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Ting Hu
,
Ying Sun
,
Xuebin Zhang
, and
Dongqian Wang

Greenhouse gas forcing has increased the likelihood of events like the 2021 wettest September in northern China by approximately twofold, while anthropogenic aerosols play a relatively minor suppressing role.

Free access
Fatemeh Farokhmanesh
,
Kevin Höhlein
, and
Rüdiger Westermann

Abstract

Numerical simulations in Earth-system sciences consider a multitude of physical parameters in space and time, leading to severe input/output (I/O) bandwidth requirements and challenges in subsequent data analysis tasks. Deep learning–based identification of redundant parameters and prediction of those from other parameters, that is, variable-to-variable (V2V) transfer, has been proposed as an approach to lessening the bandwidth requirements and streamlining subsequent data analysis. In this paper, we examine the applicability of V2V to meteorological reanalysis data. We find that redundancies within pairs of parameter fields are limited, which hinders application of the original V2V algorithm. Therefore, we assess the predictive strength of reanalysis parameters by analyzing the learning behavior of V2V reconstruction networks in an ablation study. We demonstrate that efficient V2V transfer becomes possible when considering groups of parameter fields for transfer and propose an algorithm to implement this. We investigate further whether the neural networks trained in the V2V process can yield insightful representations of recurring patterns in the data. The interpretability of these representations is assessed via layerwise relevance propagation that highlights field areas and parameters of high importance for the reconstruction model. Applied to reanalysis data, this allows for uncovering mutual relationships between landscape orography and different regional weather situations. We see our approach as an effective means to reduce bandwidth requirements in numerical weather simulations, which can be used on top of conventional data compression schemes. The proposed identification of multiparameter features can spawn further research on the importance of regional weather situations for parameter prediction and also in other kinds of simulation data.

Free access
Yawen Duan
,
Qing Yang
,
Zhuguo Ma
,
Peili Wu
,
Xiaolong Chen
, and
Jianping Duan

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 phase 5 of the Coupled Model Intercomparison 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 preindustrial 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–anticyclonic 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 circumglobal 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.

Open access
Xiao Ma
,
Hailong Liu
, and
Xidong Wang

Abstract

This study reveals the role of the tropical Atlantic variability in modulating barrier layer thickness (BLT) in peak seasons. Based on reanalysis data during 1980–2016, statistical and dynamical analyses are performed to investigate the mechanism of BLT variability associated with the tropical Atlantic modes. The regions with significant correlation between BLT and tropical Atlantic modes are located on the northwest and southeast coasts of the tropical Atlantic, which are consistent with BLT maximum variability regions. In boreal spring, BLT decreases in the northwest because less latent heat release affected by weak trade wind related to the Atlantic meridional mode (AMM) shoals the isothermal layer depth (ITLD). In the south equatorial Atlantic, deepened mixed layer depth (MLD) is controlled by the decreasing freshwater input brought by a northward shift of the intertropical convergence zone (ITCZ) and further leads to a thinner barrier layer (BL). However, a shoaling MLD appears in the north equatorial Atlantic, which results from excessive freshwater input, causing a thick BL there. In boreal summer, positive runoff anomaly caused by the Atlantic equatorial mode (AEM) leads to upper warming of the tropical northwest Atlantic and a shallowing ITLD, favoring a thinner BL there. However, a southward shift of ITCZ brings more freshwater into the south equatorial Atlantic, inducing a shallowing MLD as well as a thicker BL. AEM-driven horizontal heat advection of the south equatorial current contributes to a thick ITLD in the central southern tropical Atlantic and thus increases BLT.

Significance Statement

This research aims to reveal how the tropical Atlantic meridional and equatorial interannual climatic modes affect barrier layer thickness (BLT). These two climate modes can affect the wind field, ocean current, and precipitation through air–sea interaction processes, and further affect mixing, heat–salt transport, and stratification in the upper ocean and thus BLT. This finding is important because the barrier layer restricts the exchange of heat, momentum, mass, and nutrients between the mixed layer and the thermocline, thereby impacting local and remote weather events, the ecological environment, and the climate. Our results provide guidance for interpreting the interannual variability of BLT in the tropical Atlantic.

