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Mesoscale Climatic Simulation of Surface Air Temperature Cooling by Highly Reflective Greenhouses in SE Spain

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A long-term local cooling trend in surface air temperature has been monitored at the biggest concentration of reflective greenhouses in the world, at the Province of Almeria, SE Spain, associated with a dramatic increase in surface albedo in the area. The availability of reliable long-term climatic field data at this site offers a unique opportunity to test the skill of meso-scale meteorological models describing and predicting the impacts of land use change on local climate. Using the Weather Research and Forecast (WRF) mesoscale model, we have run a sensitivity experiment to simulate the impact of the observed surface albedo change on monthly and annual surface air temperatures. The model output showed a mean annual cooling of 0.25 ºC associated with a 0.09 albedo increase, and a reduction of 22.8 W m-2 of net incoming solar radiation at surface. Mean reduction of summer daily maximum temperatures was 0.49 ºC, with the largest single-day decrease equal to 1.3 ºC. WRF output was evaluated and compared with observations. A mean annual warm bias (MBE) of 0.42 ºC was estimated. High correlation coefficients (R2>0.9) were found between modelled and observed values. This study has particular interest in the assessment of the potential for urban temperature cooling by cool roofs deployment projects, as well as in the evaluation of mesoscale climatic models performance.
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Mesoscale Climatic Simulation of Surface Air Temperature Cooling
by Highly Reective Greenhouses in SE Spain
Pablo Campra*
,,
and Dev Millstein
University of California Berkeley, Lawrence Berkeley National Lab, Energy Analyses & Environmental Impacts Department,
Berkeley, California 94720, United States
*
SSupporting Information
ABSTRACT: A long-term local cooling trend in surface air temperature
has been monitored at the largest concentration of reective greenhouses
in the world, at the Province of Almeria, SE Spain, associated with a
dramatic increase in surface albedo in the area. The availability of reliable
long-term climatic eld data at this site oers a unique opportunity to
test the skill of mesoscale meteorological models describing and
predicting the impacts of land use change on local climate. Using the
Weather Research and Forecast (WRF) mesoscale model, we have run a
sensitivity experiment to simulate the impact of the observed surface
albedo change on monthly and annual surface air temperatures. The
model output showed a mean annual cooling of 0.25 °C associated with a
0.09 albedo increase, and a reduction of 22.8 W m2of net incoming
solar radiation at surface. Mean reduction of summer daily maximum
temperatures was 0.49 °C, with the largest single-day decrease equal to 1.3 °C. WRF output was evaluated and compared with
observations. A mean annual warm bias (MBE) of 0.42 °C was estimated. High correlation coecients (R2> 0.9) were found
between modeled and observed values. This study has particular interest in the assessment of the potential for urban temperature
cooling by cool roofs deployment projects, as well as in the evaluation of mesoscale climatic models performance.
1. INTRODUCTION
The largest concentration of reective greenhouses on the
planet is located in the coastal plains of the province of Almeria,
SE Spain. The greenhouses sustain high eciency horticul-
ture.
13
Greenhouse farming development from 1970 through
2000 dramatically transformed the semiarid pasture land, and
now, according to International Space Station personal, this
area is the only human settlement that can be seen from the
station with the naked eye. Since 2000, the total surface area of
greenhouses has remained roughly constant at 27 000 ha
(Supporting Information, SI, Figure S1).
4
The development of greenhouse agriculture has led to a local
long-term cooling trend in surface air temperatures at the area
of 0.3 °C decade1, despite the generalized warming in the
surrounding region (SE Spain) of +0.4 °C decade1.
5
The
analysis of the observational records suggested that the increase
in surface albedo associated with greenhouse development,
+0.09 averaged over all seasons, has been the most probable
cause of this cooling trend.
Urban heat islands, i.e., the dierence in temperatures
between urban and surrounding areas, can reach as much as 1°
to 6 °C in summer months.
6
Urban albedo modication to cool
local surface air temperature is a strategy already employed in
many cities. For example, reective roofs are required in certain
situations in California and mandates have been proposed in
the U.S. and Europe.
7,8
While the research community has used
meteorological modeling to estimate the impacts of cool roofs
requirements, no comparisons of modeled temperature changes
to real world temperature changes occurring with citywide
adoption of reective roofs has been pursued to date (as
citywide changes to roof characteristics are rare).
