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Tianbao Zhao
,
Weidong Guo
, and
Congbin Fu

Abstract

Based on the observed daily surface air temperature data from 597 stations over continental China and two sets of reanalysis data [NCEP–NCAR and 40-yr ECMWF Re-Analysis (ERA-40)] during 1979–2001, the altitude effects in calibrating and evaluating reanalyzed surface temperature errors are studied. The results indicate that the accuracy of interpolated surface temperature from the reanalyzed gridpoint value or the station observations depends much on the altitudes of original data. Bias of interpolated temperature is usually in proportion to the increase of local elevation and topographical complexity. Notable improvements of interpolated surface temperature have been achieved through “topographic correction,” especially for ERA-40, which highlights the necessity of removal of “elevation-induced bias” when using and evaluating reanalyzed surface temperature.

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Xing Luo
,
Jun Ge
,
Weidong Guo
,
Lei Fan
,
Chaorong Chen
,
Yu Liu
, and
Limei Yang

Abstract

Deforestation can impact precipitation through biophysical processes and such effects are commonly examined by models. However, previous studies mostly conduct deforestation experiments with a single model and the simulated precipitation responses to deforestation diverge across studies. In this study, 11 Earth system models are used to robustly examine the biophysical impacts of deforestation on precipitation, precipitation extremes, and the seasonal pattern of the rainy season through a comparison of a control simulation and an idealized global deforestation simulation with clearings of 20 million km2 of forests. The multimodel mean suggests decreased precipitation, reduced frequency and intensity of heavy precipitation, and shortened duration of rainy seasons over deforested areas. The deforestation effects can even propagate to some regions that are remote from deforested areas (e.g., the tropical and subtropical oceans and the Arctic Ocean). Nevertheless, the 11 models do not fully agree on the precipitation changes almost everywhere. In general, the models exhibit higher consistency over the deforested areas and a few regions outside the deforested areas (e.g., the subtropical oceans) but lower consistency over other regions. Such intermodel spread mostly results from divergent responses of evapotranspiration and atmospheric moisture convergence to deforestation across the models. One of the models that has multiple simulation members also reveals considerable spread of the precipitation responses to deforestation across the members due to internal model variability. This study highlights the necessity of robustly examining precipitation responses to deforestation based on multiple models and each model with multiple simulation members.

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Jun Ge
,
Bo Qiu
,
Bowen Chu
,
Duzitian Li
,
Lingling Jiang
,
Weidan Zhou
,
Jianping Tang
, and
Weidong Guo

Abstract

Regional climate models have been widely used to examine the biophysical effects of afforestation, but their performance in this respect has rarely been evaluated. To fill this knowledge gap, an evaluation method based on the “space for time” strategy is proposed here. Using this method, we validate the performance of three coupled regional models—the Regional Climate Model (RegCM), the Weather Research and Forecasting (WRF) Model, and the WRF Model run at a convection-permitting resolution (WRF-CP)—in representing the local biophysical effects of afforestation over continental China against satellite observations. The results show that WRF and WRF-CP cannot accurately describe afforestation-induced changes in surface biophysical properties (e.g., albedo or leaf area index). Second, all models exhibit poor simulations of afforestation-induced changes in latent and sensible heat fluxes. In particular, the observed increase in the summer latent heat due to afforestation is substantially underestimated by all models. Third, the models are basically reasonable in representing the biophysical impact of afforestation on temperature. The cooling of the daily mean surface temperature and 2-m temperature in summer are reproduced well. Nevertheless, the mechanism driving the cooling effect may be improperly represented by the models. Moreover, the models perform relatively poorly in representing the response of the daily minimum surface temperature to afforestation. These results highlight the necessity of evaluating the representation of the biophysical effects by a model before the model is employed to carry out afforestation experiments. This study serves as a test bed for validating regional model performance in this respect.

