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Benjamin Jaimes de la Cruz, Lynn K. Shay, Joshua B. Wadler, and Johna E. Rudzin

Abstract

Sea-to-air heat fluxes are the energy source for tropical cyclone (TC) development and maintenance. In the bulk aerodynamic formulae, these fluxes are a function of surface wind speed (U 10) and air-sea temperature and moisture disequilibrium (ΔT and Δq, respectively). While many studies have explained TC intensification through the mutual dependence between increasing U 10 and increasing sea-to-air heat fluxes, recent studies found TC intensification can occur through deep convective vortex structures that obtain their local buoyancy from sea-to-air moisture fluxes, even under relatively low-wind conditions. Herein, a new perspective on the bulk aerodynamic formulae is introduced to evaluate the relative contribution of wind-driven (U 10) and thermodynamically-driven (ΔT and Δq) ocean heat-uptake. Previously unnoticed salient properties of these formulae, reported here, are: (1) these functions are hyperbolic; and, (2) increasing Δq is an efficient mechanism for enhancing the fluxes.

This new perspective was used to investigate surface heat fluxes in six TCs during phases of steady state intensity (SS), slow intensification (SI), and rapid intensification (RI). A capping of wind-driven heat-uptake was found during periods of SS, SI, and RI. Compensation by larger values of Δq>5 g kg-1 at moderate values of U 10 led to intense inner-core moisture fluxes >600 W m-2 during RI. Peak values in Δq preferentially occurred over oceanic regimes with higher sea surface temperature (SST) and upper-ocean heat content. Thus, increasing SST and Δq is a very effective way to increase surface heat fluxes—this can be easily achieved as a TC moves over deeper warm oceanic regimes.

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Pablo Zurita-Gotor and Isaac M. Held

Abstract

This work investigates the characteristics of westward-propagating Rossby modes in idealized global general circulation models. Using a nonlinear smoothing algorithm to estimate the background spectrum and an objective method to extract the spectral peaks, the 4 leading meridional modes can be identified for each of the first 3 zonal wavenumbers, with frequencies close to the predictions from the Hough modes obtained by linearizing about a state of rest. Variations in peak amplitude for different modes, both within a simulation and across simulations, may be understood under the assumption that the forcing of the modes scales with the background spectrum. Surface friction affects the amplitude and width of the peaks but both remain finite as friction goes to zero, which implies that some other mechanism, arguably nonlinear, must also contribute to the damping of the modes. Although spectral peaks are also observed for the precipitation field with idealized moist physics, there is no evidence of mode enhancement by the convective heating. Subject to the same friction, the amplitude of the peaks are very similar in the dry and moist models when both are normalized by the background spectra.

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Bhupendra A. Raut, Robert Jackson, Mark Picel, Scott M. Collis, Martin Bergemann, and Christian Jakob

Abstract

A robust and computationally efficient object tracking algorithm is developed by incorporating various tracking techniques. Physical properties of the objects, such as brightness temperature or reflectivity, are not considered. Therefore, the algorithm is adaptable for tracking convection-like features in simulated data and remotely sensed two-dimensional images. In this algorithm, a first guess of the motion, estimated using the Fourier phase shift, is used to predict the candidates for matching. A disparity score is computed for each target-candidate pair. The disparity also incorporates overlapping criteria in the case of large objects. Then the Hungarian method is applied to identify the best pairs by minimizing the global disparity. The high disparity pairs are unmatched, and their target and candidate are declared expired and newly initiated objects, respectively. They are tested for merger and split, based on their size and overlap with the other objects. The sensitivity of track duration is shown for different disparity and size thresholds. The paper highlights the algorithm’s ability to study convective life cycles using radar and simulated data over Darwin, Australia. The algorithm skillfully tracks individual convective cells (few pixels in size) and large convective systems. The duration of tracks and cell size are found to be log-normally distributed over Darwin. The evolution of size and precipitation types of isolated convective cells is presented in the Lagrangian perspective. This algorithm is part of a vision for a modular platform (viz. TINT and tobac) that will evolve into a sustainable choice to analyze atmospheric features.

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Ming Zhang, Yonggang Liu, Jian Zhang, and Qin Wen

Abstract

The North Africa was green during the mid-Holocene (6 ka) and emitting much less dust to the atmosphere than in present day. Here we use a fully coupled atmosphere-ocean general circulation model, CESM1.2.2, to test the impact of dust reduction and greening of Sahara on the Atlantic Meridional Overturning Circulation (AMOC) during this period. Results show that dust removal leads to a decrease of AMOC by 6.2 % while greening of Sahara with 100 % shrub (100 % grass) causes an enhancement of the AMOC by 6.1 % (4.8 %). The AMOC is increased by 5.3 % (2.3 %) when both the dust reduction and green Sahara with 100 % shrub (100 % grass) are considered. The AMOC changes are primarily due to the precipitation change over the west subtropical North Atlantic, from where the salinity anomaly is advected to the deepwater formation region. Global mean surface temperature increases by 0.09 °C and 0.40 °C (0.25 °C) when global dust is removed and when North Africa and Arabian region are covered by shrub (grass), respectively, showing a dominating effect of vegetation over dust. The comparison between modeled and reconstructed sea-surface temperature is improved when the effect of vegetation is considered. The results may have implication for climate impact of future wetting over North Africa, either through global warming or through building of solar farms and wind farms.