The albedo increase at the study area is employed here as an
ideal and unique pilot experiment, where mesoscale modeling
can be compared with eld observations, helping to better
determine the impact of albedo enhancement in future land
cover change projects. Another advantage of this experience is
that the net impact on global emissions of greenhouse farming
has been quantied by life cycle assessment (LCA).
9
Because of
all these interesting features, this particular farming model
appears as a promising option to avoid competition between
climate-change mitigation strategies based on land use, such as
forestry and biofuels, and new demands for land to produce
food for a growing population in the future.
10
In this work, we pursue two goals: rst, to demonstrate
through modeling the mechanistic link between historic surface
albedo increases and historic cooling trends observed in the
area; second, to evaluate dierences between observed and
modeled temperature perturbations in order to inform future
investigations of surface albedo enhancement strategies.
Received: May 10, 2013
Revised: September 16, 2013
Accepted: September 27, 2013
Article
pubs.acs.org/est
© XXXX American Chemical Society Adx.doi.org/10.1021/es402093q |Environ. Sci. Technol. XXXX, XXX, XXXXXX
Past modeling eorts and observational studies have
investigated climatic alterations driven by land use/land cover
changes at local, mesoscale, and regional scales.
11,12
In
particular, previous modeling simulations show that albedo
increases can cool surface air temperatures. For example, Betts
used a global circulation model (HadAM3) to show that
clearing of low albedo natural vegetation in Eurasian and
American agricultural regions may have reduced annual mean
temperatures in aected regions by 0.51°C.
13
Other studies
have used global models to simulate the eects of widespread
urban albedo brightening through global deployments of cool
roofs.
1416
In most cases, the low resolution of global models (0.5°-2.5°)
limits the comparisons of model output to local eld data. To
evaluate the impact of albedo enhancements on urban scales,
regional models with higher resolution and improved land
surface representation can be employed. For example,
simulations of 0.1 albedo increases during short episodes (a
few days) in several U.S. cities (Los Angeles, Atlanta, Detroit,
Philadelphia Baltimore, Washington, and New Orleans),
showed reductions in peak summertime temperatures ranging
from 0.14 to 1.5 °C.
17
Temperature decreases of as much as
3.75 °C at single grid cells where simulated by urban albedo
brightening in California using a slightly longer time frame of
57 days.
18
Other simulations from 1 to 6 days runs found up
to 12°C of peak temperature reductions could be achieved in
New York
19
and Athens (Greece)
20
given varying increases of
urban albedo.
In order to investigate feedbacks on the atmospheric system
that may develop over longer periods and larger domains,
simulations of urban albedo increases over 12 years with a
domain covering the continental U.S. with 25 by 25 km sized
grid cells showed year-round temperatures reductions in most
cities with the largest cooling found at Los Angeles (0.53 °C),
Detroit (0.39 °C), and New York (0.3 °C).
21
In this work, it
was assumed that albedo changes varied from 0.0 to +0.115,
depending on urban density, according to previous estima-
tions.
22
Over the long simulation period, some cities showed no
signicant temperature reductions, and a few regions downwind
of urban areas showed small but signicant temperature
increases. Temperature increases were correlated with
decreased cumulus precipitation, reduction in cloud cover,
and increased shortwave radiation reaching the surface.
Some empirical studies have analyzed direct eld observa-
tions to verify the impact of high albedo surfaces on air
temperatures registered by monitoring stations. For instance, it
was reported an average summer daytime cooling of 12°C,
for a +0.4 albedo dierence between high albedo sandy surfaces
and darker surrounding areas in New Mexico desert.
23
However, due to limited temporal and spatial coverage of
reliable eld data, few observational studies link long-term
albedo changes and cooling trends. Land cover changes usually
occur on decadal and longer time scales, such that the climatic
signal requires observations over this time period.
12
Such
observational studies are scarce, as reliable temperature series of
at least 2530 years are needed in order to establish climatic
trends.
24
The impact on surface temperatures of land use
changes from grasslands to intensive agriculture in the U.S.
Great Plains was investigated using 7-years MODIS (Moderate
Resolution Imaging Spectrometer) data, suggesting that
dierences in temperature might be due to irrigation but did
not investigate the role of albedo change.
