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Marybeth C. Arcodia
,
Emily Becker
, and
Ben P. Kirtman

Abstract

Climate variability affects sea levels as certain climate modes can accelerate or decelerate the rising sea level trend, but subseasonal variability of coastal sea levels is underexplored. This study is the first to investigate how remote tropical forcing from the MJO and ENSO impact subseasonal U.S. coastal sea level variability. Here, composite analyses using tide gauge data from six coastal regions along the U.S. East and West Coasts reveal influences on sea level anomalies from both the MJO and ENSO. Tropical MJO deep convection forces a signal that results in U.S. coastal sea level anomalies that vary based on MJO phase. Further, ENSO is shown to modulate both the MJO sea level response and background state of the teleconnections. The sea level anomalies can be significantly enhanced or weakened by the MJO-associated anomaly along the East Coast due to constructive or destructive interference with the ENSO-associated anomaly, respectively. The West Coast anomaly is found to be dominated by ENSO. We examine physical mechanisms by which MJO and ENSO teleconnections impact coastal sea levels and find consistent relationships between low-level winds and sea level pressure that are spatially varying drivers of the variability. Two case studies reveal how MJO and ENSO teleconnection interference played a role in notable coastal flooding events. Much of the focus on sea level rise concerns the long-term trend associated with anthropogenic warming, but on shorter time scales, we find subseasonal climate variability has the potential to exacerbate the regional coastal flooding impacts.

Significance Statement

Coastal flooding due to sea level rise is increasingly threatening communities, but natural fluctuations of coastal sea levels can exacerbate the human-caused sea level rise trend. This study assesses the role of tropical influences on coastal subseasonal (2 weeks–3 months) sea level heights. Further, we explore the mechanisms responsible, particularly for constructive interference of signals contributing to coastal flooding events. Subseasonal signals amplify or suppress the lower-frequency signals, resulting in higher or lower sea level heights than those expected from known climate modes (e.g., ENSO). Low-level onshore winds and reduced sea level pressure connected to the tropical phenomena are shown to be indicators of increased U.S. coastal sea levels, and vice versa. Two case studies reveal how MJO and ENSO teleconnection interference played a role in notable coastal flooding events. Much of the focus on sea level rise concerns the long-term trend associated with anthropogenic warming, but on shorter time scales, we find subseasonal climate variability has the potential to exacerbate the regional coastal flooding impacts.

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Nina Horat
and
Sebastian Lerch

Abstract

Subseasonal weather forecasts are becoming increasingly important for a range of socioeconomic activities. However, the predictive ability of physical weather models is very limited on these time scales. We propose four postprocessing methods based on convolutional neural networks to improve subseasonal forecasts by correcting systematic errors of numerical weather prediction models. Our postprocessing models operate directly on spatial input fields and are therefore able to retain spatial relationships and to generate spatially homogeneous predictions. They produce global probabilistic tercile forecasts for biweekly aggregates of temperature and precipitation for weeks 3–4 and 5–6. In a case study based on a public forecasting challenge organized by the World Meteorological Organization, our postprocessing models outperform the bias-corrected forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF), and achieve improvements over climatological forecasts for all considered variables and lead times. We compare several model architectures and training modes and demonstrate that all approaches lead to skillful and well-calibrated probabilistic forecasts. The good calibration of the postprocessed forecasts emphasizes that our postprocessing models reliably quantify the forecast uncertainty based on deterministic input information in the form of ECMWF ensemble mean forecast fields only.

Open 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 (quasi-geostrophy, QG) in 2-D 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. 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. Vertical shear variance is contributed primarily by near-inertial IW at small λz , implying negligible QG contribution to vertical shear instability. Conversely, both QG and IW at the smallest λx ∼ 1 km contribute large horizontal shear variance, such that both may lead to horizontal shear instability. 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.

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Maziar Bani Shahabadi
and
Mark Buehner

Abstract

Cloud-affected microwave humidity sounding radiances were excluded from assimilation in 4D-EnVar system of the Global Deterministic Prediction System (GDPS) at Environment and Climate Change Canada (ECCC). This was due to the inability of the current radiative transfer model to consider the scattering effect from frozen hydrometeors at these frequencies. In addition to upgrading the observation operator to RTTOV-SCATT, quality control, bias correction, and 4D-EnVar assimilation components are modified to perform all-sky assimilation of Microwave Humidity Sounder (MHS) channels 2-5 observations over ocean in the GDPS. The input profiles to RTTOV-SCATT are extended to include liquid cloud, ice cloud, and cloud fraction profiles for the simulation and assimilation of MHS observations over water. There is a maximum 35% increase in number of channel 2 assimilated MHS observations with smaller increases for channels 3-5 in the all-sky compared to the clear-sky experiment, mostly because of newly assimilated cloud-affected observations. The stddev of difference between the observed GPSRO refractivity observations and the corresponding simulated values using the background state was reduced in lower troposphere below 9 km in the all-sky experiment. Verifications of forecasts against the radiosonde observations show statistically significant reductions of 1% in stddev of error for geopotential height, temperature, and horizontal wind for all-sky experiment between 72- and 120- hr forecast ranges in troposphere in Northern Hemisphere domain. Verifications of forecasts against ECMWF analyses also show small improvements in zonal mean of error stddev for temperature and horizontal wind for all-sky experiment between 72- and 120-hr forecast ranges. This work is planned for operational implementation in the GDPS in Fall 2023.

