Atmospheric Science Letters最新文献

The Mediterranean basin and Northern Africa are projected to be among the most vulnerable areas to climate change. This research documents, analyzes, and synthesizes the projected changes in precipitation P, evapotranspiration E, net water supply from the atmosphere to the surface P–E, and surface soil moisture over these regions as simulated by 17 global climate models from the sixth exercise of the Coupled Model Intercomparison Project (CMIP6) under two Shared Socioeconomic Pathways, SSP2-4.5, and SSP5-8.5. It also explores the sensitivity of the results to the chosen climate scenario and model resolution and assesses how the projections have evolved from the fifth exercise (CMIP5). Models project a statistically robust drying over the entire Mediterranean and coastal North Africa. Over the Northern Mediterranean sector, a significant precipitation decrease reaching −0.4 ∓ 0.1 mm $��{\mathrm{day}}^{�-�1�}�$ is projected during the 21st century under the SSP5-8.5 scenario. Conversely, a significant increase in precipitation of +0.05 to 0.3 ∓ 0.1 mm day⁻¹ is projected over South-Eastern Sahara under the same scenario. Evapotranspiration and soil moisture exhibit decreasing trends over the Mediterranean basin and an increase over the Sahara for both SSPs, with a notable acceleration from the 2020s. As a result, P-E is projected to decrease at a rate of about −0.3 mm day⁻¹ under the high-end scenario SSP5-8.5 over the Mediterranean whilst no significant changes are expected over the Sahara due to evapotranspiration compensation effects. CMIP6 and CMIP5 models project qualitatively similar patterns of changes but CMIP6 models exhibit more intense changes over the Mediterranean basin and South-Eastern Sahara, especially during winter.

This study classifies the spatial distribution of heavy precipitation in summer (June–August) from 1979 to 2021 in the three provinces of Northeast China (TPNC) into two patterns by using the self-organizing maps (SOM) neural network, and then quantitatively analyzes their moisture transport channels and sources using the Lagrangian model. The results show that the summer heavy precipitation in TPNC can be divided into the northern and southern patterns according to the distribution of the heavy precipitation. Both patterns of heavy precipitation are affected by the low-level vortex west of TPNC, but the strength and shape of the low vortex are different. The northern pattern is mainly influenced by the westerly flow in the vortex in the mid-high latitudes, which transports moisture from the upstream westerly region into TPNC. The southern pattern is mainly affected by the southerly jet stream southeast of TPNC, which conveys a large amount of moisture from the East Asian summer monsoon region into TPNC. In terms of the summer climatological mean, the northern pattern has a higher precipitation recycling rate, while the southern pattern has a lower recycling rate.

Based on the daily temperature observation data at 1992 stations in China, this study investigates the intra-seasonal variations and trends of extreme warm spells during 1981–2022. The results indicate that the nationwide extreme cold and warm spells have both increased rapidly since the 21st century. However, different from cold extremes which occur evenly in winter months, the nationwide super warm spells have distinct intra-seasonal differences, with more occurrences in February. The number of nationwide extreme warm spells has increased from 8 during 1981–2001 to 14 during 2002–2022, and the intensity has also increased obviously. Due to the spatial differences, the study area is divided into three regions to reveal the detailed features. It is found that the warm spell frequencies in most of China increase from December to February while decrease in northeastern China. Results demonstrate that extreme warm spells are concentrated in late winter in most regions (stations). The significant increasing trends are widespread from northern China to most parts of southern China, and the areas with increasing trend exceeding +0.6 day/decade are concentrated in North China and the middle reaches of the Yangtze River. Linear trends indicate that the significantly increasing trends in late winter contribute a major part to the variation in the whole winter in China.

This study investigated the structural and track change of cyclone Nepartak occurred over the western North Pacific in July 2021, a cyclone appeared at the surface level, using ERA5 data, focusing on the relationship with an upper-tropospheric cutoff low (COL). The COL was shown to dominate the structural change of Nepartak which developed as a subtropical cyclone with a hybrid structure. As the surface cyclone approached the COL, it was overlapped by the COL and became a cyclone with a two-storied structure, resulting in its abrupt track change. An analysis of the potential vorticity (PV) tendency showed that the movement of Nepartak toward the COL ceased because of the counter-balance of the horizontal/vertical PV advection with the PV anomaly generated by diabatic heating, whereas the surface cyclone northward motion was primarily due to the horizontal PV advection associated with the COL. Nepartak is a case in which changes in the structure and track of a cyclone are controlled by a COL.

In Europe, the increase in temperatures caused by climate change has been particularly fast in the cold season. Although the magnitude of this change is relatively well known, less research has been done on how the increase of temperatures is manifested in different large-scale weather types, called weather regimes. For example, one could expect that the weather patterns in which air is flowing from the rapidly-warming Arctic would have warmed faster than other weather patterns in recent decades. Here we show that such an asymmetric warming actually occurs in the four Euro-Atlantic weather regimes. In northern Europe, the weather regime which is typically associated with cold airmasses from the Arctic (NAO–) has warmed about 25% faster than the cold-season days on average, and about 60% faster than the regime where the air flows from the North Atlantic (NAO+). Consequently, the weather regime that on average brings the coldest weather is warming the fastest in a large part of northern Europe. In contrast, the weather regime that typically brings the warmest weather has warmed the slowest, especially in the continental Europe. Our results provide a new perspective on the reported decrease of sub-seasonal temperature variability.

