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Yukitaka Ohashi
and
Kazuki Hara

Abstract

This study attempted to forecast the morning fog expansion (MFE), commonly referred to as the “sea of clouds,” utilizing an artificial intelligence (AI) algorithm. The radiation fog phenomenon that contributes to the sea of clouds is caused by various weather conditions. Hence, the MFE was predicted using datasets from public meteorological observations and a mesoscale numerical model (MSM). In this study, a machine-learning technique, the gradient boosting method, was adopted as the AI algorithm. The Miyoshi Basin in Japan, renowned for its MFE, was selected as the experimental region. Training models were developed using datasets from October, November, and December 2018–2021. Subsequently, these models were applied to forecast MFE in 2022. The model employing the upper atmospheric prediction data from the MSM demonstrated the highest robustness and accuracy among the proposed models. For untrained data in the fog season during 2022, the model was confirmed to be sufficiently reliable for forecasting MFE, with a high hit rate of 0.935, a low Brier score of 0.119, and a high Area Under the Curve (AUC) of 0.944. Furthermore, the analysis of the importance of the features elucidated that the meteorological factors, such as synoptic-scale weak wind, temperatures close to the dew-point temperature, and the absence of middle-level cloud cover at midnight, strongly contribute to the MFE. Therefore, the incorporation of upper-level meteorological elements improves the forecast accuracy for MFE.

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Chen Liu
,
Lei Chen
, and
Stefan Liess

Abstract

The features of large-scale atmospheric circulations, storm tracks, and the mean flow–eddy interaction during winter Pacific–North American (PNA) events are investigated using National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis data at subseasonal time scales from 1979 to 2022. The day-to-day variations of storm-track activity and streamfunction reveal that storm-track activity varies along the evolution of mean flow. To better understand storm-track variability with the mean flow–eddy interaction, further exploration is made by analyzing local energy energetics. The changes in horizontal and vertical baroclinic energy conversions from background flow correspond to the storm-track anomalies over the North Pacific, indicating that the anomalies in storm tracks are due to the anomalous mean flow associated with PNA patterns impacting energy conversion through mean flow–eddy interaction. Eddy feedback driven by vorticity and heat fluxes is analyzed. This provides a concrete illustration of how eddy feedback serves as a positive factor for the upper-tropospheric circulation anomalies associated with the PNA pattern.

Significance Statement

The background flow plays a crucial role in governing storm-track dynamics. Our emphasis is on the Pacific storm tracks (PST) and their relation to Pacific–North American (PNA) patterns at subseasonal time scales. We unveil the relationship between anomalies of PST and PNA patterns using local energetics and eddy feedback on a day-by-day basis. It is noteworthy that the evolution of anomalous storm tracks during PNA events is the manifestation of mean flow–eddy interaction. Additionally, we provide detailed confirmation of the impact of anomalous storm tracks on large-scale anomalies associated with the PNA pattern.

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Yang Zhao
,
Jianping Li
,
Yuan Tian
, and
Jiao Li

Abstract

This study investigates the disparity in quantitative moisture contribution and synoptic-scale vertical motion in the lower reaches of the Yangtze River basin (LYRB) for different extreme precipitation (EP) types, which are categorized as EP associated with atmospheric river (AR&EP) or EP associated with nonatmospheric river (non-AR&EP). To analyze moisture contribution, backward tracking using the Water Accounting Model-2layers is performed. In general, the remote moisture contribution is 9.7 times greater than the local contribution, with the ocean contribution being 1.67 times stronger than the land contribution. However, terrestrial and oceanic contributions obviously increase in the EP types, especially for oceanic contribution being double in magnitude. Notably, the west Pacific (WP) contribution emerges as the dominant differentia between the EP types, playing a crucial role in the AR formation. By solving the quasigeostrophic omega equation, the upper-level jet (ULJ) stream acts as the primary dynamic forcing for transverse vertical motion in AR&EP, while the baroclinic trough exhibits a relatively weaker influence. However, both systems have a nearly equal impact on vertical velocity in non-AR&EP. The enhanced shearwise elevation in the non-AR&EP type is the response of the stronger upper-level ridge over the Tibetan Plateau (TP), which induces enhanced Q vector, the divergence pointing toward the LYRB. However, the main dynamic difference is the location of ULJ, which serves as the trigger role although weak. Diabatic forcing proves to be the decisive factor for vertical motion development, the difference attributed to the released excessive latent heating with excess moisture contribution from the WP in AR&EP with enhanced precipitation.

