Global Patterns of Biosphere-Atmosphere Energy Fluxes in...
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D (kPa) LE (W m −2 ) 0 1 2 3 4 5 0 50 100 150 200 250 300 350 400 450 1 2 3 4 5 6 7 8 −3 x 10 Figure 3. V hourly data). Colours denote 2D kernel density estimate (nonparametric probability density function). apour pressure deficit (D) constraints on latent heat fluxes (LE; daytime only, The importance of the tropics for the global hydrological cycle is highlighted by (1) the highest absolute rates of latent heat, and (2) the largest proportion of available energy converted to latent heat. In addition to tropical forests, savanna ecosystems contribute among the highest latent heat fluxes across all sites. Vapour pressure deficit limits latent heat fluxes above ~1.5 kPa through plant physiological control by stomatal closure. Evaporative fractions shows a bimodal distribution across all sites and differentiates terrestrial ecosystems by the availability of moisture, i.e. dry vs. wet systems. The general patterns and functional relationships derived from this synthesis will improve the understanding of variations in energy fluxes globally and will provide valuable insights for land-surface models based on direct measurements. Conclusions Seasonal variability of daily latent heat fluxes (Fig. 1) was lowest in the tropics, particularly in evergreen broadleaf forest and savanna, and these plant functional types (PFTs) had the highest absolute fluxes of LE. Mean annual LE exceeded mean H across all FLUXNET sites (Fig. 2). Vapour pressure deficit (D) was one of the main controls on hourly LE, with most observations below 1 kPa and pronounced reductions in LE beyond 2 kPa (Fig. 3). The partitioning of available energy (AE) into latent and sensible heat revealed climate specific patterns (Fig. 4): the evaporative fraction (EF) had the lowest seasonal variability in tropical and subtropical regions. The highest EF was found in the tropics (>0.7). In contrast, a larger proportion of AE was converted to sensible heat in arid & semi-arid regions, with EF <0.3 during most of the year. Soil moisture was the main climatic control of annual energy flux partitioning across FLUXNET sites, without pronounced climate specific patterns (Fig. 5). Results We synthesized data from the global eddy covariance network FLUXNET to investigate general patterns of biosphere-atmosphere energy fluxes in terrestrial ecosystems across biomes and climates. Our objectives are to: (1) Characterize seasonal and inter-annual variability of latent (LE) & sensible heat (H) fluxes (2) Derive general functional relationships for climatic & biophysical controls of energy fluxes (3) Quantify the effects of land-use change & disturbance on the partitioning of energy fluxes Objectives Energy fluxes of heat and moisture between land surface and atmosphere play an important role in the surface energy budget and in regulating climate. These fluxes and their feedbacks are constrained by biophysical and ecophysiological properties of terrestrial ecosystems, which are largely controlled by environmental conditions and associated changes. However, only few studies synthesized biosphere-atmosphere energy fluxes beyond the regional/continental scale and an early data-driven characterization of general patterns in energy fluxes was based on a limited number of ecosystems. Many open questions thus remain regarding biome and climate specific patterns, general functional relationships and the partitioning of available energy into sensible and latent heat fluxes. In addition, the effect of land-use on energy fluxes, their partitioning and coupling with air temperature are not well understood. Introduction Acknowledgements SW received funding by the European Commission (Marie Curie International Outgoing Fellowship, grant no. 300083, ECOWAX). PCS acknowledges funding from Montana State University, the National Science Foundation (US), the National Environmental Research Council (UK) and by the European Commission (Marie Curie European Incoming International Fellowship, grant no. 237348, TSURF). This work used eddy covariance data acquired by the FLUXNET community and in particular by the following networks: AmeriFlux (U.S. Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program (DE-FG02-04ER63917 and DE-FG02-04ER63911)), AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, FLUXNET Canada (supported by CFCAS, NSERC, BIOCAP, Environment Canada, and NRCan), Green-Grass, KoFlux, LBA, NECC, OzFlux, TCOS‐Siberia, USCCC. 