scholarly journals Reviews and syntheses: Turning the challenges of partitioning ecosystem evaporation and transpiration into opportunities

2019 ◽  
Author(s):  
Paul C. Stoy ◽  
Tarek El-Madany ◽  
Joshua B. Fisher ◽  
Pierre Gentine ◽  
Tobias Gerken ◽  
...  
Keyword(s):  
Land Surface ◽  
Water Cycle ◽  
Water Flux ◽  
Carbonyl Sulfide ◽  
Analytical Techniques ◽  
Atmospheric Composition ◽  
Reasonable Assumption ◽  
Canopy Conductance ◽  
Land Surface Models ◽  
Surface Models

Abstract. Evaporation (E) and transpiration (T) respond differently to ongoing changes in climate, atmospheric composition, and land use. Our ability to partition evapotranspiration (ET) into E and T is limited at the ecosystem scale, which renders the validation of satellite data and land surface models incomplete. Here, we review current progress in partitioning E and T, and provide a prospectus for how to improve theory and observations going forward. Recent advancements in analytical techniques provide additional opportunities for partitioning E and T at the ecosystem scale, but their assumptions have yet to be fully tested. Many approaches to partition E and T rely on the notion that plant canopy conductance and ecosystem water use efficiency (EWUE) exhibit optimal responses to atmospheric vapor pressure deficit (D). We use observations from 240 eddy covariance flux towers to demonstrate that optimal ecosystem response to D is a reasonable assumption, in agreement with recent studies, but the conditions under which this assumption holds require further analysis. Another critical assumption for many ET partitioning approaches is that ET can be approximated as T during ideal transpiring conditions, which has been challenged by observational studies. We demonstrate that T frequently exceeds 95 % of ET from some ecosystems, but other ecosystems do not appear to reach this value, which suggests that this assumption is ecosystem-dependent with implications for partitioning. It is important to further improve approaches for partitioning E and T, yet few multi-method comparisons have been undertaken to date. Advances in our understanding of carbon-water coupling at the stomatal, leaf, and canopy level open new perspectives on how to quantify T via its strong coupling with photosynthesis. Photosynthesis can be constrained at the ecosystem and global scales with emerging data sources including solar-induced fluorescence, carbonyl sulfide flux measurements, thermography, and more. Such comparisons would improve our mechanistic understanding of ecosystem water flux and provide the observations necessary to validate remote sensing algorithms and land surface models to understand the changing global water cycle.

scholarly journals Reviews and syntheses: Turning the challenges of partitioning ecosystem evaporation and transpiration into opportunities

2019 ◽  
Vol 16 (19) ◽  
pp. 3747-3775 ◽  
Author(s):  
Paul C. Stoy ◽  
Tarek S. El-Madany ◽  
Joshua B. Fisher ◽  
Pierre Gentine ◽  
Tobias Gerken ◽  
...  
Keyword(s):  
Land Surface ◽  
Water Cycle ◽  
Carbonyl Sulfide ◽  
Analytical Techniques ◽  
Atmospheric Composition ◽  
Reasonable Assumption ◽  
Canopy Conductance ◽  
Land Surface Models ◽  
Surface Models ◽  
Ecosystem Water Use Efficiency

