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Greenhouse horticulture has experienced in recent decades a dramatic spatial expansion in the semiarid province of Almeria, in southeastern (SE) Spain, reaching a continuous area of 26,000 ha in 2007, the widest greenhouse area in the world. A significant surface air temperature trend of -0.3°C decade-1 in this area during the period 1983-2006 is first time reported here. This local cooling trend shows no correlation with Spanish regional and global warming trends. Radiative forcing (RF) is widely used to assess and compare the climate change mechanisms. Surface shortwave RF (SWRF) caused through clearing of pasture land for greenhouse farming development in this area is estimated here. We present the first empirical evidences to support the working hypothesis of the development of a localized forcing created by surface albedo change to explain the differences in temperature trends among stations either inside or far from this agricultural land. SWRF was estimated from satellite-retrieved surface albedo data and calculated shortwave outgoing fluxes associated with either uses of land under typical incoming solar radiation. Outgoing fluxes were calculated from Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance data. A difference in mean annual surface albedo of +0.09 was measured comparing greenhouses surface to a typical pasture land. Strong negative forcing associated with land use change was estimated all, year round, ranging ftorn -5.0 W m-2 to -34.8 W m-2, with a mean annual value of -19.8 W m-2. According to our data of SWRF and local temperatures trends, recent development of greenhouse horticulture in this area may have masked local warming signals associated to greenhouse gases increase.
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Surface temperature cooling trends and negative radiative forcing due
to land use change toward greenhouse farming in southeastern Spain
Pablo Campra,
Monica Garcia,
Yolanda Canton,
and Alicia Palacios-Orueta
Received 4 February 2008; revised 15 May 2008; accepted 24 June 2008; published 23 September 2008.
[1]Greenhouse horticulture has experienced in recent decades a dramatic spatial
expansion in the semiarid province of Almeria, in southeastern (SE) Spain, reaching a
continuous area of 26,000 ha in 2007, the widest greenhouse area in the world. A
significant surface air temperature trend of 0.3°C decade
in this area during the period
19832006 is first time reported here. This local cooling trend shows no correlation with
Spanish regional and global warming trends. Radiative forcing (RF) is widely used to
assess and compare the climate change mechanisms. Surface shortwave RF (SWRF)
caused through clearing of pasture land for greenhouse farming development in this area
is estimated here. We present the first empirical evidences to support the working
hypothesis of the development of a localized forcing created by surface albedo change to
explain the differences in temperature trends among stations either inside or far from this
agricultural land. SWRF was estimated from satellite-retrieved surface albedo data and
calculated shortwave outgoing fluxes associated with either uses of land under typical
incoming solar radiation. Outgoing fluxes were calculated from Moderate Resolution
Imaging Spectroradiometer (MODIS) surface reflectance data. A difference in mean
annual surface albedo of +0.09 was measured comparing greenhouses surface to a typical
pasture land. Strong negative forcing associated with land use change was estimated all
year round, ranging from 5.0 W m
to 34.8 W m
, with a mean annual value of
19.8 W m
. According to our data of SWRF and local temperatures trends, recent
development of greenhouse horticulture in this area may have masked local warming
signals associated to greenhouse gases increase.
Citation: Campra, P., M. Garcia, Y. Canton, and A. Palacios-Orueta (2008), Surface temperature cooling trends and negative
radiative forcing due to land use change toward greenhouse farming in southeastern Spain, J. Geophys. Res.,11 3, D18109, doi:10.1029/
1. Introduction
[2] Anthropogenic changes to the physical properties of
the land surface can perturb the climate by altering the
Earth’s radiative energy balance, and have been regarded as
a cause of regional and even global climate change [Sagan
et al., 1979]. Furthermore, land use changes are likely to be
among the first drivers of climate change at meso- and local
scales. Surface albedo affects the shortwave radiation
budget by controlling how much incoming solar radiation
is absorbed by the surface. Because of this, changes in
surface albedo have been suspected of being the dominant
influence of mid- and high-latitude land use change on
climate [Betts, 2001]. Small changes in Earth’s albedo, even
below satellite detection limits, can lead to global temper-
ature changes equivalent to those associated with increase in
greenhouse gases [Charlson et al., 2005].
[3] Radiative forcing (RF) is a useful concept to assess
the relative influence of different human agents on climate
change [Forster et al., 2007]. The difference in outgoing
shortwave (SW) fluxes between two land uses has been
used as an estimation of observational SWRF due to land
use change [Betts, 2000]. The local SWRF due to agricul-
ture development is determined by local albedo changes,
which depend on the nature of the preexisting vegetation
replaced, but also on the reflectivity of the agricultural land.
Employing historical reconstructions of croplands, pasture
lands and primitive natural vegetation [Ramankutty and
Foley, 1999], several estimations of global RF due to surface
albedo changes from preindustrial times have been reported
[Hansen et al., 1998; Betts, 2001]. These studies simulate
the global shortwave radiation budget with radiative transfer
models within general circulation models (GCM). In an
assessment of these studies, Forster et al. [2007] concluded
a best global RF estimate of 0.2 ± 0.2 W m
, due to land
use related surface albedo change since preindustrial times.
Although the level of scientific understanding was raised
JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 113, D18109, doi:10.1029/2008JD009912, 2008
Escuela Polite´cnica Superior, Universidad de Almeria, Almeria, Spain.
Estacio´n Experimental de Zonas A
´ridas (EEZA-CSIC), Almeria, Spain.
Departamento de Edafologı´a y Quı´mica Agrı´cola, Universidad de
Almeria, Almeria, Spain.
Escuela Te´cnica Superior de Ingenieros de Montes, Universidad
Politecnica de Madrid, Madrid, Spain.
Copyright 2008 by the American Geophysical Union.
D18109 1of10
by these authors to medium-low compared to very low in
the previous IPCC report [Ramaswamy et al., 2001], still
many uncertainties rise from these estimates. On global RF
estimations relative to preindustrial or preanthropogenic
times, the biggest uncertainties depend on the characteriza-
tion of historical and present-day vegetation and surface
albedos. While there is general agreement on the albedo
associated with grassland, the data sets reveal important
differences between the albedo values associated with
forest, shrubland and cropland [Myhre and Myhre, 2003].
Myhre et al. [2005a] estimated a global RF of 0.09 W m
due to anthropogenic vegetation change since preagriculture
times to present, improving the representation of current
surface albedo by using data from MODIS surface albedo
[4] For recent land use changes at regional or local scale
these uncertainties can be overcome by observational and
satellite data available. Few satellite observational estima-
tions of RF based on anthropogenic surface albedo change
at local and regional scales have been reported, and few of
them quantify the impact of RF on surface temperature
trends. Fishman et al. [1994] reported in a field study on the
meso-scale cooling effects of high albedo sandy surfaces,
compared to surrounding areas. An average impact on the air
temperature of 12°C cooler during daytime was associated
to a mean difference in albedo of approximately 0.40, but
no RF estimations were carried out by these authors. In
another study, Nair et al. [2007] estimated observational RF
values at the top-of-the-atmosphere (TOA) associated with
clearing native vegetation for agricultural land use in
southwest Australia, using observations from the Clouds
and Earth’s Radiant Energy System (CERES). Jin and Roy
[2005] reported a positive surface RF associated with fire-
induced albedo changes over half continental Australia,
based on MODIS surface reflectance data. Myhre et al.
[2005b] used Meteosat satellite data to calculate RF for
changes in the surface albedo from burnt scars due to
biomass burning.
[5] The province of Almeria in southeastern Spain
(Figure 1) has experienced from the 1970s a rapid devel-
opment of greenhouse horticulture (GH). From the mid-
1980s, the land covered by greenhouses doubled, reaching
an area of almost 26,000 ha in 2007 [Sanjuan,2007]
(Figure 2). The coastal plain called Campo de Dalias
accounts for 70% of total greenhouse area in the province
and has become a continuous greenhouse-covered surface
of 18,300 ha in 2007. Before this farming development,
semiarid pasture communities had been replacing most
previous natural vegetation of semiarid shrubland (Rhamno
angustifoliiMayteneto europaei sigmetum association)
[Rivas-Martinez, 1987]. Favorable climatic conditions, due
to high insolation (around 3000 hours a
temperatures during the growing season (October May),
with absence of frost, have been the basis for the success
of greenhouse horticulture in this province, which still
continues at an average net growth rate of 500 ha a
[Sanjuan, 2007].
