Decadal Stabilization of Soil Inorganic Nitrogen as a Benchmark for Global Land Models

Abstract Global land models are now routinely incorporating the nitrogen (N) cycle into simulations, but the identification of its benchmarks has lagged behind. An important variable in these models is the soil inorganic N (SIN) which is the resultant of different input and output N processes. Howev...
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Autor*in:	Ning Wei [verfasserIn] Erqian Cui [verfasserIn] Kun Huang [verfasserIn] Zhenggang Du [verfasserIn] Jian Zhou [verfasserIn] Xiaoni Xu [verfasserIn] Jing Wang [verfasserIn] Liming Yan [verfasserIn] Jianyang Xia [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	benchmarking analysis biogeochemistry global land model soil inorganic nitrogen terrestrial nitrogen cycle

Übergeordnetes Werk:	In: Journal of Advances in Modeling Earth Systems - American Geophysical Union (AGU), 2014, 11(2019), 4, Seite 1088-1099
Übergeordnetes Werk:	volume:11 ; year:2019 ; number:4 ; pages:1088-1099

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1029/2019MS001633

Katalog-ID:	DOAJ051549735

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520			\|a Abstract Global land models are now routinely incorporating the nitrogen (N) cycle into simulations, but the identification of its benchmarks has lagged behind. An important variable in these models is the soil inorganic N (SIN) which is the resultant of different input and output N processes. However, whether and how the SIN pool and its spatiotemporal variation can be used as benchmarks for models remains unclear. Here we first constructed a database of measured SIN at 756 sites from 1980 to 2010 across China, one of the regions that has been experiencing the highest external N input. Although there was great spatial variability of the measured SIN pool, no significant changes were detected across China during 1980–2010 based on a bootstrapping approach. The medians of the measured SIN across China were 63, 70, and 65 mg/kg during the 1980s, 1990s, and 2000s, respectively. Then, we used the regional SIN database to evaluate two versions of the Community Land Model (i.e., CLM4.5 and CLM5.0). In comparison with the observation (median 75 mg/kg) at grid‐cell scale, both CLM4.5 (median 0.70 mg/kg) and CLM5.0 (median 0.79 mg/kg) underestimated the SIN pools across China. Although the drivers of such modeling biases are difficult to identify at the current stage, improved representations of both input and output processes of the SIN pool in the models are highly recommended. These findings suggest that a decadal stabilization of the SIN pool in terrestrial ecosystems and the spatial distribution of the SIN pool may be a useful benchmark for global biogeochemical models.
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650		4	\|a biogeochemistry
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650		4	\|a soil inorganic nitrogen
650		4	\|a terrestrial nitrogen cycle
653		0	\|a Physical geography
653		0	\|a Oceanography
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700	0		\|a Jian Zhou \|e verfasserin \|4 aut
700	0		\|a Xiaoni Xu \|e verfasserin \|4 aut
700	0		\|a Jing Wang \|e verfasserin \|4 aut
700	0		\|a Liming Yan \|e verfasserin \|4 aut
700	0		\|a Jianyang Xia \|e verfasserin \|4 aut
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author_variant	n w nw e c ec k h kh z d zd j z jz x x xx j w jw l y ly j x jx
matchkey_str	article:19422466:2019----::eaasaiiainfolnraintoeaaecmr
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allfields	10.1029/2019MS001633 doi (DE-627)DOAJ051549735 (DE-599)DOAJf7a681c7d645422a9092d949f11c6347 DE-627 ger DE-627 rakwb eng GB3-5030 GC1-1581 Ning Wei verfasserin aut Decadal Stabilization of Soil Inorganic Nitrogen as a Benchmark for Global Land Models 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Global land models are now routinely incorporating the nitrogen (N) cycle into simulations, but the identification of its benchmarks has lagged behind. An important variable in these models is the soil inorganic N (SIN) which is the resultant of different input and output N processes. However, whether and