Significance Statement

The main objective of this study is to investigate quantitative moisture contribution by applying Water Accounting Model-2layers and vertical motion attribution using the quasigeostrophic omega equation for extreme precipitation types based on the presence or absence of atmospheric river. Our findings reveal excessive moisture from the west Pacific serving not only as key in atmospheric river formation but also as the primary trigger for intensified diabatic vertical motion, inducing enhanced precipitation. The direction of strong winds in the north of the Tibetan Plateau holds crucial forecasting implications, which determine the location of the upper-level jet stream downstream. The transverse vertical motion, induced by the upper-level jet stream, plays the dominant dynamic role in both extreme precipitation (EP) types.

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Yu Lin
,
Haishen Lü
,
Karl-Erich Lindenschmidt
,
Zhongbo Yu
,
Yonghua Zhu
,
Mingwen Liu
, and
Tingxing Chen

Abstract

River ice changes due to climate change significantly impact river hydrology, economies, and societies. This study employed the CMIP6 data and a river ice model to predict global river ice changes in response to climate change. Results indicate significant declines in global river ice due to global warming. With each 1°C increase in surface air temperature (SAT) in the future, river ice extent of ice-affected rivers decrease by 2.11 percentage points, and ice duration shorten by 8.4 days. Under the SSP2-4.5 scenario, the long-term mean SAT is 1.2°C to 2.5°C higher than in the near-term. This leads to a 1.9 percentage points to 4.4 percentage points decrease in global river ice extent, a 6.8 to 15.1-day decrease in river ice duration, and ice-free rivers increasing by up to 4.02%. The SSP5-8.5 scenario predicts a warmer long-term mean SAT, leading to greater reductions in river ice. Geographically, river ice loss is most notable in North America, Europe, Siberia, and the Tibetan Plateau (TIB), particularly in peninsular, coastal, and mountainous regions due to the combined effects of initial temperatures and temperature increases. Overall, the E.Europe (EEU) shows the greatest loss of river ice on average. Monthly analyses show the most substantial decreases from October to June, indicating pronounced seasonal variability. This study provides valuable insights for addressing challenges related to river ice changes in high-latitude and high-elevation regions.

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Teryn J. Mueller
,
Christina M. Patricola
, and
Emily Bercos-Hickey

Abstract

El Niño–Southern Oscillation (ENSO) influences seasonal Atlantic tropical cyclone (TC) activity by impacting environmental conditions important for TC genesis. However, the influence of future climate change on the teleconnection between ENSO and Atlantic TCs is uncertain, as climate change is expected to impact both ENSO and the mean climate state. We used the Weather Research and Forecasting Model on a tropical channel domain to simulate 5-member ensembles of Atlantic TC seasons in historical and future climates under different ENSO conditions. Experiments were forced with idealized sea surface temperature configurations based on the Community Earth System Model (CESM) Large Ensemble representing: a monthly varying climatology, eastern Pacific El Niño, central Pacific El Niño, and La Niña. The historical simulations produced fewer Atlantic TCs during eastern Pacific El Niño compared to central Pacific El Niño, consistent with observations and other modeling studies. For each ENSO state, the future simulations produced a similar teleconnection with Atlantic TCs as in the historical simulations. Specifically, La Niña continues to enhance Atlantic TC activity, and El Niño continues to suppress Atlantic TCs, with greater suppression during eastern Pacific El Niño compared to central Pacific El Niño. In addition, we found a decrease in the Atlantic TC frequency in the future relative to historical regardless of ENSO state, which was associated with a future increase in northern tropical Atlantic vertical wind shear and a future decrease in the zonal tropical Pacific sea surface temperature (SST) gradient, corresponding to a more El Niño–like mean climate state. Our results indicate that ENSO will remain useful for seasonal Atlantic TC prediction in the future.