Restricted access
Peng Cheng

Abstract

A linear three-dimensional analytical model was developed to investigate the lateral circulation in an elongated tidal channel with mildly curved bends of which radius of curvature is larger than the width. The curvature induced lateral circulation has two components with the same amplitude, namely a periodic component having an overtide frequency and a steady component. The combination of the two components allows the strength of the lateral circulation to vary periodically and the rotation direction to be unchanged during a tidal period. Friction modifies the strength and structure of the lateral circulation. The phase between the lateral flow and streamwise tidal flow decreases with increasing friction, indicating that the two flows are not necessarily in phase unless friction is strong. The lateral circulations driven by Coriolis and curvature centrifugal forces augment each other during one phase and compete in the opposite phase, and the relative importance of the two circulations is determined by the Rossby number and friction. The adaptation time is the same for spin-up and spin-down of the curvature induced lateral circulation and is determined by water depth and vertical eddy viscosity. The estimation of the adaptation time depends on leading modes because the transition solution of the curvature induced lateral circulation comprises a series of cosine modes. These results provide a theoretical basis for interpreting curvature induced lateral circulation in tidal channels and coastal headlands.

Restricted access
Free access
Jianing Li
,
Qingxuan Yang
,
Hui Sun
,
Shuwen Zhang
,
Lingling Xie
,
Qingye Wang
,
Wei Zhao
, and
Jiwei Tian

Abstract

This study focuses on the statistical features of dissipation flux coefficient Γ in the upper South China Sea (SCS). Based on the microscale measurements collected at 158 stations in the upper SCS and derived dissipation rates of turbulent kinetic energy and temperature variance ε and χT , via a modified method, we estimate Γ and analyze its spatiotemporal variation in an energetic and a quiescent region. We show that Γ is highly variable, which scatters over three orders of magnitude from 10−2 to 101 in both regions. Ιn the energetic region, Γ is slightly greater than in the quiescent region; their median values are 0.23 and 0.17, respectively. Vertically, Γ presents a clear increasing tendency with depth in both regions, though the increasing rate is greater in the energetic region than in the quiescent region. In the upper SCS, Γ positively depends on the buoyancy Reynolds number Re b and negatively depends on the ratio of the Ozmidov scale to the Thorpe scale R OT and is scaled as Γ Re b 1 / 2 R OT 4 / 3 , which holds for both regions. The vertical decreasing of R OT is observed, which yields parameterization of R OT = 10−0.002 z ; this parameterization improves the performance of the Thorpe-scale method by reducing at least 50% of the bias between the observed and parameterized ε. These results shed new light on the spatiotemporal variability and modulating mechanism of Γ in the upper ocean.

Significance Statement

The great global ocean conveyor is maintained by vertical mixing. Turbulent kinetic energy released by local internal wave breaking goes into two parts: one part is used to furnish this vertical mixing, and the rest is dissipated into irreversible heat. The ratio of these two parts is termed as the dissipation flux coefficient and is usually treated as a constant. Our measurements suggest that this coefficient is highly spatiotemporally variable. Specific relationships are obtained when scaling this coefficient with other parameters, and mechanisms modulating this coefficient are also explored. This study sheds light on how much turbulent kinetic energy contributes to elevating the potential energy and its associated influences not only in marginal seas but also in open oceans.