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Jun Ge
,
Weidong Guo
,
Andrew J. Pitman
,
Martin G. De Kauwe
,
Xuelong Chen
, and
Congbin Fu

Abstract

China is several decades into large-scale afforestation programs to help address significant ecological and environmental degradation, with further afforestation planned for the future. However, the biophysical impact of afforestation on local surface temperature remains poorly understood, particularly in midlatitude regions where the importance of the radiative effect driven by albedo and the nonradiative effect driven by energy partitioning is uncertain. To examine this issue, we investigated the local impact of afforestation by comparing adjacent forest and open land pixels using satellite observations between 2001 and 2012. We attributed local surface temperature change between adjacent forest and open land to radiative and nonradiative effects over China based on the Intrinsic Biophysical Mechanism (IBM) method. Our results reveal that forest causes warming of 0.23°C (±0.21°C) through the radiative effect and cooling of −0.74°C (±0.50°C) through the nonradiative effect on local surface temperature compared with open land. The nonradiative effect explains about 79% (±16%) of local surface temperature change between adjacent forest and open land. The contribution of the nonradiative effect varies with forest and open land types. The largest cooling is achieved by replacing grasslands or rain-fed croplands with evergreen tree types. Conversely, converting irrigated croplands to deciduous broadleaf forest leads to warming. This provides new guidance on afforestation strategies, including how these should be informed by local conditions to avoid amplifying climate-related warming.

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Jing Sun
,
Kun Yang
,
Weidong Guo
,
Yan Wang
,
Jie He
, and
Hui Lu

Abstract

The Inner Tibetan Plateau (ITP; also called the Qiangtang Plateau) appears to have experienced an overall wetting in summer (June, July, and August) since the mid-1990s, which has caused the rapid expansion of thousands of lakes. In this study, changes in atmospheric circulations associated with the wetting process are analyzed for 1979–2018. These analyses show that the wetting is associated with simultaneously weakened westerlies over the Tibetan Plateau (TP). The latter is further significantly correlated with the Atlantic multidecadal oscillation (AMO) on interdecadal time scales. The AMO has been in a positive phase (warm anomaly of the North Atlantic Ocean sea surface) since the mid-1990s, which has led to both a northward shift and weakening of the subtropical westerly jet stream at 200 hPa near the TP through a wave train of cyclonic and anticyclonic anomalies over Eurasia. These anomalies are characterized by an anomalous anticyclone to the east of the ITP and an anomalous cyclone to the west of the ITP. The former weakens the westerly winds, trapping water vapor over the ITP while the latter facilitates water vapor intruding from the Arabian Sea into the ITP. Accordingly, summer precipitation over the ITP has increased since the mid-1990s.

Open access
Chaorong Chen
,
Jun Ge
,
Weidong Guo
,
Yipeng Cao
,
Yu Liu
,
Xing Luo
, and
Limei Yang

Abstract

Afforestation can impact surface temperature through local and nonlocal biophysical effects. However, the local and nonlocal effects of afforestation in China have rarely been explicitly investigated. In this study, we separate the local and nonlocal effects of idealized afforestation in China based on a checkerboard method and the regional Weather Research and Forecasting (WRF) Model. Two checkerboard pattern–like afforestation simulations (AFF1/4 and AFF3/4) with regularly spaced afforested and unaltered grid cells are performed; afforestation is implemented in one out of every four grid cells in AFF1/4 and in three out of every four grid cells in AFF3/4. The mechanisms for the local and nonlocal effects are examined through the decomposition of the surface energy balance. The results show that the local effects dominate surface temperature responses to afforestation in China, with a cooling effect of approximately −1.00°C for AFF1/4 and AFF3/4. In contrast, the nonlocal effects warm the land surface by 0.14°C for AFF1/4 and 0.41°C for AFF3/4. The local cooling effects mainly result from 1) enhanced sensible and latent heat fluxes and 2) decreases in downward shortwave radiation due to increased low cloud cover fractions. The nonlocal warming effects mainly result from atmospheric feedbacks, including 1) increases in downward shortwave radiation due to decreased low cloud cover fractions and 2) increases in downward longwave radiation due to increased middle and high cloud cover fractions. This study highlights that, despite the unexpected nonlocal warming effect, afforestation in China still has great potential in mitigating climate warming through biophysical processes.

Free access