Open access
Qingye Min
and
Renhe Zhang

Abstract

The South Pacific Oscillation (SPO), characterized by a north–south dipole-like pattern of sea level pressure anomalies, is one of the key factors in understanding tropical–extratropical interactions in the South Pacific. We show that in boreal summer (June–August), the center of the northern lobe sea level pressure anomalies in the SPO is shifted to the east gradually after the 1960–70s. This study focuses on the relationship between the boreal summer SPO and following winter El Niño–Southern Oscillation (ENSO) diversity before and after the eastward shift of the SPO’s subtropical lobe. The eastward shift of the SPO’s subtropical lobe altered both the seasonal footprint mechanism and the trade wind charging mechanism associated with the SPO and thus profoundly influenced the ENSO diversity. It is revealed that when the northern lobe of the SPO shifts to the west of its average location, it tends to strengthen the eastern Pacific (EP) El Niño mainly via the seasonal footprint mechanism. But after the SPO’s northern lobe shifts to the east of its average location, it tends to promote the development of central Pacific (CP) El Niño mainly via the trade wind charging mechanism. The changes in the spatial structure of convection over the tropical Pacific and Indian Oceans may be one of the possible causes for the eastward shift in the SPO’s northern lobe. The findings in the present study have implications for a better understanding of ENSO diversity.

Significance Statement

Previous studies have demonstrated that the South Pacific Oscillation (SPO), as an important El Niño–Southern Oscillation (ENSO) precursor in the South Pacific, has the potential to provide an enhancement of the prediction of specific ENSO flavor. However, the historical variation in the SPO’s spatial structure and related changes in the relationship with the diversity of ENSO are still unclear. In this paper, we show that the subtropical lobe of the boreal summer (June–August) SPO is shifted to the east gradually after the 1960–70s. The changes in the spatial structure have also altered both the seasonal footprint mechanism and the trade wind charging mechanism which play important roles in the developmental processes of different types of ENSO. Our work highlights the importance of the interdecadal changes in the spatial structure of the SPO in understanding the relationship between the SPO and ENSO diversity.

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Ivan Mitevski
,
Rei Chemke
,
Clara Orbe
, and
Lorenzo M. Polvani

Abstract

In the Southern Hemisphere, Earth system models project an intensification of winter storm tracks by the end of the 21st century. Previous studies using idealized models showed that storm track intensity saturates with increasing temperatures, suggesting that the intensification of the winter storm tracks might not continue further with increasing greenhouse gases. Here, we examine the response of mid-latitude winter storm tracks in the Southern Hemisphere to increasing CO2 from two to eight times preindustrial concentrations in more realistic Earth System Models. We find that at high CO2 levels (beyond 4×CO2), winter storm tracks no longer exhibit an intensification across the extratropics. Instead, they shift poleward, weakening the storm tracks at lower mid-latitudes and strengthening at higher mid-latitudes. By analyzing the eddy kinetic energy (EKE) budget, the non-linear storm track response to an increase in CO2 levels in the lower mid-latitudes is found to stem from a scale-dependent conversion of eddy available potential energy to EKE. Specifically, in the lower mid-latitudes, this energy conversion acts to oppositely change the EKE of long and short scales at low CO2 levels, but, at high CO2 levels, it mostly reduces the EKE of shorter scales, resulting in a poleward shift of the storms. Furthermore, we identify a “tug of war” between the upper and lower temperature changes as the primary driver of the non-linear scale-dependent EKE response in the lower mid-latitudes. Our results suggest that in the highest emission scenarios beyond the 21st century, the storm tracks’ response may differ in magnitude and latitudinal distribution from projected changes by 2100.

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Kevin M. Grise
and
George Tselioudis

Abstract

Two common methods used to develop a process-level understanding of global cloud cover are 1) analyzing large-scale meteorological variables (cloud controlling factors) associated with cloud variability and 2) classifying cloud types using clustering algorithms applied to satellite data, such as the International Satellite Cloud Climatology Project (ISCCP) weather states. The cloud controlling factor method is advantageous to apply to climate models, as it does not rely on cloud parameterizations or the availability of satellite simulator output. The purpose of this study is to document the relationship between cloud controlling factors and the ISCCP weather states in the observational record, providing a benchmark for the application of cloud controlling factors to study individual cloud types in future studies.

