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Guo Zhang, Guangsheng Zhou, Fei Chen, Michael Barlage, and Lulin Xue


It is still a daunting challenge for land surface models (LSMs) to correctly represent surface heat exchange for water-limited desert steppe ecosystems. This study aims to improve the ability of the Noah LSM to simulate surface heat fluxes through addressing uncertainties in precipitation forcing conditions, rapidly evolving vegetation properties, soil hydraulic properties (SHPs), and key parameterization schemes. Three years (2008–10) of observed surface heat fluxes and soil temperature over a desert steppe site in Inner Mongolia, China, are used to verify model simulations. The proper seasonal distribution of precipitation, along with more realistic vegetation parameters, can improve the simulation of sensible heat flux (SH) and the seasonal variability of latent heat flux. Correctly representing the low-surface exchange coefficient is crucial for improving SH for short vegetation like this desert steppe site. Relating C zil, the coefficient in the Noah surface exchange coefficient calculation, with canopy height h improves the simulated SH and the diurnal range of soil temperature over the simulation compared with using the default constant C zil. The exponential water stress formulation proposed here for the Jarvis scheme improves the partitioning between soil evaporation and transpiration. It is found that the surface energy fluxes are very sensitive to SHPs. This study highlights the important role of the proper parameter values and appropriate parameterizations for the surface exchange coefficient and water stress function in canopy resistance in capturing the observed surface energy fluxes and soil temperature variations for this desert steppe site.

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Fei Chen, Guo Zhang, Michael Barlage, Ying Zhang, Jeffrey A. Hicke, Arjan Meddens, Guangsheng Zhou, William J. Massman, and John Frank


Bark beetle outbreaks have killed billions of trees and affected millions of hectares of forest during recent decades. The objective of this study was to quantify responses of surface energy and hydrologic fluxes 2–3 yr following a spruce beetle outbreak using measurements and modeling. The authors used observations at the Rocky Mountains Glacier Lakes Ecosystem Experiments Site (GLEES), where beetles killed 85% of the basal area of spruce from 2005–07 (prebeetle) to 2009/10 (postbeetle). Observations showed increased albedo following tree mortality, more reflected solar radiation, and less net radiation, but these postoutbreak radiation changes are smaller than or comparable to their annual preoutbreak variability. The dominant signals from observations were a large reduction (27%) in summer daytime evaporation and a large increase (25%) in sensible heat fluxes. Numerous Noah LSM with multiparameterization options (Noah-MP) simulations incorporating beetle-caused tree mortality effects were conducted to assess their impact on the surface hydrological cycle components that were not directly observed. Model results revealed substantial seasonal variations: more spring snowmelt and runoff, less spring–summer transpiration, and drier soil in summer and fall. This modeled trend is similar to observed runoff changes in harvested forests where reduced forest density resulted in more spring snowmelt and annual water yields. Model results showed that snow albedo changes due to increased litter cover beneath killed trees altered the seasonal pattern of simulated snowmelt and snow water equivalent, but these changes are small compared to the effect of leaf loss. This study highlights the need to include the transient effects of forest disturbances in modeling land–atmosphere interactions and their potential impacts on regional weather and climate.

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Hanqin Tian, Jia Yang, Chaoqun Lu, Rongting Xu, Josep G. Canadell, Robert B. Jackson, Almut Arneth, Jinfeng Chang, Guangsheng Chen, Philippe Ciais, Stefan Gerber, Akihiko Ito, Yuanyuan Huang, Fortunat Joos, Sebastian Lienert, Palmira Messina, Stefan Olin, Shufen Pan, Changhui Peng, Eri Saikawa, Rona L. Thompson, Nicolas Vuichard, Wilfried Winiwarter, Sönke Zaehle, Bowen Zhang, Kerou Zhang, and Qiuan Zhu


Nitrous oxide (N2O) is an important greenhouse gas and also an ozone-depleting substance that has both natural and anthropogenic sources. Large estimation uncertainty remains on the magnitude and spatiotemporal patterns of N2O fluxes and the key drivers of N2O production in the terrestrial biosphere. Some terrestrial biosphere models have been evolved to account for nitrogen processes and to show the capability to simulate N2O emissions from land ecosystems at the global scale, but large discrepancies exist among their estimates primarily because of inconsistent input datasets, simulation protocol, and model structure and parameterization schemes. Based on the consistent model input data and simulation protocol, the global N2O Model Intercomparison Project (NMIP) was initialized with 10 state-of-the-art terrestrial biosphere models that include nitrogen (N) cycling. Specific objectives of NMIP are to 1) unravel the major N cycling processes controlling N2O fluxes in each model and identify the uncertainty sources from model structure, input data, and parameters; 2) quantify the magnitude and spatial and temporal patterns of global and regional N2O fluxes from the preindustrial period (1860) to present and attribute the relative contributions of multiple environmental factors to N2O dynamics; and 3) provide a benchmarking estimate of N2O fluxes through synthesizing the multimodel simulation results and existing estimates from ground-based observations, inventories, and statistical and empirical extrapolations. This study provides detailed descriptions for the NMIP protocol, input data, model structure, and key parameters, along with preliminary simulation results. The global and regional N2O estimation derived from the NMIP is a key component of the global N2O budget synthesis activity jointly led by the Global Carbon Project and the International Nitrogen Initiative.

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