[6] Spatial patterns of temperature change for the Spanish
region have been recently described using high quality
controlled and homogenized series to elaborate the Spanish
Daily Adjusted Temperature Series (SDATS) [Brunet et al.,
2006], the 22 most reliable, longest, continuous, homoge-
nized and quality-controlled surface air temperature time
series in Spain. Brunet et al. [2007] selected these records to
generate the Spanish regional temperature series (STS),
composed of the regional mean, maximum and minimum
temperatures time series developed from the 22 daily
adjusted records. A general and highly significant warming
has been observed for the 1901 2005 and 1973 2005
periods, with STS annual mean temperature trends of
+0.13 and +0.48°C decade
, respectively. Three climate
stations surrounded by greenhouse development were
selected in the province of Almeria as representative of
GH farming area. To minimize possible impacts due to
subtle circulation changes caused by agricultural land on
temperature trends of nearby pasture area selected to deter-
Figure 1. Study site. (left) SE Spanish INM Meteorological Stations used as temperature series
controls: Murcia (MU), Granada (GR), Malaga (MA) and Almeria (AL) airports. Province of Almeria is
shown in grey color. (right) Greenhouse farmland (GH) Campo de Dalias (in white). Agroclimatic
Experimental Stations: Mojonera (MOJ) and Palmerillas (PAL).
mine SWRF, three reliable stations far enough from this
area (at least 120 Km away), and with long enough
available time series of temperature, were selected as
temperature series controls.
[7] Using an empirical approach, here we assess the
hypothesis of a causal connection between SWRF associ-
ated to land use change toward greenhouse farming, and
detected trends in local surface air temperature series of the
last twenty years. Our assumption is that change in surface
albedo because of rapid GH development has created a
response in near surface air temperature that is measurable
by weather stations that monitored the farm area throughout
the last decades, showing a significant cooling effect. In the
null hypothesis of no differential forcing, the long-term
climate trends should be very similar between greenhouse
and control stations, where no localized forcing is assumed
to occur.
[8] MODIS surface albedo data were used to estimate the
seasonal change in shortwave radiation budget between
both land uses. To minimize differences in outgoing short-
wave radiation (OSR) related to other factors than albedo
change, such as spatial variability of atmospheric turbidity
due to altitude, water vapor, ozone, or aerosols, sectors of
well-conserved shrubland adjacent to greenhouse land were
selected as representative of semiarid pasture surfaces for
albedo and radiation measurements.
2. Data and Area of Study
[9] The study area is known as Campo de Dalias,the
widest greenhouse area in the world, and is located on the
coast of the Almeria province (SE Spain) (Figure 1). It is a
coastal plain with a relatively gentle relief, limited by the
Mediterranean at the south and the Sierra de Gador range
(above 2000 m high) at the north, and occupies an area of
around 33,000 ha. Its climate is Mediterranean, with mild
winters and low annual precipitation: average annual tem-
perature and rainfall are 18.8°C and 220 mm, respectively.
Detailed description of the study area is provided elsewhere
[Castilla and Hernandez, 2005; Pulido-Bosch et al., 2000;
Fernandez et al., 2007]. Most greenhouses are called parral
type, consisting of low-cost structures covered with a flat
layer of plastic (polyethylene) and without heating equip-
ment. This type of greenhouse is considered the archetype
of the Mediterranean greenhouse agrosystem, characterized
by low technological and energy inputs [Baille,2002].
During summer months, natural ventilation is not sufficient
to extract excess of energy from the greenhouses, so farmers
usually whiten the roofs by whitewashing (painting with
slaked lime) to reduce incident radiation and avoid excess
heating and humidity of growing crops inside. At the end of
August, this slaked lime layer is removed to allow enough
solar radiation inside for winter and spring crops.
[10] Long-term temperature time series (19502006)
were obtained from meteorological stations located in
Figure 1. All stations selected are outside urban locations,
whether in airports or rural experimental stations, so urban
heat island effects can be neglected. Two agroclimatic
experimental stations in the province of Almeria were
selected as GH representative sites: Mojonera (MOJ) at
N, 2°42
W (Institute for Research and Training in
Agriculture and Fisheries IFAPA, Junta de Andalucia), and
Palmerillas (PAL) at 36°48
N, 2°43
W(Las Palmerillas–
Cajamar Foundation Research Station). These two stations
are located inside the coastal plain Campo de Dalias.
Almeria airport station (AL) is located by the sea 20 Km
east from this main greenhouse plain. Greenhouse facilities
have more recently spread at the east of this station, but it is
not completely surrounded by them as MOJ and PAL.
Granada (GR), Malaga (MA) and Murcia (MU) airports
stations, (120 km, 180 km and 170 km away from AL
station, respectively), were selected as control stations
around the GH area, assuming negligible influence of
greenhouse forcing in their climatic data. Records from
GR and MA series have been recently used to elaborate
the SDATS [Brunet et al., 2006]. No inhomogeneity
breakpoints were found by these authors in GR and MA
series for the periods considered here. GR is the only inland
station and exhibits greater continentality, as it is located
600 m and separated from the sea influence by Sierra
Nevada (3400 m high); MA, MU, AL, MOJ and PAL
stations lay next to the coast and have a milder Mediterra-
nean climate. The stations in southeastern Spain (MU, AL,
MOJ and PAL) are characterized by a more arid climate
than GR and MA. MU and AL are first order stations of the
Spanish Meteorological Office (INM), and MOJ and PAL
Figure 2. Growth of land area dedicated to greenhouse farming from 1985 to 2007 in the study site
(province of Almeria and coastal flatland Campo de Dalias) (Data from Sanjuan, 2007).
are agroclimatic stations included in the cooperative net-
work of the INM. Raw data from all stations have been
subjected to different quality controls, mostly gross error
checks, internal consistency, temporal and spatial coher-
ence. Data homogenization of series not included in the
SDATS was addressed based on available metadata, accord-
ing to WMO Guidance on Metadata and Homogeneity
[Aguilar et al., 2003]. RClimDex software has been used
for quality control and RHtest (with 5 years test window)
was carried to detect inhomogeneities in stations at the
province of Almeria. RHtest is based on a two-phase
regression model with a linear trend for the entire series
and identifies step changes in station temperature time series
[Wang, 2003]. Additionally, no statistical differences were
found between MOJ and PAL time series (Kolmogorov
Smirnov test, P> 0.05). Both GH stations lay just 1.8 Km
from each other and are highly correlated, as shown by
Pearson productmoment correlation (P< 0.05) obtained
from their first difference series.
[11] Mean annual values for each record were obtained
from monthly means based on daily maximum and mini-
mum surface air temperatures. Records for 1950 2006
were supplied by the INM for AL, MA, MU and GR. Data
from 1972 are available for these stations, but there are only
common records available from 1983 for both MOJ and
PAL. MOJ time series was obtained from IFAPA (Junta de
Andalucia), and PAL series from Cajamar Foundation, and
were selected as temperature series representative of the GH
area (Campo de Dalias). Trend values are the slopes of the
least-squares fit lines of mean annual temperatures versus
time, in units of °C decade
. All trends were tested for
statistical significance at the 95% level.
[12] In order to remove the variability common to differ-
ent data sets, difference time series were generated from
every pair of single data series, and the significance of the
trends of every difference series was then assessed. This
method isolates those differences that may be attributed to
differences in data set production methods, canceling out a
large fraction of the noise that obscures the underlying
linear trends [Wigley et al., 2006].
[13] Time series of surface reflectance at 500 m resolution
for the area of study were acquired from the MODIS
(Moderate Resolution Imaging Spectrometer) instrument
on board of the NASA Terra polar orbiting satellite for the
period 2001 to 2005. The Surface Reflectance product
(MOD09A1) provides surface spectral reflectance estimates
for bands 17 corresponding to 8 days composites remov-
ing atmospheric scattering and absorption effects [Vermote
and Vermeulen, 1999].
3. Methodology
[14] Two surface types were selected for the determina-
tion of OSR fluxes based on MODIS surface albedo data.
The whole sector Campo de Dalias was selected as repre-
sentative of greenhouse surface for OSR determination.
