline the
difficulty in resolving land–atmosphere coupling at 1/8∘×1/8∘ resolution.
Using the NLDAS dataset and being mindful of the uncertainties in LSM results, we
expand our focus to look at spatial trends in the relevant variables across
the contiguous United States for JJAS over the 1990–2015 time period. Figure 7 shows that surface JJAS all-sky SWdn has increased significantly by
+0.78 Wm-2 a-1 from 1990 to 2015 across the central US
(30–50∘ N, 105–85∘ W, denoted by the green box in Fig. 7). Figure 7 also
reveals a close correspondence between the all-sky NLDAS trend and the
all-sky trends derived from site measurements in the SURFRAD (1997–2014),
USCRN (2003–2014), and CIES (1990–2015) networks, increasing confidence in
the NLDAS dataset. Deviations between data products may be explained by the
inconsistent time periods of comparison. Accompanying the change in SWdn is
an increase in average JJAS air temperatures over much of the central and
eastern US (+0.07 K a-1). Precipitation decreases slightly in the
central US (-0.19 kg m-2 a-1), mostly in a few isolated regions
over the Great Lakes. The total JJAS enhancement in NLDAS all-sky SWdn over
the central US over the 1990–2015 time period is +20 Wm-2, similar
in magnitude to the increase observed during sunny years at the Ameriflux
(+28.1 Wm-2) and ICN (PER1 =+16.3 Wm-2, PER2 =+8.5 Wm-2) sites. The 2000–2014 clear-sky SWdn enhancements that we
simulate with RRTMG_SW at Bondville and Goodwin Creek
(+13.9 and +6.2 Wm-2) are about half the NLDAS enhancements
averaged over the central US for the longer time period of 1990–2015.
June–July–August–September (JJAS) trends in surface
meteorological variables from 1990 to 2015. Surface downward solar radiation
(SWdn), air temperature, and precipitation are assimilated from observations
in the NASA Land Data Assimilation System (NLDAS). Overlaid on the SWdn plot
are observed trends from the US Climate Reference Network (USCRN: circles,
2003–2014), SURFRAD (squares, 1997–2015), and the Cary Institute for
Ecosystem Studies (CIES: diamond, 1990–2015). The green box in the
temperature panel represents the central US (30–50∘ N, 105–85∘ W). In the
soil moisture panel, we combine model results by first determining which of
the LSM trends agree in sign in each grid cell and then showing the mean of
just those models that agree. White indicates those regions that fail
statistical significance (i.e., p > 0.05).
Figure 7 also shows the soil moisture response to increasing SWdn and warmer
temperatures over 1990–2015, as calculated by the three LSMs. We combine
LSM results by first determining which of the model trends agree in sign in
each grid cell and then taking the mean of just those models that agree. The
combined trend reveals decreased soil moisture across the central US
between 1990 and 2015 (-0.85 kg m-2 a-1, averaged over the region
defined in Fig. 7), accompanied by an increase in sensible heating in the
same region (+0.28 Wm-2 a-1). This decrease in soil moisture
translates to a 1990–2015 decrease in volumetric soil water content of
-2.2 %, within the range of what is observed as the JJAS difference
between sunny and cloudy years at the Ameriflux (-0.14 %) and ICN (PER1 =-3.0 %, PER2 =-3.4 %) sites in
Illinois. Since the precipitation
patterns seem to be unchanging or small over much of the central US during
1990–2015, the LSM soil moisture results provide evidence of a climate
response to greater evapotranspiration in the presence of enhanced SWdn.
We emphasize that our main goal in examining the 1990–2015 NLDAS dataset is
to probe the regional response of soil moisture and temperature to trends in
all-sky SWdn. Coincidentally, the trends in all-sky SWdn across the
central US in the NLDAS dataset are similar in magnitude to the trends in
clear-sky SWdn in the RRTMG_SW model at Bondville for
a shorter time period. Given the similar magnitude of the observed all-sky
and clear-sky SWdn trends and the covariability of AOD with clear-sky SWdn
at Bondville, we infer the potential meteorological consequences of the
observed AOD trends in the central US with greater confidence. This
inference is limited due to the availability of just one surface site that
measures direct and diffuse components of all-sky SWdn, clear-sky SWdn, and
AOD but can be used as an example of assessing aerosol–climate interactions
in future studies.