Abstract. Evaporation (E) and transpiration (T) respond differently to ongoing changes in climate, atmospheric composition, and land use. It is difficult to partition ecosystem-scale evapotranspiration (ET) measurements into E and T, which makes it difficult to validate satellite data and land surface models. Here, we review current progress in partitioning E and T and provide a prospectus for how to improve theory and observations going forward. Recent advancements in analytical techniques create new opportunities for partitioning E and T at the ecosystem scale, but their assumptions have yet to be fully tested. For example, many approaches to partition E and T rely on the notion that plant canopy conductance and ecosystem water use efficiency exhibit optimal responses to atmospheric vapor pressure deficit (D). We use observations from 240 eddy covariance flux towers to demonstrate that optimal ecosystem response to D is a reasonable assumption, in agreement with recent studies, but more analysis is necessary to determine the conditions for which this assumption holds. Another critical assumption for many partitioning approaches is that ET can be approximated as T during ideal transpiring conditions, which has been challenged by observational studies. We demonstrate that T can exceed 95 % of ET from certain ecosystems, but other ecosystems do not appear to reach this value, which suggests that this assumption is ecosystem-dependent with implications for partitioning. It is important to further improve approaches for partitioning E and T, yet few multi-method comparisons have been undertaken to date. Advances in our understanding of carbon–water coupling at the stomatal, leaf, and canopy level open new perspectives on how to quantify T via its strong coupling with photosynthesis. Photosynthesis can be constrained at the ecosystem and global scales with emerging data sources including solar-induced fluorescence, carbonyl sulfide flux measurements, thermography, and more. Such comparisons would improve our mechanistic understanding of ecosystem water fluxes and provide the observations necessary to validate remote sensing algorithms and land surface models to understand the changing global water cycle.

scholarly journals Using satellite-based estimates of evapotranspiration and groundwater changes to determine anthropogenic water fluxes in land surface models

2015 ◽  
Vol 8 (4) ◽  
pp. 3565-3592 ◽  
Author(s):  
R. G. Anderson ◽  
M.-H. Lo ◽  
S. Swenson ◽  
J. S. Famiglietti ◽  
Q. Tang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Climate Models ◽  
Management Practice ◽  
Water Flux ◽  
Water Volume ◽  
Land Surface Models ◽  
Community Land Model ◽  
Irrigation Intensity ◽  
Surface Models

Abstract. Irrigation is a widely used water management practice that is often poorly parameterized in land surface and climate models. Previous studies have addressed this issue via use of irrigation area, applied water inventory data, or soil moisture content. These approaches have a variety of drawbacks including data latency, accurately prescribing irrigation intensity, and conservation of water volume for soil moisture approach. In this study, we parameterize irrigation fluxes using satellite observations of evapotranspiration (ET) against ET from a suite of land surface models without irrigation. We then apply this water flux into the Community Land Model (CLM) and use an iterative approach to estimate groundwater recharge and partition the water flux between groundwater and surface water. The ET simulated by CLM with irrigation matches the magnitude and seasonality of observed satellite ET well, with a mean difference of 6.3 mm month−1 and a correlation of 0.95. Differences between the new CLM ET values and observed ET values are always less than 30 mm month−1 and the differences show no pattern with respect to seasonality. The results reinforce the importance of accurately parameterizing anthropogenic hydrologic fluxes into land surface and climate models to assess environmental change under current and future climates and land management regimes.

scholarly journals Eco‐evolutionary optimality as a means to improve vegetation and land‐surface models

2021 ◽  
Author(s):  
Sandy P. Harrison ◽  
Wolfgang Cramer ◽  
Oskar Franklin ◽  
Iain Colin Prentice ◽  
Han Wang ◽  
...  
Keyword(s):  
Land Surface ◽  
Land Surface Models ◽  
Surface Models ◽  
Evolutionary Optimality

scholarly journals The CarboEurope Regional Experiment Strategy

2006 ◽  
Vol 87 (10) ◽  
pp. 1367-1380 ◽  
Author(s):  
A. J. Dolman ◽  
J. Noilhan ◽  
P. Durand ◽  
C. Sarrat ◽  
A. Brut ◽  
...  
Keyword(s):  
Land Surface ◽  
Major Product ◽  
State Variables ◽  
Land Surface Models ◽  
Quality Metric ◽  
Key Characteristics ◽  
Surface Models ◽  
Global Soil ◽  
Standard Deviations ◽  
Model Agreement

