Atmospheric Science Letters最新文献

The Siberian storm track is one of the drivers of the East Asian extreme weather events. Using the daily JRA-55 reanalysis data from 1980 to 2021, this study examines roles of eddy generation and jet characteristics in setting the annual cycle of Siberian storm track. It is found that there are two peaks of Siberian storm track intensity in boreal spring and autumn. The possible reason for such an annual cycle is explored by analyzing the maximum Eady growth rate over the Siberian region and jet characteristics. The stronger Siberian Eady growth rate in boreal spring and autumn, favoring a stronger baroclinic eddy generation, could contribute to the stronger intensity of Siberian storm tracks in these two seasons. Furthermore, the Siberian jet stream cores during boreal spring and autumn are located north of 50° N and resembles more an eddy-driven jet. While in winter, the subtropical jet stream enhanced and the eddy-driven jet becomes relatively weaker, which is less efficient to generate midlatitude baroclinic eddies. Besides, the eddy-driven jet can modulate the horizontal wave propagations from upstream, which also plays a role in amplifying the spring and autumn Siberian storm tracks.

In this study, the flood season in South China (SC) was divided into three stages: two first rainy seasons (FRSs) around the South China Sea summer monsoon onset and one second rainy season when Typhoon prevails, denoted as FRS1, FRS2, and SRS, respectively, and then we diagnosed the moist static energy (MSE) budget associated with the 10–30-day persistent heavy rainfall (PHR) over SC during these periods. The results indicate that there are great differences in the recharge of PHR-related MSE in different stages of the flood season in SC: The FRS1 MSE associated with PHR moves southeastward from midlatitude; the large MSE is maintained in SC during the FRS2; during the SRS, the MSE perturbation propagates from the tropical western North Pacific to SC. From the perspective of the local MSE budget in SC, meridional and zonal advection play a key role in the maximum MSE change in the FRS1; the FRS2 and SRS MSE tendency is mainly determined by zonal advection and meridional advection, respectively. In contrast, the 10–30-day propagating perturbation of MSE changes during both the FRS1 and FRS2 are mainly affected by the zonal advection, while the meridional circulation is dominant in the SRS. The cumulative contribution of external forcing (including radiation and surface heat fluxes) during the SRS to the propagation of PHR-related MSE perturbation can reach more than 30%, and the closer to the land, the stronger the external forcing. During the FRS (including FRS1 and FRS2), however, the external forcing contributes little, even negatively.

On 20–22 July 2012, a severe rainstorm occurred in the Sichuan basin of Southwest China and in the Beijing area of North China. This rainstorm was related to the activities of a Tibetan Plateau vortex (TPV) and Southwest China vortex (SWCV). By using radiosonde, satellite brightness temperature, and NCEP_FNL data, we investigated the helicity characteristics nearly the vortexes and their effect on convection. Results showed that (1) strong precipitation in the Sichuan basin was mainly related to the interaction between the TPV and SWCV, while strong precipitation in the Beijing area was related to the northward movement of a cyclonic vortex caused by a split in the SWCV. (2) During the occurrence of the rainstorm, four mesoscale convection systems (MCSs) were observed. Their vertical structure showed a positive vorticity–negative divergence in the lower levels, and negative vorticity–positive divergence in the upper levels, accompanied by vertical upward movement. This was an important factor in the development and maintenance of MCSs, as well as one of the mechanisms for producing heavy precipitation. On this basis, we further discussed the effect of helicity on the MCSs in the atmospheric environment with rotational characteristics. Results showed that the increase in negative water vapour helicity and storm-relative helicity were more likely to cause a strong development of MCSs.

As global surface temperatures continue to rise, both the duration and the intensity of heat waves across most land areas are expected to increase. The 2022 European summer broke a number of temperature records where a new record daily maximum temperature of 40.3°C was reached on 19th July making it the hottest July heat wave event in the UK. This paper aims to detect and analyse historical heat wave events, particularly prior to 1927 and compare these with recent events, particularly, 2022, which featured four summer heat wave events in the UK. This allows us to understand how noteworthy historical extremes are in comparison to those in recent decades, to place modern events into historical context, and to extend the sample of extreme events. Summer heat wave events have been detected between 1878 and 2022 from long station data in the UK. Heat wave extent, duration, and intensity have been analysed to compare past heat waves to the recent 2022 heat waves. For each of the summer months at least one of the top 10 most intense events between 1878 and 2022 occurred in the earliest third of the dataset (before 1927) emphasising the value of analysing early heat events. In all detected events, the anomalous UK heat was part of large-scale European extreme heat when examining 20th-century reanalysis data, associated with a high-pressure system. The 2022 July event resembles in pattern of warming and circulation some earlier events, for example, in 1925. While there is a clear trend in the monthly data and the overall frequency of anomalously hot days, heat wave activity on daily scales even in the period 1878 and 1926 is considerable and in some cases comparable to modern heat wave events in the UK. The most intense events detected led to societal impacts based on UK newspaper articles from the period including impacts on the agricultural sector, health impacts, and travel disruptions, broadly comparable to impacts from recent events.

Transport in numerical weather models is typically restricted to advection by the resolved wind field, and representation of other flow processes relies on forcing or coupling to other models. A discussion of non-advective transport in numerical weather models is presented and illustrated using two examples. These are the sea breeze and surface water flow. Simple models of these phenomena are represented in an adapted version of the Met Office Unified Model (UM) by means of modifying the existing cold-pool scheme in the UM. This approach of incorporating different transport processes in one framework could facilitate a better representation of the Earth system, by increasing interaction between meteorological, surface and subsurface processes.