Under certain approximations, the Clapeyron equation can be integrated to yield a simple exponential relation giving the saturation vapor pressure over a condensed phase as a function of temperature. The derivation usually assumes that the vapor behaves as an ideal gas with constant specific heat, and that the fluid also has constant specific heat. In addition, the specific fluid volume is neglected in comparison with the specific vapor volume. In this case, the Clapeyron equation is separable and readily integrable in closed form. It is shown here that this latter assumption is not required. A simple closed-form relation between saturation vapor pressure and temperature is derived which includes the condensed phase-specific volume. Two examples of the use of this result are presented.

Rossby wave packets (RWPs), are atmospheric perturbations linked to the occurrence of extreme weather events such as heatwaves, extratropical cyclone development and other equally destructive phenomena. Under certain circumstances, these packets can last from several days to 2–3 weeks in the atmosphere. Therefore, forecast models should be able to correctly predict their formation and development to enhance extreme weather events prediction from 10 to 30 days in advance. In this study, we assess whether the NCEP and IAP-CAS sub-seasonal forecast models can predict the evolution of observed RWPs that last more than 8 days (long-lived RWPs or LLRWPs) during southern hemisphere summer. Results show that the NCEP (IAP-CAS) model forecasts LLRWPs that appear eastward (westward) from the observed LLRWPs. Both models forecasted LLRWPs that rapidly lose energy after the 6^th–7^th lead day of simulation, which could limit LLRWPs prediction to the synoptic time scale. Additionally, both models better forecast LLRWPs when the packets manifest in the eastern Pacific. Southern Annular mode (SAM) and El Niño Southern-Oscillation (ENSO) do not seem to exert a large influence in the representation of LLRWPs. Nevertheless, during the best LLRWPs forecasts, the observed circulation anomalies signal the manifestation of negative SAM events. In contrast, both forecast models struggle at forecasting LLRWPs when a blocking situation develops to the South of Australia. Lastly, an inactive Madden Julian Oscillation (MJO) seems to favor the development of accurate LLRWPs forecasts, whereas during phases 3, 5 in the NCEP model and 3, 8 for IAP-CAS, the models struggle at forecasting LLRWPs.

Using ERA5 reanalysis data from March 2021 to February 2022 and the China Meteorological Administration Global Forecasting System (CMA-GFS) operational forecast dataset of 500 hPa geopotential height in the Northern Hemisphere in the same period, the multiscale features of forecast errors are analyzed. The results indicate that the anomaly correlation coefficient (ACC) of 500 hPa geopotential height and its multiscale components in the Northern Hemisphere keep decreasing with the extension of forecast lead time, and there are no seasonal differences in the evolution of the ACC. The effective forecast skills by season for the CMA-GFS model are above 6 days at multiscale, with the highest skills in winter and the planetary-scale components. In space, significant seasonal differences are observed in the locations of the extreme values of multiscale forecast errors for 500 hPa geopotential height, and the spatial distribution of forecast errors reflects the inadequate prediction of the intensity of large-scale trough and ridge systems at middle and high latitudes and the phase-shift prediction of small troughs and ridges at middle latitudes. Generally, the forecast errors of the original field and planetary-scale component show wavelike or banded distribution, and the synoptic-scale forecast errors are always distributed in latitudinal wavelike patterns alternating between positive and negative, without significant differences in the distribution of land, sea, and terrain. The first empirical orthogonal function modes of multiscale forecast errors almost retain their respective feature. In temporal, the spring, summer, and autumn time series all have quasi-biweekly positive and negative phase transitions within the monthly scale, and the significant phase transition in winter only occurs around January 1st. These results deepen the understanding of the distribution and possible causes of forecast errors of the CMA-GFS model and provide ideas for the improvement and revision of the model.

The representation of land–atmosphere coupling in forecast models can significantly impact weather prediction. A previous case study in Northern India incorporating both model and observational data identified atmospheric biases in a high-resolution forecast linked to soil moisture that impacted the representation of the monsoon trough, an important driver of regional rainfall. The aim of the current work is to understand whether this behavior is present in operational forecasts run by the India National Centre for Medium Range Weather Forecasting (NCMRWF). We utilize satellite observations and reanalysis to evaluate model fields in June, July, August, and September forecasts from 2020. Our analysis reveals systematic rapid growth in warm boundary layer biases during the daytime over North West India, which weaken overnight, consistent with excessive daytime surface sensible heat flux. The cumulative effect of these biases produces temperatures more than 4K warmer in 60-h forecasts. These effects are enhanced by dry surface conditions. The biases impact circulation in the forecasts, which have implications for regional rainfall. The spatial distribution of warm biases in the Indo-Gangetic Plain is remarkably consistent with the location of areas equipped for irrigation, a process that is not explicitly represented in the model. Our results provide compelling evidence that the development of an irrigation scheme within the model is needed to address the substantial forecast biases that we document.