A comprehensive 30×30 arc‐second resolution gridded soil characteristics data set of China has been developed for use in the land surface modeling. It includes physical and chemical attributes of soils derived from 8979 soil profiles and the Soil Map of China (1:1,000,000). We used the polygon linkage method to derive the spatial distribution of soil properties. The profile attribute database and soil map are linked under the framework of the Genetic Soil Classification of China which avoids uncertainty in taxon referencing. Quality control information (i.e., sample size, soil classification level, linkage level, search radius and texture) is included to provide “confidence” information for the derived soil parameters. The data set includes 28 attributes for 8 vertical layers at the spatial resolution of 30×30 arc‐seconds. Based on this data set, the estimated storage of soil organic carbon in the upper 1 m of soil is 72.5 Pg, total N is 6.6 Pg, total P is 4.5 Pg, total K is 169.9 Pg, alkali‐hydrolysable N is 0.55 Pg, available P is 0.03 Pg, and available K is 0.61 Pg. These estimates are reasonable compared with previous studies. The distributions of soil properties are consistent with common knowledge of Chinese soil scientists and the spatial variations over large areas are well represented. The data set can be incorporated into land models to better represent the role of soils in hydrological and biogeochemical cycles in China.
Realistic projection of future climate‐carbon (C) cycle feedbacks requires better understanding and an improved representation of the C cycle in permafrost regions in the current generation of Earth system models. Here we evaluated 10 terrestrial ecosystem models for their estimates of net primary productivity (NPP) and responses to historical climate change in permafrost regions in the Northern Hemisphere. In comparison with the satellite estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS; 246 ± 6 g C m−2 yr−1), most models produced higher NPP (309 ± 12 g C m−2 yr−1) over the permafrost region during 2000–2009. By comparing the simulated gross primary productivity (GPP) with a flux tower‐based database, we found that although mean GPP among the models was only overestimated by 10% over 1982–2009, there was a twofold discrepancy among models (380 to 800 g C m−2 yr−1), which mainly resulted from differences in simulated maximum monthly GPP (GPPmax). Most models overestimated C use efficiency (CUE) as compared to observations at both regional and site levels. Further analysis shows that model variability of GPP and CUE are nonlinearly correlated to variability in specific leaf area and the maximum rate of carboxylation by the enzyme Rubisco at 25°C (Vcmax_25), respectively. The models also varied in their sensitivities of NPP, GPP, and CUE to historical changes in climate and atmospheric CO2 concentration. These results indicate that model predictive ability of the C cycle in permafrost regions can be improved by better representation of the processes controlling CUE and GPPmax as well as their sensitivity to climate change.
The majority of extant studies that focus on performance and efficiency benchmarking of firms utilize only operational measures while neglecting to integrate stock market indicators in their methodological frameworks. Such an approach may lead to erroneous or biased conclusions given that operational and stock measures serve to capture different dimensions and attributes of an overall firm's activities, health, and prospects. Thus, we build and implement a two‐stage network data envelopment analysis process that utilizes both operational and stock market indicators in order to evaluate the performance of nine major international airline companies from 2006 until 2016. In our analysis, we show that there is heterogeneity in the performance of all airlines across time. Most notably, during the 2013–2014 European debt crisis and U.S. debt‐ceiling crisis, we find that stock market‐based performance scores declined significantly for all our sampled companies. We also show that while low cost carriers generally maintain higher operational‐based performance scores than their full service counterparts, full service carriers earn higher performance scores based on stock market indicators. This finding lends support to our approach and our general premise that argues that performance evaluation methods can yield more comprehensive conclusions if both operational and stock market indicators are utilized.
Abstract. The northern-high-latitude permafrost contains almost twice the carbon content of the atmosphere, and it is widely considered to be a non-linear and tipping element in the earth's climate system under global warming. Solar geoengineering is a means of mitigating temperature rise and reduces some of the associated climate impacts by increasing the planetary albedo; the permafrost thaw is expected to be moderated under slower temperature rise. We analyze the permafrost response as simulated by five fully coupled earth system models (ESMs) and one offline land surface model under four future scenarios; two solar geoengineering scenarios (G6solar and G6sulfur) based on the high-emission scenario (ssp585) restore the global temperature from the ssp585 levels to the moderate-mitigation scenario (ssp245) levels via solar dimming and stratospheric aerosol injection. G6solar and G6sulfur can slow the northern-high-latitude permafrost degradation but cannot restore the permafrost states from ssp585 to those under ssp245. G6solar and G6sulfur tend to produce a deeper active layer than ssp245 and expose more thawed soil organic carbon (SOC) due to robust residual high-latitude warming, especially over northern Eurasia. G6solar and G6sulfur preserve more SOC of 4.6 ± 4.6 and 3.4 ± 4.8 Pg C (coupled ESM simulations) or 16.4 ± 4.7 and 12.3 ± 7.9 Pg C (offline land surface model simulations), respectively, than ssp585 in the northern near-surface permafrost region. The turnover times of SOC decline slower under G6solar and G6sulfur than ssp585 but faster than ssp245. The permafrost carbon–climate feedback is expected to be weaker under solar geoengineering.
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