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Mengnan Zhao, Rui M. Ponte, Ou Wang, and Rick Lumpkin

Abstract

Properly fitting ocean models to observations is crucial for improving model performance and understanding ocean dynamics. Near-surface velocity measurements from the Global Drifter Program (GDP) contain valuable information about upper-ocean circulation and air–sea fluxes on various space and time scales. This study explores whether GDP measurements can be used for usefully constraining the surface circulation from coarse-resolution ocean models, using global solutions produced by the consortium for Estimating the Circulation and Climate of the Ocean (ECCO) as an example. To address this problem, a careful examination of velocity data errors is required. Comparisons between an ECCO model simulation, performed without any data constraints, and GDP and Ocean Surface Current Analyses Real-Time (OSCAR) velocity data, over the period 1992–2017, reveal considerable differences in magnitude and pattern. These comparisons are used to estimate GDP data errors in the context of the time-mean and time-variable surface circulations. Both instrumental errors and errors associated with limitations in model physics and resolution (representation errors) are considered. Given the estimated model–data differences, errors, and signal-to-noise ratios, our results indicate that constraining ocean-state estimates to GDP can have a substantial impact on the ECCO large-scale time-mean surface circulation over extensive areas. Impact of GDP data constraints on the ECCO time-variable circulation would be weaker and mainly limited to low latitudes. Representation errors contribute substantially to degrading the data impacts.

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Guihua Wang, Shang-Ping Xie, Rui Xin Huang, and Changlin Chen

Abstract

The subsurface ocean response to anthropogenic climate forcing remains poorly characterized. From the Coupled Model Intercomparison Project (CMIP), a robust response of the lower thermocline is identified, where the warming is considerably weaker in the subtropics than in the tropics and high latitudes. The lower thermocline change is inversely proportional to the thermocline depth in the present climatology. Ocean general circulation model (OGCM) experiments show that sea surface warming is the dominant forcing for the subtropical gyre change in contrast to natural variability for which wind dominates, and the ocean response is insensitive to the spatial pattern of surface warming. An analysis based on a ventilated thermocline model shows that the pattern of the lower thermocline change can be interpreted in terms of the dynamic response to the strengthened stratification and downward heat mixing. Consequently, the subtropical gyres become intensified at the surface but weakened in the lower thermcline, consistent with results from CMIP experiments.

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Di Liu, Guiling Wang, Rui Mei, Zhongbo Yu, and Huanghe Gu

Abstract

This paper focuses on diagnosing the strength of soil moisture–atmosphere coupling at subseasonal to seasonal time scales over Asia using two different approaches: the conditional correlation approach [applied to the Global Land Data Assimilation System (GLDAS) data, the Climate Forecast System Reanalysis (CFSR) data, and output from the regional climate model, version 4 (RegCM4)] and the Global Land–Atmosphere Coupling Experiment (GLACE) approach applied to the RegCM4. The conditional correlation indicators derived from the model output and the two observational/reanalysis datasets agree fairly well with each other in the spatial pattern of the land–atmosphere coupling signal, although the signal in CFSR data is stronger and spatially more extensive than the GLDAS data and the RegCM4 output. Based on the impact of soil moisture on 2-m air temperature, the land–atmosphere coupling hotspots common to all three data sources include the Indochina region in spring and summer, the India region in summer and fall, and north-northeastern China and southwestern Siberia in summer. For precipitation, all data sources produce a weak and spatially scattered signal, indicating the lack of any strong coupling between soil moisture and precipitation, for both precipitation amount and frequency. Both the GLACE approach and the conditional correlation approach (applied to all three data sources) identify evaporation and evaporative fraction as important links for the coupling between soil moisture and precipitation/temperature. Results on soil moisture–temperature coupling strength from the GLACE-type experiment using RegCM4 are in good agreement with those from the conditional correlation analysis applied to output from the same model, despite substantial differences between the two approaches in the terrestrial segment of the land–atmosphere coupling.

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Lei Wang, Zhi-Jun Yao, Li-Guang Jiang, Rui Wang, Shan-Shan Wu, and Zhao-Fei Liu

Abstract

The spatiotemporal changes in 21 indices of extreme temperature and precipitation for the Mongolian Plateau from 1951 to 2012 were investigated on the basis of daily temperature and precipitation data from 70 meteorological stations. Changes in catastrophic events, such as droughts, floods, and snowstorms, were also investigated for the same period. The correlations between catastrophic events and the extreme indices were examined. The results show that the Mongolian Plateau experienced an asymmetric warming trend. Both the cold extremes and warm extremes showed greater warming at night than in the daytime. The spatial changes in significant trends showed a good homogeneity and consistency in Inner Mongolia. Changes in the precipitation extremes were not as obvious as those in the temperature extremes. The spatial distributions in changes of precipitation extremes were complex. A decreasing trend was shown for total precipitation from west to east as based on the spatial distribution of decadal trends. Drought was the most serious extreme disaster, and prolonged drought for longer than 3 yr occurred about every 7–11 yr. An increasing trend in the disaster area was apparent for flood events from 1951 to 2012. A decreasing trend was observed for the maximum depth of snowfall from 1951 to 2012, with a decreased average maximum depth of 10 mm from the 1990s.