Currently, almost 70% of this coastal plain is covered by
greenhouses. The rest of the surface in this plain has been
intensely anthropized and it was not possible to find parcels
at MODIS resolution to represent the primitive natural
vegetation or even the last pasture cover that was cleared
from the 1970s for GH development. In order to represent
the original pasture use of this coastal plain before the
greenhouse development from the 1970s, an adjacent parcel
called ‘‘Las Amoladeras’’ was selected (centered at 36°49
), after preliminary screening of other parcels. This is a
protected and a well conserved coastal plain that lays 30 Km
from the main GH area and was chosen because its current
land use and vegetation are very similar to the replaced
pastures of Campo de Dalias.
[15] Instantaneous surface broadband albedo (a
i), repre-
sentative of an 8 day period, was obtained through the
equation proposed by Liang [2001]:
þ0:112r5þ0:018r70:0015 ð1Þ
where ris the reflectivity in the MODIS bands indicated by
the subscript. We used the instantaneous surface albedo at
the time of satellite overpass (a
) as an estimate of the daily
surface albedo (a
), as Jacob and Olioso [2005] demon-
strated that using instantaneous values at times close to the
satellite overpass in place of the daily mean albedo value
did not produce significant differences (P< 0.01). Outliers
uncorrelated with the time series and with albedo values
greater than 0.5, corresponding to cloudy days, where
identified and removed.
[16] In order to assess remote sensing albedo estimates, we
used available field estimates of albedo obtained from the two
surface types. Field measurements over the GH plastic
surface were acquired on 19 June 2005, using a GER-2600
(SpectraVista) hand-held radiometer (0.352.51 mm) cover-
ing 0.5 m
. Instantaneous directional albedos (nadir) were
estimated at midday (12:00 h) from the ratio of outgoing/
incoming radiance integral. Pasture surface albedos have
been measured in Almerı´a in a station close to our study
site (Latitude: 37°8
N, 2°22
W) between November and
December 1997 and in spring 1998 [Domingo et al., 2000],
using an albedometer placed 0.5 m above canopy (CM11;
Kipp and Zonen, Delft, The Netherlands). Data from both
types of cover were then compared with MODIS samples for
the same date of spectral measurements acquisition.
[17] Incoming shortwave radiation at the surface (ISR)
corresponding to 8 d averages was calculated daily using
the solar insolation model POTRAD, which calculates the
potential amount of radiation on a surface as a function of
elevation, latitude and longitude, solar geometry, slope and
aspect of a given site, and takes into account the influence
of the surrounding topography and atmospheric transmis-
sivity [Van Dam, 2000]. A transmissivity value of 0.6 was
used. Detailed information about clouds distribution, thick-
ness or cloud type was not available for the study area, so
clouds were not taken into account by the software. To
assess the incoming shortwave radiation at surface esti-
mated with POTRAD model, and the influence of cloud
cover in the estimation, we used daily means (8-d aver-
ages) for incoming shortwave radiation (Wm
) measured
with a pyranometer (CM 6B/7B Kipp & Zonen, Delft,
BV), in a field experimental station located 40 km distant
from the study site (Latitude: 37°8
N, 2°22
W) between
20002005. These data were then correlated with
expected insolation modeled with POTRAD for the same
site and period.
[18] The outgoing shortwave radiation OSR was estimated
by equation (2) from the incoming shortwave radiation ISR
and surface albedo a(equation (1)). Atmospheric scattering
and absorption of solar radiation of reflected light at the
surface were not taken into account in OSR calculations:
[19] Daily shortwave radiative forcing (SWRF) at the
surface due to albedo change were calculated as the differ-
ence in the daily outgoing shortwave radiation fluxes (OSR)
between the two different land use surfaces, with the
formula [Betts, 2001]:
[20] Finally, seasonal variability curves for albedo, OSR
and SWRF represent a synthetic year generated for every
date from the average of the 5 records available for the
period 20012005.
4. Results
4.1 Surface Air Temperature Trends
[21] Remarkable warming signals have been detected for
all time series available from 1972, where a clear trend
change occurs after a cooling period during the 50
s and 60
(Figure 3). Considering the period 1972 2006, control
stations GR, MA, and MU have comparable and significant
warming trends of around +0.5°C decade
(P< 0.05).
AL trend however is significantly lower, with +0.37°C
(Table 1). From the mid 80’s, a clear divergence
is shown between temperatures registered at control stations
and the two stations in the greenhouse area: MOJ and PAL.
While control series maintain high warming trends (around
+0.4°C decade
), MOJ and PAL show significant cooling
trends (P< 0.01) of 0.29 ± 0.12 and 0.32 ± 0.11°C
, respectively. No significant differences between
these two GH time series were detected (P> 0.05), showing
similar temporal evolution. AL series shows no significant
trend from 1983 (P> 0.1), and annual mean temperatures
seem to have stabilized during this period.
[22] Difference time series generated from every pair of
single data series [Wigley et al., 2006], were used to classify
the pairs of stations into three time series (1983 2005)
groups (Figure 4), indicating the similarities of the series in
every group: control, greenhouse and AL. Very significant
differences (P< 0.01) were shown only between control
(GR, MU and MA) and greenhouse stations (MOJ/PAL).
AL showed again an intermediate behavior, with lower but
significant trend differences when paired with either control
or greenhouse stations. Trend differences were not signifi-
cant among control stations difference series (P> 0.8), and
between MOJ and PAL (P> 0.5), indicating the high degree
of homogeneity of their time series.
Figure 3. Annual mean surface air temperature anomalies time series for the six stations considered. A
moving average of 2 terms has been applied to smooth the data. Anomalies are related to the reference
period 19611990. MOJ and PAL related to AL average value.
Table 1. Decadal Trends and Standard Errors (in °C decade
) of Mean Annual Surface Air Temperatures for Every Meteorological
Station and for the Periods 1972 2006 and 19832006
Ttime series MU GR MA AL MOJ PAL
1972 2006 0.54 ± 0.07 0.48 ± 0.08 0.48 ± 0.06 0.37 ± 0.06 N/A
1983 2006 0.43 ± 0.12 0.38 ± 0.17 0.40 ± 0.13 0.08
± 0.13 0.29 ± 0.12 0.32 ± 0.11
Trend values are estimated to be statistically significantly different from zero (at the 95% level).
Non available at 95% level.
Non available data.
4.2. Seasonal Variations in Surface Albedo
[23] Surface albedo values of greenhouse surface were
consistently higher than pasture values in all seasons, with
annual average values of 0.28 ± 0.05 and 0.19 ± 0.02,
respectively (Figure 5). Albedo values exhibited strong
seasonality, with a maximum value for GH of 0.35 mea-
sured in summer, and a minimum of 0.20 in winter. Pasture
surface albedo showed lower seasonal variation, from 0.22
in summer to 0.16 in winter. Biggest differences in albedo
between GH and pasture surfaces of approximately 0.15
were measured in summer, and the smallest difference of
0.05 registered in winter, with a mean annual value of 0.09.
It is noticeable the asymmetric shape of GH and difference
curves, with a step decrease from maximum summer values
and a gradual increase from winter minimum value, not
reflected in the pasture curve.
[24] A mean daily albedo value of 0.4 ± 0.06 was
obtained in the field over plastic GH cover with the
spectroradiometer at the available date. In order to compare
with MODIS daily albedo estimate, we have to take into
account that MODIS GH pixels (1 km
) include minor
portions of other types of land use (bare soil, roads, etc)
with lower reflectivity than plastic surface. Nonetheless,
when MODIS GH pixels (n = 45) with the highest propor-
tion of greenhouses cover were selected, albedo estimated
for the same date was 0.36 ± 0.04. For pasture land the
Figure 4. Trends of the difference time series between stations for the period 1983– 2006. Error bars
showing 95% confidence intervals. *Nonsignificant (P> 0.1).