how the SIN pool and its spatiotemporal variation can be used as benchmarks for models remains unclear. Here we first constructed a database of measured SIN at 756 sites from 1980 to 2010 across China, one of the regions that has been experiencing the highest external N input. Although there was great spatial variability of the measured SIN pool, no significant changes were detected across China during 1980–2010 based on a bootstrapping approach. The medians of the measured SIN across China were 63, 70, and 65 mg/kg during the 1980s, 1990s, and 2000s, respectively. Then, we used the regional SIN database to evaluate two versions of the Community Land Model (i.e., CLM4.5 and CLM5.0). In comparison with the observation (median 75 mg/kg) at grid‐cell scale, both CLM4.5 (median 0.70 mg/kg) and CLM5.0 (median 0.79 mg/kg) underestimated the SIN pools across China. Although the drivers of such modeling biases are difficult to identify at the current stage, improved representations of both input and output processes of the SIN pool in the models are highly recommended. These findings suggest that a decadal stabilization of the SIN pool in terrestrial ecosystems and the spatial distribution of the SIN pool may be a useful benchmark for global biogeochemical models. benchmarking analysis biogeochemistry global land model soil inorganic nitrogen terrestrial nitrogen cycle Physical geography Oceanography Erqian Cui verfasserin aut Kun Huang verfasserin aut Zhenggang Du verfasserin aut Jian Zhou verfasserin aut Xiaoni Xu verfasserin aut Jing Wang verfasserin aut Liming Yan verfasserin aut Jianyang Xia verfasserin aut In Journal of Advances in Modeling Earth Systems American Geophysical Union (AGU), 2014 11(2019), 4, Seite 1088-1099 (DE-627)584406932 (DE-600)2462132-8 19422466 nnns volume:11 year:2019 number:4 pages:1088-1099 https://doi.org/10.1029/2019MS001633 kostenfrei https://doaj.org/article/f7a681c7d645422a9092d949f11c6347 kostenfrei https://doi.org/10.1029/2019MS001633 kostenfrei https://doaj.org/toc/1942-2466 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2019 4 1088-1099
spelling	10.1029/2019MS001633 doi (DE-627)DOAJ051549735 (DE-599)DOAJf7a681c7d645422a9092d949f11c6347 DE-627 ger DE-627 rakwb eng GB3-5030 GC1-1581 Ning Wei verfasserin aut Decadal Stabilization of Soil Inorganic Nitrogen as a Benchmark for Global Land Models 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Global land models are now routinely incorporating the nitrogen (N) cycle into simulations, but the identification of its benchmarks has lagged behind. An important variable in these models is the soil inorganic N (SIN) which is the resultant of different input and output N processes. However, whether and how the SIN pool and its spatiotemporal variation can be used as benchmarks for models remains unclear. Here we first constructed a database of measured SIN at 756 sites from 1980 to 2010 across China, one of the regions that has been experiencing the highest external N input. Although there was great spatial variability of the measured SIN pool, no significant changes were detected across China during 1980–2010 based on a bootstrapping approach. The medians of the measured SIN across China were 63, 70, and 65 mg/kg during the 1980s, 1990s, and 2000s, respectively. Then, we used the regional SIN database to evaluate two versions of the Community Land Model (i.e., CLM4.5 and CLM5.0). In comparison with the observation (median 75 mg/kg) at grid‐cell scale, both CLM4.5 (median 0.70 mg/kg) and CLM5.0 (median 0.79 mg/kg) underestimated the SIN pools across China. Although the drivers of such modeling biases are difficult to identify at the current stage, improved representations of both input and output processes of the SIN pool in the models are highly recommended. These findings suggest that a decadal stabilization of the SIN pool in terrestrial ecosystems and the spatial distribution of the SIN pool may be a useful benchmark for global biogeochemical models. benchmarking analysis biogeochemistry global land model soil inorganic nitrogen terrestrial nitrogen cycle Physical geography Oceanography Erqian Cui verfasserin aut Kun Huang verfasserin aut Zhenggang Du verfasserin aut Jian Zhou verfasserin aut Xiaoni Xu verfasserin aut Jing Wang verfasserin aut Liming Yan verfasserin aut Jianyang Xia verfasserin aut In Journal of Advances in Modeling Earth Systems American Geophysical Union (AGU), 2014 11(2019), 4, Seite 1088-1099 (DE-627)584406932 (DE-600)2462132-8 19422466 nnns volume:11 year:2019 number:4 pages:1088-1099 https://doi.org/10.1029/2019MS001633 kostenfrei https://doaj.org/article/f7a681c7d645422a9092d949f11c6347 kostenfrei https://doi.org/10.1029/2019MS001633 kostenfrei https://doaj.org/toc/1942-2466 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2019 4 1088-1099