The Second Global Soil Wetness Project (GSWP-2) is an initiative to compare and evaluate 10-year simulations by a broad range of land surface models under controlled conditions. A major product of GSWP-2 is the first global gridded multimodel analysis of land surface state variables and fluxes for use by meteorologists, hydrologists, engineers, biogeochemists, agronomists, botanists, ecologists, geographers, climatologists, and educators. Simulations by 13 land models from five nations have gone into production of the analysis. The models are driven by forcing data derived from a combination of gridded atmospheric reanalyses and observations. The resulting analysis consists of multimodel means and standard deviations on the monthly time scale, including profiles of soil moisture and temperature at six levels, as well as daily and climatological (mean annual cycle) fields for over 50 land surface variables. The monthly standard deviations provide a measure of model agreement that may be used as a quality metric. An overview of key characteristics of the analysis is presented here, along with information on obtaining the data.

scholarly journals Discontinuous Daily Temperatures in the WATCH Forcing Datasets

2015 ◽  
Vol 16 (1) ◽  
pp. 465-472 ◽  
Author(s):  
Henning W. Rust ◽  
Tim Kruschke ◽  
Andreas Dobler ◽  
Madlen Fischer ◽  
Uwe Ulbrich
Keyword(s):  
Land Surface ◽  
Water Cycle ◽  
Research Unit ◽  
Climatic Research Unit ◽  
Daily Maximum ◽  
Monthly Means ◽  
Tropical Africa ◽  
Average Temperature ◽  
Surface Models ◽  
The Tropics

Abstract The Water and Global Change (WATCH) forcing datasets have been created to support the use of hydrological and land surface models for the assessment of the water cycle within climate change studies. They are based on 40-yr ECMWF Re-Analysis (ERA-40) or ECMWF interim reanalysis (ERA-Interim) with temperatures (among other variables) adjusted such that their monthly means match the monthly temperature dataset from the Climatic Research Unit. To this end, daily minimum, maximum, and mean temperatures within one calendar month have been subjected to a correction involving monthly means of the respective month. As these corrections can be largely different for adjacent months, this procedure potentially leads to implausible differences in daily temperatures across the boundaries of calendar months. We analyze day-to-day temperature fluctuations within and across months and find that across-months differences are significantly larger, mostly in the tropics and frigid zones. Average across-months differences in daily mean temperature are typically between 10% and 40% larger than their corresponding within-months average temperature differences. However, regions with differences up to 200% can be found in tropical Africa. Particularly in regions where snowmelt is a relevant player for hydrology, a few degrees Celsius difference can be decisive for triggering this process. Daily maximum and minimum temperatures are affected in the same regions, but in a less severe way.

scholarly journals On the utility of land surface models for agricultural drought monitoring

2012 ◽  
Vol 16 (9) ◽  
pp. 3451-3460 ◽  
Author(s):  
W. T. Crow ◽  
S. V. Kumar ◽  
J. D. Bolten
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Cross Correlation ◽  
Root Zone ◽  
Vegetation Indices ◽  
Agricultural Drought ◽  
Drought Monitoring ◽  
Global Evaluation ◽  
Land Surface Models ◽  
Surface Models

Abstract. The lagged rank cross-correlation between model-derived root-zone soil moisture estimates and remotely sensed vegetation indices (VI) is examined between January 2000 and December 2010 to quantify the skill of various soil moisture models for agricultural drought monitoring. Examined modeling strategies range from a simple antecedent precipitation index to the application of modern land surface models (LSMs) based on complex water and energy balance formulations. A quasi-global evaluation of lagged VI/soil moisture cross-correlation suggests, when globally averaged across the entire annual cycle, soil moisture estimates obtained from complex LSMs provide little added skill (< 5% in relative terms) in anticipating variations in vegetation condition relative to a simplified water accounting procedure based solely on observed precipitation. However, larger amounts of added skill (5–15% in relative terms) can be identified when focusing exclusively on the extra-tropical growing season and/or utilizing soil moisture values acquired by averaging across a multi-model ensemble.

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