Discussion
Here we assemble the evidence of changing surface climate in the US and
consider the possible role of aerosols in driving this change. During the
2000–2014 time period, observed AOD decreases significantly at both
Bondville, IL (-0.047) and Goodwin Creek, MS (-0.052). Clear-sky total SWdn
increases at these sites by 12.7 Wm-2 (Bondville) and 7.8 Wm-2
(Goodwin Creek) over the same time period, suggesting that the declining
aerosols are at least partly responsible for these trends. All-sky total
SWdn also increases at Goodwin Creek. However, the diffuse component of
clear-sky SWdn increases at both Bondville (+6.6 Wm-2) and Goodwin
Creek (+5.2 Wm-2), consistent with previous studies (e.g., Gan et
al., 2014) and the cause of these increases remains an open question. We do
not find evidence of aircraft contrails influencing observed diffuse SWdn at
SURFRAD sites in the aftermath of 11 September 2001, and thus caution
against attributing increasing clear-sky diffuse SWdn trends to increasing
US air traffic as has been done in previous studies (e.g., Long et al.,
2009; Augustine and Dutton, 2013).
Using the RRTMG_SW radiative transfer model driven by
observed AOD, we simulate increases in total and direct clear-sky SWdn at
both sites that are consistent with observations and decreases in diffuse
SWdn that are contrary to the observations. Previous studies invoked trends
in aircraft contrails to explain the unexpected changes in diffuse SWdn at
SURFRAD sites across the US (e.g., Gan et al., 2014), but application of
observed cirrus cloud fraction to RRTMG_SW does not resolve
this issue. A cross-validated multivariate regression analysis further shows
that observed monthly mean AOD accounts for 20 % of the JJAS variability
in clear-sky direct SWdn at Bondville, with cirrus cloud liquid water path
and AOD reproducing 26 % of the variability in clear-sky diffuse SWdn at
this site. No combination of predictors, however, explains the variability
of clear-sky direct or diffuse SWdn at Goodwin Creek, casting doubt on the
role of aerosol–radiation interactions on local meteorology at this site.
Besides AOD and cirrus cloud cover, we are left with few other variables
that could influence the direct–diffuse partitioning of clear-sky SWdn, and
the cause of the observed increase in SWdn during the 2000–2014 time frame is
not clear. With more sites across the southeast, we could diagnose these
inconsistent results as either site-specific, or symptomatic of the larger
region.
Our analysis of the Ameriflux data (1998–2007) and ICN data (1990–2014)
suggests that soil moisture declines in response to enhanced solar
radiation. In particular, we see possible evidence of a soil moisture
feedback at the Bondville Ameriflux station, where the difference in JJAS
SWdn between sunny and cloudy summers is nearly 30 Wm-2, peaking in
September. A sunny summer reduces soil moisture, especially in August
(-3.5 %), and enhances sensible heat fluxes by +8.7 Wm-2, with peak
values in September. The SURFRAD data show an all-sky annual SWdn trend of
+0.58 Wm-2 a-1 at Bondville and a +1.0 Wm-2 a-1 at
Goodwin Creek for 2000–2014. This rate translates to changes in SWdn of
+8.7 and +15 Wm-2 over this time period at these sites,
or roughly one-fourth to one-half the change in SWdn between sunny and
cloudy years at the Ameriflux station. Despite large spatial heterogeneity,
the land surface models in Sect. 6 show a reduction of volumetric soil
water content of as much as -2.2 % over the central US from 1990 to 2015.
Given the observed trends in SWdn, this result is consistent in sign with
the 0.14–3.4 % decrease in soil moisture content during sunnier summers at
the Ameriflux and ICN sites in Illinois. The observed soil moisture and
temperature responses between the sunny and cloudy regimes are of the same
order of magnitude as those simulated by Mickley et al. (2012) for aerosol
vs. no aerosol regimes over the eastern US, lending confidence to the
conclusions of that model study. Our results are also consistent with Eshel
(2016), who found that the observed SWdn increase from 1988 to 2014 at a rural
site in the northeast could be explained in a radiative transfer model only
when considering trends in anthropogenic aerosols.
Our Ameriflux, ICN, and NLDAS results show the climate response to
increasing surface SWdn. The RRTMG_SW results in Bondville
show that changing aerosols influences SWdn trends. Taken together, the
observations and modeled results suggest that aerosol–radiation interactions
are significant at Bondville, a conclusion doubted in previous studies (Long
et al., 2009; Augustine and Dutton, 2013). We find evidence that these
interactions play a role in the observed climate trends at Bondville,
similar in response to modelling studies that probed the influence of
aerosols on the warming hole (Leibensperger et al., 2012b). Changes in
overhead aerosol contribute about one-fourth of the interannual variability
in direct and diffuse clear-sky SWdn. If the aerosol trends at Bondville are
representative of the larger region, the recent decline in AOD may partly
account for the 1.8 K increase in surface temperatures across the larger
region for JJAS in the NLDAS dataset. In contrast, aerosol–radiation
interactions do not appear to contribute to the interannual variability in
SWdn at Goodwin Creek, casting doubt on the role of the direct aerosol
effect in the reversal of the US warming hole in the southeast.
Our results underscore the difficulty in attributing the warming hole to
only aerosols or only aerosol–radiation interactions using observations.
