Development of observation-based global multilayer soil moisture products for 1970 to 2016
<p>Soil moisture (SM) datasets are critical to understanding the global water, energy, and biogeochemical cycles and benefit extensive societal applications. However, individual sources of SM data (e.g., in situ and satellite observations, reanalysis, offline land surface model simulations, Ea...
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Copernicus Publications
2021-09-01
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Series: | Earth System Science Data |
Online Access: | https://essd.copernicus.org/articles/13/4385/2021/essd-13-4385-2021.pdf |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Y. Wang Y. Wang J. Mao M. Jin M. Jin F. M. Hoffman X. Shi S. D. Wullschleger Y. Dai |
spellingShingle |
Y. Wang Y. Wang J. Mao M. Jin M. Jin F. M. Hoffman X. Shi S. D. Wullschleger Y. Dai Development of observation-based global multilayer soil moisture products for 1970 to 2016 Earth System Science Data |
author_facet |
Y. Wang Y. Wang J. Mao M. Jin M. Jin F. M. Hoffman X. Shi S. D. Wullschleger Y. Dai |
author_sort |
Y. Wang |
title |
Development of observation-based global multilayer soil moisture products for 1970 to 2016 |
title_short |
Development of observation-based global multilayer soil moisture products for 1970 to 2016 |
title_full |
Development of observation-based global multilayer soil moisture products for 1970 to 2016 |
title_fullStr |
Development of observation-based global multilayer soil moisture products for 1970 to 2016 |
title_full_unstemmed |
Development of observation-based global multilayer soil moisture products for 1970 to 2016 |
title_sort |
development of observation-based global multilayer soil moisture products for 1970 to 2016 |
publisher |
Copernicus Publications |
series |
Earth System Science Data |
issn |
1866-3508 1866-3516 |
publishDate |
2021-09-01 |
description |
<p>Soil moisture (SM) datasets are critical to understanding
the global water, energy, and biogeochemical cycles and benefit extensive
societal applications. However, individual sources of SM data (e.g., in situ
and satellite observations, reanalysis, offline land surface model
simulations, Earth system model – ESM – simulations) have source-specific
limitations and biases related to the spatiotemporal continuity,
resolutions, and modeling and retrieval assumptions. Here, we developed seven
global, gap-free, long-term (1970–2016), multilayer (0–10, 10–30,
30–50, and 50–100 cm) SM products at monthly 0.5<span class="inline-formula"><sup>∘</sup></span> resolution
(available at <a href="https://doi.org/10.6084/m9.figshare.13661312.v1">https://doi.org/10.6084/m9.figshare.13661312.v1</a>; Wang and Mao, 2021) by
synthesizing a wide range of SM datasets using three statistical methods
(unweighted averaging, optimal linear combination, and emergent constraint).
The merged products outperformed their source datasets when evaluated with
in situ observations (mean bias from <span class="inline-formula">−</span>0.044 to 0.033 m<span class="inline-formula"><sup>3</sup></span> m<span class="inline-formula"><sup>−3</sup></span>, root
mean square errors from 0.076 to 0.104 m<span class="inline-formula"><sup>3</sup></span> m<span class="inline-formula"><sup>−3</sup></span>, Pearson
correlations from 0.35 to 0.67) and multiple gridded datasets that did not
enter merging because of insufficient spatial, temporal, or soil layer
coverage. Three of the new SM products, which were produced by applying any
of the three merging methods to the source datasets excluding the ESMs,
had lower bias and root mean square errors and higher correlations than the
ESM-dependent merged products. The ESM-independent products also showed a
better ability to capture historical large-scale drought events than the
ESM-dependent products. The merged products generally showed reasonable
temporal homogeneity and physically plausible global sensitivities to
observed meteorological factors, except that the ESM-dependent products
underestimated the low-frequency temporal variability in SM and
overestimated the high-frequency variability for the 50–100 cm depth.
Based on these evaluation results, the three ESM-independent products were
finally recommended for future applications because of their better
performances than the ESM-dependent ones. Despite uncertainties in the raw
SM datasets and fusion methods, these hybrid products create added value
over existing SM datasets because of the performance improvement and
harmonized spatial, temporal, and vertical coverages, and they provide a new
foundation for scientific investigation and resource management.</p> |
url |
https://essd.copernicus.org/articles/13/4385/2021/essd-13-4385-2021.pdf |
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spelling |
doaj-3c578c3eced14f1fb0274d9d9f0fc2012021-09-07T13:12:12ZengCopernicus PublicationsEarth System Science Data1866-35081866-35162021-09-01134385440510.5194/essd-13-4385-2021Development of observation-based global multilayer soil moisture products for 1970 to 2016Y. Wang0Y. Wang1J. Mao2M. Jin3M. Jin4F. M. Hoffman5X. Shi6S. D. Wullschleger7Y. Dai8Institute for a Secure and Sustainable Environment, University of Tennessee, Knoxville, TN 37902, USAEnvironmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USAEnvironmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USAInstitute for a Secure and Sustainable Environment, University of Tennessee, Knoxville, TN 37902, USADepartment of Industrial and Systems Engineering, University of Tennessee, Knoxville, TN 37996, USAComputational Sciences and Engineering Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USAEnvironmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USAEnvironmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USASchool of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, 519082, China<p>Soil moisture (SM) datasets are critical to understanding the global water, energy, and biogeochemical cycles and benefit extensive societal applications. However, individual sources of SM data (e.g., in situ and satellite observations, reanalysis, offline land surface model simulations, Earth system model – ESM – simulations) have source-specific limitations and biases related to the spatiotemporal continuity, resolutions, and modeling and retrieval assumptions. Here, we developed seven global, gap-free, long-term (1970–2016), multilayer (0–10, 10–30, 30–50, and 50–100 cm) SM products at monthly 0.5<span class="inline-formula"><sup>∘</sup></span> resolution (available at <a href="https://doi.org/10.6084/m9.figshare.13661312.v1">https://doi.org/10.6084/m9.figshare.13661312.v1</a>; Wang and Mao, 2021) by synthesizing a wide range of SM datasets using three statistical methods (unweighted averaging, optimal linear combination, and emergent constraint). The merged products outperformed their source datasets when evaluated with in situ observations (mean bias from <span class="inline-formula">−</span>0.044 to 0.033 m<span class="inline-formula"><sup>3</sup></span> m<span class="inline-formula"><sup>−3</sup></span>, root mean square errors from 0.076 to 0.104 m<span class="inline-formula"><sup>3</sup></span> m<span class="inline-formula"><sup>−3</sup></span>, Pearson correlations from 0.35 to 0.67) and multiple gridded datasets that did not enter merging because of insufficient spatial, temporal, or soil layer coverage. Three of the new SM products, which were produced by applying any of the three merging methods to the source datasets excluding the ESMs, had lower bias and root mean square errors and higher correlations than the ESM-dependent merged products. The ESM-independent products also showed a better ability to capture historical large-scale drought events than the ESM-dependent products. The merged products generally showed reasonable temporal homogeneity and physically plausible global sensitivities to observed meteorological factors, except that the ESM-dependent products underestimated the low-frequency temporal variability in SM and overestimated the high-frequency variability for the 50–100 cm depth. Based on these evaluation results, the three ESM-independent products were finally recommended for future applications because of their better performances than the ESM-dependent ones. Despite uncertainties in the raw SM datasets and fusion methods, these hybrid products create added value over existing SM datasets because of the performance improvement and harmonized spatial, temporal, and vertical coverages, and they provide a new foundation for scientific investigation and resource management.</p>https://essd.copernicus.org/articles/13/4385/2021/essd-13-4385-2021.pdf |