Influence of Underlying Surface on Distribution of Hourly Heavy Rainfall over the Middle Yangtze River Valley

The variation of boundary layer circulation caused by the influence of complex underlying surface is one of the reasons why it is difficult to forecast hourly heavy rainfall (HHR) in the middle Yangtze River Valley (YRV). Based on the statistics of high-resolution observation data, it is found that the low resolution data underestimate the frequency of HHR in the mountain that are between the twain-lake basins in the middle YRV (TLB-YRV). The HHR frequency of mountainous area in the TLB-YRV is much higher than that of Dongting Lake on its left and is equivalent to the HHR frequency of Poyang Lake on its right. The hourly reanalysis data of ERA5 were used to study the variation of boundary layer circulation when HHR occurred. It can be found that the boundary layer circulation corresponding to different underlying surfaces changed under the influence of the weather system. Firstly, the strengthening of the weather system in the early morning resulted in the strengthening of the southwest low-level air flow, which intensified the uplift of the windward slope air flow on the west and south slopes of the mountainous areas in the TLB-YRV. As a result, the sunrise HHR gradually increases from the foot of the mountain. The high-frequency HHR period of sunrise occurs when the supergeostrophic effect is weakened, the low-level vorticity and frontal forcing are strengthened, and the water vapor flux convergence begins to weaken. Secondly, the high-frequency HHR period of the sunset is caused by stronger local uplift and more unstable atmospheric stratification, but the enhanced local uplift is caused by the coupling of the terrain forcing of the underlying surface and the enhanced northern subgeostrophic flow, which causes the HHR to start closer to the mountain top at sunset than at sunrise

A Thunderstorm Gale Forecast Method Based on the Objective Classification and Continuous Probability

Potential prediction is an important research content of thunderstorm gale weather forecast, and it is still a challenge because the environmental field of thunderstorm gale presents different characteristics under different weather conditions. Using the 12-year thunderstorm gale data of Hubei province in central China and the reanalysis data of National Center for Environmental Prediction (NCEP), this study analyzed the percentile distribution of environmental physical quantities of thunderstorm gale, and the continuous probability method was adopted to establish the probability forecast models of thunderstorm gale in four different types of weather situation, which are in the rear of trough type, in front of trough type, in the periphery of the western Pacific subtropical high type and easterly airflow type. Finally, probability prediction was realized by objective classification criterion in operation. The results show that the method based on objective classification and continuous probability can significantly improve the probability of thunderstorm gale detection, and also reduce the missing alarm rate of thunderstorm gale. Moreover, the quantitative test of 16 weather processes under four types of weather situations also shows that the continuous probability method has a higher probability of detection than the bisection method, and significantly reduces the missing alarm of extreme wind by the bisection method

Prediction of Suitable Distribution Area of Plateau pika (Ochotona curzoniae) in the Qinghai–Tibet Plateau under Shared Socioeconomic Pathways (SSPs)

The Qinghai–Tibet Plateau is one of the regions most strongly affected by climate change. The climate feedback of the distribution of plateau pika, a key species, is closely related to the trophic structure of the plateau ecosystem and the development of agriculture and animal husbandry on the plateau. In order to understand the impact of future climate change on the suitable distribution area of plateau pika, potential suitable distribution areas of Plateau pika were predicted using the MaxEnt model under three climate scenarios (SSP 1-2.6, SSP 2-4.5, and SSP 5-8.5) in the near term (2021–2040) and medium term (2041–2060). The predictions were found to be highly accurate with AUC values of 0.997 and 0.996 for the training and test sets. The main results are as follows: (1) The precipitation of the wettest month (BIO 16), mean diurnal range (BIO 2), slope, elevation, temperature seasonality (BIO 4), and annual mean temperature (BIO 1) were the main influencing factors. (2) In the historical period, the total suitable distribution area of Plateau pika in the Qinghai–Tibet Plateau accounted for 29.90% of the total area at approximately 74.74 × 104 km2, concentrated in the eastern and central areas of the Qinghai–Tibet Plateau. (3) The total suitable distribution area of pika exhibited an expansion trend under SSP 1-2.6 and SSP 2-4.5 in the near term (2021–2040), and the expansion area was concentrated in the eastern and central parts of the Qinghai–Tibet Plateau. The expansion area was the largest in Qinghai Province, followed by Sichuan Province and Tibet. In contrast, the suitable distribution area shrank in the Altun Mountains, Xinjiang. Under SSP 5-8.5 in the near term and all scenarios in the medium term (2041–2060), the suitable distribution area of Plateau pika decreased to different degrees. The shrinkage area was concentrated at the margin of the Qaidam Basin, central Tibet, and the Qilian Mountains in the east of Qinghai Province. (4) Plateau pika migrated toward the east or southeast on the Qinghai–Tibet Plateau under the three climate scenarios. Under most of the scenarios, the migration distance was longer in the medium term than in the near term