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Xuejin Wang, Baoqing Zhang, Feng Li, Xiang Li, Xuliang Li, Yibo Wang, Rui Shao, Jie Tian, and Chansheng He

Abstract

From 1998 to the present, the Chinese government has implemented numerous large-scale ecological programs to restore ecosystems and improve environmental protection in the agro-pastoral ecotone of northern China (APENC). However, it remains unclear how vegetation restoration modulates intraregional moisture cycles and changes regional water balance. To fill this gap, we first investigated the variation in precipitation (P) from the China Meteorological Forcing Dataset and evapotranspiration (ET) estimated using the Priestley–Taylor Jet Propulsion Laboratory model under two scenarios: dynamic vegetation (DV) and no dynamic vegetation (no-DV). We then used the dynamic recycling model to analyze the changes in precipitation recycling ratio (PRR). Finally, we examined how vegetation restoration modulates intraregional moisture recycling to change the regional water cycle in APENC. Results indicate P increased at an average rate of 4.42 mm yr−2 from 1995 to 2015. ET with DV exhibited a significant increase at a rate of 1.57, 3.58, 1.53, and 1.84 mm yr−2 in the four subregions, respectively, compared with no-DV, and the annual mean PRR values were 10.15%, 9.30%, 11.01%, and 12.76% in the four subregions, and significant increasing trends were found in the APENC during 1995–2015. Further analysis of regional moisture recycling shows that vegetation restoration does not increase local P directly, but has an indirect effect by enhancing moisture recycling process to produce more P by increasing PRR. Our findings show that large-scale ecological restoration programs have a positive effect on local moisture cycle and precipitation.

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Xing Chen, Mukesh Kumar, Rui Wang, Adam Winstral, and Danny Marks

Abstract

Previous studies have shown that gauge-observed daily streamflow peak times (DPTs) during spring snowmelt can exhibit distinct temporal shifts through the season. These shifts have been attributed to three processes: 1) melt flux translation through the snowpack or percolation, 2) surface and subsurface flow of melt from the base of snowpacks to streams, and 3) translation of water flux in the streams to stream gauging stations. The goal of this study is to evaluate and quantify how these processes affect observed DPTs variations at the Reynolds Mountain East (RME) research catchment in southwest Idaho, United States. To accomplish this goal, DPTs were simulated for the RME catchment over a period of 25 water years using a modified snowmelt model, iSnobal, and a hydrology model, the Penn State Integrated Hydrologic Model (PIHM). The influence of each controlling process was then evaluated by simulating the DPT with and without the process under consideration. Both intra- and interseasonal variability in DPTs were evaluated. Results indicate that the magnitude of DPTs is dominantly influenced by subsurface flow, whereas the temporal shifts within a season are primarily controlled by percolation through snow. In addition to the three processes previously identified in the literature, processes governing the snowpack ripening time are identified as additionally influencing DPT variability. Results also indicate that the relative dominance of each control varies through the melt season and between wet and dry years. The results could be used for supporting DPTs prediction efforts and for prioritization of observables for DPT determination.

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Rui Mao, Dao-Yi Gong, Tianbao Zhao, Wenshan Wang, and Jing Yang

Abstract

High relative humidity (HRH) is defined as a relative humidity of at least 80%, which is often associated with the occurrence of cloud layers. Thus, the frequency of HRH and its changes in the troposphere may be related to the occurrence frequency of cloud layers and their changes. In this study, trends in the frequency of HRH (defined as days with relative humidity ≥80%) over China from the surface to the midtroposphere (≥400 hPa) from 1979 to 2012 were analyzed using a homogenized humidity dataset for spring (March–May), summer (June–August), autumn (September–November), and winter (December–February). The results for the ground level indicate decreasing trends at most stations in southeastern China in spring and in northern China in summer. In the lower troposphere (850 and 700 hPa), most stations over China exhibit positive trends in summer, autumn, and winter. For the midtroposphere (500–400 hPa), increasing trends dominate over China in spring, summer, and autumn. Finally, six reanalysis datasets, the NCEP–NCAR, NCEP–DOE, CFSR, ERA-Interim, MERRA, and JRA-55 datasets, were compared with the observed increasing trends in HRH frequency in the low-to-middle troposphere. Similar increasing trends in HRH frequency in the reanalysis datasets and the homogenized humidity data are observed in certain seasons and for certain regions. These results are consistent with the increasing low-to-middle cloud amounts in recent decades.

