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Roy Barkan
,
Kaushik Srinivasan
, and
James C. McWilliams

Abstract

The interactions between oceanic mesoscale eddies, submesoscale currents, and internal gravity waves (IWs) are investigated in submesoscale-resolving realistic simulations in the North Atlantic Ocean. Using a novel analysis framework that couples the coarse-graining method in space with temporal filtering and a Helmholtz decomposition, we quantify the effects of the interactions on the cross-scale kinetic energy (KE) and enstrophy fluxes. By systematically comparing solutions with and without IW forcing, we show that externally forced IWs stimulate a reduction in the KE inverse cascade associated with mesoscale rotational motions and an enhancement in the KE forward cascade associated with divergent submesoscale currents, i.e., a “stimulated cascade” process. The corresponding IW effects on the enstrophy fluxes are seasonally dependent, with a stimulated reduction (enhancement) in the forward enstrophy cascade during summer (winter). Direct KE and enstrophy transfers from currents to IWs are also found, albeit with weaker magnitudes compared with the stimulated cascades. We further find that the forward KE and enstrophy fluxes associated with IW motions are almost entirely driven by the scattering of the waves by the rotational eddy field, rather than by wave–wave interactions. This process is investigated in detail in a companion manuscript. Finally, we demonstrate that the stimulated cascades are spatially localized in coherent structures. Specifically, the magnitude and direction of the bidirectional KE fluxes at submesoscales are highly correlated with, and inversely proportional to, divergence-dominated circulations, and the inverse KE fluxes at mesoscales are highly correlated with strain-dominated circulations. The predominantly forward enstrophy fluxes in both seasons are also correlated with strain-dominated flow structures.

Restricted access
Scott D. Rudlosky
,
Joseph Patton
,
Eric Palagonia
,
John Y. N. Cho
, and
James M. Kurdzo

Abstract

Quantifying the costs of radar outages allows value to be attributed to the alternate datasets that help mitigate outages. When radars are offline, forecasters rely more heavily on nearby radars, surface reports, numerical weather prediction models, and satellite observations. Monetized radar benefit models allow value to be attributed to individual radars for mitigating the threat to life from tornadoes, flash floods, and severe winds. Eighteen radars exceed $20 million in annual benefits for mitigating the threat to life from these convective hazards. The Jackson, Mississippi, radar (KDGX) provides the most value ($41.4 million), with the vast majority related to tornado risk mitigation ($29.4 million). During 2020–23, the average radar is offline for 2.57% of minutes or 9.27 days per year and experiences an average of 58.9 outages per year lasting 4.32 h on average. Radar outage cost estimates vary by location and convective hazard. Outage cost estimates concentrate at the top, with 8, 2, 4, and 5 radars exceeding $1 million in outage costs during 2020, 2021, 2022, and 2023, respectively. The KDGX radar experiences outage frequencies of 4.92% and 5.50% during 2020 and 2023, resulting in outage cost estimates > $2 million in both years. Combining outage cost estimates for all radars suggests that approximately $29.1 million in annual radar outage costs may be attributable as value to alternative datasets for helping mitigate radar outage impacts.

Significance Statement

This study combines information on radar status and monetized radar benefit models to attribute value to individual radars, estimate radar outage costs, and quantify the potential value of alternative datasets during outage-induced gaps in coverage. Eighteen radars exceed $20 million in annual benefits for mitigating the combined threat to life from tornadoes, flash floods, and severe winds. The first and third most valuable radars, both in Mississippi, experience outage frequencies twice the national average, accounting for a disproportionate share of the overall outage costs. Our findings suggest that characterizing and mitigating these outages might provide a near-term solution to better protect these communities from convective hazards. Combining outage cost estimates for all radars suggests that approximately $29.1 million in annual radar outage costs may be attributable as value to alternative datasets for helping mitigate the impacts of radar outages.