Most ISCCP weather states are linked to distinct dynamical regimes characterized by unique combinations of six cloud controlling factors. These relationships are present in both the long-term mean climatology and in daily-to-monthly climate variability. For example, deep convective and midlatitude storm clouds dominate ascending regions. In descending regions, shallow cumulus is more frequent in regimes characterized by weak boundary-layer temperature inversions (EIS) and strong subsidence, and stratocumulus is more frequent in regimes with larger values of EIS, weaker subsidence, and relatively weak near-surface cold advection. Mid-level clouds are prominent in descending regions with strong cold advection. Overall, the results of this study suggest promise in using cloud controlling factors to identify dynamical regimes where individual cloud types are more or less likely and to understand the physical processes responsible for the transitions among them.

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Kelly Lombardo
and
Miranda Bitting

Abstract

The annual, seasonal, and diurnal spatiotemporal heavy convective precipitation patterns over a pan-European domain are analyzed in this study using a combination of datasets, including the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) (IMERG) precipitation rate product, E-OBS ground-based precipitation gauge data, European climatological gauge-adjusted radar precipitation dataset (EURADCLIM), Operational Programme for the Exchange of Weather Radar Information (OPERA) ground-based radar-derived precipitation rates, and fifth major global reanalysis produced by ECMWF (ERA5) total and convective precipitation products. Arrival Time Difference Network (ATDnet) lightning data are used in conjunction with IMERG and EURADCLIM precipitation rates, with an imposed threshold of 10 mm h−1 to classify precipitation as convective. Annually, the largest convective precipitation accumulations are over the European seas and coastlines. In summer, convective precipitation is more common over the European continent, though relatively large accumulations exist over the northern coastal waters and the southern seas, with a seasonal localized maximum over the northern Adriatic Sea. Activity shifts southward to the Mediterranean and its coastlines in autumn and winter, with maxima over the Ionian Sea, the eastern Adriatic Sea, and the adjacent coastline. Over the continent, 1%–10% of the total precipitation accumulated is classified as convective, increasing to 10%–40% over the surrounding seas. In contrast, 30%–50% of ERA5 precipitation accumulations over land is produced by the convective parameterization scheme and 40%–60% over the seas; however, only 1% of ERA5 convective precipitation accumulations are from rain rates exceeding 10 mm h−1. Regional analyses indicate that convective precipitation rates over the inland mountains follow diurnal heating, though little to no diurnal pattern exists in convective precipitation rates over the seas and coastal mountains.

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Yang Zhou
,
Binshuo Liu
,
Boyang Lei
,
Qifan Zhao
,
Shanlei Sun
, and
Haishan Chen

Abstract

The ERA5 reanalysis during cold months (November-March) of 1979-2020 was used for determining four cluster centroids through the k-means for classifying regional anomalies of the daily geopotential height at 500 hPa (H500) over northeastern China. EOF was used to reduce dimensionality. Four clusters were linked to the EOF patterns with clear meteorological meanings, which are associated with the evolutions of ridge and trough over northeastern China. Those systems relate to warm and cold advections at 850 hPa. In each H500 cluster, the advection is the major contributor leading to temperature changes at 850 hPa, which significantly relates to the changes and anomalies of daily minimum air temperature at 2m (T2min). Furthermore, the jet activities over Asia relate to more or less occurrence of specific H500 clusters in jet phases. This is because anomalous westerlies are generally in favor of positive anomalies of vorticity tendency at 500 hPa. For the reforecasts during 2004-2019 in the CMA S2S model, the hit rates above 50% for all the H500 clusters are within 9.5 days, which are in between those for the first two and the last two clusters. The correct prediction of H500 anomalies improves the T2min prediction up to 12 days, compared with 8 days for the incorrect one. The good prediction of the jet activities leads to more accurate prediction of H500 anomalies. Therefore, improvement of the model prediction of the jet activities and the H500 anomalies will lead to better prediction of winter weather near the ground over northeastern China.

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