allfields_unstemmed	10.1029/2019MS001633 doi (DE-627)DOAJ051549735 (DE-599)DOAJf7a681c7d645422a9092d949f11c6347 DE-627 ger DE-627 rakwb eng GB3-5030 GC1-1581 Ning Wei verfasserin aut Decadal Stabilization of Soil Inorganic Nitrogen as a Benchmark for Global Land Models 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Global land models are now routinely incorporating the nitrogen (N) cycle into simulations, but the identification of its benchmarks has lagged behind. An important variable in these models is the soil inorganic N (SIN) which is the resultant of different input and output N processes. However, whether and how the SIN pool and its spatiotemporal variation can be used as benchmarks for models remains unclear. Here we first constructed a database of measured SIN at 756 sites from 1980 to 2010 across China, one of the regions that has been experiencing the highest external N input. Although there was great spatial variability of the measured SIN pool, no significant changes were detected across China during 1980–2010 based on a bootstrapping approach. The medians of the measured SIN across China were 63, 70, and 65 mg/kg during the 1980s, 1990s, and 2000s, respectively. Then, we used the regional SIN database to evaluate two versions of the Community Land Model (i.e., CLM4.5 and CLM5.0). In comparison with the observation (median 75 mg/kg) at grid‐cell scale, both CLM4.5 (median 0.70 mg/kg) and CLM5.0 (median 0.79 mg/kg) underestimated the SIN pools across China. Although the drivers of such modeling biases are difficult to identify at the current stage, improved representations of both input and output processes of the SIN pool in the models are highly recommended. These findings suggest that a decadal stabilization of the SIN pool in terrestrial ecosystems and the spatial distribution of the SIN pool may be a useful benchmark for global biogeochemical models. benchmarking analysis biogeochemistry global land model soil inorganic nitrogen terrestrial nitrogen cycle Physical geography Oceanography Erqian Cui verfasserin aut Kun Huang verfasserin aut Zhenggang Du verfasserin aut Jian Zhou verfasserin aut Xiaoni Xu verfasserin aut Jing Wang verfasserin aut Liming Yan verfasserin aut Jianyang Xia verfasserin aut In Journal of Advances in Modeling Earth Systems American Geophysical Union (AGU), 2014 11(2019), 4, Seite 1088-1099 (DE-627)584406932 (DE-600)2462132-8 19422466 nnns volume:11 year:2019 number:4 pages:1088-1099 https://doi.org/10.1029/2019MS001633 kostenfrei https://doaj.org/article/f7a681c7d645422a9092d949f11c6347 kostenfrei https://doi.org/10.1029/2019MS001633 kostenfrei https://doaj.org/toc/1942-2466 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2019 4 1088-1099
allfieldsGer	10.1029/2019MS001633 doi (DE-627)DOAJ051549735 (DE-599)DOAJf7a681c7d645422a9092d949f11c6347 DE-627 ger DE-627 rakwb eng GB3-5030 GC1-1581 Ning Wei verfasserin aut Decadal Stabilization of Soil Inorganic Nitrogen as a Benchmark for Global Land Models 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Global land models are now routinely incorporating the nitrogen (N) cycle into simulations, but the identification of its benchmarks has lagged behind. An important variable in these models is the soil inorganic N (SIN) which is the resultant of different input and output N processes. However, whether and how the SIN pool and its spatiotemporal variation can be used as benchmarks for models remains unclear. Here we first constructed a database of measured SIN at 756 sites from 1980 to 2010 across China, one of the regions