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Xiong Zhou
,
Guohe Huang
,
Yurui Fan
,
Xiuquan Wang
, and
Yongping Li

Abstract

Long-term hydrological projections can vary substantially depending on the combination of meteorological forcing dataset, hydrologic model (HM), emissions scenario, and natural climate variability. Identifying dominant sources of model spread in an ensemble of hydrologic projections is critically important for developing reliable hydrological projections in support of flooding risk assessment and water resources management; however, it is not well understood due to the multifactor and multiscale complexities involved in the long-term hydrological projections. Therefore, a stepwise clustered Bayesian (SCB) ensemble method will be first developed to improve the performance of long-term hydrological projections. Meanwhile, a mixed-level factorial inference (MLFI) approach is employed to estimate multiple uncertainties in hydrological projections over the Jing River basin (JRB). MLFI is able to reveal the main and interactive effects of the anthropogenic emission and model choices on the SCB ensemble projections. The results suggest that the daily maximum temperature under RCP8.5 in the 2050s and 2080s is expected to respectively increase by 3.2° and 5.2°C, which are much higher than the increases under RCP4.5. The maximum increase of the RegCM driven by CanESM2 (CARM)-projected changes in streamflow for the 2050s and 2080s under RCP4.5 is 0.30 and 0.59 × 103 m s−3 in November, respectively. In addition, in a multimodel GCM–RCM–HM ensemble, hydroclimate is found to be most sensitive to the choice of GCM. Moreover, it is revealed that the percentage of contribution of anthropogenic emissions to the changes in monthly precipitation is relatively smaller, but it makes a more significant contribution to the total variance of changes in potential evapotranspiration and streamflow.

Significance Statement

Increasing concerns have been paid to climate change due to its aggravating impacts on the hydrologic regime, leading to water-related disasters. Such impacts can be investigated through long-term hydrological projection under climate change. However, it is not well understood what factor plays a dominant role in inducing extensive uncertainties associated with the long-term hydrological projections due to plausible meteorological forcings, multiple hydrologic models, and internal variability. The stepwise cluster Bayesian ensemble method and mixed-level factorial inference approach are employed to quantify the contribution of multiple uncertainty sources. We find that the total variance of changes in monthly precipitation, potential evapotranspiration, and streamflow can be mainly explained by the model choices. The identified dominant factor accounting for projection uncertainties is critically important for developing reliable hydrological projections in support of flooding risk assessment and water resources management. It is suggested that more reliable models should be taken into consideration in order to improve the projection robustness from a perspective of the Loess Plateau.

Free access
Daosheng Wang
,
Jicai Zhang
,
Ya Ping Wang
,
Xianqing Lv
,
Yang Yang
,
Daidu Fan
, and
Shu Gao

Abstract

The model parameters in the suspended cohesive sediment transport model are quite important for the accurate simulation of suspended sediment concentrations (SSCs). Based on a three-dimensional cohesive sediment transport model and its adjoint model, the in situ observed SSCs at four stations are assimilated to simulate the SSCs and to estimate the parameters in Hangzhou Bay in China. Numerical experimental results show that the adjoint method can efficiently improve the simulation results, which can benefit the prediction of SSCs. The time series of the modeled SSCs present a clear semidiurnal variation, in which the maximal SSCs occur during the flood tide and near the high water level due to the large current speeds. Sensitivity experiments prove that the estimated results of the settling velocity and resuspension rate, especially the temporal variations, are robust to the model settings. The temporal variations of the estimated settling velocity are negatively correlated with the tidal elevation. The main reason is that the mean size of the suspended sediments can be reduced during the flood tide, which consequently decreases the settling velocity according to Stokes’s law, and it is opposite in the ebb tide. The temporal variations of the estimated resuspension rate and the current speeds have a significantly positive correlation, which accords with the dynamics of the resuspension rate. The temporal variations of the settling velocity and resuspension rate are reasonable from the viewpoint of physics, indicating the adjoint method can be an effective tool for estimating the parameters in the sediment transport models.

Full access
Hongdou Fan
,
Lin Wang
,
Yang Zhang
,
Youmin Tang
,
Wansuo Duan
, and
Lei Wang

Abstract

Based on 36-yr hindcasts from the fifth-generation seasonal forecast system of the European Centre for Medium-Range Weather Forecasts (SEAS5), the most predictable patterns of the wintertime 2-m air temperature (T2m) in the extratropical Northern Hemisphere are extracted via the maximum signal-to-noise (MSN) empirical orthogonal function (EOF) analysis, and their associated predictability sources are identified. The MSN EOF1 captures the warming trend that amplifies over the Arctic but misses the associated warm Arctic–cold continent pattern. The MSN EOF2 delineates a wavelike T2m pattern over the Pacific–North America region, which is rooted in the tropical forcing of the eastern Pacific-type El Niño–Southern Oscillation (ENSO). The MSN EOF3 shows a wavelike T2m pattern over the Pacific–North America region, which has an approximately 90° phase difference from that associated with MSN EOF2, and a loading center over midlatitude Eurasia. Its sources of predictability include the central Pacific-type ENSO and Eurasian snow cover. The MSN EOF4 reflects T2m variability surrounding the Tibetan Plateau, which is plausibly linked to the remote forcing of the Arctic sea ice. The information on the leading predictable patterns and their sources of predictability is further used to develop a calibration scheme to improve the prediction skill of T2m. The calibrated prediction skill in terms of the anomaly correlation coefficient improves significantly over midlatitude Eurasia in a leave-one-out cross-validation, implying a possible way to improve the wintertime T2m prediction in the SEAS5.

