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Rapid urbanization in China in the past several decades has been shown to affect surface air temperature (SAT) locally, but its global impact is unclear. Using a global climate model, we have investigated the potential impact of urbanization in China on SAT at the global scale. The expansion of urban areas in China from 1985 to 2017 leads to winter surface air warming by as much as 0.8°C in North America (NA), largely caused by warm temperature advection due to global‐scale atmospheric circulation changes. The East Asian jet stream moves northward in eastern and northeastern China where the expansion of urban areas has increased SAT and sensible heat flux, forcing change of the atmospheric stationary waves and so the structure of the jet streams. Plain Language Summary: Rapid urbanization in China has been found to impact surface air temperature (SAT) at local and regional scales significantly through altered land surface properties. However, its impacts on global climate are less clear. Using a state‐of‐the‐art global climate model, we show that tremendous expansion of urban areas in China from 1985 to 2017 has resulted in global‐scale atmospheric circulation changes by altered surface properties and enhanced anthropogenic heating. Anomalous atmospheric circulation engenders changes of SAT by as much as 0.8°C in winter over NA, which is more pronounced than the local SAT changes in China for any season. This study provides a robust conceptual advance in understanding the climate implications of land use change especially on the global impacts of urbanization. Key Points: The fractional coverage of impermeable land surface has increased by six‐fold in China from 1985 to 2017Urbanization in China results in winter surface air warming by as much as 0.8°C in North AmericaThe altered atmospheric stationary waves and East Asian jet streams are responsible for winter warming in North America [ABSTRACT FROM AUTHOR]

We evaluate the Community Atmosphere Model Version 5 (CAM5) with a higher-order turbulence closure scheme, named Cloud Layers Unified By Binomials (CLUBB), and a Multiscale Modeling Framework, referred to as the 'superparameterization' (SP) with two different microphysics configurations to investigate their influences on rainfall simulations over southern Amazonia. The two different microphysics configurations in SP are the one-moment cloud microphysics without aerosol treatment (SP1) and two-moment cloud microphysics coupled with aerosol treatment (SP2). Results show that both SP2 and CLUBB effectively reduce the low biases of rainfall, mainly during the wet season, and reduce low biases of humidity in the lower troposphere with further reduced shallow clouds and increased surface solar flux. These changes increase moist static energy in the lower atmosphere and contribute to stronger convection and more rainfall. SP2 appears to realistically capture the observed increase of relative humidity prior to deep convection, and it significantly increases rainfall in the afternoon; CLUBB significantly delays the afternoon peak rainfall and produces more precipitation in the early morning, due to more gradual transition between shallow and deep convection. In CAM5 and CAM5 with CLUBB, occurrence of more deep convection appears to be a result of stronger heating rather than higher relative humidity. [ABSTRACT FROM AUTHOR]

Four representative two-stream canopy radiative transfer models were examined and intercompared using the same configuration. Based on the comparison results, two modifications were introduced to the widely used Dickinson-Sellers model and then incorporated into the Community Land Model (CLM4.5). The modified model was tested against Monte-Carlo simulations and produced significant improvements in the simulated canopy transmittance and albedo values. In direct comparison with MODIS albedo data, the modified model shows good performance over most snow/ice-free vegetated areas, especially for regions that are covered by dense canopy. The modified model shows seasonally dependent behavior mainly in the near-infrared band. Thus, the improvements are not present in all seasons. Large biases are still noticeable in sparsely vegetated areas, in particular for the snow/ice covered regions, that is possibly related to the model, the land surface input data, or even the observations themselves. Further studies focusing on the impact of the seasonal changes in leaf optical properties, the parameterizations for snow/ice covered regions and the case of sparsely vegetated areas, are recommended. [ABSTRACT FROM AUTHOR]

The article reports on smart-water-network (SWN) modeling technology and its significant role in effective planning for sustainable urban watershed management. It mentions its development in response to the impact of urbanization on natural water cycle which can lead to flooding, poor water quality and erosion. An overview of the United Nations Department of Economic and Social Affairs' (UNDESA) data on urban population growth is also presented.

Worldwide measurements of nearly 130 C3 species covering all major plant functional types are analysed in conjunction with model simulations to determine the effects of mesophyll conductance ( gm) on photosynthetic parameters and their relationships estimated from A/ Ci curves. We find that an assumption of infinite gm results in up to 75% underestimation for maximum carboxylation rate Vcmax, 60% for maximum electron transport rate Jmax, and 40% for triose phosphate utilization rate Tu. Vcmax is most sensitive, Jmax is less sensitive, and Tu has the least sensitivity to the variation of gm. Because of this asymmetrical effect of gm, the ratios of Jmax to Vcmax, Tu to Vcmax and Tu to Jmax are all overestimated. An infinite gm assumption also limits the freedom of variation of estimated parameters and artificially constrains parameter relationships to stronger shapes. These findings suggest the importance of quantifying gm for understanding in situ photosynthetic machinery functioning. We show that a nonzero resistance to CO2 movement in chloroplasts has small effects on estimated parameters. A non-linear function with gm as input is developed to convert the parameters estimated under an assumption of infinite gm to proper values. This function will facilitate gm representation in global carbon cycle models. [ABSTRACT FROM AUTHOR]

The article focuses on the use of a singular value decomposition (SVD) method to a 50-year climate simulation to explore the space-time connections between springtime soil moisture and summer precipitation over the continental U.S. It examines the influences of the relative importance of the land and ocean on precipitation changes with the seasons. A review of the coupling of Common Land Model (CLM) with National Center for Atmospheric Research Community Climate Model Version 3, which offers the soil moisture and precipitation data for the study, is presented.