Figure 5. Seasonal variations of broadband albedos of greenhouse and pasture surfaces, and for the
difference series (GH-P). Average values and for the period 2001– 2005. The temporal variations
(standard deviations) are plotted as vertical bars.
albedometer provided an average daily albedo value of
0.158 ± 0.002, for available dates [Domingo et al., 2000],
comparable to MODIS pasture estimates for the same
4.3. Seasonal Variations in Outgoing Shortwave
and SW Radiative Forcing (SWRF)
[25] Annual mean incoming SW radiation at greenhouse
surface was 195.98 W m
for the 20012005 period, with
values ranging from 86.97 W m
in winter to 298.11 W
(data not shown). Seasonal variations of diurnally
averaged OSR for greenhouse and pasture areas, as well
as the difference time series for the period of study are
represented in Figure 6. Strong differences between both
land use types were observed, with higher values over
greenhouse areas all year around due to higher albedo of
plastic cover. Mean OSR annual values were 58.4 W m
for GH and 38.5 W m
for pasture. Maximum fluxes were
detected in summer for both surfaces, with 98 W m
65 W m
for GH and pasture, respectively. OSR showed
the lowest values in winter, with 20 W m
for GH and
13 W m
for pasture. The range of seasonal variation is
much wider in GH (78 W m
) than in pasture (51 W m
[26] In Figure 6 observational SWRF due to land use
change is represented by the difference between GH and
pasture OSR averaged values for the 2000 2005 period
(plotted here with opposite sign to RF). Mean annual SWRF
was 19.8 W m
. Minimum forcing remained almost
constant (between 5 and 6Wm
) during November
and December, gradually increasing since January to a
maximum value by the end of July of 34.8 W m
. From
August, a steep decrease in the forcing is observed, falling
by the end of October next to the minimum annual values.
This asymmetry in the seasonal difference curve is deter-
mined by the asymmetric shape of both the albedo and OSR
curves for GH surface (Figures 5 and 6). This curve shape is
not depicted by the more symmetric pasture albedo and
OSR curves.
5. Discussion
5.1. Surface Air Temperature Trends
[27] Mean annual temperature trends for control time
series GR, MA and MU agree with northern hemisphere
reported warming trends for the last three decades [Brohan
et al., 2006], as well as with regional trends for Spain (STS)
and Europe [Klein Tank et al., 2002; Castro et al., 2005;
Brunet et al., 2007]. Temperature fluctuations shown in the
time series (Figure 3) are attributed to natural processes
(such as major volcanic eruptions, ENSO, QBO, etc.), and
mean short breakpoints in the long-term warming were
detected in all control stations. The most remarkable in all
series is the sudden cooling following the eruption of Mt.
Pinatubo in 1991. Nevertheless, trend differences between
controls and stations in Almeria province (MOJ/PAL/AL)
are consistent with our hypothesis that a massive growth of
greenhouse horticulture has impacted long-term trends in
surface temperatures of these farming areas. AL station is
adjacent to high albedo surfaces, and shows a weaker
forcing effect than GH stations completely surrounded by
agricultural land (MOJ and PAL). The three temperature
series in the province of Almerı´a also clearly disagree with
the pattern of variability for southeastern and eastern Spain
from 1973 to 2005 reported by Brunet et al. [2007], with
and annual trend of +0.54°Cdecade
that indicates a
strong rise in temperatures and accelerated warming over
this subregion.
5.2. Seasonal Variations in Surface Albedo
[28] Mean surface albedo value measured for GH (0.28)
is higher than previous estimates of cropland albedo at
global scale, ranging from 0.15 to 0.20 [Myhre and Myhre,
2003]. Nevertheless, our estimation was calculated for the
Figure 6. Seasonal variations of daily averaged outgoing shortwave radiation fluxes (OSR) reflected
from greenhouse, pasture and the difference series (-SWRF) between surfaces for the 2001 2005 period.
The temporal variations (standard deviations) are plotted as vertical bars.
whole coastal plain of Campo de Dalias, and there is a wide
range of variation depending on the parcel selected (data not
shown). Most important variability in GH albedo depend on
whether annual whitewashing of the plastic surface had
been applied or not. Smaller GH parcels screened (data not
shown) where whitewashing had been fully applied, showed
the maximum mean annual albedo values of 0.32 ± 0.03,
but were not considered representative of the whole GH
area selected (Campo de Dalias), that includes small
fractions of other types of land uses apart from greenhouses,
such as urban cover or abandoned farmland.
[29] The observed asymmetry in the shapes of GH albedo
and OSR curves (Figures 5 and 6) is probably attributable to
the annual timing of the whitewashing of the plastic covers
carried out regularly by farmers. Whitewashing is performed
during summer to prevent summer crops from damage
caused by insolation excess. After summer, the slaked-lime
is washed out to get adequate radiation conditions during
the last stage of winter crops (JanuaryFebruary) and the
crops change.
[30] Mean annual surface albedo of the pasture area
selected (0.19) was inside the range of values for shrubland
previously reported at global scale (0.16 0.29) [Myhre and
Myhre, 2003]. In preliminary estimations of surface albedo
of other pasture parcels screened nearby the GH area, a
range of 0.13 to 0.19 was measured depending on surface
reflectance, but we selected our representative parcel of
study according to higher similarities with past pastures
cleared for GH development in the coastal plain. Clearing of
pasture land for GH development follows the maximum
pattern previously reported for the increase in the surface
albedo in the Northern Hemisphere midlatitudes, consider-
ing anthropogenic vegetation changes from preagriculture
times to present [Myhre and Myhre, 2003], particularly
evident in eastern Europe and the eastern United States
caused by the conversion of forest to cropland. In our area
of study, the measured increase of the annual mean surface
albedo of +0.09 is similar to the maximum values calculated
at global scale (around +0.10) [Betts, 2001]. Therefore,
extensive white plastic cover has a comparable effect on
the differences in mean annual albedo as long-lasting snow
cover at high latitudes exerts related to previous forest
coverage. On the contrary, this increase in GH albedo is
opposite to the decrease in the farmland surface albedo of
approximately between 0.02 and 0.01 simulated for
Mediterranean latitudes in those studies, related to preagri-
culture times.
5.3. Seasonal Variations in Outgoing Shortwave
and SW Radiative Forcing (SWRF)
[31] The magnitude of localized SWRF due to GH devel-
opment over the last decades reported here (19.8 W m
is considerably greater than most previous computations of
simulated global mean RF due to land use change over the
past [Hansen et al., 1998; Betts, 2000, 2001; Myhre et al.,
2005a]. Although it has been considered 0.2 W m
good estimation for this global forcing since preindustrial
times [Forster et al., 2007], most of these global simulations
show a very high degree of spatial variability, with regions
showing the strongest local negative RF (5Wm
) found
in the major agricultural areas of North America and
Eurasia. In some of these estimations, the increase in surface
albedo due to long-lasting winter snow cover in northern
deforested latitudes is again responsible for the maximum
negative RF estimated values (10 W m
)[Myhre et al.,
2005a]. Mean annual SWRF due to GH development
(19.8 W m
) almost doubles the magnitude of this global
maximum, thus reflecting the relative strength of the local-
ized forcing over the last decades in the area of study.
Furthermore, GH albedo change maximize in the period
with maximum solar radiation (Figure 5) while deforesta-
tion at northern latitudes has a maximum albedo change
when solar radiation has its minimum (G. Myhre, personal
communication, 2008).
[32] Our observational estimation largely offsets the pos-
itive forcing of approximately between +2 and +6 W m
assigned to this region in global simulation studies from
preagriculture times, and of course, the global forcing
relative to preindustrial times exerted by greenhouse gases,
estimated at +2.3 W m
[Hansen et al., 1998]. In one of
the few related studies on observational estimation of
forcing associated with land use change at regional scale
to date [Nair et al., 2007] an observational estimate of mean
annual SWRF of 7.0 W m
was reported in Southwest
Australia, due to land use change for agricultural purposes,
considering that half of the whole area of study had been
cleared. These authors estimated a maximum SWRF value
of 13.9 W m
in case 100% of the land was cleared.
Though our SWRF estimate refers to a 70% GH cover,
alternative forcing measurements in minor parcels with an
almost complete coverage of GH reached the strongest
SWRF of 30.2 W m
(data not shown).
[33] As stated before [Myhre and Myhre, 2003], the most
important source of uncertainty in the estimation of RF due
to land use change is the correct characterization of surface
albedo, that depends on both the pasture vegetation and soil,
and the reflectance of the plastic surfaces to be compared. In
this case, the selection of the parcels representative of
preexisting pasture land cover cleared for GH development
and the variation in albedo due to the heterogeneity of
whitewash surface can extent the range of mean annual
SWRF from 19 W m
to a maximum of 37 W m
(data not shown). The degree of vegetation cover of the
pastures studied for SWRF estimation, varying from shrub-
land to grassland, is in great part responsible for this
variability. Nevertheless, we considered GH and pasture
parcels selected as the most representative of both land uses,
although they yielded the weaker negative SWRF of all
pairs of parcels compared in preliminary screening.