Restricted access
Lihui Ji
and
Ana P. Barros

Abstract

A 3D numerical model was built to serve as a virtual microphysics laboratory (VML) to investigate rainfall microphysical processes. One key goal for the VML is to elucidate the physical basis of warm precipitation processes toward improving existing parameterizations beyond the constraints of past physical experiments. This manuscript presents results from VML simulations of classical tower experiments of raindrop collisional collection and breakup. The simulations capture large raindrop oscillations in shape and velocity in both horizontal and vertical planes and reveal that drop instability increases with diameter due to the weakening of the surface tension compared with the body force. A detailed evaluation against reference experimental datasets of binary collisions over a wide range of drop sizes shows that the VML reproduces collision outcomes well including coalescence, and disk, sheet, and filament breakups. Furthermore, the VML simulations captured spontaneous breakup, and secondary coalescence and breakup. The breakup type, fragment number, and size distribution are analyzed in the context of collision kinetic energy, diameter ratio, and relative position, with a view to capture the dynamic evolution of the vertical microstructure of rainfall in models and to interpret remote sensing measurements.

Significance Statement

Presently, uncertainty in precipitation estimation and prediction remains one of the grand challenges in water cycle studies. This work presents a detailed 3D simulator to characterize the evolution of drop size distributions (DSDs), without the space and functional constraints of laboratory experiments. The virtual microphysics laboratory (VML) is applied to replicate classical tower experiments from which parameterizations of precipitation processes used presently in weather and climate models and remote sensing algorithms were derived. The results presented demonstrate that the VML is a robust tool to capture DSD dynamics at the scale of individual raindrops (precipitation microphysics). VML will be used to characterize DSD dynamics across scales for environmental conditions and weather regimes for which no measurements are available.

Open access
Siegfried D. Schubert
,
Yehui Chang
,
Anthony M. DeAngelis
,
Young-Kwon Lim
,
Natalie P. Thomas
,
Randal D. Koster
,
Michael G. Bosilovich
,
Andrea M. Molod
,
Allison Collow
, and
Amin Dezfuli

Abstract

In late December of 2022 and the first half of January 2023, an unprecedented series of atmospheric rivers (ARs) produced near-record heavy rains and flooding over much of California. Here, we employ the NASA GEOS AGCM run in a “replay” mode, together with more idealized simulations with a stationary wave model, to identify the remote forcing regions, mechanisms, and underlying predictability of this flooding event. In particular, the study addresses the underlying causes of a persistent positive Pacific–North American (PNA)-like circulation pattern that facilitated the development of the ARs. We show that the pattern developed in late December as a result of vorticity forcing in the North Pacific jet exit region. We further provide evidence that this vorticity forcing was the result of a chain of events initiated in mid-December with the development of a Rossby wave (as a result of forcing linked to the MJO) that propagated from the northern Indian Ocean into the North Pacific. As such, both the initiation of the event and the eventual development of the PNA depended critically on internally generated Rossby wave forcings, with the North Pacific jet playing a key role. This, combined with contemporaneous SST (La Niña) forcing that produced a circulation response in the AGCM that was essentially opposite to the positive PNA, underscores the fundamental lack of predictability of the event at seasonal time scales. Forecasts produced with the GEOS-coupled model suggest that useful skill in predicting the PNA and extreme precipitation over California was in fact limited to lead times shorter than about 3 weeks.

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Shaohua Chen
,
Haikun Zhao
,
Philip J. Klotzbach
,
Jian Cao
,
Jia Liang
,
Weican Zhou
, and
Liguang Wu