that has been experiencing the highest external N input. Although there was great spatial variability of the measured SIN pool, no significant changes were detected across China during 1980–2010 based on a bootstrapping approach. The medians of the measured SIN across China were 63, 70, and 65 mg/kg during the 1980s, 1990s, and 2000s, respectively. Then, we used the regional SIN database to evaluate two versions of the Community Land Model (i.e., CLM4.5 and CLM5.0). In comparison with the observation (median 75 mg/kg) at grid‐cell scale, both CLM4.5 (median 0.70 mg/kg) and CLM5.0 (median 0.79 mg/kg) underestimated the SIN pools across China. Although the drivers of such modeling biases are difficult to identify at the current stage, improved representations of both input and output processes of the SIN pool in the models are highly recommended. These findings suggest that a decadal stabilization of the SIN pool in terrestrial ecosystems and the spatial distribution of the SIN pool may be a useful benchmark for global biogeochemical models. benchmarking analysis biogeochemistry global land model soil inorganic nitrogen terrestrial nitrogen cycle Physical geography Oceanography Erqian Cui verfasserin aut Kun Huang verfasserin aut Zhenggang Du verfasserin aut Jian Zhou verfasserin aut Xiaoni Xu verfasserin aut Jing Wang verfasserin aut Liming Yan verfasserin aut Jianyang Xia verfasserin aut In Journal of Advances in Modeling Earth Systems American Geophysical Union (AGU), 2014 11(2019), 4, Seite 1088-1099 (DE-627)584406932 (DE-600)2462132-8 19422466 nnns volume:11 year:2019 number:4 pages:1088-1099 https://doi.org/10.1029/2019MS001633 kostenfrei https://doaj.org/article/f7a681c7d645422a9092d949f11c6347 kostenfrei https://doi.org/10.1029/2019MS001633 kostenfrei https://doaj.org/toc/1942-2466 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2019 4 1088-1099
allfieldsSound	10.1029/2019MS001633 doi (DE-627)DOAJ051549735 (DE-599)DOAJf7a681c7d645422a9092d949f11c6347 DE-627 ger DE-627 rakwb eng GB3-5030 GC1-1581 Ning Wei verfasserin aut Decadal Stabilization of Soil Inorganic Nitrogen as a Benchmark for Global Land Models 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Global land models are now routinely incorporating the nitrogen (N) cycle into simulations, but the identification of its benchmarks has lagged behind. An important variable in these models is the soil inorganic N (SIN) which is the resultant of different input and output N processes. However, whether and how the SIN pool and its spatiotemporal variation can be used as benchmarks for models remains unclear. Here we first constructed a database of measured SIN at 756 sites from 1980 to 2010 across China, one of the regions that has been experiencing the highest external N input. Although there was great spatial variability of the measured SIN pool, no significant changes were detected across China during 1980–2010 based on a bootstrapping approach. The medians of the measured SIN across China were 63, 70, and 65 mg/kg during the 1980s, 1990s, and 2000s, respectively. Then, we used the regional SIN database to evaluate two versions of the Community Land Model (i.e., CLM4.5 and CLM5.0). In comparison with the observation (median 75 mg/kg) at grid‐cell scale, both CLM4.5 (median 0.70 mg/kg) and CLM5.0 (median 0.79 mg/kg) underestimated the SIN pools across China. Although the drivers of such modeling biases are difficult to identify at the current stage, improved representations of both input and output processes of the SIN pool in the models are highly recommended. These findings suggest that a decadal stabilization of the SIN pool in terrestrial ecosystems and the spatial distribution of the SIN pool may be a useful benchmark for global biogeochemical models. benchmarking analysis biogeochemistry global land model soil inorganic nitrogen terrestrial nitrogen cycle Physical geography Oceanography Erqian Cui verfasserin aut Kun Huang verfasserin aut Zhenggang Du verfasserin aut Jian Zhou verfasserin aut Xiaoni Xu verfasserin aut Jing Wang verfasserin aut Liming Yan verfasserin aut Jianyang Xia verfasserin aut In Journal of Advances in Modeling Earth Systems American Geophysical Union (AGU), 2014 11(2019), 4, Seite 1088-1099 (DE-627)584406932 (DE-600)2462132-8 19422466 nnns volume:11 year:2019 number:4 pages:1088-1099 https://doi.org/10.1029/2019MS001633 kostenfrei https://doaj.org/article/f7a681c7d645422a9092d949f11c6347 kostenfrei https://doi.org/10.1029/2019MS001633 kostenfrei https://doaj.org/toc/1942-2466 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2019 4 1088-1099