Even though we find evidence of aerosol–radiation interactions at Bondville,
our result at Goodwin Creek contrasts with Tosca et al. (2017), who
concluded that the observed increase in surface SWdn between 2007 and 2017
at this site was a result of aerosol–radiation interactions. Though we agree
with these authors on the sign of the observed surface SWdn trend and find
that RRTMG_SW can indeed reproduce a positive clear-sky SWdn
trend when driven by aerosols (Fig. 2), we do not find evidence of
interannual covariability between AOD and clear-sky SWdn at Goodwin Creek.
Hence, we disagree that the SURFRAD observations point to aerosol–radiation
interactions at this site, as we believe that evidence of covariability
between AOD and SWdn on interannual timescales is a necessary condition in
asserting aerosol–radiation interactions. Yu et al. (2014), however, found
evidence of aerosol–cloud interactions in the southeastern US, so such
interactions could potentially be important in that region.
Agriculture is a major industry in the central US, and decreases in soil
moisture from increased SWdn may have made the region more vulnerable to
drought, as suggested by previous model studies (Mickley et al., 2012;
Leibensperger et al., 2012b). From our analysis of tower fluxes and the NLDAS
assimilation, we find a consistent land–atmosphere response to SWdn as seen
in these model studies. Specifically, soil moisture responds to local
enhancements in SWdn that further amplifies SWdn, especially in late summer.
Previous studies have diagnosed the strong influence of tropical Pacific
SSTs on drought occurrence in the US (e.g., Schubert et al., 2004; Seager
and Hoerling, 2014). However, drought models that rely on Pacific SSTs
predict a prolonged drought during the 1970s, a period in reality
characterized by increased precipitation, especially in the central and
eastern United States (e.g., Seager and Hoerling, 2014). We speculate that
high loading of anthropogenic aerosol during the 1970s may have led to more
moist conditions in the central US, countering the SST influence and
reducing drought risk. While the model results of Leibensperger et al. (2012a, b) are consistent with this hypothesis, more rigorous model studies
with state-of-the-science hydrology and chemistry are needed to confirm it.
We underscore the findings of other studies (e.g., Milly and Dunne, 2011)
that caution modeling studies against projecting hydrological change in
models without finding consistency with surface energy balance changes.
A drawback of this study is that it relies on relatively short-term records
of aerosols and surface SWdn. There is also some uncertainty in the SURFRAD
measurements, at least when compared to the derived trends per year of SWdn.
In trends reported here, however, we find that the standard deviation of the
residual noise is greater than the instrument uncertainty. Finally, our
study relies on just a few measurement sites to infer relationships of AOD
with other variables across a broad region. We find evidence of
aerosol–radiation interactions at Bondville but not Goodwin Creek. Though we
use site-specific data to come to these conclusions, the good match between
site measurements and assimilated NLDAS SWdn data, however, lends confidence
that increased surface SWdn has indeed occurred over a broad region. As more
in situ measurements of SWdn and AOD are recorded and as USCRN and other
national networks are expanded, we expect the discrepancies between SURFRAD
sites will be better explained.
This study provides observational evidence of the influence of AOD on SWdn
and key variables such as soil moisture. By linking trends in AOD, SWdn, and
soil moisture, our results point to the importance of considering
atmospheric composition as an additional driver of drought. Currently, many
regions of the developing world (e.g., China and India) have much higher
aerosol loading than the US and are planning strategies to reduce aerosol
sources and improve air quality (Lu et al., 2011). These regions also depend
on favorable meteorological conditions for agricultural production to feed
growing populations. Our study suggests there may be inadvertent
consequences of aerosol reduction on regional climate.
The SURFRAD radiance and AOD observations are available for download at
ftp://aftp.cmdl.noaa.gov/data/radiation/surfrad/. ICN soil and meteorological data are available for download at
http://www.isws.illinois.edu/warm/datatype.asp. Ameriflux soil and meteorological data are available for download at
http://ameriflux.lbl.gov/. USCRN meteorological data are available for download at
https://www.ncdc.noaa.gov/crn/qcdatasets.html. CIES radiance data are available for download at
https://cary-environmental-monitoring.squarespace.com/metsolardata/. AERONET aerosol inversion products are
available for download at https://aeronet.gsfc.nasa.gov/. CERES Level 3 cloud data products are available for download at
https://ceres.larc.nasa.gov/order_data.php. MERRA-2 and NLDAS reanalyses are available for download at
https://disc.gsfc.nasa.gov/. Instructions and model code for the radiative transfer model RRTMG_SW is available for
download at http://rtweb.aer.com/rrtm_frame.html.
The Supplement related to this article is available online at https://doi.org/10.5194/acp-17-13559-2017-supplement.
The authors declare that they have no conflict of interest.
Acknowledgements
This work was supported by the National Aeronautics and Space Administration, MAP grant NNX13AO08G.
Edited by: Yun Qian
Reviewed by: three anonymous referees
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