Reconciling global land model estimates and country reporting of anthropogenic land CO2 sources and sinks with the CMIP6 LUMIP NOAA/GFDL LM4.1 simulations

Author(s):  
Elena Shevliakova ◽  
Sergey Malyshev ◽  
Richard Houghton ◽  
Louis Verchot

<p>Global land models, which often served as components Earth system models, and national GHG inventories rely on different methods and produce different estimates of anthropogenic CO<sub>2</sub> emissions and uptakes from land use land cover changes throughout historical period. For example, for 2005 -2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO2 yr<sup>–1</sup> while the bookkeeping models is 5.2 ± 2.6 GtCO2 yr<sup>–1</sup> (IPCC SPM 2019).  Previous estimates with the 16 global stand-alone land models produced an estimate of the net land sink of 11.2 ± 2.6 GtCO2 yr<sup>–1</sup> during 2007– 2016 for the natural response of land to human-induced environmental changes such as increasing atmospheric CO<sub>2</sub> concentration, nitrogen deposition, and climate change (IPCC SPM 2019).  However, these 16 models do not provide separate estimates for the managed and unmanaged lands. </p><p> </p><p>Here we use results from simulations with the NOAA/GFDL new land model LM4.1 from the CMIP6 Land Use Model Inercomparison Project (LUMIP) to demonstrate how to reconcile the discrepancy between the inventories and land models estimates of the anthropogenic CO<sub>2 </sub>land emissions by using bookkeeping accounting approach applied to the model results.  In addition, we separate estimates of land fluxes on managed and unmanaged lands. Key features of this model include advanced, second generation dynamic vegetation representation and canopy competition, fire, and land use representation driven by full set of gross transitions from the CMIP6 land use scenarios.  We demonstrate how bookkeeping accounting combined with the LUMIP experiments can enhance understanding of land sector net emission estimates and their applications.</p>

2022 ◽  
Author(s):  
TC Chakraborty ◽  
Yun Qian

Abstract Although the influence of land use/land cover change on climate has become increasingly apparent, cities and other built-up areas are usually ignored when estimating large-scale historical climate change or for future projections since cities cover a small fraction of the terrestrial land surface1,2. As such, ground-based observations of urban near-surface meteorology are rare and most earth system models do not represent historical or future urban land cover3–7. Here, by combining global satellite observations of land surface temperature with historical estimates of built-up area, we demonstrate that the urban temperature signal on continental- to regional-scale warming has become non-negligible, especially for rapidly urbanizing regions in Asia. Consequently, expected urban expansion over the next century suggest further increased urban influence on surface climate under all future climate scenarios. Based on these results, we argue that, in line with other forms of land use/land cover change, urbanization should be explicitly included in future climate change assessments. This would require extensive model development to incorporate urban extent and biophysics in current-generation earth system models to quantify potential urban feedbacks on the climate system at multiple scales.


2019 ◽  
Vol 12 (5) ◽  
pp. 1753-1764 ◽  
Author(s):  
Min Chen ◽  
Chris R. Vernon ◽  
Maoyi Huang ◽  
Katherine V. Calvin ◽  
Ian P. Kraucunas

Abstract. Demeter is a community spatial downscaling model that disaggregates land use and land cover changes projected by integrated human–Earth system models. Demeter has not been intensively calibrated, and we still lack good knowledge about its sensitivity to key parameters and parameter uncertainties. We used long-term global satellite-based land cover records to calibrate key Demeter parameters. The results identified the optimal parameter values and showed that the parameterization substantially improved the model's performance. The parameters of intensification ratio and selection threshold were the most sensitive and needed to be carefully tuned, especially for regional applications. Further, small parameter uncertainties after calibration can be inflated when propagated into future scenarios, suggesting that users should consider the parameterization equifinality to better account for the uncertainties in Demeter-downscaled products. Our study provides a key reference for Demeter users and ultimately contributes to reducing the uncertainties in Earth system model simulations.


2019 ◽  
Author(s):  
Min Chen ◽  
Chris R. Vernon ◽  
Maoyi Huang ◽  
Katherine V. Calvin ◽  
Ian P. Kraucunas

Abstract. Demeter is a community spatial downscaling model that disaggregates land use and land cover changes projected by integrated human-Earth system models. Demeter has not been intensively calibrated, and we still lack a good knowledge about its sensitivity to key parameters and the parameter uncertainties. We used long-term global satellite-based land cover records to calibrate key Demeter parameters. The results identified the optimal parameter values and showed that the parameterization substantially improved the model’s performance. The parameters of intensification ratio and selection threshold were the most sensitive and needed to be carefully tuned, especially for regional applications. Further, small parameter uncertainties after calibration can be inflated when propagated into future scenarios, suggesting that users should consider the parameterization equifinality to better account for the uncertainties in the Demeter downscaled products. Our study provides a key reference for Demeter users, and ultimately contribute to reducing the uncertainties in Earth system model simulations.


2021 ◽  
Vol 14 (14) ◽  
Author(s):  
Syed Atif Bokhari ◽  
Zafeer Saqib ◽  
Amjad Ali ◽  
Arif Mahmud ◽  
Nadia Akhtar ◽  
...  

2020 ◽  
Vol 18 ◽  
pp. 100314 ◽  
Author(s):  
Abdulla - Al Kafy ◽  
Md. Shahinoor Rahman ◽  
Abdullah-Al- Faisal ◽  
Mohammad Mahmudul Hasan ◽  
Muhaiminul Islam

2011 ◽  
Vol 2 (6) ◽  
pp. 828-850 ◽  
Author(s):  
Roger A. Pielke ◽  
Andy Pitman ◽  
Dev Niyogi ◽  
Rezaul Mahmood ◽  
Clive McAlpine ◽  
...  

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