Free access
Xiang Xiao
,
Yangyang Xu
,
Xiaorui Zhang
,
Fan Wang
,
Xiao Lu
,
Zongwei Cai
,
Guy Brasseur
, and
Meng Gao

Abstract

Climate change and air pollution are two intimately interlinked global concerns. The frequency, intensity, and duration of heat waves are projected to increase globally under future climate change. A growing body of evidence indicates that health risks associated with the joint exposure to heat waves and air pollution can be greater than that due to individual factors. However, the cooccurrences of heat and air pollution extremes in China remain less explored in the observational records. Here we investigate the spatial pattern and temporal trend of frequency, intensity, and duration of cooccurrences of heat and air pollution extremes using China’s nationwide observations of hourly PM2.5 and O3, and the ERA5 reanalysis dataset over 2013–20. We identify a significant increase in the frequency of cooccurrence of wet-bulb temperature (Tw ) and O3 exceedances (beyond a certain predefined threshold), mainly in the Beijing–Tianjin–Hebei (BTH) region (up by 4.7 days decade−1) and the Yangtze River delta (YRD). In addition, we find that the increasing rate (compared to the average levels during the study period) of joint exceedance is larger than the rate of Tw and O3 itself. For example, Tw and O3 coextremes increased by 7.0% in BTH, higher than the percentage increase of each at 0.9% and 5.5%, respectively. We identify same amplification for YRD. This ongoing upward trend in the joint occurrence of heat and O3 extremes should be recognized as an emerging environmental issue in China, given the potentially larger compounding impact to public health.

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Yu-Fan Geng
,
Shang-Ping Xie
,
Xiao-Tong Zheng
, and
Chuan-Yang Wang

Abstract

Tropical precipitation change under global warming varies with season. The present study investigates the characteristics and cause of the seasonality in rainfall change. Diagnostically, tropical precipitation change is decomposed into thermodynamic and dynamic components. The thermodynamic component represents the wet-get-wetter effect and its seasonality is due mostly to that in the mean vertical velocity, especially in the monsoon regions. The dynamic component includes the warmer-get-wetter effect due to the spatial variations in sea surface temperature (SST) warming, while the seasonality is due to that of the climatological SST and can be largely reproduced by an atmospheric model forced with the monthly climatological SST plus the annual-mean SST warming pattern. In the eastern equatorial Pacific where the SST warming is locally enhanced; for example, rainfall increases only during the March–May season when the climatological SST is high enough for deep convection. To the extent that the seasonality of tropical precipitation change over oceans arises mostly from that of the climatological SST, the results support the notion that reducing model biases in climatology improves regional rainfall projections.

Free access
Yu-Chiao Liang
,
Jin-Yi Yu
,
Eric S. Saltzman
, and
Fan Wang

Abstract

During 2013–15, prolonged near-surface warming in the northeastern Pacific was observed and has been referred to as the Pacific warm blob. Here, statistical analyses are conducted to show that the generation of the Pacific blob is closely related to the tropical Northern Hemisphere (TNH) pattern in the atmosphere. When the TNH pattern stays in its positive phase for extended periods of time, it generates prolonged blob events primarily through anomalies in surface heat fluxes and secondarily through anomalies in wind-induced ocean advection. Five prolonged (≥24 months) blob events are identified during the past six decades (1948–2015), and the TNH–blob relationship can be recognized in all of them. Although the Pacific decadal oscillation and El Niño can also induce an arc-shaped warming pattern near the Pacific blob region, they are not responsible for the generation of Pacific blob events. The essential feature of Pacific blob generation is the TNH-forced Gulf of Alaska warming pattern. This study also finds that the atmospheric circulation anomalies associated with the TNH pattern in the North Atlantic can induce SST variability akin to the so-called Atlantic cold blob, also through anomalies in surface heat fluxes and wind-induced ocean advection. As a result, the TNH pattern serves as an atmospheric conducting pattern that connects some of the Pacific warm blob and Atlantic cold blob events. This conducting mechanism has not previously been explored.

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Liao-Fan Lin
,
Ardeshir M. Ebtehaj
,
Rafael L. Bras
,
Alejandro N. Flores
, and
Jingfeng Wang

Abstract

The objective of this study is to develop a framework for dynamically downscaling spaceborne precipitation products using the Weather Research and Forecasting (WRF) Model with four-dimensional variational data assimilation (4D-Var). Numerical experiments have been conducted to 1) understand the sensitivity of precipitation downscaling through point-scale precipitation data assimilation and 2) investigate the impact of seasonality and associated changes in precipitation-generating mechanisms on the quality of spatiotemporal downscaling of precipitation. The point-scale experiment suggests that assimilating precipitation can significantly affect the precipitation analysis, forecast, and downscaling. Because of occasional overestimation or underestimation of small-scale summertime precipitation extremes, the numerical experiments presented here demonstrate that the wintertime assimilation produces downscaled precipitation estimates that are in closer agreement with the reference National Centers for Environmental Prediction stage IV dataset than similar summertime experiments. This study concludes that the WRF 4D-Var system is able to effectively downscale a 6-h precipitation product with a spatial resolution of 20 km to hourly precipitation with a spatial resolution of less than 10 km in grid spacing—relevant to finescale hydrologic applications for the era of the Global Precipitation Measurement mission.

