Atmospheric Science Letters最新文献

The boreal winter of 2022/23 was notable as a third consecutive winter in which La Niña had an influence on the European weather. The GloSea6 seasonal forecast system predicted a blocked circulation pattern in the North Atlantic in early winter (December), and then a transition through mid-winter (January) into a more zonal pattern in late winter (February), consistent with the canonical La Niña teleconnection pattern seen previously. The seasonal forecast for the UK was an increased likelihood of near average temperatures, and drier- and calmer-than-average conditions. Both the predicted broad-scale circulation patterns and UK winter mean weather conditions verified well against observations, and we show that seasonal forecasts of the North Atlantic Oscillation (NAO) over the last 10 winters show similar skill to previously reported hindcasts. Throughout the winter, the Madden–Julian Oscillation (MJO) was particularly active. On three occasions, it exhibited strong phases 6 and 7. There was also a sudden stratospheric warming (SSW) that occurred on 16th February. This was followed by colder conditions and associated impacts similar to the canonical negative NAO response over the UK, although the main impact fell in March and so did not affect the winter (December–January–February) mean conditions.

The impact of model vertical resolutions on simulation of the Madden–Julian Oscillation (MJO) was investigated using five AMIP simulations by the Grid-point Atmospheric Model of IAP LASG, version 3 (GAMIL3) with different vertical layers. Results showed that higher vertical resolutions produce a stronger and superior eastward propagation, coupled circulation–convection relationship, and MJO strength, as well as other convectively coupled equatorial waves when compared to the lowest vertical resolution. The improvements may be related to a better description of the tropical circulation in the higher vertical resolutions and model top, albeit without the significant improvement of MJO convection and stratospheric quasi-biennial oscillation in all simulations. Among the four tested high resolutions, the simulations with higher vertical resolutions from the surface to about 850 hPa produced better eastward propagation and larger total explained variance of the MJO, indicating the importance of the lower troposphere in simulating the MJO.

Tropical free-tropospheric humidity plays a crucial role for the Earth's radiative balance and climate sensitivity. In addition to atmospheric humidity, stable water isotopes can provide important information about the hydrological cycle. We use the isotope- and water tagging-enabled version of the COSMO_iso model to determine isotopic fingerprints of diagnosed moisture pathways over the western tropical Atlantic (WTA). A convection-permitting, high-resolution (5 km) nudged simulation is performed for January–February 2020. During this period, the target region is characterized by alternating large-scale circulation regimes with different humidity and isotope signatures. Moist conditions in the middle troposphere (300–650 hPa) are associated with moisture transport from the south, east, southeast, as well as evaporation from the North Atlantic, while dry conditions correspond to extratropical transport from the north and west. To predict the contribution of different moisture sources, we used a statistical model based on the local specific humidity and temperature as predictors and obtained an R-squared (R²) of 0.52. Adding water isotopes improved the prediction (R² = 0.73), showing that isotopes provide unique information on moisture sources and transport patterns beyond conventional local observations.

Climate models exhibit biases in the mean state and in variability across different regions of the Earth. For example, atmosphere-only models have a poleward bias in summertime jet streams across the Northern Hemisphere (NH). This can result from many processes, including misrepresentation of Rossby waves that can propagate in different directions and thereby interact with jet streams. However, Rossby-wave biases can result from biased background state of the climate system as well. The propagation speed of Rossby waves depends on jet stream strength, thus a poleward displacement of the jet stream can hinder westward propagation of Rossby waves at higher latitudes and displace eastward propagating Rossby waves (downstream development). These biases then impact other regions resulting in biased atmospheric circulation across the NH. Indeed, in this study we confirm this via regional nudging experiments within the Norwegian Earth System Model. Namely, nudged horizontal winds over the North Pacific can improve Rossby wave statistics and thereby atmospheric circulation over Eurasia (i.e., upstream). However, nudging over the North Atlantic has little effect on boreal summer atmospheric circulation. This implies that improving biases over the North Pacific is crucial for a better representation of modelled boreal summer circulation over Eurasia.

The study exploits the air temperature and precipitation data from ERA5-Land reanalysis and E-OBS gridded observations that are freely available from the Copernicus Climate Change Service. The objectives of the study are to analyze the distribution of Köppen climate zones and to detect the changes in the presence and coverage of the specific climate types in Southeastern Europe. The results are shown separately for the following reference periods: 1961–1990, 1971–2000, 1981–2010, and 1991–2020. In the period 1961–1990, the most dominant climate type in Southeastern Europe was fully humid temperate climate with warm summer (Cfb), while fully humid continental climate with warm summer (Dfb) was also highly present there, together with fully humid temperate climate with hot summer (Cfa). In the period 1991–2020, the shift of Köppen climate zones appeared in such a way that the area with Dfb continental climate, that is often called snow or cold climate, is significantly reduced and this type is replaced with Cfb temperate climate. At the same time, Cfa climate type with hot summer is spread across wider area, mainly instead of Cfb with warm summer, now reaching almost the same percentage of coverage as Cfb type.