25
We have selected a representative annual cycle (year 2005)
to run both control and albedo enhancement simulations, and
determine monthly and annual changes in surface air
temperatures, as well as in the surface energy budget. This
year was selected due to the availability of previous analyses
5
of
surface temperatures and MODIS surface albedo data to further
establish comparison between our results and these observa-
tional data. Two experiments were run for the same period and
domain, changing only the albedo values in the land surface
model to mimic either present greenhouses cover or previous
pastureland cover. The scope of our sensitivity experiments is
limited to assess the skill of WRF to simulate the impact of
albedo changes on surface air temperatures in the area. All
other biogeophysical and biogeochemical changes associated to
historic land cover change in the study area have intentionally
not been taken into account in order to focus on the potential
of albedo enhancement for local adaptation of any human
settlements to projected global warming.
2. MODELING METHODOLOGY
Climatic and Land Surface Model. The Weather
Research and Forecasting Model (WRF) version 3.2.1 was
used for simulations.
26
WRF is a mesoscale model designed to
serve both operational forecasting and atmospheric research
needs. The basic computations are based on solving the
equations of motion, heat, and moisture and continuity. The
model uses higher-order numerics and the dynamics conserves
scalar variables.
The NOAH Land Surface Model (LSM)
27
has been coupled
to WRF
28
and was used to simulate surface soil moisture, soil
temperature, and canopy moisture. It provides surface uxes
and surface skin temperature as lower boundary conditions for
a coupled atmospheric model. WRF is suitable for a broad
spectrum of applications across scales ranging from meters to
thousands of kilometres.
WRF software architecture was built in CARVER IBM
iDataPlex supercomputer at the US Department of Energy
(DOE) National Energy Research Scientic Computing Center
(NERSC) in Berkeley, CA. A 3-nested grid conguration was
used, with grid sizes of 36, 12, and 4 km, respectively. The
center-point of the coarse domain is located at the greenhouse
farming area, 36.7 N and 2.7 W. The innermost domain (with
46 ×46 cells) covers the whole province of Almeria and part of
neighboring provinces of Granada and Jaen, SE of Spain. The
vertical dimension is divided onto 28 layers. Geographical data
sets were downloaded from NCEP/NCAR.
In our WRF sensitivity experiments, we have used a ceteris
paribusexperimental approach, i.e., holding all else constant,
intentionally assuming no changes in other biogeophysical land
cover properties and considering albedo as a single independent
variable, so that the eect on the dependent variable (2-m
temperature) can be isolated, thus focusing the model runs on
the impact on surface air temperatures of observed historic
albedo change in the area.
29
The 24-category U.S. Geological survey (USGS) land use
classication scheme was selected to provide land-cover data for
the model domains. Greenhouse farming is not specically
represented in available land use schemes. Instead, the study
area is still classied as USGS shrubland category (number 8),
along with the rest of semiarid lowlands in the province of
Almeria. This default category was selected to represent pre-
existing pasture land (PS) in the area now covered by
greenhouses, but albedo was modied and adjusted monthly
Environmental Science & Technology Article
dx.doi.org/10.1021/es402093q |Environ. Sci. Technol. XXXX, XXX, XXXXXXB
according to previous analysis of MODIS data.
5
To simulate
albedo change in the area, a new greenhouses category (GH)
was included in the scheme to represent present greenhouse
farming land cover, and inserted in the pixels where
greenhouses are located. Albedo was the only parameter that
was changed in this new category, keeping the rest of USGS
category shrublanddefault values unchanged. Time series of
surface reectance at 500 m resolution for the area of study
were acquired from the MODIS instrument on board of the
NASA Terra polar orbiting satellite for the year 2005. The
Surface Reectance product (MOD09A1) provides surface
spectral reectance estimates for bands 17 corresponding to 8
days composites removing atmospheric scattering and
absorption eects.
30
The entire area of greenhouses farming
located west of the city of Almeria (SI Figure S1) was selected
as representative of greenhouse surface for monthly albedo
determination. Currently, almost 70% of this coastal plain is
covered by greenhouses, although the albedo data used here
have been estimated for a parcel covering the whole area. This
way, although the nal albedo of an individual greenhouse can
reach as much as 0.4, monthly and annual values were
estimated averaging all greenhouses area.