[34] Another source of uncertainty is the temporal
variability of incoming SW radiation observed with instru-
mental data due to cloudiness or changes in atmospheric
conditions. This temporal variability, as represented by the
average of standard error for each date during the recorded
period, represents a small percentage of the mean annual
incoming shortwave radiation at this region (4.75 %). High
correlation was found between field measures and
POTRAD modeled insolation series for clear sky conditions
(Pearson-correlation coefficient = 0.97; Root Mean Square
Error = 16.93 Wm
; Mean Annual Error = 3%, expressed
as a percentage of the mean of n = 46 dates). Therefore, it
can be assumed that the level of uncertainty due to cloud-
iness in SWRF estimates using the POTRAD model is low.
[35] While there could be a strong correlation between the
decrease in temperature records and the increase in SWRF
due to GH development, this does not necessarily imply that
albedo change is the main causative factor of the observed
trends, as reflectivity alterations are not the only effect of
land use change on climate. Local climate sensitivity to GH
forcing needs further studies to be determined. Related
cooling effects of historical land use change toward
higher-albedo surfaces have been simulated [Brovkin et al.,
1999; Betts, 2001], suggesting that albedo difference is the
main driver of temperature change in temperate agricul-
tural regions. Although global mean climate response can
be small due to a weak global albedo forcing, the
response can be remarkable in some regions, as can be
seen when spatial distribution of this forcing is considered
[Hansen et al., 2005]. Through these models, annual mean
temperatures 12 K lower than natural vegetation have
been simulated for some agricultural regions, in response
to increases in surface albedo of +0.1, comparable to GH
development increase reported here. In those cases, the
main vegetation change was the conversion of forest to
cropland in high latitudes, where snow-covered areas have
much higher surface albedo over open land (as cropland)
than in forested areas.
[36] Previous observational studies show a dominant
influence of high albedo surfaces on local surface temper-
ature trends [Fishman et al., 1994]. Christy et al. [2006]
have reported the darkening and moistening of formerly dry
high-albedo surface in semiarid environments as the main
cause of increase in surface temperatures caused by farming
development in California San Joaquin Valley. In our case,
however, the change is an increase in surface albedo, and
though the influence of irrigation under a plastic surface still
remains undetermined, cooling temperature trends indicate
that it probably has little impact compared to negative
forcing exerted by increased surface reflectivity.
6. Conclusions
[37] Our results show that, at local and meso-scale,
greenhouse farming is very likely the most powerful driver
of climate change in the area of study, probably due to the
dramatic increase in surface albedo of the highly reflective
plastic cover over a widespread agricultural area, which
largely offsets positive forcing (+2 W m
) very probably
induced by global increase in greenhouse gases [Forster et
al., 2007]. The main general implication of these findings is
to highlight the importance of human development of high
albedo surfaces in the strategies of mitigation and adaptation
to global warming at local scale. However control stations
records outside the GH area show that little or no effects on
surface temperature extend far from the high albedo area, so
the forcing caused by greenhouse development seems to be
very localized.
[38] Although other climate change agents out of the
scope of this work cannot be ruled out, the attribution of
the temperature cooling trend in GH area to a negative
radiative forcing due to change in surface albedo is strongly
supported by our analyses of satellite data. The most likely
explanation is that higher surface albedo reduces net
incoming shortwave energy, and therefore diminishes
the energy absorbed by the surface emitted as longwave
radiation, resulting in lower surface skin temperature, as well
as a lower transfer of sensible heat over greenhouses with
respect to pasture cover. The lower surface temperature, and
the decrease in the total available energy at the surface that
needs to be dissipated, generates the cooling trend detected in
the near-surface air temperatures in this farming area
[39] Further analyses must be undertaken to establish or
refute causality between SWRF and temperature trends
discussed here. The purpose of this work is to present the
first empirical evidences of this causal connection through
an estimation of SW budget inside and outside the GH area,
but other significant feedbacks to the atmosphere from
changes in the cover of terrestrial surface by greenhouse
farming still remain to be investigated. Model-simulations
and radiative transfer calculations including constraints
arising from high albedo GH surfaces at the temporal and
spatial scale of this study should be carried out in order to
corroborate our results by comparison of expected
responses to detected temperature trends. However evalua-
tion of net radiation and soil heat transfer at daily scales,
and quantification of the turbulent fluxes (sensible and
latent heat), are necessary to fully determine how the
surface energy balance is affected by the changes in cover:
[40] Uncertainties in the local energy budget must be
reduced with the determination of longwave fluxes, and net
radiative forcing due to short plus longwave differences
between both land uses has yet to be quantified. Neverthe-
less, it is important to notice that when comparing RF
values from earlier estimates, it has been assumed in this
work that net forcing is dominated by the shortwave
component and that land use changes do not significantly
impact the TOA longwave fluxes [Nair et al., 2007].
[41] The relative influence on local climate of other
physical changes must be explored. The land use climate
forcing that we have estimated here does not fully represent
GH land use effects, as there are other changes in surface
properties affecting the surface energy balance that have not
been considered. For instance, eco-physiological and aero-
dynamic changes and alterations of roughness still remain
undetermined. The complex role of evapotranspiration as-
sociated to this drip-irrigated soil under a plastic cover must
be investigated [Fernandez et al., 2007]. Cooling effect of
higher albedo could have been enhanced by the increase in
latent heat flux derived from irrigation within the green-
houses (released as water vapor by greenhouses ventilation),
with respect to previous pasture cover, further reducing
sensible heat transfer and surface air temperature. On the
contrary, irrigation might also cause a positive forcing by
the increase in water vapor in the lower atmosphere
[Boucher et al., 2004; Christy et al., 2006].
[42] In order to assess the net influence of greenhouse
farming on local climate, the role of annual biomass growth
as carbon sink must be quantified and expressed as RF
[Betts, 2000]. While forestation at northern latitudes and
most conventional crops are generally associated to positive
forcing by reduction in surface albedo, greenhouse devel-
opment in semi-desert surfaces exert a negative forcing that
is probably further increased by the forcing caused by
carbon sequestration of these highly productive crops.
[43] Even the RF concept might not be the most appropri-
ate concept in our case, so that other alternative metrics
[Pielke et al., 2002] could be advisable to estimate and model
the net impact on the local climate of GH development.
[44]Acknowledgments. We thank the INM (Spanish National
Institute of Meteorology), Cajamar Foundation, and IFAPA (JJAA) for
providing climatic data. This work received financial support from several
different research projects: PROBASE (CGL2006-11619/HID), funded
by the Spanish Ministry of Education and Science; AQUASEM (P06-
RNM-01732), funded by the Regional Government of Andalucia; DESIRE
(Desertification, mitigation and remediation of land), funded by the
European Commission.
Aguilar, E., I. Auer, M. Brunet, T. C. Peterson, and J. Wieringa (2003),
Guidelines on climate metadata and homogenization, WCDMP-No. 53,
WMO-TD No. 1186, World Meteorological Organization, Geneva.
Baille, A. (2002), Trends in greenhouse technology for improved climate
control in mild winter climates, Acta Hort.,559, 161 – 167.
Betts, R. A. (2000), Offset of the potential carbon sink from boreal foresta-
tion by decreases in surface albedo, Nature,408, 187 – 190.
Betts, R. A. (2001), Biogeophysical impacts of land use on present-day
climate: near-surface temperature change and radiative forcing, Atmos.
Sci. Lett.,2, 39 – 51, doi:10.1006/asle.2001.0023.
Boucher, O., G. Myhre, and A. Myhre (2004), Direct human influence of
irrigation on atmospheric water vapour and climate, Clim. Dyn.,22,
Brohan, P., J. J. Kennedy, I. Haris, S. B. F. Tett, and P. D. Jones (2006),
Uncertainty estimates in regional and global observed temperature
changes: A new dataset from 1850, J. Geophys. Res.,11, D12106,
Brovkin, V., A. Ganapolski, M. Claussen, C. Kubatzki, and V. Petoukhov
(1999), Modelling climate response to historical land cover change,
Global Ecol. Biog.,8, 509 – 517.