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Xiuzhen Li
,
Donghai Wang
, and
Wen Zhou

Abstract

South China encountered an exceptionally heavy pre-summer rainy season in 2022 with the regional precipitation ranking first in the past 44 years. This study aims to analyze the multiple-time-scale variations of precipitation in this pre-summer rainy season to shed light on the complex dynamics influencing pre-summer precipitation over South China. The findings reveal that the variation of precipitation was dominated by the 10–20-day oscillation during April–May, while interannual variation and trend during May–June. The 10–20-day oscillation of precipitation in pre-summer rainy season in South China demonstrates a strong association with cold-air activity, which can be traced back to the propagation of disturbances along a teleconnection, which represents the dominant mode of intraseasonal atmospheric circulation over Eurasia in high latitudes during April–May. This teleconnection plays a crucial role in facilitating cold-air invasion and triggering precipitation over East China and South China. The interannual component of abnormal precipitation is strong during May–June of 2022. It is primarily attributed to the abnormal highs in the lower troposphere over the subtropical western North Pacific and Japan. These abnormal highs are likely stimulated by the combined influences of Eurasian teleconnection propagation and cooling sea surface temperature anomalies (SSTAs) over the tropical central and eastern Pacific in the third year of a consecutive La Niña event. However, the universality of the impact of Eurasian teleconnection propagation on the abnormal high over Japan on interannual scale necessitates further investigation. Furthermore, there is a significant upward trend in pre-summer rainfall over South China, accounting for 38% of the total anomaly observed in 2022.

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Ryosuke Okugawa
,
Kazuaki Yasunaga
,
Atsushi Hamada
, and
Satoru Yokoi

Abstract

Large amounts of tropical precipitation have been observed as significantly concentrated over the western coast of Sumatra Island. In the present study, we used a cloud-resolving model to perform 14-day numerical simulations and reproduce the distinctive precipitation distributions over western Sumatra Island and adjacent areas. The control experiment, in which the warmer sea surface temperature (SST) near the coast was incorporated and the terminal velocity and effective radius of ice clouds were parameterized to be temperature dependent, adequately reproduced the precipitation concentration as well as the diurnal cycles of precipitation. We then used the column-integrated frozen moist static energy budget equation, which is virtually equivalent to the column-integrated moisture budget equation under the weak temperature gradient assumption, to formulate sensitivity experiments focusing on the effects of coastal SST and upper-level ice clouds. Analysis of the time-averaged fields revealed that the column-integrated moisture and precipitation in the coast were significantly reduced when a cooler coastal SST or larger ice cloud particle size was assumed. Based on the comparison of the sensitivity experiments and in situ observations, we speculate that ice clouds, which are exported from inland convection that is strictly regulated by solar radiation, promote the accumulation of moisture in the coastal region by mitigating radiative cooling. Together with the moisture and heat supplied by the warm ocean surface, they contribute to the large amounts of precipitation here.

Open access
Azusa Takeishi
and
Chien Wang

Abstract

Raindrop formation processes in warm clouds mainly consist of condensation and collision–coalescence of small cloud droplets. Once raindrops form, they can continue growing through collection of cloud droplets and self-collection. In this study, we develop novel emulators to represent raindrop formation as a function of various physical or background environmental conditions by using a sophisticated aerosol–cloud model containing 300 droplet size bins and machine learning methods. The emulators are then implemented in two microphysics schemes in the Weather Research and Forecasting Model and tested in two idealized cases. The simulations of shallow convection with the emulators show a clear enhancement of raindrop formation compared to the original simulations, regardless of the scheme in which they were embedded. On the other hand, the simulations of deep convection show a more complex response to the implementation of the emulators, in terms of the changes in the amount of rainfall, due to the larger number of microphysical processes involved in the cloud system (i.e., ice-phase processes). Our results suggest the potential of emulators to replace the conventional parameterizations, which may allow us to improve the representation of physical processes at an affordable computational expense.

Significance Statement

Formation of raindrops marks a critical stage in cloud evolution. Accurate representations of raindrop formation processes require detailed calculations of cloud droplet growth processes. These calculations are often not affordable in weather and climate models as they are computationally expensive due to their complex dependence on cloud droplet size distributions and dynamical conditions. As a result, simplified parameterizations are more frequently used. In our study we trained machine learning models to learn raindrop formation rates from detailed calculations of cloud droplet evolutions in 1000 parcel-model simulations. The implementation of the developed models or the emulators in a weather forecasting model shows a change in the total rainfall and cloud characteristics, indicating the potential improvement of cloud representations in models if these emulators replace the conventional parameterizations.