language	English
source	In Journal of Advances in Modeling Earth Systems 11(2019), 4, Seite 1088-1099 volume:11 year:2019 number:4 pages:1088-1099
sourceStr	In Journal of Advances in Modeling Earth Systems 11(2019), 4, Seite 1088-1099 volume:11 year:2019 number:4 pages:1088-1099
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	benchmarking analysis biogeochemistry global land model soil inorganic nitrogen terrestrial nitrogen cycle Physical geography Oceanography
isfreeaccess_bool	true
container_title	Journal of Advances in Modeling Earth Systems
authorswithroles_txt_mv	Ning Wei @@aut@@ Erqian Cui @@aut@@ Kun Huang @@aut@@ Zhenggang Du @@aut@@ Jian Zhou @@aut@@ Xiaoni Xu @@aut@@ Jing Wang @@aut@@ Liming Yan @@aut@@ Jianyang Xia @@aut@@
publishDateDaySort_date	2019-01-01T00:00:00Z
hierarchy_top_id	584406932
id	DOAJ051549735
language_de	englisch
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ051549735</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230502085812.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230227s2019 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1029/2019MS001633</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ051549735</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJf7a681c7d645422a9092d949f11c6347</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">GB3-5030</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">GC1-1581</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Ning Wei</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Decadal Stabilization of Soil Inorganic Nitrogen as a Benchmark for Global Land Models</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Global land models are now routinely incorporating the nitrogen (N) cycle into simulations, but the identification of its benchmarks has lagged behind. An important variable in these models is the soil inorganic N (SIN) which is the resultant of different input and output N processes. However, whether and how the SIN pool and its spatiotemporal variation can be used as benchmarks for models remains unclear. Here we first constructed a database of measured SIN at 756 sites from 1980 to 2010 across China, one of the regions that has been experiencing the highest external N input. Although there was great spatial variability of the measured SIN pool, no significant changes were detected across China during 1980–2010 based on a bootstrapping approach. The medians of the measured SIN across China were 63, 70, and 65 mg/kg during the 1980s, 1990s, and 2000s, respectively. Then, we used the regional SIN database to evaluate two versions of the Community Land Model (i.e., CLM4.5 and CLM5.0). 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callnumber-first	G - Geography, Anthropology, Recreation
author	Ning Wei
spellingShingle	Ning Wei misc GB3-5030 misc GC1-1581 misc benchmarking analysis misc biogeochemistry misc global land model misc soil inorganic nitrogen misc terrestrial nitrogen cycle misc Physical geography misc Oceanography Decadal Stabilization of Soil Inorganic Nitrogen as a Benchmark for Global Land Models
authorStr	Ning Wei
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topic_title	GB3-5030 GC1-1581 Decadal Stabilization of Soil Inorganic Nitrogen as a Benchmark for Global Land Models benchmarking analysis biogeochemistry global land model soil inorganic nitrogen terrestrial nitrogen cycle
topic	misc GB3-5030 misc GC1-1581 misc benchmarking analysis misc biogeochemistry misc global land model misc soil inorganic nitrogen misc terrestrial nitrogen cycle misc Physical geography misc Oceanography
topic_unstemmed	misc GB3-5030 misc GC1-1581 misc benchmarking analysis misc biogeochemistry misc global land model misc soil inorganic nitrogen misc terrestrial nitrogen cycle misc Physical geography misc Oceanography