Brunet, M., O. Saladie, P. D. Jones, J. Sigro, A. Moberg, E. Aguilar,
A. Walther, D. Lister, D. Lopez, and C. Almarza (2006), The development
of a new daily adjusted temperature dataset for Spain (1850– 2003),
Int. J. Clim.,26, 1777 – 1802.
Brunet, M., et al. (2007), Temporal and spatial temperature variability
and change over Spain during 1850 2005, J. Geophys. Res.,112,
D12117, doi:10.1029/2006JD008249.
Castilla, N., and J. Hernandez (2005), The plastic greenhouse industry in
Spain, Chronica Hort.,45, 15 – 20.
Castro, M., J. Martı´n-Vide, and S. Alonso (2005), El clima de Espan˜a:
pasado, presente y escenarios del clima para el siglo XXI, in Evaluacio´n
Preliminar de los Impactos en Espan˜ a por Efecto del Cambio Climatico.
J. M. Moreno (Coord.), Ministerio de Medio Ambiente, Madrid, Spain.
Charlson, R. J., F. P. J. Valero, and J. H. Seinfeld (2005), In search of
balance, Science,308, 806 – 807.
Christy, J. R., W. B. Norris, K. Redmon, and K. P. Gallo (2006),
Methodology and results of calculating central California surface
temperature trends: Evidence of human-induced climate change, J. Clim.,
19, 548 – 563.
Domingo, F., L. Villagarcı´a, A. J. Brenner, and J. Puigdefabregas (2000),
Measuring and modelling the radiation balance of a heterogeneous shrub-
land, Plant Cell Environ.,23, 27 – 38, doi:10.1046/j.1365-3040.
Fernandez, M. D., A. M. Gonzalez, J. Carren˜ o, C. Perez, and S. Bonachela
(2007), Analysis of on-farm irrigation performance in Mediterranean
greenhouses, Agric. Water Manage.,89, 251 – 260.
Fishman, B., H. Taha, and H. Akbari (1994), Mesoscale Cooling Effects of
High-Albedo Surfaces: Analysis of Meteorological Data from White
Sands National Monument and White Sands Missile Range, Lawrence
Berkeley Laboratory report No. 35056, Heat Island Group Reports,
Lawrence Berkeley National Laboratory, Berkeley, CA.
Forster, P., et al. (2007), Changes in atmospheric constituents and in
radiative forcing, in Climate Change 2007: The Physical Science Basis.
Contribution of Working Group I to the Fourth Assessment Report of the
Intergovernmental Panel on Climate Change, edited by S. Solomon et al.,
pp. 131 217, Cambridge Univ. Press, Cambridge, U. K.
Hansen, J., M. Sato, A. Lacis, R. Ruedy, I. Tegen, and E. Matthews (1998),
Climate forcings in the Industrial Era, Proc. Natl. Acad. Sci. U. S. A.,95,
12,753 – 12,758.
Hansen, J., et al. (2005), Efficacy of climate forcings, J. Geophys. Res.,110,
D18104, doi:10.1029/2005JD005776.
Jacob, F., and A. Olioso (2005), Derivation of diurnal courses of albedo and
reflected solar irradiance from airborne POLDER data acquired near solar
noon, J. Geophys. Res.,110 , D10104, doi:10.1029/2004JD004888.
Jin, Y., and D. P. Roy (2005), Fire-induced albedo change and its radiative
forcing at the surface in northern Australia, Geophys. Res. Lett.,32,
L13401 doi:10.1029/2005GL022822.
Klein Tank, A., J. Wijngaard, and A. van Engelen (2002), Climate of
Europe: Assessment of Observed Daily Temperature and Precipitation
Extremes, 36 pp., Royal Netherlands MeteorologicaI Institute, De Bilt,
Liang, S. L. (2001), Narrowband to broadband conversions of land surface
albedo I algorithms, Remote Sens. Environ.,76, 213 – 238.
Myhre, G., and A. Myhre (2003), Uncertainties in radiative forcing
due to surface albedo changes caused by land-use changes, J. Clim.,16,
1511 – 1524.
Myhre, G., M. M. Kvalevaq, and C. B. Schaaf (2005a), Radiative forcing
due to anthropogenic vegetation change based on MODIS surface albedo
data, Geophys. Res. Lett.,32, L21410, doi:10.1029/2005GL024004.
Myhre, G., Y. Govaerts, J. M. Haywood, T. K. Berntsen, and A. Lattanzio
(2005b), Radiative effect of surface albedo change from biomass burning,
Geophys. Res. Lett.,32, L20812, doi:10.1029/2005GL022897.
Nair, U. S., D. Ray, J. Wang, S. A. Christopher, T. J. Lyons, R. M. Welch,
and R. A. Pielke (2007), Observational estimates of radiative forcing due
to land use change in southwest Australia, J. Geophys. Res.,112,
D09117, doi:10.1029/2006JD007505.
Pielke, R. A., G. Marland, R. A. Betts, T. N. Chase, J. L. Eastman, J. O.
Niles, D. Niyogi, and S. W. Running (2002), The influence of land-use
change and landscape dynamics on the climate system: Relevance to
climate-change policy beyond the radiative effect of greenhouse gases,
Phil. Trans. R. Soc. Lond.,360, 1 – 15.
Pulido-Bosch, A., P. Pulido-Leboeuf, L. Molina-Sanchez, A. Vallejos, and
W. Martin-Rosales (2000), Intensive agriculture, wetlands, quarries and
water management. A case study (Campo de Dalias, SE Spain) Environ.
Geol.,40, 163 – 168.
Ramankutty, N., and J. A. Foley (1999), Estimating historical changes in
global land cover: Croplands from 1700 to 1992, Global Biogeochem.
Cycles,13, 997 – 1027.
Ramaswamy, V., et al. (2001), Radiative forcing of climate change, in
Climate Change 2001: The Scientific Basis. Contribution of Working
Group I to the Third Assessment Report of the Intergovernmental Panel
on Climate Change, edited by F. Joos and J. Srinivasan, pp. 350 – 416,
Cambridge Univ. Press, Cambridge, U. K.
Rivas-Martinez, S. (1987), Mapa de las series de vegetacion de Espan˜a,
ICONA, MAPA, Madrid.
Sagan, C., O. B. Toon, and J. B. Pollack (1979), Anthropogenic albedo
changes and the Earth’s climate, Science,206, 1363 – 1368.
Sanjuan, J. F. (2007), Deteccion de la superficie invernada en la provinciade
Almeria a traves de ima´genes Aster, edited by I. M. Cuadrado-Gomez,
Fundacion para la Investigacion Agraria de la Provincia de Almeria,
Van Dam, O. (2000), Modelling incoming Potential Radiation on a land
surface with PCRaster, POTRAD5.MOD manual, Utrecht Centre for
Environment and Landscape dynamics, Utrecht University, Utrecht.
Vermote, E. F., and A. Vermeulen (1999), Atmospheric correction
algorithm: Spectral reflectances (MOD09), ATBD version 4.0.
Wang, X. L. (2003), Comments on detection of undocumented change-
points: A revision of the two-phase regression model, J. Clim.,16,
3383 – 3385.
Wigley, T. M. L., V. Ramaswamy, J. R. Christy and J. R. Lanzante (2006),
Statistical issues regarding trends, in Temperature Trends in the Lower
Atmosphere: Steps for Understanding and Reconciling Differences,
edited by T. R. Karl et al., p. 136, A Report by the Climate Change Science
Program and the Subcommittee on Global Change Research, Washington,
D. C.
P. Campra, CITE II D.27, Universidad de Almeria, Carretera Sacramento
s/n. La Canada de San Urbano, 04120 Almeria, Spain. (
Y. Canton, Departamento de Edafologı´a y Quı´mica Agrı´cola, EPS D.
1.48, Universidad de Almeria, Carretera Sacramento s/n. La Canada de San
Urbano, 04120 Almeria, Spain.
M. Garcia, Estacio´n Experimental de Zonas A
´ridas-CSIC, General
Segura, 1; Almeria 04001, Spain.
A. Palacios-Orueta, Departamento de Silvopascicultura, Escuela Te´ cnica
Superior de Ingenieros de Montes, Universidad Politecnica de Madrid,
Ciudad Universitaria s/n. 28040 Madrid, Spain.