1 Sebastian Wolf , 2 3 4 1 Paul Stoy , Markus Reichstein , Alessandro Cescatti , Dennis Baldocchi 1 Department of Environmental Science, Policy and Management, University of California, Berkeley, USA 2 3 4 Montana State University, USA; Max Planck Institute for Biogeochemistry, Germany; European Commission – DG Joint Research Centre, Italy * [email protected] Global Patterns of Biosphere-Atmosphere Energy Fluxes in Terrestrial Ecosystems Global Patterns of Biosphere-Atmosphere Energy Fluxes in Terrestrial Ecosystems Figure 2. sensible (H) fluxes across FLUXNET sites. Bars denote histogram and lines the pdf estimated with a non-parametric kernel smoothing method. The annual water equivalent for LE would be 513±278 mm (mean ± SD). Probability density function (pdf) of annual latent heat (LE) and 0 1 2 3 0.0 0.2 0.4 0.6 0.8 1.0 1.2 pdf LE [ GJ m -2 yr -1 ] n: 954 Mean: 1.08 Median: 0.95 SD: 0.58 0 1 2 3 H [ GJ m -2 yr -1 ] n: 957 Mean: 0.8 Median: 0.76 SD: 0.56 Figure 5. Probability density function (pdf) of evaporative fraction (EF; left panel) and dependency of EF on soil water content (SWC; right panel) by climate across FLUXNET sites. 0.0 0.2 0.4 0.6 0.8 1.0 0 1 2 3 4 pdf EF n: 917 Mean: 0.57 Median: 0.57 SD: 0.18 0 20 40 60 80 100 0.0 0.2 0.4 0.6 0.8 1.0 EF SWC [ % ] Temp TemC Trop Dry Bor Arc StM R 2 =0.27 (p<0.001), n=462 Figure 4. Seasonal variability of evaporative fraction (EF) by climate Temperate (Temp), Temperate-continental with hot or warm summers (TempC), Tropical (Trop), Arid and semi arid (Dry), Boreal (Bor), Arctic (Arc), Subtropical-Mediterranean (StM). : EF 0 100 200 300 0 0.2 0.4 0.6 0.8 1 DOY Temp TemC Trop Dry Bor Arc StM Figure 1. Seasonal variability of daily functional type (PFT): Cropland (CRO), Shrubland (Shrub), Deciduous Broadleaf Forest (DBF), Evergreen Broadleaf Forest (EBF), Evergreen Needleleaf Forest (ENF), Grassland (GRA), Mixed Forest (MF), Savanna (Sav), Wetland (Wet). latent heat (LE) and sensible (H) fluxes by plant 0 2 4 6 8 10 LE (MJ m −2 day −1 ) 0 50 100 150 200 250 300 350 0 2 4 6 8 H (MJ m −2 day −1 ) DOY Crop Shrub DBF EBF ENF GRA Sav Wet MF
Transcript of Global Patterns of Biosphere-Atmosphere Energy Fluxes in...
D (kPa)
LE
(W
m−
2)
0 1 2 3 4 50
50
100
150
200
250
300
350
400
450
1
2
3
4
5
6
7
8
−3x 10
Figure 3. Vhourly data). Colours denote 2D kernel density estimate (nonparametric probability density function).
apour pressure deficit (D) constraints on latent heat fluxes (LE; daytime only,
Conclusions
The importance of the tropics for the global hydrological cycle is highlighted by (1) the highest
absolute rates of latent heat, and (2) the largest proportion of available energy converted to latent heat.
In addition to tropical forests, savanna ecosystems contribute among the highest latent heat fluxes
across all sites. Vapour pressure deficit limits latent heat fluxes above ~1.5 kPa through plant
physiological control by stomatal closure. Evaporative fractions shows a bimodal distribution across all
sites and differentiates terrestrial ecosystems by the availability of moisture, i.e. dry vs. wet systems.
The general patterns and functional relationships derived from this synthesis will improve the
understanding of variations in energy fluxes globally and will provide valuable insights for land-surface
models based on direct measurements.
Conclusions
Results
Seasonal variability of daily latent heat
fluxes (Fig. 1) was lowest in the tropics,
particularly in evergreen broadleaf forest and
savanna, and these plant functional types
(PFTs) had the highest absolute fluxes of LE.
Mean annual LE exceeded mean H across all
FLUXNET sites (Fig. 2). Vapour pressure
deficit (D) was one of the main controls on
hourly LE, with most observations below 1 kPa
and pronounced reductions in LE beyond 2 kPa
(Fig. 3). The partitioning of available energy
(AE) into latent and sensible heat revealed
climate specific patterns (Fig. 4): the
evaporative fraction (EF) had the lowest
seasonal variability in tropical and
subtropical regions. The highest EF was
found in the tropics (>0.7). In contrast, a
larger proportion of AE was converted to
sensible heat in arid & semi-arid regions,
with EF <0.3 during most of the year. Soil
moisture was the main climatic control of
annual energy flux partitioning across
FLUXNET sites, without pronounced
climate specific patterns (Fig. 5).