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title	Decadal Stabilization of Soil Inorganic Nitrogen as a Benchmark for Global Land Models
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title_full	Decadal Stabilization of Soil Inorganic Nitrogen as a Benchmark for Global Land Models
author_sort	Ning Wei
journal	Journal of Advances in Modeling Earth Systems
journalStr	Journal of Advances in Modeling Earth Systems
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author_browse	Ning Wei Erqian Cui Kun Huang Zhenggang Du Jian Zhou Xiaoni Xu Jing Wang Liming Yan Jianyang Xia
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author-letter	Ning Wei
doi_str_mv	10.1029/2019MS001633
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title_sort	decadal stabilization of soil inorganic nitrogen as a benchmark for global land models
callnumber	GB3-5030
title_auth	Decadal Stabilization of Soil Inorganic Nitrogen as a Benchmark for Global Land Models
abstract	Abstract Global land models are now routinely incorporating the nitrogen (N) cycle into simulations, but the identification of its benchmarks has lagged behind. An important variable in these models is the soil inorganic N (SIN) which is the resultant of different input and output N processes. However, whether and how the SIN pool and its spatiotemporal variation can be used as benchmarks for models remains unclear. Here we first constructed a database of measured SIN at 756 sites from 1980 to 2010 across China, one of the regions that has been experiencing the highest external N input. Although there was great spatial variability of the measured SIN pool, no significant changes were detected across China during 1980–2010 based on a bootstrapping approach. The medians of the measured SIN across China were 63, 70, and 65 mg/kg during the 1980s, 1990s, and 2000s, respectively. Then, we used the regional SIN database to evaluate two versions of the Community Land Model (i.e., CLM4.5 and CLM5.0). In comparison with the observation (median 75 mg/kg) at grid‐cell scale, both CLM4.5 (median 0.70 mg/kg) and CLM5.0 (median 0.79 mg/kg) underestimated the SIN pools across China. Although the drivers of such modeling biases are difficult to identify at the current stage, improved representations of both input and output processes of the SIN pool in the models are highly recommended. These findings suggest that a decadal stabilization of the SIN pool in terrestrial ecosystems and the spatial distribution of the SIN pool may be a useful benchmark for global biogeochemical models.
abstractGer	Abstract Global land models are now routinely incorporating the nitrogen (N) cycle into simulations, but the identification of its benchmarks has lagged behind. An important variable in these models is the soil inorganic N (SIN) which is the resultant of different input and output N processes. However, whether and how the SIN pool and its spatiotemporal variation can be used as benchmarks for models remains unclear. Here we first constructed a database of measured SIN at 756 sites from 1980 to 2010 across China, one of the regions that has been experiencing the highest external N input. Although there was great spatial variability of the measured SIN pool, no significant changes were detected across China during 1980–2010 based on a bootstrapping approach. The medians of the measured SIN across China were 63, 70, and 65 mg/kg during the 1980s, 1990s, and 2000s, respectively. Then, we used the regional SIN database to evaluate two versions of the Community Land Model (i.e., CLM4.5 and CLM5.0). In comparison with the observation (median 75 mg/kg) at grid‐cell scale, both CLM4.5 (median 0.70 mg/kg) and CLM5.0 (median 0.79 mg/kg) underestimated the SIN pools across China. Although the drivers of such modeling biases are difficult to identify at the current stage, improved representations of both input and output processes of the SIN pool in the models are highly recommended. These findings suggest that a decadal stabilization of the SIN pool in terrestrial ecosystems and the spatial distribution of the SIN pool may be a useful benchmark for global biogeochemical models.