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Dasol Kim, Chang-Hoi Ho, Hiroyuki Murakami, and Doo-Sun R. Park

Abstract

Understanding the mechanisms related to the variations in the rainfall structure of tropical cyclones (TCs) is crucial in improving forecasting systems of TC rainfall and its impact. Using satellite precipitation and reanalysis data, we examined the influence of along-track large-scale environmental conditions on inner-core rainfall strength (RS) and total rainfall area (RA) for Atlantic TCs during the TC season (July–November) from 1998 to 2019. Factor analysis revealed three major factors associated with variations in RS and RA: large-scale low and high pressure systems [factor 1 (F1)]; environmental flows, sea surface temperature, and humidity [factor 2 (F2)]; and maximum wind speed of TCs [factor 3 (F3)]. Results from our study indicate that RS increases with an increase in the inherent primary circulation of TCs (i.e., F3) but is less affected by large-scale environmental conditions (i.e., F1 and F2), whereas RA is primarily influenced by large-scale low and high pressure systems (i.e., F1) over the entire North Atlantic and partially influenced by environmental flows, sea surface temperature, humidity, and maximum wind speed (i.e., F2 and F3). A multivariable regression model based on the three factors accounted for the variations of RS and RA across the entire basin. In addition, regional distributions of mean RS and RA from the model significantly resembled those from observations. Therefore, our study suggests that large-scale environmental conditions over the North Atlantic Ocean are important predictors for TC rainfall forecasts, particularly with regard to RA.

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Chuanhao Wu, Pat J.-F. Yeh, Jiali Ju, Yi-Ying Chen, Kai Xu, Heng Dai, Jie Niu, Bill X. Hu, and Guoru Huang

Abstract

Drought projections are accompanied with large uncertainties due to varying estimates of future warming scenarios from different modeling and forcing data. Using the standardized precipitation index (SPI), this study presents a global assessment of uncertainties in drought characteristics (severity S and frequency Df) projections based on the simulations of 28 general circulation models (GCMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5). A hierarchical framework incorporating a variance-based global sensitivity analysis was developed to quantify the uncertainties in drought characteristics projections at various spatial (global and regional) and temporal (decadal and 30-yr) scales due to 28 GCMs, three representative concentration pathway scenarios (RCP2.6, RCP4.5, RCP8.5), and two bias-correction (BC) methods. The results indicated that the largest uncertainty contribution in the globally projected S and Df is from the GCM uncertainty (>60%), followed by BC (<35%) and RCP (<16%) uncertainty. Spatially, BC reduces the spreads among GCMs particularly in Northern Hemisphere (NH), leading to smaller GCM uncertainty in the NH than the Southern Hemisphere (SH). In contrast, the BC and RCP uncertainties are larger in the NH than the SH, and the BC uncertainty can be larger than GCM uncertainty for some regions (e.g., southwest Asia). At the decadal and 30-yr time scales, the contributions for three uncertainty sources show larger variability in S than Df projections, especially in the SH. The GCM and BC uncertainties show overall decreasing trends with time, while the RCP uncertainty is expected to increase over time and even can be larger than BC uncertainty for some regions (e.g., northern Asia) by the end of this century.

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Wenfeng Lai, Jianping Gan, Ye Liu, Zhiqiang Liu, Jiping Xie, and Jiang Zhu

Abstract

To improve the forecasting performance in dynamically active coastal waters forced by winds, tides, and river discharges in a coupled estuary–shelf model off Hong Kong, a multivariable data assimilation (DA) system using the ensemble optimal interpolation method has been developed and implemented. The system assimilates the conductivity–temperature–depth (CTD) profilers, time series buoy measurement, and remote sensing sea surface temperature (SST) data into a high-resolution estuary–shelf ocean model around Hong Kong. We found that the time window selection associated with the local dynamics and the number of observation samples are two key factors in improving assimilation in the unique estuary–shelf system. DA with a varied assimilation time window that is based on the intratidal variation in the local dynamics can reduce the errors in the estimation of the innovation vector caused by the model–observation mismatch at the analysis time and improve simulation greatly in both the estuary and coastal regions. Statistically, the overall root-mean-square error (RMSE) between the DA forecasts and not-yet-assimilated observations for temperature and salinity has been reduced by 33.0% and 31.9% in the experiment period, respectively. By assimilating higher-resolution remote sensing SST data instead of lower-resolution satellite SST, the RMSE of SST is improved by ~18%. Besides, by assimilating real-time buoy mooring data, the model bias can be continuously corrected both around the buoy location and beyond. The assimilation of the combined buoy, CTD, and SST data can provide an overall improvement of the simulated three-dimensional solution. A dynamics-oriented assimilation scheme is essential for the improvement of model forecasting in the estuary–shelf system under multiple forcings.