Cities are particularly vulnerable to surface water flooding. It is also well-known that they influence local rainfall themselves, which has important implications for climate change adaptation planning for cities. At km-scale resolution, convection-permitting climate models (CPCMs) better resolve cities and should better represent local urban temperature and rainfall modifications. However, using state-of-the-art pan-African CPCM simulations with the Met Office Unified Model (CP4), we show that for the city of Johannesburg, South Africa, this is not the case. A significant enhancement of rainfall occurs over the city compared with surrounding rural areas, which is not seen in available observations. We demonstrate this is associated with an overestimated urban heat island effect, which leads to additional triggering of rainfall. Urban signals in future rainfall change are small compared with changes in the wider surroundings, the latter of which we expect to be more reliable than in models with parameterized convection. This suggests that deficiencies in representation of urban processes are of secondary importance in terms of future percentage change in rainfall. We recommend urban planners apply relative changes in CP4 as an uplift to observations, where available, or treat absolute future rainfall as an upper estimate if used directly.

In current land surface models or satellite remote sensing retrievals, clear-sky surface albedo (α) is usually assumed to be symmetrical and relies only on the solar elevation angle (SEA). Based on 1-min high-resolution measurements of surface radiation fluxes, this study demonstrated that the diurnal variations of clear-sky surface albedo exhibited a significant asymmetrical pattern in both summer and winter seasons over a semi-arid grassland of the China's Loess Plateau. The results indicated that α values in the morning were generally larger than those in the afternoon at the same SEA, and diurnal asymmetry of surface albedo was distinctly prominent with SEA <40° in summer (before 9:30 a.m.) or SEA <20° in winter (before 10:00 am), and tended to diminish at midday. The averaged morning/afternoon albedo differences under sunny days were 0.05 (30.4%) and 0.09 (37.8%) in summer and winter seasons, respectively. Air relative humidity was positively correlated with the diurnal asymmetry of surface albedo, ascribed to probable formation of dew in the morning. Depression of the dew point was negatively linked to the morning/afternoon albedo differences, which was attributed to the strong scattering of incident sunlight by dewdrops could enhance the morning surface albedo. Such diurnal asymmetry of surface albedo should be included in the parameterization scheme of mesoscale and region-scale climate models in the semi-arid areas of China's Loess Plateau.

North China experienced an extreme precipitation event from July 29 to August 1, 2023 (i.e., the “23.7” event) causing severe floods, significant infrastructure damage and multiple fatalities. To enhance comprehension of the mechanism behind the extreme precipitation of the “23.7” event, water vapor transport paths and sources were determined, and water vapor contribution of each source was quantitatively evaluated based on Lagrangian methods. Results showed that the extreme precipitation of the “23.7” event was closely related to large-scale water vapor transport and convergence from low-latitude oceans. There were five main water vapor sources which corresponded to five transport pathways. Path 1 was derived from tropical West Pacific, containing the most trajectories (195), carrying the most water vapor (69.3%) and contributing the most to the extreme precipitation of the “23.7” event (45.7%). Path 2 was guided by the cross-equatorial flow through South China Sea, contributing to 10.1% of the precipitation. Path 3 originating from eastern tropical Indian Ocean and Path 4 from the west source near the Caspian Sea contributed less to the precipitation. Last but not the least, water vapor evaporation from eastern China contributed more than 30% to the extreme precipitation, making this region another important water vapor source.

Research on weather and climate extremes has become integral to climate science due to their increasing societal relevance and impacts in the context of anthropogenic climate change. In this perspective we examine recent changes and evolving paradigms in the study of extreme events, emphasizing the increasingly interdisciplinary nature of research and their societal implications. We discuss the importance of understanding the physical basis of extreme events and its linkages to climate impacts, highlighting the need for collaboration across multiple disciplines. Furthermore, we explore the challenge of big climate data analysis and the application of novel statistical methods, such as machine learning, in enhancing our understanding of extreme events. Additionally, we address the engagement with different stakeholder groups and the evolving landscape of climate services and private-sector involvement. We conclude with reflections on the risks and opportunities for early career researchers in navigating these interdisciplinary and societal demands, stressing the importance of meaningful scientific engagement, and removing barriers to inclusivity and collaboration in climate research.

This research introduces a novel index for the South Atlantic High Pressure (SAHP) system to enhance understanding of regional climate variability and change. Subtropical highs significantly influence regional climates, yet comprehensive indices to measure their behaviours are lacking. Utilizing ERA5 reanalysis data from 1940 to 2023, the proposed index estimates a weighted centroid of the area surrounding the maximum sea level pressure within a 3 hPa range. This method ensures robustness and flexibility in contiguous area estimation specific to subtropical high events. Results showed the index effectively reflects the position and intensity of the SAHP. The study reveals that latitudinal variability of the SAHP has a strong unimodal structure, whereas longitudinal variability exhibits a bimodal structure. Seasonal patterns of the index show noticeable changes, with winter (JJA) and spring (SON) months having relatively high index values compared to summer (DJF) and autumn (MAM) months, underscoring the intra-annual variability of the SAHP index. During ENSO events, the mean centroid position of the SAHP shifts significantly, moving westwards and polewards during El Niño and showing greater stability during La Niña. The index, with minimal computation requirements and flexibility, can be applied across diverse datasets, aiding in the assessment of future subtropical high changes.