5
Model Runs. Model initialization data and boundary
conditions were obtained from NCEP/NCAR Global Rean-
alysis 1 Data, GRIB1 format, 2.5°resolution, output frequency
6 h, 17 pressure levels (100010 hPa, excluding surface). Sea
surface temperatures (SST) where updated daily during model
runs, and were obtained from National Centers for Environ-
mental Prediction/Marine Modeling and Analysis Branch
(NCEP/MMAB) Real-Time SST archives (0.5°resolution
and daily output frequency).
Two separated monthly WRF runs were carried on for the
year 2005 over the 3 nested domains, with a spinup of 15 days
each. Pasture (PS) simulations were run with default USGS
land surface parameters, but albedo was adjusted monthly in
the shrubland category, according to MODIS eld data.
5
Average monthly albedo values from MODIS eld data were
inserted prior to every run at the two scenarios, high albedo
(GH) and low albedo (PS). Greenhouses (GH) simulations
were run inserting the eld albedo values from MODIS in the
pixels where greenhouses where located in the year of
simulation. ARW-WRF 3.2.1 physics options selected are
shown in SI Table S1.
Model Validation. Model performance was validated
comparing WRF-GH output 2m-temperatures (T2) at the
selected pixel against observations of near surface air temper-
atures registered at eld station PAL (Las PalmerillasCajamar
Foundation Research Station), located at 36°48N, 2°43W,
inside the 4 ×4 km pixel at x= 11, y= 22 of the innermost
domain. Another eld station, Mojonera (MOJ) (Institute for
Research and Training in Agriculture and Fisheries IFAPA,
Junta de Andalucia) is also located inside this pixel, and lays just
1.8 km from PAL. Results were analyzed at the Almeria
International airport station (AL), 36°50N, 2°21W, 30
km from the main greenhouses development area. PAL and
MOJ stations are included in the cooperative network of the
Spanish Agencia Estatal de Meteorologia (AEMET), and AL
station belongs to the Spanish ocial meteorological network.
Raw data from both stations have been subjected to dierent
quality controls, mostly gross error checks, internal consistency,
temporal and spatial coherence. The method for model
evaluation was adapted from previous ones.
31,32
Scatter plots
between both daily and monthly observed and modeled
temperatures were used as graphical displays to elucidate
model performance. Linear regression slopes and correlation
coecients were calculated. Monthly and annual estimations of
mean bias error (MBE), normalized bias error (MNBE), mean
absolute gross error (MAGE), and normalized mean absolute
gross error (MANGE) were calculated from modeled-observed
pairs of 24 h averages. All analyses included a Student ttest at
the 0.05 signicance level. Statgraphic Plus 4.1 was the software
used for statistical analyses.
33
3. RESULTS
Analysis of MODIS data indicated a 0.09 mean annual albedo
increase from PS to GH averaged over all greenhouses farming
area.
5
Albedo increased most during the summer, with a
maximum monthly increase of +0.13 in August and September
(Table 1). The lowest albedo increase (+0.06) was observed in
the winter months of February and November.
At the greenhouses area, mean year-round surface temper-
ature was 0.25 °C cooler in the higher albedo simulation (GH)
than in the lower albedo scenario (PS), with average
temperature decreases found in all months (Figure 1), ranging
from 0.40 °C in June to 0.10 °C in December (Table 1). SI
Figure S2 shows maximum daily temperatures in summer
months (JunJulAug) for both scenarios. Mean reduction of
Table 1. Mean Monthly and Annual Changes in Albedo, Surface Air Temperature, Net Solar Radiation, and Heat Flux at
Surface
a
albedo change ΔT2(°C) ΔSWDOWN (W m2)
b
ΔHFX (W m2)
c
ΔT2/ΔSWDOWN
January +0.07 0.17 8.60 5.50 0.020
February +0.06 0.14 8.50 7.20 0.016
March +0.09 0.22 17.3 10.4 0.013
April +0.10 0.29 27.6 20.3 0.011
May +0.09 0.27 26.8 19.9 0.010
June +0.12 0.40 41.3 31.4 0.010
July +0.12 0.35 42.1 32.6 0.008
August +0.13 0.39 39.7 31.9 0.010
September +0.13 0.29 30.5 24.2 0.010
October +0.09 0.25 15.9 12.1 0.016
November +0.06 0.13 7.80 5.91 0.017
December +0.07 0.10 7.90 4.50 0.013
YEAR 2005 +0.09 0.25 22.8 17.1 0.011
a
Last column: ratio of temperature change per unit of net incoming radiation.
b
Change in net shortwave radiation.
c
Change in heat ux.
