Simple Models Outperform More Complex Big‐Leaf Models of Daily Transpiration in Forested Biomes

Bright, Ryan M.; Miralles, Diego G.; Poyatos, Rafael; Eisner, Stephanie

doi:10.1029/2022gl100100

Cited by 13 publications

(6 citation statements)

References 109 publications

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“…Yet, to adequately mimic the E‐vegetation dependence identified above, this is presumably what is required. Estimating E‐vegetation dependence is thus rendered problematic by difficulties linking the latent heat flux (E/ET) and surface albedo phenomena with surface temperature and climate change (Bright et al., 2022; Chen & Dirmeyer, 2020; Duveiller et al., 2022).…”

Section: Discussionmentioning

confidence: 99%

Even cooler insights: On the power of forests to (water the Earth and) cool the planet

Ellison,

Pokorný,

Wild

2024

Global Change Biology

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Scientific innovation is overturning conventional paradigms of forest, water, and energy cycle interactions. This has implications for our understanding of the principal causal pathways by which tree, forest, and vegetation cover (TFVC) influence local and global warming/cooling. Many identify surface albedo and carbon sequestration as the principal causal pathways by which TFVC affects global warming/cooling. Moving toward the outer latitudes, in particular, where snow cover is more important, surface albedo effects are perceived to overpower carbon sequestration. By raising surface albedo, deforestation is thus predicted to lead to surface cooling, while increasing forest cover is assumed to result in warming. Observational data, however, generally support the opposite conclusion, suggesting surface albedo is poorly understood. Most accept that surface temperatures are influenced by the interplay of surface albedo, incoming shortwave (SW) radiation, and the partitioning of the remaining, post‐albedo, SW radiation into latent and sensible heat. However, the extent to which the avoidance of sensible heat formation is first and foremost mediated by the presence (absence) of water and TFVC is not well understood. TFVC both mediates the availability of water on the land surface and drives the potential for latent heat production (evapotranspiration, ET). While latent heat is more directly linked to local than global cooling/warming, it is driven by photosynthesis and carbon sequestration and powers additional cloud formation and top‐of‐cloud reflectivity, both of which drive global cooling. TFVC loss reduces water storage, precipitation recycling, and downwind rainfall potential, thus driving the reduction of both ET (latent heat) and cloud formation. By reducing latent heat, cloud formation, and precipitation, deforestation thus powers warming (sensible heat formation), which further diminishes TFVC growth (carbon sequestration). Large‐scale tree and forest restoration could, therefore, contribute significantly to both global and surface temperature cooling through the principal causal pathways of carbon sequestration and cloud formation.

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Section: Discussionmentioning

confidence: 99%

Even cooler insights: On the power of forests to (water the Earth and) cool the planet

Ellison,

Pokorný,

Wild

2024

Global Change Biology

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“…Recent efforts have applied collocation analysis to assess transpiration estimates. Bright et al 35 utilized the additive triple collocation (TC) model to scrutinize the performance of diverse models in estimating daily transpiration.…”

Section: Background and Summarymentioning

confidence: 99%

A harmonized global gridded transpiration product based on collocation analysis

Li,

Han,

Liu

et al. 2024

Sci Data

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Transpiration (T) is pivotal in the global water cycle, responding to soil moisture, atmospheric stress, climate changes, and human impacts. Therefore, establishing a reliable global transpiration dataset is essential. Collocation analysis methods have been proven effective for assessing the errors in these products, which can subsequently be used for multisource fusion. However, previous results did not consider error cross-correlation, rendering the results less reliable. In this study, we employ collocation analysis, taking error cross-correlation into account, to effectively analyze the errors in multiple transpiration products and merge them to obtain a more reliable dataset. The results demonstrate its superior reliability. The outcome is a long-term daily global transpiration dataset at 0.1°from 2000 to 2020. Using the transpiration after partitioning at FLUXNET sites as a reference, we compare the performance of the merged product with inputs. The merged dataset performs well across various vegetation types and is validated against in-situ observations. Incorporating non-zero ECC considerations represents a significant theoretical and proven enhancement over previous methodologies that neglected such conditions, highlighting its reliability in enhancing our understanding of transpiration dynamics in a changing world.

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“…Recent efforts have applied collocation analysis to assess transpiration estimates. Bright et al (2022) utilized the additive triple collocation (TC) model to scrutinize the performance of diverse models in estimating daily transpiration. Park et al (2023) amalgamated three products (e.g., ERA5L, GLDAS, and MERRA2) using TC-derived error information over East Asia.…”

Section: Introductionmentioning

confidence: 99%

A harmonized global gridded transpiration product based on collocation analysis

Li,

Han,

Liu

et al. 2023

Preprint

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Transpiration (T) is pivotal in the global water cycle, responding to soil moisture, atmospheric stress, climate changes, and human impacts. Therefore, establishing a reliable global transpiration dataset is essential. Different global transpiration products exhibit significant differences, necessitating the evaluation of errors. Collocation analysis methods have been proven effective for assessing the errors in these products, which can subsequently be used for multisource fusion. However, previous results did not consider error cross-correlation, rendering the results less reliable. In this study, we employ collocation analysis, taking error cross-correlation into account, to effectively analyze the errors in multiple transpiration products and merge them to obtain a more reliable dataset. The results demonstrate its superior reliability. The outcome of this research is a long-term daily global transpiration dataset at 0.1° resolution from 2000 to 2020. Using the transpiration after partitioning at FLUXNET sites as a reference, we compare the performance of the merged product with input datasets. The merged dataset performs well across various vegetation types and is validated against in-situ observations. Incorporating non-zero ECC considerations represents a significant theoretical and proven enhancement over previous methodologies that neglected such conditions, highlighting its reliability in enhancing our understanding of transpiration dynamics in a changing world.

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Simple Models Outperform More Complex Big‐Leaf Models of Daily Transpiration in Forested Biomes

Cited by 13 publications

References 109 publications

Even cooler insights: On the power of forests to (water the Earth and) cool the planet

Even cooler insights: On the power of forests to (water the Earth and) cool the planet

A harmonized global gridded transpiration product based on collocation analysis

A harmonized global gridded transpiration product based on collocation analysis

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