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... Its application has increased with an average annual growth rate of about 6% according to statistics from the Chinese Agricultural Yearbook and National Bureau of Statistics of China (Xiong et al. 2019), and plastic-mulchcovered croplands has already become a new surface characteristic in the arid and semiarid regions of China. Meanwhile, plastic mulch can also alter surface albedo and the radiation balance (Graefe and Sandmann 2015;Bonachela et al. 2020b); change the energy exchange process between the ground surface and the atmosphere (Tarara 2000;Wang et al. 2019;Bonachela et al. 2020b;Zhao et al. 2021); and further influence ecological, biophysical, and plant physiological processes, as well as regional and global climate through atmospheric circulation (Tooming 2002;Campra et al. 2008;Chen et al. 2019). As a result, the physical processes of the land-atmosphere interactions within film-mulched agroecosystems have also attracted more scholarly attention lately (Bonachela et al. 2020b;Jones et al. 2021;Ochege et al. 2022). ...
... reduction in summertime surface air temperature. Therefore, accurate estimation of surface albedo is important in quantifying surface radiation transfer and energy budget in ecohydrological models (Giambelluca et al. 1999;Iziomon and Mayer 2002;Campra et al. 2008;Graefe and Sandmann 2015;Bonachela et al. 2020a,b), and numerical weather forecasting and climate predictions (Yang et al. 2012;Wu et al. 2020). ...
In partial plastic mulch-covered croplands, the complicated co-existence of bare soil surface, mulched soil surface, and dynamically changing canopy surface results in challenges in accurately estimating field surface albedo ( α ) and its components (bare soil surface albedo, α b ; mulched soil surface albedo, α m ; and canopy surface albedo, α c ) during the whole growth period. To accurately estimate α , α b , α m , and α c , and to quantify the three surfaces’ contributions to field shortwave radiation reflections ( F b , F m , F c ), (1) a modified two-stream (MTS) approximation solution that considered the effect of plastic mulch has been proposed to accurately estimate α; (2) dynamic variations of α b , α m , and α c , and F b , F m , F c have been characterized. Therein, α b and α m were determined from corresponding parameterization schemes, α c is determined using mulched irrigated croplands surface albedo (MICA) relationship between α and α b , α m , and α c that established in this study. Results indicated that: (1) compared with measurements, considering the effect of plastic mulch will significantly improve estimation of α when ground surface is not fully covered by crop canopy, while not will underestimate α by a mean value of 0.061 in the early growth period; (2) mean values of α , α b , α m , and α c during the whole growth period were 0.198, 0.174, 0.308, and 0.160, respectively, while the corresponding F b , F m , and F c were 0.08, 0.42, and 0.50, respectively.
... Optically thick cirrus clouds have high albedo, which produces negative radiative forcing, and the albedo effect cools the atmosphere (Jensen et al. 1994;McFarquhar et al. 2000;Fu and Liou 1993;. The degree and extent of greenhouse or albedo effects will lead to significant atmospheric differential heating and cooling on vertical as well as horizontal scales and appear to have a profound influence on synoptic and regional weather systems (Liou 1986;Forster et al. 2007;Campra et al. 2008). For wellmixed greenhouse gases, a positive radiative forcing implies global warming (Ramanathan and Collins 1991;Hansen et al. 1997). ...
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Cirrus clouds are highly reflective clouds that play an important role in the atmospheric radiative balance and contribute to climate change. We present the seasonal distribution of cirrus cloud occurrence, characteristics and evolution over a coastal station (Goa, 15.4°N, 73.8°E, 40 m above MSL) in India using ground-based micro pulse lidar and radiosonde observations from July 2013 to June 2015. The frequency of cirrus occurrence was approximately 44%, 33%, 17% and 6% in winter (JF), premonsoon (MAM), southwest monsoon (JJAS) and postmonsoon season (OND), respectively. Thicker cirrus was more frequent in September, with an average value of > 1.7 ± 0.89 km. The frequency of cirrus descent occurs almost similarly in monsoon and postmonsoon (42% and 43% respectively). Two extreme cirrus descending cases were observed during the monsoon: (1) on 22 August 2014 with a displacement of 9.6 km from the initial height of 14 km with a descending rate and geometrical thickness of 0.4 ms⁻¹ and 1.5 km, respectively, and (2) on 14 September 2013 with a displacement of 7.8 km with descending rate and thickness of 0.2 ms⁻¹ and 2.3 km respectively. Relatively high humidity (> 60%) and low (< − 20 °C) ambient temperature caused thick cirrus formation in September 2013. However, during August 2014 event, relatively thinner cirrus was observed, and the same is attributed to lower humidity conditions (45 to 60%). The wind shear associated with the tropical easterly jet (TEJ) plays a major role in cirrus displacement by modifying their vertical velocity. The positive and negative vertical velocity fields cause cirrus to have a descending shape. The gradual descending pattern of cirrus is moving parallel to the vertical velocity contour, while the rapid descending in 2014 was mainly due to the occurrence of cirrus perpendicular to the velocity contour. Overall, this study highlights the descending nature of cirrus clouds over a coastal station in India, which can impact surface radiative characteristics.
... They needed to be considered. Apart from that, thermal environments also varied for contextual factors, such as openness (SVF) [45] and albedo [46]. Four physical factors were considered for the TCP exploration: TCD, LAI, SVF, and albedo. ...
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Residents were suffering from climatic issues resulting from global warming and urban heat islands (UHI). Researchers have explored ways of mitigating these issues. They have discovered several factors that adjust micro-climate, including vegetation. Vegetation, especially trees, can significantly mitigate heat stress, often by providing canopied spaces. However, the temperature differences between various points under individual trees have rarely been investigated. The present study aimed to determine these temperature distribution patterns. A new concept, the tree cooling pond effect (TCP), was proposed and defined in a similar way to UHI. The level of TCP was represented by the mean radiant temperature (MRT) difference between four points in line with the direction of tree shade (A, next to the trunk; B, the midpoint between A & C; C, the margin of the shade; and D, 1 m away from C and in the sunshine). The MRT was measured and shown to increase slightly when moving from A to C, with a sharp increase between C and D. Physical characteristics of the trees, especially the tree crown diameter (TCD), impacted the incremental change (∆MRT) significantly. Through linear regression, it was found that ∆MRT was polynomially correlated with tree characteristics; e.g., TCD and distance from the trunk. For a tree with a TCD of 16.6 m, the ∆MRT between Point A and Point D was up to 18°C; this result indicates that trees had insignificant cooling effects on the unshaded area (in the sunshine) despite neighbouring it. This study represents an initial effort; it visually illustrate tree cooling by identifying several critical points to delineate the pond, which has rarely been considered in previous studies.
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Greenhouse cultivation has been expanding rapidly in recent years, being crucial for food security but raising environmental concerns. Yet, currently little knowledge exists on its global extent and possible drivers of the expansion. Here, we present a global assessment of greenhouse cultivation and map 1.3 million hectares of greenhouse infrastructures in 2019 using commercial satellite data at 3 m resolution, including both large and small scale greenhouse infrastructure. We show that only 61% are concentrated in large greenhouse clusters, and that the remaining 39% are small-scale greenhouse cultivation, which are challenging to detect with public satellite data. By studying the temporal development of the 65 largest clusters (> 1500 ha), we show a surge in greenhouse cultivation in the Global South since the early 2000s, including a dramatic increase in China, which accounts for 60% of the global coverage. Our assessment raises awareness that the true extent of areas polluted by greenhouse plastic is much larger than previously thought, with wide-ranging implications on environmental and socioeconomic conditions.
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The micrometeorological elements, radiation budget, and surface energy distribution at four sites with land cover types of vegetable, orchard, maize, and desert in the Heihe River basin (HRB) from June 2012 to September 2012 are compared to investigate the differences in the land–atmosphere interaction between different surface types and the biophysical effects of land use and land cover change on surface temperature. The desert site has the highest soil surface temperature during both daytime and nighttime. The strongest cooling effects of maize, orchard, and vegetable are −20.43, −19.35, and −16.42 K, respectively, during daytime, and the average cooling effects are −1.38, −2.52, and −0.93 K, respectively, at nighttime. The differences in the surface cooling effects of the non-desert sites relative to the desert are attributed to the differences in albedo and incoming shortwave radiation, emissivity and incoming longwave radiation, sensible heat flux, latent heat flux, and soil surface heat flux, according to the direct decomposed temperature metric theory. The radiation terms have negative feedbacks on the cooling effects in the non-desert sites. Latent heat flux plays a key role in the differences in the surface temperature among the four sites during both daytime and nighttime, and the soil surface heat flux is also a main factor at night.