Abstract

On interannual time scales, there is significant meridional migration of the boreal summer (May–October) synoptic-scale wave (SSW) train relative to the summer monsoon trough line over the western North Pacific (WNP) during 1979–2021. The associated plausible physical reasons for the SSW meridional migration are investigated by comparing analyses between two distinct groups: atypical SSW years where SSWs tend to prevail northward of the summer monsoon trough line and typical SSW years where SSWs largely occur along the summer monsoon trough line. During typical SSW years, SSWs originate primarily from equatorial mixed Rossby-gravity (MRG) waves and then develop into off-equatorial tropical depression (TD) waves in the lower troposphere of the monsoon region. During atypical SSW years, SSWs appear to be sourced from upper-level easterlies, propagating downward to the lower troposphere in the monsoon region, with a prevailing TD wave structure. A budget analysis of barotropic eddy kinetic energy suggests that interannual meridional SSW migration is closely related to changes in the vorticity distribution along the summer monsoon trough over the WNP, especially the western part of the summer monsoon trough. These changes cause low-frequency zonal convergence and shear differences, changing barotropic conversion around the monsoon trough and modulating interannual SSW meridional movement. In response to these changes, there are corresponding differences in SSW sources: a predominate MRG–TD wave pattern in typical SSW years and a predominate TD wave pattern in atypical SSW years. These results improve our understanding of the interannual variability of large-scale circulation and tropical cyclones.

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Valentina Ortiz-Guzmán
,
Martin Jucker
, and
Steven C. Sherwood

Abstract

The Southern Hemisphere climate and weather are affected by several modes of variability and climate phenomena across different time and spatial scales. An additional key component of the atmosphere dynamics that greatly influences weather is quasi-stationary Rossby waves, which attract particular interest as they are often associated with synoptic-scale extreme events. In the Southern Hemisphere extratropical circulation, the most prominent quasi-stationary Rossby wave pattern is the zonal wavenumber 3 (ZW3), which has been shown to have impacts on meridional heat and momentum transport in mid- to high latitudes and on the Antarctic sea ice extent. However, little is known about its impacts outside of polar regions. In this work, we use ERA5 reanalysis data on monthly time scales to explore the influence of phase and amplitude of ZW3 on temperature and precipitation across the Southern Hemisphere midlatitudes. Our results show a significant impact in various regions for all seasons. One of the most substantial effects is observed in precipitation over southeastern Brazil during austral summer, where different phases of the ZW3 force opposite anomalies. When using the ZW3 phase and amplitude as prior information, the probability of occurrence of precipitation extremes in this region increases up to three times. Additionally, we find that this ZW3 weather signature is largely independent of the zonally symmetric Southern Annular Mode (SAM); neither does it seem to be linked to El Niño–Southern Oscillation (ENSO) or Indian Ocean dipole (IOD) signal.

Restricted access
Anda Vladoiu
,
Ren-Chieh Lien
, and
Eric Kunze

Abstract

Shipboard ADCP velocity and towed CTD chain density measurements from the eastern North Pacific pycnocline are used to segregate energy between linear internal waves (IW) and linear vortical motion [quasigeostrophy (QG)] in 2D wavenumber space spanning submesoscale horizontal wavelengths λx ∼ 1–50 km and finescale vertical wavelengths λz ∼ 7–100 m. Helmholtz decomposition and a new Burger number (Bu) decomposition yield similar results despite different methodologies. While these wavelengths are conventionally attributed to internal waves, both QG and IW contribute significantly at all measured scales. Partition between IW and QG total energies depends on Bu. For Bu < 0.01, available potential energy EP exceeds horizontal kinetic energy EK and is contributed mostly by QG. In contrast, energy is nearly equipartitioned between QG and IW for Bu ≫ 1. For Bu < 2, EK is contributed mainly by IW, and EP by QG, while, for Bu > 2, contributions are reversed. Finescale near-inertial IW dominate vertical shear variance, implying negligible QG contribution to vertical shear instability. In contrast, both QG and IW at the smallest λx ∼ 1 km contribute large horizontal shear variance, so that both may lead to horizontal shear instability, while QG, with its longer time scales, likely dominates isopycnal stirring. Both QG and IW contribute to vortex stretching at small vertical scales. For QG, the relative vorticity contribution to linear potential vorticity anomaly increases with decreasing horizontal and increasing vertical scales.

