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  • Author or Editor: Min Chen x
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Yaling Liu
,
Dongdong Chen
,
Soukayna Mouatadid
,
Xiaoliang Lu
,
Min Chen
,
Yu Cheng
,
Zhenghui Xie
,
Binghao Jia
,
Huan Wu
, and
Pierre Gentine

Abstract

Soil moisture (SM) links the water and energy cycles over the land–atmosphere interface and largely determines ecosystem functionality, positioning it as an essential player in the Earth system. Despite its importance, accurate estimation of large-scale SM remains a challenge. Here we leverage the strength of neural network (NN) and fidelity of long-term measurements to develop a daily multilayer cropland SM dataset for China from 1981 to 2013, implemented for a range of different cropping patterns. The training and testing of the NN for the five soil layers (0–50 cm, 10-cm depth each) yield R 2 values of 0.65–0.70 and 0.64–0.69, respectively. Our analysis reveals that precipitation and soil properties are the two dominant factors determining SM, but cropping pattern is also crucial. In addition, our simulations of alternative cropping patterns indicate that winter wheat followed by fallow will largely alleviate the SM depletion in most parts of China. On the other hand, cropping patterns of fallow in the winter followed by maize/soybean seem to further aggravate SM decline in the Huang-Huai-Hai region and southwestern China, relative to prevalent practices of double cropping. This may be due to their low soil porosity, which results in more soil water drainage, as opposed to the case that winter crop roots help maintain SM. This multilayer cropland SM dataset with granularity of cropping patterns provides an important alternative and is complementary to modeled and satellite-retrieved products.

Full access
Xin-Min Zeng
,
B. Wang
,
Y. Zhang
,
Y. Zheng
,
N. Wang
,
M. Wang
,
X. Yi
,
C. Chen
,
Z. Zhou
, and
H. Liu

Abstract

To quantify and explain effects of different land surface schemes (LSSs) on simulated geopotential height (GPH) fields, we performed simulations over China for the summer of 2003 using 12-member ensembles with the Weather Research and Forecasting (WRF) Model, version 3. The results show that while the model can generally simulate the seasonal and monthly mean GPH patterns, the effects of the LSS choice on simulated GPH fields are substantial, with the LSS-induced differences exceeding 10 gpm over a large area (especially the northwest) of China, which is very large compared with climate anomalies and forecast errors. In terms of the assessment measures for the four LSS ensembles [namely, the five-layer thermal diffusion scheme (SLAB), the Noah LSS (NOAH), the Rapid Update Cycle LSS (RUC), and the Pleim–Xiu LSS (PLEX)] in the WRF, the PLEX ensemble is the best, followed by the NOAH, RUC, and SLAB ensembles. The sensitivity of the simulated 850-hPa GPH is more significant than that of the 500-hPa GPH, with the 500-hPa GPH difference fields generally characterized by two large areas with opposite signs due to the smoothly varying nature of GPHs. LSS-induced GPH sensitivity is found to be higher than the GPH sensitivity induced by atmospheric boundary layer schemes. Moreover, theoretical analyses show that the LSS-induced GPH sensitivity is mainly caused by changes in surface fluxes (in particular, sensible heat flux), which further modify atmospheric temperature and pressure fields. The temperature and pressure fields generally have opposite contributions to changes in the GPH. This study emphasizes the importance of choosing and improving LSSs for simulating seasonal and monthly GPHs using regional climate models.

Full access
Tzu-Ying Yang
,
Cho-Ying Huang
,
Jehn-Yih Juang
,
Yi-Ying Chen
,
Chao-Tzuen Cheng
, and
Min-Hui Lo

Abstract

Fog plays a vital role in maintaining ecosystems in montane cloud forests. In these forests, a large amount of water on the surface of leaves and canopy (hereafter canopy water) evaporates during the morning. This biophysical process plays a critical factor in regulating afternoon fog formation. Recent studies have found that alterations in precipitation, temperature, humidity, and CO2 concentrations associated with future climate changes may affect terrestrial hydroclimatology, but the responses in cloud forests remain unclear. Utilizing numerical experiments with the Community Land Model, we explored changes in surface evaporative fluxes in Chi-Lan Mountain cloud forests in northeastern Taiwan under the RCP8.5 scenario with changes in the aforementioned various atmospheric variables. The results showed that increased rainfall intensity in climate change runs decreased the accumulation of canopy water, while larger water vapor concentrations led to more nighttime condensation on leaves. Elevated CO2 concentrations did not greatly impact canopy water amounts, but photosynthesis was enhanced, while transpiration was reduced and contributed to decreased latent heat fluxes, implying the importance of forest plant physiology in modulating land evaporative fluxes. Evapotranspiration decreased in Chi-Lan due to multiple combined factors, in contrast to the expected intensification in the global water cycle under global warming. The study, however, is restricted to an offline land surface model without land–atmosphere interactions and the interactions with adjacent grids, which deserves further analyses for the water cycle changes in the montane cloud forest regions.

Open access
Rong-Yu Gu
,
Min-Hui Lo
,
Chi-Ya Liao
,
Yi-Shin Jang
,
Jehn-Yih Juang
,
Cho-Ying Huang
,
Shih-Chieh Chang
,
Cheng-I Hsieh
,
Yi-Ying Chen
,
Housen Chu
, and
Kuang-Yu Chang

Abstract

Hydroclimate in the montane cloud forest (MCF) regions is unique for its frequent fog occurrence and abundant water interception by tree canopies. Latent heat (LH) flux, the energy flux associated with evapotranspiration (ET), plays an essential role in modulating energy and hydrological cycles. However, how LH flux is partitioned between transpiration (stomatal evaporation) and evaporation (nonstomatal evaporation) and how it impacts local hydroclimate remain unclear. In this study, we investigated how fog modulates the energy and hydrological cycles of MCF by using a combination of in situ observations and model simulations. We compared LH flux and associated micrometeorological conditions at two eddy-covariance sites—Chi-Lan (CL), an MCF, and Lien-Hua-Chih (LHC), a noncloud forest in Taiwan. The comparison between the two sites reveals an asymmetric LH flux with an early peak at 0900 local time in CL as opposed to LHC, where LH flux peaks at noon. The early peak of LH flux and its evaporative cooling dampen the increase in near-surface temperature during the morning hours in CL. The relatively small diurnal temperature range, abundant moisture brought by the valley wind, and local ET result in frequent afternoon fog formation. Fog water is then intercepted by the canopy, sustaining moist conditions throughout the night. To further illustrate this hydrological feedback, we used a land surface model to simulate how varying canopy water interception can affect surface energy and moisture budgets. Our study highlights the unique hydroclimatological cycle in the MCF and, specifically, the inseparable relationship between the canopy and near-surface meteorology during the diurnal cycle.

Open access