Prediction of Suitable Distribution Area of <i>Plateau pika</i> (<i>Ochotona curzoniae</i>) in the Qinghai–Tibet Plateau under Shared Socioeconomic Pathways (SSPs)

The Qinghai–Tibet Plateau is one of the regions most strongly affected by climate change. The climate feedback of the distribution of plateau pika, a key species, is closely related to the trophic structure of the plateau ecosystem and the development of agriculture and animal husbandry on the plateau. In order to understand the impact of future climate change on the suitable distribution area of plateau pika, potential suitable distribution areas of Plateau pika were predicted using the MaxEnt model under three climate scenarios (SSP 1-2.6, SSP 2-4.5, and SSP 5-8.5) in the near term (2021–2040) and medium term (2041–2060). The predictions were found to be highly accurate with AUC values of 0.997 and 0.996 for the training and test sets. The main results are as follows: (1) The precipitation of the wettest month (BIO 16), mean diurnal range (BIO 2), slope, elevation, temperature seasonality (BIO 4), and annual mean temperature (BIO 1) were the main influencing factors. (2) In the historical period, the total suitable distribution area of Plateau pika in the Qinghai–Tibet Plateau accounted for 29.90% of the total area at approximately 74.74 × 104 km2, concentrated in the eastern and central areas of the Qinghai–Tibet Plateau. (3) The total suitable distribution area of pika exhibited an expansion trend under SSP 1-2.6 and SSP 2-4.5 in the near term (2021–2040), and the expansion area was concentrated in the eastern and central parts of the Qinghai–Tibet Plateau. The expansion area was the largest in Qinghai Province, followed by Sichuan Province and Tibet. In contrast, the suitable distribution area shrank in the Altun Mountains, Xinjiang. Under SSP 5-8.5 in the near term and all scenarios in the medium term (2041–2060), the suitable distribution area of Plateau pika decreased to different degrees. The shrinkage area was concentrated at the margin of the Qaidam Basin, central Tibet, and the Qilian Mountains in the east of Qinghai Province. (4) Plateau pika migrated toward the east or southeast on the Qinghai–Tibet Plateau under the three climate scenarios. Under most of the scenarios, the migration distance was longer in the medium term than in the near term

Effect of Fermentation with Two Molds on Characteristics of Chicken Meat

In the present study, we investigated the characteristics of chicken meat fermented with Penicillium nalgiovense and Penicillium chrysogenum. Hardness and springiness gradually decreased, while gumminess gradually increased during fermentation. Fermentation with P. chrysogenum led to higher hardness and lower gumminess than fermentation with P. nalgiovense. Fermentation with two molds resulted in similar microstructure, such as granule formation and fractured myofibril. The highest percentage of secondary structure was ɑ-helix, and tyrosine residues were buried after fermentation. P. nalgiovense-fermented samples contained more bound water, lower relative content of alkanes, and higher relative content of aldehydes than P. chrysogenum-fermented samples