Open access
Pei-Syuan Liao
,
Chia-Wei Lan
,
Yu-Chiao Liang
, and
Min-Hui Lo

Abstract

The annual range (AR) of precipitation in the Amazon River basin has increased steadily since 1979. This increase may have resulted from natural variability and/or anthropogenic forcing, such as local land-use changes and global warming, which has yet to be explored. In this study, climate model experiments using the Community Earth System Model, version 2 (CESM2), were conducted to examine the relative contributions of sea surface temperatures (SSTs) variability and anthropogenic forcings to the AR changes in the Amazon rainfall. With CESM2, we design several factorial simulations, instead of actual model projection. We found that the North Atlantic SSTs fluctuation dominantly decreases the precipitation AR trend over the Amazon by −85%. In contrast, other factors, including deforestation and carbon dioxide, contributed to the trend changes, ranging from 25% to 35%. The dynamic component, specifically the tendency of vertical motion, made negative contributions, along with the vertical profiles of moist static energy (MSE) tendency. Seasonal-dependent changes in atmospheric stability could be associated with variations in precipitation. It is concluded that surface ocean warming associated with the North Atlantic natural variability and global warming is the key factor in the increased precipitation AR over the Amazon from 1979 to 2014. The continuous local land-use changes may potentially influence the precipitation AR in the future.

Significance Statement

The annual range (AR) in precipitation, the difference between wet- and dry-season precipitation, has increased from 1979 to 2014 in the Amazon. This increase may have resulted from global warming, deforestation, and sea surface temperature variability in North Atlantic and Pacific. To explore the role of each of these factors in altering the Amazon precipitation AR, five experiments were designed in the climate model (CESM). Among these experiment results, the effect of North Atlantic SSTs was the strongest. In the future, deforestation, global warming, and different ocean temperature states in the North Atlantic and Pacific may become increasingly influential on the changes in precipitation. Further investigation is needed to ascertain how the AR of precipitation in the Amazon will change.

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Kouya Nakamura
,
Shoichiro Kido
,
Takashi Ijichi
, and
Tomoki Tozuka

Abstract

The mean vertical advection of anomalous vertical temperature gradient is considered the dominant generation mechanism of positive sea surface temperature (SST) anomalies associated with the canonical El Niño. However, most past studies had a residual term in their heat budget analysis and/or did not quantify the role of vertical mixing even though active vertical turbulent mixing in the upper ocean is observed in the eastern equatorial Pacific. To quantitatively assess the importance of vertical mixing, a mixed layer heat budget analysis is performed using a hindcast simulation forced by daily mean atmospheric reanalysis data. It is found that when the mixed layer depth is defined as the depth at which potential density increases by 0.125 kg m−3 from the sea surface, the development of positive SST anomalies is predominantly governed by reductions in the cooling by vertical mixing, and their magnitude is much larger than those by vertical advection. The anomalous warming by vertical mixing may be partly explained by an anomalous deepening of the thermocline that leads to a decrease in the vertical temperature gradient, giving rise to suppression of the climatological cooling by vertical mixing. Also, an anomalously thick mixed layer reduces sensitivity to cooling by the mean vertical mixing and contributes to the anomalous SST warming. On the other hand, the dominant negative feedbacks are attributed to both anomalous surface heat loss and anomalous deepening of the mixed layer that weakens warming by the mean surface heat flux.

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Zili Shen
,
Anmin Duan
,
Wen Zhou
,
Yuzhuo Peng
, and
Jinxiao Li

Abstract

Two large ensemble simulations are adopted to investigate the relative contribution of external forcing and internal variability to Arctic sea ice variability on different time scales since 1960 by correcting the response error of models to external forcing using observational datasets. Our study suggests that previous approaches might overestimate the real impact of internal variability on Arctic sea ice change especially on long time scales. Our results indicate that in both March and September, internal variability plays a dominant role on all time scales over the twentieth century, while the anthropogenic signal on sea ice change can be steadily and consistently detected on a time scale of more than 20 years after the 2000s. We also reveal that the dominant mode of internal variability in March shows consistency across different time scales. On the contrary, the pattern of internal variability in September is highly nonuniform over the Arctic and varies across different time scales, indicating that sea ice internal variability in September at different time scales is driven by different factors.

Open access