Full access
Qinbo Xu
,
Chun Zhou
,
Linlin Zhang
,
Fan Wang
,
Wei Zhao
, and
Dunxin Hu

Abstract

The deep western boundary current (DWBC) was studied based on a full-depth mooring east of Luzon Island in the Northern Philippine Sea deep basin during the period from January 2018 to May 2020. On average, the DWBC in the Philippine Sea flows southward with a velocity of approximately 1.18 cm s−1 at a depth of 3050 m. Significant intraseasonal and seasonal variations of the DWBC are identified. The intraseasonal variations have multiple spectral peaks in the range of 30–200 days, with the most obvious peak at approximately 120 days. On the seasonal time scale, the DWBC intensifies in summer/autumn and weakens in winter/spring, corresponding well with the seasonal variation of the ocean bottom pressure (OBP) from the Gravity Recovery and Climate Experiment. Both intraseasonal and seasonal variations have no significant correlation with the temporal variations in the upper and middle layers but have a certain correlation with transport through the Yap–Mariana Junction (YMJ). A set of experiments based on an inverted-reduced-gravity model and the OBP data reveal that the temporal variations originating from the YMJ could propagate counterclockwise along the boundary of the deep basin to the western boundary of the deep Philippine Sea, dominating the temporal variations of DWBC.

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Yuanlong Li
,
Yaru Guo
,
Yanan Zhu
,
Shoichiro Kido
,
Lei Zhang
, and
Fan Wang

Abstract

Prominent interannual-to-decadal variations were observed in both heat content and mesoscale eddy activity in the southeast Indian Ocean (SEIO) during 1993–2020. The 2000–01 and 2008–14 periods stand out with increased 0–700-m ocean heat content (OHC) by ∼4.0 × 1021 J and enhanced surface eddy kinetic energy (EKE) by 12.5% over 85°–115°E, 35°–12°S. This study provides insights into the key dynamical processes conducive to these variations by analyzing observational datasets and high-resolution regional ocean model simulations. The strengthening of the Indonesian Throughflow (ITF) and anomalous cyclonic winds over the SEIO region during the two periods are demonstrated to be the most influential. While the ITF caused prevailing warming of the upper SEIO, the cyclonic winds cooled the South Equatorial Current and attenuated the warming in the subtropical SEIO by evoking upwelling Rossby waves. The EKE increase exerts significant influence on OHC only in the Leeuwin Current system. Dynamical instabilities of the Leeuwin Current give rise to high EKEs and westward eddy heat transport in climatology. As the Leeuwin Current was enhanced by both the ITF and local winds, the elevated EKEs drove anomalous heat convergence on its offshore flank. This process considerably contributes to the OHC increase in the subtropical SEIO and erases the wind-driven cooling during the two warm periods. This work highlights the vital role of eddies in regional heat redistribution, with implications for understanding time-varying ocean heat storage in a changing climate.

Free access
Qiuping Ren
,
Young-Oh Kwon
,
Jiayan Yang
,
Rui Xin Huang
,
Yuanlong Li
, and
Fan Wang

Abstract

The storage of anthropogenic heat in oceans is geographically inhomogeneous, leading to differential warming rates among major ocean basins with notable regional climate impacts. Our analyses of observation-based datasets show that the average warming rate of 0–2000 m Atlantic Ocean since 1960 is nearly threefold stronger than that of the Indo-Pacific Oceans. This feature is robustly captured by historical simulations of the Climate Model Intercomparison Project Phase 6 (CMIP6) and is projected to persist into the future. In CMIP6 simulations, the ocean heat uptake through surface heat fluxes plays a central role in shaping the inter-basin warming contrasts. In addition to the slowdown of the Atlantic Meridional Overturning Circulation as stressed in some existing studies, alterations of atmospheric conditions under greenhouse warming are also essential for the increased surface heat flux into the North Atlantic. Specifically, the reduced anthropogenic aerosol concentration in the North Atlantic since the 1980s has been favorable for the enhanced Atlantic Ocean heat uptake in CMIP6 models. Another previously overlooked factor is the geographic shape of the Atlantic Ocean which is relatively wide in mid-latitudes and narrow in low-latitudes, in contrast to that of the Indo-Pacific Oceans. Combined with the poleward migration of atmospheric circulations, which leads to the meridional pattern of surface heat uptake with broadly enhanced heat uptake in mid-latitude oceans due to reduced surface wind speed and cloud cover, the geographic shape effect renders a higher basin-average heat uptake in the Atlantic.

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