Environmental Science & Technology Article
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maximum daily temperatures in summer was 0.49 °C. The
largest decrease in daily maximum temperatures was 1.3 °Con
July 16th, one of the three hottest days of the year. Daytime
temperature dierences were roughly twice night-time dier-
ences (SI Figure S3). Additionally, results where analyzed at AL
station, 30 km from the main greenhouse development area.
As expected, the annual average temperature reduction between
GH and PS scenarios was lower than at the study site
surrounded by greenhouses (0.14 vs 0.25) (last column, SI
Table S3).
For both scenarios, mean WRF simulated annual solar
radiation (SWDOWN) reaching the surface was 223.9 W m2,
and ranged from 344 W m2in July to 106 W m2in
December. Changes to key energy budget components between
the PS and GH simulations are shown (Figure 2). As expected,
increased surface reectivity reduced net shortwave absorption
at the surface, with a mean annual decrease of 22.8 W m2
(Table 1). The largest reduction of net SWDOWN at the
surface occurred in June (42.1 W m2), and the minimum in
November (7.80 W m2). A similar pattern of seasonal change
was observed for sensible heat uxes (HFX), with a maximum
reduction in July of 32.6 W m2, and minimum in December of
4.50 W m2. Mean year-round HFX decrease was 17.1 W m2.
Latent heat (LH) changes were almost negligible, with a mean
annual change of 0.8 W m2. Changes in the long wave (LW)
radiation budget also had lower magnitudes than the shortwave
components.
The changes in the diurnal cycles of net SWDOWN and
HFX for a hot summer day (July 16th) are shown in SI Figure
S4. Changes to HFX were found during daylight but were
almost negligible at night. On July 16th, the average 24 h net
SWDOWN (349 W m2) was reduced by 41.6 W m2(albedo
was increased in the GH simulation +0.12 for July). Maximum
values for net SWDOWN and HFX were seen at noon, 120.5
Wm
2, and 80 W m2, respectively.
To validate the model, simulated 2-m surface air temper-
atures (T2) were compared with eld data from the PAL
station. No statistically signicant dierence between the
annual means of the model and observation records was
found (95.0% condence level, Studentsttest). However,
signicant dierences in standard deviations and variances were
found, showing a larger degree of dispersion of model-
estimated temperatures than of observed values (at 95%
condence level based on F-test). The scatter-plot between
observed (PAL) and WRF-GH modeled daily averages of T2 is
shown in Figure 3 (and for monthly values at SI Figure S5).
The correlation coecient was high for the daily means series
(R2= 0.92), and even higher for monthly averages comparison
(R2= 0.99). Linear regression slopes (signicant at the 0.01
level based on a Studentsttest) ranged around 1.0, with 1.11
±0.02 and 1.12 ±0.02 for daily and monthly averages,
respectively, suggesting a good match between simulated and
observed values. Warm biases are suggested from the
scatterplot for daily values above 296 K, in the summer
temperatures range (Figure 3). Dierence statistics for monthly
values, MBE, MNBE, MAGE, and MANGE are shown in SI
Table S2. Warm bias was detected in summer and spring
months (March through September), while cold bias was
shown in winter (October through February). Annual MBE
was +0.42 °C, ranging from the coldest bias in December
(0.94 °C) to the warmest bias in July (+1.69 °C).
Figure 1. WRF-simulated mean monthly 2-m surface air temperature
series in pasture and greenhouses scenarios (PS, GH), and observed
eld data from stations La Mojonera (MOJ) and Las Palmerillas
(PAL). Year 2005.
Figure 2. Mean annual change in surface energy budget components
after albedo increase from pasture to greenhouses land use, year 2005.
(HFX = Heat ux; LH = Latent heat; GRDFLX = Ground ux;
SWDOWN = Incoming SW radiation; OSW = Outgoing SW
radiation; Net SW = Net SW radiation; GLW = Incoming LW
radiation; OLW = Outgoing LW radiation; and Net LW = net LW
radiation).
Figure 3. Scatterplot and linear regression equation of mean daily
surface air temperature observations in PAL station and WRF-GH
output (high albedo scenario).
Environmental Science & Technology Article
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Additionally, model bias was calculated for AL station, showing
higher MBE (+0.64) (SI Table S3).