abstract_unstemmed	Abstract Global land models are now routinely incorporating the nitrogen (N) cycle into simulations, but the identification of its benchmarks has lagged behind. An important variable in these models is the soil inorganic N (SIN) which is the resultant of different input and output N processes. However, whether and how the SIN pool and its spatiotemporal variation can be used as benchmarks for models remains unclear. Here we first constructed a database of measured SIN at 756 sites from 1980 to 2010 across China, one of the regions that has been experiencing the highest external N input. Although there was great spatial variability of the measured SIN pool, no significant changes were detected across China during 1980–2010 based on a bootstrapping approach. The medians of the measured SIN across China were 63, 70, and 65 mg/kg during the 1980s, 1990s, and 2000s, respectively. Then, we used the regional SIN database to evaluate two versions of the Community Land Model (i.e., CLM4.5 and CLM5.0). In comparison with the observation (median 75 mg/kg) at grid‐cell scale, both CLM4.5 (median 0.70 mg/kg) and CLM5.0 (median 0.79 mg/kg) underestimated the SIN pools across China. Although the drivers of such modeling biases are difficult to identify at the current stage, improved representations of both input and output processes of the SIN pool in the models are highly recommended. These findings suggest that a decadal stabilization of the SIN pool in terrestrial ecosystems and the spatial distribution of the SIN pool may be a useful benchmark for global biogeochemical models.
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title_short	Decadal Stabilization of Soil Inorganic Nitrogen as a Benchmark for Global Land Models
url	https://doi.org/10.1029/2019MS001633 https://doaj.org/article/f7a681c7d645422a9092d949f11c6347 https://doaj.org/toc/1942-2466
remote_bool	true
author2	Erqian Cui Kun Huang Zhenggang Du Jian Zhou Xiaoni Xu Jing Wang Liming Yan Jianyang Xia
author2Str	Erqian Cui Kun Huang Zhenggang Du Jian Zhou Xiaoni Xu Jing Wang Liming Yan Jianyang Xia
ppnlink	584406932
callnumber-subject	GB - Physical Geography
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isOA_txt	true
hochschulschrift_bool	false
doi_str	10.1029/2019MS001633
callnumber-a	GB3-5030
up_date	2024-07-03T20:59:59.663Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ051549735</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230502085812.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230227s2019 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1029/2019MS001633</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ051549735</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJf7a681c7d645422a9092d949f11c6347</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">GB3-5030</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">GC1-1581</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Ning Wei</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Decadal Stabilization of Soil Inorganic Nitrogen as a Benchmark for Global Land Models</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Global land models are now routinely incorporating the nitrogen (N) cycle into simulations, but the identification of its benchmarks has lagged behind. An important variable in these models is the soil inorganic N (SIN) which is the resultant of different input and output N processes. However, whether and how the SIN pool and its spatiotemporal variation can be used as benchmarks for models remains unclear. Here we first constructed a database of measured SIN at 756 sites from 1980 to 2010 across China, one of the regions that has been experiencing the highest external N input. Although there was great spatial variability of the measured SIN pool, no significant changes were detected across China during 1980–2010 based on a bootstrapping approach. The medians of the measured SIN across China were 63, 70, and 65 mg/kg during the 1980s, 1990s, and 2000s, respectively. Then, we used the regional SIN database to evaluate two versions of the Community Land Model (i.e., CLM4.5 and CLM5.0). In comparison with the observation (median 75 mg/kg) at grid‐cell scale, both CLM4.5 (median 0.70 mg/kg) and CLM5.0 (median 0.79 mg/kg) underestimated the SIN pools across China. Although the drivers of such modeling biases are difficult to identify at the current stage, improved representations of both input and output processes of the SIN pool in the models are highly recommended. These findings suggest that a decadal stabilization of the SIN pool in terrestrial ecosystems and the spatial distribution of the SIN pool may be a useful benchmark for global biogeochemical models.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">benchmarking analysis</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">biogeochemistry</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">global land model</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">soil inorganic nitrogen</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">terrestrial nitrogen cycle</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Physical geography</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Oceanography</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Erqian 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