Open access
Víctor C. Mayta
and
Ángel F. Adames Corraliza

Abstract

Observations of column water vapor in the tropics show significant variations in space and time, indicating that it is strongly influenced by the passage of weather systems. It is hypothesized that many of the influencing systems are moisture modes, systems whose thermodynamics are governed by moisture. On the basis of four objective criteria, results suggest that all oceanic convectively coupled tropical depression (TD)-like waves and equatorial Rossby waves are moisture modes. These modes occur where the horizontal column moisture gradient is steep and not where the column water vapor content is high. Despite geographical basic-state differences, the moisture modes are driven by the same mechanisms across all basins. The moist static energy (MSE) anomalies propagate westward by horizontal moisture advection by the trade winds. Their growth is determined by the advection of background moisture by the anomalous meridional winds and anomalous radiative heating. Horizontal maps of column moisture and 850-hPa streamfunction show that convection is partially collocated with the low-level circulation in nearly all the waves. Both this structure and the process of growth indicate that the moisture modes grow from moisture–vortex instability. Last, space–time spectral analysis reveals that column moisture and low-level meridional winds are coherent and exhibit a phasing that is consistent with a poleward latent energy transport. Collectively, these results indicate that moisture modes are ubiquitous across the tropics. That they occur in regions of steep horizontal moisture gradients and grow from moisture–vortex instability suggests that these gradients are inherently unstable and are subject to continuous stirring.

Significance Statement

Over the tropics, column water vapor has been found to be highly correlated with precipitation, especially in slowly evolving systems. These observations and theory support the hypothesis that moisture modes exist, a type of precipitating weather system that does not exist in dry theory. In this study, we found that all oceanic tropical depression (TD)-like waves and equatorial Rossby waves are moisture modes. These systems exist in regions where moisture varies greatly in space, and they grow by transporting air from the humid areas of the tropics toward their low pressure center. These results indicate that the climatological-mean distribution of moisture in the tropics is unstable and is subject to stirring by moisture modes.

Open access
Hao Fu
and
Morgan O’Neill

Abstract

Cloud-permitting simulations have shown that tropical cyclones (TCs) can form spontaneously in a quiescent environment with uniform sea surface temperature. While several mesoscale feedbacks are known to amplify an existing midlevel vortex, how the noisy deep convection produces the initial midlevel vortex remains unclear. This paper develops a theoretical framework to understand the evolution of the midlevel mesoscale vorticity’s histogram in the first two days of spontaneous tropical cyclogenesis, which we call the “stochastic spin-up stage”. The mesoscale vorticity is produced by two random processes related to deep convection: the random stretching of planetary vorticity (f) and the tilting of random vertical shear. The mesoscale vorticity is modeled as the sum of three independent normal distributions, which include the cyclones produced by stretching, cyclones produced by tilting, and anticyclones produced by tilting. Their collective effect is calculated with the central limit theorem. The theory predicts that the standard deviation of the midlevel mesoscale vorticity is universally proportional to the square root of the domain-averaged accumulated rainfall, agreeing with simulations. The theory predicts a critical latitude below which tilting is dominant in producing mesoscale vorticity. Treating the magnitude of random vertical shear as a fitting parameter, the critical latitude is shown to be around 12°N. Because the magnitude of vertical shear should be larger in the real atmosphere, this result suggests tilting is an important source of mesoscale vorticity fluctuation in the tropics.

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Matthieu Kohl
and
Paul A. O’Gorman

Abstract

The vertical velocity distribution in the atmosphere is asymmetric with stronger upward than downward motion. This asymmetry is important for the distribution of precipitation and its extremes and for an effective static stability that has been used to represent the effects of latent heating on extratropical eddies. Idealized GCM simulations show that the asymmetry increases as the climate warms, but current moist dynamical theories based around small-amplitude modes greatly overestimate the increase in asymmetry with warming found in the simulations. Here, we first analyze the changes in asymmetry with warming using numerical inversions of a moist quasigeostrophic omega equation applied to output from the idealized GCM. The inversions show that increases in the asymmetry with warming in the GCM simulations are primarily related to decreases in moist static stability on the left-hand side of the moist omega equation, whereas the dynamical forcing on the right-hand side of the omega equation is unskewed and contributes little to the asymmetry of the vertical velocity distribution. By contrast, increases in asymmetry with warming for small-amplitude modes are related to changes in both moist static stability and dynamical forcing leading to enhanced asymmetry in warm climates. We distill these insights into a toy model of the moist omega equation that is solved for a given moist static stability and wavenumber of the dynamical forcing. In comparison to modal theory, the toy model better reproduces the slow increase of the asymmetry with climate warming in the idealized GCM simulations and over the seasonal cycle from winter to summer in reanalysis.

Significance Statement

Upward velocities are stronger than downward velocities in the atmosphere, and this asymmetry is important for the distribution of precipitation because precipitation is linked to upward motion. An important and open question is what sets this asymmetry and how much it increases as the climate warms. Past work has shown that current theories greatly overestimate the increase in asymmetry with warming in idealized simulations. In this work, we develop a more complete theory and show that it is able to better reproduce the slow increase of the asymmetry with warming that is found over the seasonal cycle from winter to summer and in idealized simulations of warming climates.

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