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Jiamin Wang, Xiaodan Guan, Yuping Guan, Kaiwei Zhu, Rui Shi, Xiangning Kong, and Shuyang Guo

Abstract

Due to global warming, the lengths of the four seasons, which are always taken as constant values, have experienced significant variations with rising temperature. Such changes play different roles on regional climate change, with the most significant effect on drylands. To guarantee local crop yields and preserve ecosystems, the identification of the changes of the four seasons in drylands is important. Our results show that, relative to humid lands, changing trends in lengths of spring, summer and autumn were particularly enhanced in drylands of the Northern Hemisphere mid-latitudes during 1951-2020. In this period, summer length has increased by 0.51 day per year, while spring and autumn lengths have contracted by 0.14 and 0.14 day per year, respectively. However, the enhanced changes in drylands did not appear in winter length. Such changes of spring, summer and autumn in drylands are dominated by internal variability over the entire study period, with a stronger external forcing effect on drylands than on humid lands. In drylands, the external forcing contributed to the changes in lengths of spring, summer and autumn by 30.1%, 42.2% and 29.4%, respectively. The external forcing has become an increasingly important component since 1990, with the ability to dominate all seasons in drylands after 2010. Nevertheless, only one out of the 16 Coupled Model Intercomparison Project Phase 6 (CMIP6) models used in this study can capture the enhanced changes in the lengths of spring, summer and autumn in drylands. Further investigation on the local effects of changes in seasons on agriculture and ecosystem would be needed, especially for the fragile regions.

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Kang Xu, Rui Xin Huang, Weiqiang Wang, Congwen Zhu, and Riyu Lu

Abstract

The interannual fluctuations of the equatorial thermocline are usually associated with El Niño activity, but the linkage between the thermocline modes and El Niño is still under debate. In the present study, a mode function decomposition method is applied to the equatorial Pacific thermocline, and the results show that the first two dominant modes (M1 and M2) identify two distinct characteristics of the equatorial Pacific thermocline. The M1 reflects a basinwide zonally tilted thermocline related to the eastern Pacific (EP) El Niño, with shoaling (deepening) in the western (eastern) equatorial Pacific. The M2 represents the central Pacific (CP) El Niño, characterized by a V-shaped equatorial Pacific thermocline (i.e., deep in the central equatorial Pacific and shallow on both the western and eastern boundaries). Furthermore, both modes are stable and significant on the interannual time scale, and manifest as the major feature of the thermocline fluctuations associated with the two types of El Niño events. As good proxies of EP and CP El Niño events, thermocline-based indices clearly reveal the inherent characteristics of subsurface ocean responses during the evolution of El Niño events, which are characterized by the remarkable zonal eastward propagation of equatorial subsurface ocean temperature anomalies, particularly during the CP El Niño. Further analysis of the mixed layer heat budget suggests that the air–sea interactions determine the establishment and development stages of the CP El Niño, while the thermocline feedback is vital for its further development. These results highlight the key influence of equatorial Pacific thermocline fluctuations in conjunction with the air–sea interactions, on the CP El Niño.

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Lu Yang, Mingxuan Chen, Xiaoli Wang, Linye Song, Meilin Yang, Rui Qin, Conglan Cheng, and Siteng Li

Abstract

The ability to forecast thermodynamic conditions aloft and near the surface is critical to the accurate forecasting of precipitation type at the surface. This paper presents an experimental version of a new scheme for diagnosing precipitation type. The method considers the optimum surface temperature threshold associated with each precipitation type and combines model-based explicit fields of hydrometeors with higher-resolution modified thermodynamic and topographic information to determine precipitation types in North China. Based on over 60 years of precipitation-type samples from North China, this study explores the climatological characteristics of the five precipitation types—snow, rain, ice pellets (IP), rain/snow mix (R/S MIX), and freezing rain (FZ)—as well as the suitable air temperature T a and wet-bulb temperature T w thresholds for distinguishing different precipitation types. Direct output from numerical weather prediction (NWP) models, such as temperature and humidity, was modified by downscaling and bias correction, as well as by incorporating the latest surface observational data and high-resolution topographic data. Validation of the precipitation-type forecasts from this scheme was performed against observations from the 2016 to 2019 winter seasons and two case studies were also analyzed. Compared with the similar diagnostic routine in the High-Resolution Rapid Refresh (HRRR) forecasting system used to predict precipitation type over North China, the skill of the method proposed here is similar for rain and better for snow, R/S MIX, and FZ. Furthermore, depiction of the diagnosed boundary between R/S MIX and snow is good in most areas. However, the number of misclassifications for R/S MIX is significantly larger than for rain and snow.

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