Showing papers by "Peili Wu published in 2022"

The decline in the groundwater table depth over the past four decades in China simulated by the Noah-MP land model

Abstract: Faced with intensified climate change and ever-increasing water demand, the groundwater table depth is vital to sustaining terrestrial environments in a country such as China; however, on a regional scale, insufficient research has been conducted on its variability thus far. Using a land model forced with reanalysis climate data, this paper investigates groundwater table depth changes across China for the 1979–2018 period. The results show a significant overall reduction in the groundwater table depth in China during the past 40 years without explicit consideration of direct human influence. There is an approximately 0.2 m decrease on average, but it is approximately 0.5 m in southern China and 0.8 m to the north of 35°N despite a 1.2 m rise in part of this region due to an increasingly wet climate and a topographic water convergence. The findings provide a first-order pattern of historical groundwater table responses to climate change, highlighting inherent links among subsurface-surface-atmosphere water cycles and worsened terrestrial water availability in China. A model evaluation compared with in situ observations has demonstrated the model’s ability to realistically portray terrestrial water and energy balances on regional scales, as well as the enhancement of their seasonality with incorporated lateral groundwater flow processes. This ability gives us reasonable confidence in the simulated trends and spatial variability. Nonetheless, the mean groundwater table still shows large biases relative to observations, and the problems of human influence, two-way interactions between groundwater and surface water, and local topographical complexity have yet to be properly addressed in the present study and deserve further research.

Constraining extreme precipitation projections using past precipitation variability

Abstract: Abstract Projected changes of future precipitation extremes exhibit substantial uncertainties among climate models, posing grand challenges to climate actions and adaptation planning. Practical methods for narrowing the projection uncertainty remain elusive. Here, using large model ensembles, we show that the uncertainty in projections of future extratropical extreme precipitation is significantly correlated with the model representations of present-day precipitation variability. Models with weaker present-day precipitation variability tend to project larger increases in extreme precipitation occurrences under a given global warming increment. This relationship can be explained statistically using idealized distributions for precipitation. This emergent relationship provides a powerful constraint on future projections of extreme precipitation from observed present-day precipitation variability, which reduces projection uncertainty by 20–40% over extratropical regions. Because of the widespread impacts of extreme precipitation, this has not only provided useful insights into understanding uncertainties in current model projections, but is also expected to bring potential socio-economic benefits in climate change adaptation planning.

A Moderate Mitigation Can Significantly Delay the Emergence of Compound Hot Extremes

Abstract: Compound hot extremes (ChotEs) that refer to continuous heats throughout days and nights are projected to increase, causing more serious impacts on human health than daytime or nighttime heats alone. Previous studies have focused on daytime heats, but the timing of substantial increase in ChotEs relative to natural variability, which is defined as the time of emergence (ToE) for ChotEs, remains unknown. Here we examine ToE for duration of summertime ChotEs from coupled model intercomparison project phase 6 climate model projections under two shared socioeconomic pathway scenarios (i.e., SSP245 and SSP585). We further quantify the cumulative fraction of areal and population exposed to the emergence at global and continental scales. We find that, without implementation of climate mitigation policies (i.e., SSP585), global mean ToE is around 2062 (with 16%–84% uncertainty range of 2048–2072). On the basis of the ToE for each grid cell, 80.7% (with uncertainty range of 64.2%–96.7%) of global lands will expose to the emergence by 2080. Such substantial increases in ChotEs will lead to 75.2% (66.8%–93%) of global population exposed to the emergence by the end of 21st century. A moderate mitigation (i.e., SSP245) can delay the ToE by over 14 years and, more importantly, reduce the global land areal and population exposures by 50.3% and 39.7% respectively. Regionally, northern Europe, central America and western North America benefit the most. Therefore, early action towards moderate development socioeconomic pathways can remarkably cut back the possibility of large population exposure to ChotEs and relevant impacts.