4. DISCUSSION
The results of our WRF simulations support our hypothesis
that the increase in albedo by greenhouses farming has been
one of the main drivers of the historical reduction in surface air
temperatures registered by eld stations. The modeled
reduction in net SWDOWN absorbed by the surface, 22.8 W
m2annual average, was similar to the observed change of
19.9 W m2found in our previous observational study,
5
derived from MODIS remote sensing data for the period
20012005. The temperature dierences between the WRF
simulations (PS and GH) varied along the annual cycle (Figure
4). Farmers whitewashgreenhouse roofs every June to
alleviate excess heat inside during summer months. The slaked
lime is later washed away at the end of September to allow
enough light to enter inside during winter growing season. A
sudden decrease of albedo in the site is shown by MODIS data
from September to October. In the simulations, the maximum
T2 dierence (June) was observed prior to the maximum
albedo dierence (August and September) when insolation is
decreasing but slaked lime still remains on top of the
greenhouses.
However, the ratio of monthly temperature to net
SWDOWN changes is not constant along the annual cycle,
suggesting a higher sensitivity of the model output to changes
in radiation in winter, and lower values in summer (Table 1).
This observation might be related to the seasonal variation in
the partition between sensible to latent heat (Bowen ratio),
with higher air moisture content in summer months.
Field data show that 2-m temperature at AL was 0.53 K
warmer than PAL over the annual cycle (SI Table S3), raising
the question: can the relative cooling in PAL compared to AL
be attributed to greenhouses development? Simulated AL was
0.71 and 0.60 K warmer than PAL in the GH and PS annual
simulations, respectively. The 0.11 dierence between the two
deltas indicates that only some of the dierence in temperatures
between AL and PAL can be explained by greenhouses
development. Additionally, observed dierences between AL
and PAL were lowest in June when simulated dierences
peaked (SI Figure S6). The mismatch in timing of observed
and simulated peak dierences between AL and PAL may be
somewhat explained by missed timing in whitewashing
activities. However, the magnitude of the dierences between
simulated and observed monthly AL-PAL temperature
gradients is larger than the modeled sensitivity to greenhouse
albedo changes, indicating that xing albedo characterizations
would not be sucient to remove the discrepancies.
The potential inuence of irrigation on temperature
reductions was intentionally not addressed in our modeling
study. The values of latent heat (LH) change obtained in our
WRF-GH output data are not the result of new para-
metrizations of evapotranspiration (ET) by crops, or the
irrigation loaded onto the farming system, but only represents
the change in simulated LH driven by albedo increase. Mean
daily measured greenhouse reference potential ET ranges from
less than 1 mm day1during winter to values of approximately
4 mm day1during summer.
3
However, the majority of
irrigation in this area occurs during the winter and spring
growing season when greenhouse farming is most active, and
drip-irrigation is the major system applied, with reduced losses
by evaporation. There is little irrigation during July and August.
Thus, the role of increased evapotranspiration from green-
houses might be less important during summer months, when
the largest temperature changes were simulated.
However, including irrigation alone will not represent all the
factors that may alter the dynamics of moist enthalpy in this
unique type of land cover change.
11,34
Land surface
representations of local pasture and greenhouses agriculture
are still far from being adequate, and many uncertainties
remain. A full assessment of all of these changes would require
Figure 4. Monthly albedo dierences and absolute values of mean air
surface temperature change from high to low albedo scenarios (GH to
PS simulations).
Table 2. Modeling Studies of Albedo Enhancement and Impact on Local Summer Temperatures (°C)
albedo enhancement at pixel
scale peak T
a
reduction one single
summer day average summer daily max T
a
reduction grid size
a
and location
this study 0.12 1.3 0.49 4 km2,Almeria (Spain)
Taha (2008)
18
0.15 2 N/A
b
5km
2Los Angeles
Sailor (2003)
17
0.1 0.140.58 N/A 2 km2U.S. cities
Synnefa et al. (2008)
20
0.4 1.5 N/A 0.67 km2Athens
(Greece)
Lynn et al. (2009)
19
0.35 12 N/A 1.3 km2New York
(U.S.)
Millstein and
Menon (2011)
21
0.020.11 0.020.5 [+0.27, 0.64] Continental U.S.