The increasing complexity and impacts of fire seasons in the United States have prompted efforts to improve early warning systems for wildland fire management. Outlooks of potential fire activity at lead-times of several weeks can help in wildland fire resource allocation as well as complement short-term meteorological forecasts for ongoing fire events. Here, we describe an experimental system for developing downscaled ensemble-based subseasonal forecasts for the contiguous US using NCEP's operational Climate Forecast System version 2 model. These forecasts are used to calculate forecasted fire danger indices from the United States (US) National Fire Danger Rating System in addition to forecasts of evaporative demand. We further illustrate the skill of subseasonal forecasts on weekly timescales using hindcasts from 2011 to 2021. Results show that while forecast skill degrades with time, statistically significant week 3 correlative skill was found for 76% and 30% of the contiguous US for Energy Release Component and evaporative demand, respectively. These results highlight the potential value of experimental subseasonal forecasts in complementing existing information streams in weekly-to-monthly fire business decision making for suppression-based decisions and geographic reallocation of resources during the fire season, as well for proactive fire management actions outside of the core fire season.

Quantitative assessment of urbanization effect on surface air temperature (SAT) change provides crucial basis for formal detection and attribution analyses of climate change. However, debates about urbanization-related warming bias in documented regional SAT trend still persist, mainly due to different determination of rural stations. Here the urbanization effect on SAT change over the Beijing–Tianjin–Hebei region in China during 1980–2019 is estimated through three kinds of ways (i.e., comparisons between urban and rural stations [arithmetically station-averaged], urban-dominated and rural-dominated patches [patch-weighted mean], and realistic urban and rural areas [area-weighted mean]). The last method explicitly takes urban and rural land cover fractions into account when calculating urban/rural and regional mean SAT trends. Urbanization-induced warming in the annual mean SAT change of urban stations (areas) through the three ways are estimated as 0.159°C, 0.195°C, and 0.138°C per decade, respectively. And urbanization effect on regional averaged annual mean SAT calculated by patch-weighted and area-weighted methods are 0.113°C and 0.050°C per decade, respectively, which account for 33.8% and 14.8% of the total regional warming. The urbanization effect on observed SAT change estimated by considering realistic urban/rural land cover proportions is much lower than traditional station-unweighted way.

As a reaction to the expanding challenges associated with social susceptibility and their interconnection to diverse environmental threats, parametric insurance plays a key role as an innovation tool in the insurance sector to enhance social resilience to natural disasters and extreme climatic conditions, which can tremendously impact several economic sectors, including agriculture and as a result food security. In this context, this research investigates the association between rainfall Gini index and drought events in Western Europe. For this purpose, we acquired ERA5 data for daily precipitation for five locations from 1980 to 2022. Gini index (GI) values were calculated and analyzed for each location with the Mann–Kendall test at a 5% significance level. As expected, a minimal decreasing trend has been observed for daily precipitation, while an increasing trend was recorded for Gini index. In addition, data on the soil moisture index (SMI) and top drought events were extracted from the European Drought Observatory (EDO) to explore their potential connection with the Gini index over time and space. Although a moderately low to negligible correlation, ranging between −0.27 and 0.02, was found between SMI and GI, a qualitative comparison between major drought episodes and Gini index anomaly showed that similar spatiotemporal patterns are present across the region, particularly for extreme drought events in 1996–1997 and 2003. The current study elucidates the rainfall Gini index's efficiency as a drought indicator for qualitative analysis, yet more work must be conducted to quantitatively evaluate its association with drought magnitude.

Mesoscale convective systems (MCSs) in the tropics play an integral role in the water cycle, are associated with local hazardous weather conditions, and have significant remote impacts on the midlatitude jet stream. Although it is known that MCSs occur in relatively moist environments, it is unclear how far in advance favorable ingredients (lift, instability, and moisture) in the mesoscale environment precede MCS formation. In this study, an automated MCS tracking algorithm and global reanalyses are used to examine the pre-MCS environment for 3295 MCSs that occurred in the tropics in a 3-month period. Results showed that increased water vapor and mesoscale ascent implied by low-level convergence and upper-level divergence preceded MCS formation by up to 24 h. Regional variations in pre-MCS environment conditions were apparent and are discussed. Future work will study to what extent these moisture and wind anomalies can be used to predict MCS formation.

Numerical weather prediction centers increasingly make use of cloudy and rainy microwave radiances. Currently, the high microwave frequencies are simulated using simplified assumptions regarding the radiative properties of frozen hydrometeors. In particular, one single particle shape is often used for all precipitating frozen particles, all over the globe, and for all cloud types. In this paper, a multi-SSP (single scattering properties) approach for 1D Bayesian inversions is examined. Two experiments were set up: (1) one with three SSPs and (2) one with the previous SSPs plus one which leads to very cold brightness temperature distributions. For that purpose, we used observations from the GPM Microwave Imager radiometer over 2 months period and forecasts from the Météo-France convective scale AROME model. The results showed that mixtures of SSP are chosen by the inversion method for meteorological conditions with low scattering and that a single particle is chosen for those with high scattering to perform the inversions. Despite the fact that no specific weather scenes were found to be associated with a particular SSP the most efficient scattering particles can be favored for some of them.