Prominent vegetation greening in spring and autumn across China during the 1981–2018 period

Abstract: Vegetation greening in China has been extensively examined, but little is known about its seasonal characteristics and its association with soil moisture (SM) and temperature changes. Using high-resolution (0.1°, 8 d) datasets of leaf area index (LAI), together with SM, soil temperature (ST) datasets, and the dominance analysis method, this study is designed to detect seasonal vegetation changes across China during 1981–2018 and its links to climate change. The results show that 56.8% of land area across China experienced a greening trend while 6.6% browning trend through 1981–2018. LAI increasing area expanded to a maximum of 59.3% in spring and the decreasing area reached a maximum of 10.6% in autumn. Spring increases in LAI in main vegetation regions were significantly correlated with positive ST anomalies, while autumn decreases in LAI except sparsely vegetated regions were correlated with negative SM anomalies. Combined SM and temperature anomalies explain 10.9% of the observed LAI changes, which is 4 times larger than that directly explained by precipitation and surface air temperature (2.7%). The warming of soil under climate change was driving the LAI increases, while drying was largely responsible for LAI decreases. These findings provide further evidence of climate change impacts on regional ecosystems and highlight the importance of soil heat and water conditions in translating global warming signals.

Disentangling the Driving Mechanisms of Tripole Mode of Summer Rainfall Over Eastern China

Abstract: The spatial distribution of summer rainfall anomalies over eastern China often shows a tripole pattern with rainfall anomalies over the Yangtze River basin varies in opposite phase with North China and South China. It is not clear whether this tripole pattern is an intrinsic atmospheric mode or it is remotely forced. Using two sets of model-outputs from 20 models participating in the fifth Coupled Model Inter-comparison Project (CMIP5), this paper investigates the driving mechanisms of this leading rainfall mode and its major influencing factors. One set (piControl) is fully coupled atmosphere-ocean simulations under constant pre-industrial forcing and the other (sstClim) is atmosphere-alone models forced by prescribed climatological sea surface temperatures (SSTs). By comparing results from these two different sets of simulations, it is found that the tripole pattern is the leading mode of summer precipitation variability over eastern China with or without oceanic forcing. It can be regarded as an intrinsic atmospheric mode although air-sea interaction can modify its temporal variability. The cyclonic/anti-cyclonic atmospheric circulation anomaly over the northern North Pacific is identified as a key factor in both experiments. As atmospheric internal variability, it is related to a circum-global zonal wave train propagating along the westerly jet stream. When air-sea interactions involved, modulation from SST anomalies is exerted through the meridional Pacific-Japan/ East Asia Pacific wave train propagating along the East Asian coast. Our results suggest that the North Pacific could be another key region providing potential predictability to the East Asian monsoon in addition to the Indo-Pacific.

Ecological Response to Climate Change Across China From Combined Soil Temperature and Moisture Changes

Abstract: A coupled soil temperature (ST) and moisture (SM) balance reflects a synthetic climate regime, having huge ecological impacts. This paper used ST and SM data from the European Center for Medium‐Range Weather Forecasts climate reanalysis‐Land and the Coupled Model Intercomparison Project Phase 6 and leaf area index (LAI) data from the Global Land Surface Satellite Product Suite. The focus was on understanding joint ST‐SM changes and the resulting ecological response across China. The results show that during 2000–2020, 24.5% of the land area in China experienced a warming‐drying trend resulting in a 9.7% LAI decrease, while 6.4% of the area experienced a warming‐wetting trend leading to an 8.6% LAI increase. During 2015–2100, 30.6% of the land area in China will be warmer and drier, while 55.2% of the area will be warmer but wetter across three shared socioeconomic pathways (SSP126, 245, and 585). Superimposed on the long‐term trends, there are also significant spatiotemporal variabilities in ST and SM on annual to decadal timescales. The LAI also showed substantial short‐term fluctuations in both typical regions and ecosystems despite consistent long‐term increases. Our findings suggest that ecosystems could be impaired on annual to decadal scales by adverse soil conditions in the twenty‐first century, but in terms of long‐term trends, ecosystems may be resilient partly because of the compensating effects of global warming and regional hydrological changes. Impact studies should thus focus more on annual to decadal soil‐ecosystem anomalous events.