Menon et al. (2010)
14
0.01 N/A 0.03 0.5°, U.S.
Oleson et al. (2010)
15
0.58 (roofs only) 0.5 1.9°×2.5°global
Akbari et al. (2012)
16
0.01 N/A 0.010.07
c
global urban
d
a
Innermost domain of the simulation.
b
N/A = no data given.
c
Global annual temperature change (K).
d
Grid size non available.
Environmental Science & Technology Article
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further parametrization of the land surface model, particularly
of greenhouses land cover properties. However, there is an
absence of greenhouse observational data required to properly
characterize key biogeophysical and biogeochemical properties
and their representation in the land use model used for
simulations, and thus adding a detailed parametrization of
greenhouse agriculture was beyond the scope of this work. The
focus on equivalent temperature or moist enthalpy as
independent variable of these experiments is an interesting
approach for the future assessment of overall changes in moist
and heat content in the near atmosphere over the study area.
34
To estimate the net forcing caused by overall biogeophysical
and biogeochemical changes that aect mesoscale climate,
particularly changes in moist enthalpy and the seasonal
partition between sensible and latent uxes in the surface air
over the greenhouses area, a number of factors must be
considered along with irrigation
11
and are discussed further in
the SI (Table S4).
The temperature reductions obtained in our sensitivity
experiments focused on albedo changes are comparable to
other existing modeling studies for a similar range of albedo
increase. A comparison between some of these simulations and
our results for summer months is shown in Table 2. Note that
most of these studies were run only during one or a few days of
summer, as opposed to the full year modeled here. There is not
a direct linear relationship between albedo increase and
temperature reduction across locations, as local variables can
inuence this relationship. Despite these variations, and
although some of these studies are not directly comparable,
all of them oer a common overview of the potential cooling
that can be achieved by the implementation of albedo
enhancement strategies.
Besides these considerations, the results of the WRF
simulations reported here, along with the conclusion of
previous empirical research at the study site
5
support the
hypothesis that the increased albedo from greenhouse develop-
ment has been one of the main drivers of historical temperature
cooling in the area. Although these results respond to a very
particular case of albedo enhancement by land cover change,
they support the use of mesoscale meteorological modeling as a
tool for predicting the eects of solar radiation management
strategies, such as urban cool roofs, as local adaptation
measures to warming and summer heat waves. Further
improvements of land model parametrization stated above
would help identify other factors associated to this particular
land use change that might also be responsible of the observed
cooling, in addition to albedo enhancement.
Feedbacks and other inuences to the global climatic system
were not addressed here. In this case, an approximation to the
indirect climatic impact of greenhouses development, including
an estimation of the net carbon footprint of greenhouse
horticulture and CO2osets equivalence of albedo increase, has
been reported elsewhere.
9,35
ASSOCIATED CONTENT
*
SSupporting Information
Location of the study site, WRF simulated maximum daily
surface temperatures in summer months, seven days averaged
dierence in hourly temperature from GH to PS simulations,
changes in diurnal cycles of net incoming radiation and heat
ux on one summer day, scatterplot of mean monthly observed
vs simulated temperatures, and annual change in the monthly
surface air temperature dierences between two stations (PAL
and AL) for observed temperatures, for high and low albedo
simulations. Tables: physics and dynamics options used in
WRF simulations, statistical measures for WRF output
validation, comparison of simulated and observed temperatures
at two locations, land surface properties to be considered in
future research in the site. This material is available free of
charge via the Internet at http://pubs.acs.org.
AUTHOR INFORMATION
Corresponding Author
*E-mail: pcampra@ual.es.
Present Address
Ctra. Sacramento S/N Escuela Superior de Ingenieria, D.2.36.
University of Almeria, Almeria 04131, Spain.
Author Contributions
The manuscript was written through contributions of all
authors. All authors have given approval to the nal version of
the manuscript. The authors contributed equally.
Notes
The authors declare no competing nancial interest.
ACKNOWLEDGMENTS
We would like to acknowledge Surabi Menon for providing
valuable advice and resources needed for the research, and Igor
Sednev for his valuable help in building WRF architecture. The
work at Lawrence Berkeley National Laboratory was supported
by the US Department of Energy under Contract No.DE-
AC0205CH1123. The Laboratory Directed Research and
Development Program at LBNL and the DOE Atmospheric
System Research Program supported this research. Other
expenses were covered by the Program Jose Castillejoof the
Ministerio de Educación, Cultura y Deporte, Spanish Govern-
ment.
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