Restricted access
Moritz Haas
,
Bedartha Goswami
, and
Ulrike von Luxburg

Abstract

Network-based analyses of dynamical systems have become increasingly popular in climate science. Here we address network construction from a statistical perspective and highlight the often ignored fact that the calculated correlation values are only empirical estimates. To measure spurious behaviour as deviation from a ground truth network, we simulate time-dependent isotropic random fields on the sphere and apply common network construction techniques. We find several ways in which the uncertainty stemming from the estimation procedure has major impact on network characteristics. When the data has locally coherent correlation structure, spurious link bundle teleconnections and spurious high-degree clusters have to be expected. Anisotropic estimation variance can also induce severe biases into empirical networks. We validate our findings with ERA5 reanalysis data. Moreover we explain why commonly applied resampling procedures are inappropriate for significance evaluation and propose a statistically more meaningful ensemble construction framework. By communicating which difficulties arise in estimation from scarce data and by presenting which design decisions increase robustness, we hope to contribute to more reliable climate network construction in the future.

Restricted access
Alexandra C. Mazurek
and
Russ S. Schumacher

Abstract

Previous work on continental convective systems has indicated that there is a positive relationship between short-term rainfall rates and storm- to mesoscale rotation. However, little has been done to explore this relationship in dense observing networks or in landfalling tropical cyclone (LTC) environments. In an effort to quantify the relationship between rainfall rates and embedded rotation of this scale, we use several sets of observations that were collected during Tropical Storm Imelda (2019). First, a meteorological overview of the event is presented, and the ingredients that led to its flash flood-producing rainfall are discussed. Then, two analyses that investigate the relationship between rainfall rates and storm- to mesoscale rotation in the LTC remnants are examined. The first method relies on products from the Multi-Radar Multi-Sensor system, where two spatial averaging approaches are applied to the 0-2 km accumulated rotation track and gauge bias-corrected quantitative precipitation estimate products over hourly time periods. Using these fields as proxies for rotation and rain rates, the results show a positive spatiotemporal relationship between the two products. The second method time matches subjectively identified radar-based rotation and 5-minute surface rain gauge observations. There, we show that nearly twice the amount of rain was recorded by the gauges when storm- to mesoscale rotation was present nearby, and the differences in 5-minute rainfall observations between when rotation was present versus not was statistically significant. Together, these results indicate that more rain tended to fall in locations where there was rotation embedded in the system.

Restricted access
Brian R. Greene
and
Scott T. Salesky

Abstract

For decades, stable boundary layer (SBL) turbulence has proven challenging to measure, parameterize, simulate, and interpret. Uncrewed aircraft systems (UAS) are becoming a reliable method to sample the atmospheric boundary layer, offering new perspectives for understanding the SBL. Moreover, continual computational advances have enabled the use of large-eddy simulations (LES) to simulate the atmosphere at ever-smaller scales. LES is therefore a powerful tool in establishing a baseline framework to understand the extent to which vertical profiles from UAS can represent larger-scale SBL flows. To quantify the representativeness of observations from UAS profiles and eddy-covariance observations within the SBL, we performed a random error analysis using a suite of six large-eddy simulations for a wide range of stabilities. We combine these random error estimates with emulated observations of a UAS and eddy-covariance systems to better inform future observational studies. For each experiment, we estimate relative random errors using the so-called relaxed filtering method for first- and second-order moments as functions of height and averaging time. We show that the random errors can be on the same order of magnitude as other instrument-based errors due to bias or dynamic response. Unlike instrument errors, however, random errors decrease with averaging time. For these reasons, we recommend coupling UAS observations with other ground-based instruments as well as dynamically adjusting the UAS vertical ascent rate to account for how errors change with height and stability.

Significance Statement

Weather-sensing uncrewed aircraft systems are rapidly being realized as effective tools to collect valuable observations within the atmospheric boundary layer. To fully capitalize on this novel observational technique, it is necessary to develop an understanding of how well their observations can represent the surrounding atmosphere across various spatial and temporal scales. In this study we quantify the representativeness of atmospheric observations in the stable boundary layer by evaluating the random errors for parameters such as temperature, wind speed, and fluxes as estimated from a suite of large-eddy simulations. Our results can better inform future studies utilizing uncrewed aircraft systems by highlighting how random errors in their observations relate to vertical ascent rate, atmospheric stability, and measurement height.

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