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Yong-Fei Zhang, Mitchell Bushuk, Michael Winton, Bill Hurlin, Xiaosong Yang, Tom Delworth, and Liwei Jia

Abstract

The current GFDL seasonal prediction system achieved retrospective sea ice extent (SIE) skill without direct sea ice data assimilation. Here we develop sea ice data assimilation, shown to be a key source of skill for seasonal sea ice predictions, in GFDL’s next-generation prediction system, the Seamless System for Prediction and Earth System Research (SPEAR). Satellite sea ice concentration (SIC) observations are assimilated into the GFDL Sea Ice Simulator version 2 (SIS2) using the ensemble adjustment Kalman filter (EAKF). Sea ice physics is perturbed to form an ensemble of ice–ocean members with atmospheric forcing from the JRA-55 reanalysis. Assimilation is performed every 5 days from 1982 to 2017 and the evaluation is conducted at pan-Arctic and regional scales over the same period. To mitigate an assimilation overshoot problem and improve the analysis, sea surface temperatures (SSTs) are restored to the daily Optimum Interpolation Sea Surface Temperature version 2 (OISSTv2). The combination of SIC assimilation and SST restoring reduces analysis errors to the observational error level (~10%) from up to 3 times larger than this (~30%) in the free-running model. Sensitivity experiments show that the choice of assimilation localization half-width (190 km) is near optimal and that SIC analysis errors can be further reduced slightly either by reducing the observational error or by increasing the assimilation frequency from every 5 days to daily. A lagged-correlation analysis suggests substantial prediction skill improvements from SIC initialization at lead times of less than 2 months.

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A. Cobb, A. Michaelis, S. Iacobellis, F. M. Ralph, and L. Delle Monache

Abstract

Atmospheric rivers (ARs) are responsible for intense winter rainfall events impacting the U.S. West Coast, and have been studied extensively during CalWater and AR Recon field programs (2014–20). A unique set of 858 dropsondes deployed in lines transecting 33 ARs are analyzed, and integrated vapor transport (IVT) is used to define five regions: core, cold and warm sectors, and non-AR cold and warm sides. The core is defined as having at least 80% of the maximum IVT in the transect. Remaining dropsondes with IVT > 250 kg m−1 s−1 are assigned to cold or warm sectors, and those outside of this threshold form non-AR sides. The mean widths of the three AR sectors are approximately 280 km. However, the core contains roughly 50% of all the water vapor transport (i.e., the total IVT), while the others each contain roughly 25%. A low-level jet occurs most often in the core and warm sector with mean maximum wind speeds of 28.3 and 21.7 m s−1, comparable to previous studies, although with heights approximately 300 m lower than previously reported. The core exhibits characteristics most favorable for adiabatic lifting to saturation by the California coastal range. On average, stability in the core is moist neutral, with considerable variability around the mean. A relaxed squared moist Brunt–Väisälä frequency threshold shows ~8%–12% of core profiles exhibiting near-moist neutrality. The vertical distribution of IVT, which modulates orographic precipitation, varied across AR sectors, with 75% of IVT residing below 3115 m in the core.

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Hongjie Li and Yongsheng Xu

Abstract

Stratified geostrophic turbulence theory predicts an inverse energy cascade for the barotropic (BT) mode. Satellite altimetry has revealed a net inverse cascade in the baroclinic (BC) mode. Here the spatial variabilities of BT and BC kinetic energy fluxes in the Antarctic Circumpolar Current (ACC) were investigated using ECCO2 data, which synthesize satellite data and in situ measurements with an eddy-permitting general circulation model containing realistic bathymetry and wind forcing. The BT and BC inverse kinetic energy cascades both reveal complex spatial variations that could not be explained fully by classical arguments. For example, the BC injection scales match better with most unstable scales than with the first-mode deformation scales, but the opposite is true for the BT mode. In addition, the BT and BC arrest scales do not follow the Rhines scale well in terms of spatial variation, but show better consistency with their own energy-containing scales. The reverse cascade of the BT and BC modes was found related to their EKE, and better correlation was found between the BT inverse cascade and barotropization. Speculations of the findings were proposed; however, further observations and modeling experiments are needed to test these interpretations. Spectral flux anisotropy exhibits a feature associated with oceanic jets that is consistent with classical expectations. Specifically, the spectral flux along the along-stream direction remains negative at scales up to that of the studied domain (~2000 km), while that in the perpendicular direction becomes positive close to the scale of the width of a typical jet.

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