Results
Objectives
We synthesized data from the global eddy covariance network FLUXNET to investigate
general patterns of biosphere-atmosphere energy fluxes in terrestrial ecosystems across
biomes and climates. Our objectives are to:
(1) Characterize seasonal and inter-annual variability of latent (LE) & sensible heat (H) fluxes
(2) Derive general functional relationships for climatic & biophysical controls of energy fluxes
(3) Quantify the effects of land-use change & disturbance on the partitioning of energy fluxes
Objectives
Introduction
Energy fluxes of heat and moisture between land surface and atmosphere play an important
role in the surface energy budget and in regulating climate. These fluxes and their feedbacks are
constrained by biophysical and ecophysiological properties of terrestrial ecosystems, which are
largely controlled by environmental conditions and associated changes. However, only few
studies synthesized biosphere-atmosphere energy fluxes beyond the regional/continental scale
and an early data-driven characterization of general patterns in energy fluxes was based on a
limited number of ecosystems. Many open questions thus remain regarding biome and
climate specific patterns, general functional relationships and the partitioning of
available energy into sensible and latent heat fluxes. In addition, the effect of land-use on
energy fluxes, their partitioning and coupling with air temperature are not well understood.
Introduction
Acknowledgements
SW received funding by the European Commission (Marie Curie
International Outgoing Fellowship, grant no. 300083, ECOWAX). PCS
acknowledges funding from Montana State University, the National
Science Foundation (US), the National Environmental Research Council
(UK) and by the European Commission (Marie Curie European Incoming
International Fellowship, grant no. 237348, TSURF).
This work used eddy covariance data acquired by the FLUXNET
community and in particular by the following networks: AmeriFlux (U.S.
Department of Energy, Biological and Environmental Research, Terrestrial
Carbon Program (DE-FG02-04ER63917 and DE-FG02-04ER63911)),
AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont,
ChinaFlux, FLUXNET Canada (supported by CFCAS, NSERC, BIOCAP,
Environment Canada, and NRCan), Green-Grass, KoFlux, LBA, NECC,
OzFlux, TCOS‐Siberia, USCCC.
1Sebastian Wolf , 2 3 4 1Paul Stoy , Markus Reichstein , Alessandro Cescatti , Dennis Baldocchi1 Department of Environmental Science, Policy and Management, University of California, Berkeley, USA2 3 4 Montana State University, USA; Max Planck Institute for Biogeochemistry, Germany; European Commission – DG Joint Research Centre, Italy
Global Patterns of Biosphere-Atmosphere Energy Fluxes in Terrestrial EcosystemsGlobal Patterns of Biosphere-Atmosphere Energy Fluxes in Terrestrial Ecosystems
Figure 2. sensible (H) fluxes across FLUXNET sites. Bars denote histogram andlines the pdf estimated with a non-parametric kernel smoothing method.The annual water equivalent for LE would be 513±278 mm (mean ± SD).
Probability density function (pdf) of annual latent heat (LE) and
0 1 2 3
0.0
0.2
0.4
0.6
0.8
1.0
1.2
pd
f
LE [ GJ m- 2 yr- 1 ]
n: 954Mean: 1.08Median: 0.95SD: 0.58
0 1 2 3
H [ GJ m- 2 yr- 1 ]
n: 957Mean: 0.8Median: 0.76SD: 0.56
Figure 5. Probability density function (pdf) of evaporative fraction (EF; left panel) and dependency of EF on soil water content (SWC; right panel) byclimate across FLUXNET sites.
0.0 0.2 0.4 0.6 0.8 1.0
0
1
2
3
4
EF
n: 917Mean: 0.57Median: 0.57SD: 0.18
0 20 40 60 80 100
0.0
0.2
0.4
0.6
0.8
1.0
EF
SWC [ % ]
TempTemCTropDryBorArcStMR2=0.27 (p<0.001), n=462
Figure 4. Seasonal variability of evaporative fraction (EF) by climateTemperate (Temp), Temperate-continental with hot or warm summers (TempC), Tropical (Trop), Arid and semi arid (Dry), Boreal (Bor), Arctic (Arc), Subtropical-Mediterranean (StM).
:
EF
0 100 200 3000
0.2
0.4
0.6
0.8
1
DOY
Temp TemC Trop Dry Bor Arc StM
Figure 1. Seasonal variability of daily functional type (PFT): Cropland (CRO), Shrubland (Shrub), Deciduous Broadleaf Forest (DBF), Evergreen Broadleaf Forest (EBF), Evergreen Needleleaf Forest (ENF), Grassland (GRA), Mixed Forest (MF), Savanna (Sav), Wetland (Wet).
latent heat (LE) and sensible (H) fluxes by plant
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