Greenhouses are an important part of modern facility-based agriculture. While creating well-being for human society, greenhouses also bring negative impacts such as air pollution, soil pollution, and water pollution. Therefore, it is of great significance to obtain information such as the area and quantity of greenhouses. It is still a challenging task to find a low-cost, high-efficiency, and easy-to-use method for the dual extraction of greenhouse area and quantity on a large scale. In this study, relatively easy-to-obtain high-resolution Google Earth remote sensing images are used as the experimental data source, and an area and quantity simultaneous extraction framework (AQSEF) is constructed to extract both the area and quantity of greenhouses. The AQSEF uses UNet and YOLO v5 series networks as core operators to complete model training and prediction, and main components such as SWP, OSW&NMS and GCA complete data postprocessing. To evaluate the feasibility of our method, we take Beijing, China, as the research area and select multiple accuracy evaluation indicators in the two branches for accuracy verification. The results show that the mIoU, OA, Kappa, Recall and Precision with the best performance model in the area extraction branch can reach 0.931, 0.987, 0.867, 0.91 and 0.914, respectively. Additionally, the Recall, Precision, AP@0.5 and mAP@0.5: 0.95 values of the best performance model are 0.781, 0.891, 0.812 and 0.509, respectively, in the extraction of the quantity of greenhouses. Finally, in Beijing, the area covered by greenhouses is approximately 85.443 km2, and the quantity of greenhouses is approximately 155,464. With the proposed method, the time consumed for area extraction and quantity extraction is 6.73 h and 12.97 h, respectively. The experimental results show that AQSEF helps to overcome the spatiotemporal diversity of greenhouses and quickly and accurately map a high-spatial-resolution greenhouse distribution product within the research area.
This paper analyzed observations from the Great Plains Irrigation Experiment (GRAINEX) to better understand L-A interactions and PBL evolution. This study is focused on a day when the largest forcing on the boundary layer originated from the land surface/land use. To examine these impacts, we also applied the Weather Research and Forecasting (WRF) model. Results from the observations show that compared to non-irrigated areas, air temperature, wind speed, and PBL height were lower while dew point temperature and latent heat flux were higher over irrigated areas. Findings suggest that entrainment layer drying and differences in energy partitioning over irrigated and non-irrigated areas played an important role in PBL evolution. In the final hours of the day, the PBL collapsed faster over non-irrigated areas compared to irrigated. The WRF model simulations agree with these observations. They also show that the extent of irrigation (expressed as irrigation fraction or IF) in an area impacts L-A response. Under ∼60% IF, the latent heat flux and mixing ratio reach their highest value while temperature and PBLH are at their lowest, and sensible heat flux is near its lowest value. Results are reversed for ∼2% IF. It is concluded that irrigation notably impacts L-A interactions and PBL evolution.
Urbanization has changed the Earth’s surface, resulting in the urban heat island effect. There has been a recent focus on increasing urban albedo as a strategy to mitigate this phenomenon. Studies on Montreal’s albedo have primarily looked at the impact of albedo manipulations upon the urban heat island effect. However, the current albedo of the island, broken down by land use type, has yet to be quantified. Therefore, previous studies often rely on generalized urban albedo and land use estimates that have not been proven to be generalizable to Montreal. This study attempted to quantify the current albedo of the Island of Montreal through urban land use categorization. The findings were then used to estimate albedo increase under different roof replacement scenarios. Data sets for building footprints, vegetation, and roadways were incomplete in Montreal, requiring the combination of several sources to obtain representative data for analysis. This study found the albedo of Montreal island to be 0.19 ± 0.057. Further, the hypothetical roof change scenarios then aligned with a 0.1 albedo increase, which is the albedo change used in current urban heat island effect mitigation literature. Using the albedo increase potential that resulted from the three scenarios tested here, future research should explore further estimation of the associated surface and air temperature decrease.
Greenhouse crops in mild winter climates cannot be grown all year round and their yield does not fulfil the quality standards because of inadequate climatic conditions prevailing in the rudimentary shelters used as greenhouse. In order to alleviate the strong heat load and consecutive plant stress during summer, it is necessary to improve greenhouse design and control of the inside climatic variables. Technological solutions are presently available but are often considered, rightly or not, as too expensive by the growers. Therefore, the basic problem can be defined as an optimisation one, i.e. how to find a compromise between the two extreme cases represented by the rudimentary shelters of mild-winter countries and the expensive high-tech glasshouses of North-Europe. The first part of the paper addresses this issue and focuses on the knowledge and methodology necessary for finding this compromise. The determination of the best cost-effective solution is difficult due to the incomplete knowledge on the mean and long-term crop plant response to climate manipulation. Therefore, there is a need: for (i) specific background knowledge on the crop response to a given improvement in greenhouse design and climate control, and (ii) a methodology of optimisation that takes into account the response of the crop, the cost of the improved structure and climate control system, as well as some other parameters and criteria that are involved in the decision-making process. The role of crop models and simulation tools is briefly discussed. The second part of the paper deals with the present research trend in greenhouse technology, at the light of the publications on greenhouse environmental control during the late 90'. Some topics appear to merge, like ventilation, greenhouse transmission, and climate control. Finally, the way the growers respond to technological improvements in their production system is discussed. It is highly probable that the use of more performing greenhouses is of little value if not accompanied by a better education and training of growers.
A procedure is described to construct time series of regional surface temperatures and is then applied to interior central California stations to test the hypothesis that century-scale trend differences between irrigated and nonirrigated regions may be identified. The procedure requires documentation of every point in time at which a discontinuity in a station record may have occurred through (a) the examination of metadata forms (e.g., station moves) and (b) simple statistical tests. From this "homogeneous segments" of temperature records for each station are defined. Biases are determined for each segment relative to all others through a method employing mathematical graph theory. The debiased segments are then merged, forming a complete regional time series. Time series of daily maximum and minimum temperatures for stations in the irrigated San Joaquin Valley (Valley) and nearby nonirrigated Sierra Nevada (Sierra) were generated for 1910-2003. Results show that twentieth-century Valley minimum temperatures are warming at a highly significant rate in all seasons, being greatest in summer and fall (> +0.25°C decade-1). The Valley trend of annual mean temperatures is +0.07° ± 0.07°C decade-1. Sierra summer and fall minimum temperatures appear to be cooling, but at a less significant rate, while the trend of annual mean Sierra temperatures is an unremarkable -0.02° ± 0.10°C decade-1. A working hypothesis is that the relative positive trends in Valley minus Sierra minima (>0.4°C decade-1 for summer and fall) are related to the altered surface environment brought about by the growth of irrigated agriculture, essentially changing a high-albedo desert into a darker, moister, vegetated plain.
The climate of Earth and its global mean surface temperature are the consequence of a balance between the amount of solar radiation absorbed by Earth's surface and atmosphere and the amount of outgoing longwave radiation emitted by the system. The former is governed by the albedo (reflectivity) of the system, whereas the latter depends strongly on the atmospheric content of gases and particles (such as clouds and dust). Although the theory of absorption of infrared radiation by gases in the atmosphere (1) is well accepted and embodied in climate models, the observational and theoretical treatments of albedo, aerosols, and clouds are still under development. One brevium (2) and two reports (3, 4) in this issue report estimates of Earth's albedo and of solar radiation reaching the surface, but the uncertainties remain large. The buildup of CO_2 (5), CH_4, and other greenhouse gases during the past century has led to an increased absorption of infrared radiation in the atmosphere (enhanced greenhouse effect) and a consequent warming (“positive forcing”) of the climate. But human-made changes in aerosols and clouds can cause enhanced albedo and hence cooling (“negative forcing”), and they may already have offset a substantial part of the enhanced greenhouse effect. Present trends suggest that by 2050, the magnitude of the enhanced greenhouse effect will be so large that the net anthropogenic forcing will be unequivocally positive and substantial in magnitude (6).