Influence of Irregular Coastlines on a Tornadic Mesovortex in the Pearl River Delta during the Monsoon Season. Part I: Pre-storm Environment and Storm Evolution

The Pearl River Delta(PRD),a tornado hotspot,forms a distinct trumpet-shaped coastline that concaves toward the South China Sea.During the summer monsoon season,low-level southwesterlies over the PRD’s sea surface tend to be turned toward the west coast,constituting a convergent wind field along with the landward-side southwesterlies,which influences regional convective weather.This two-part study explores the roles of this unique land–sea contrast of the trumpet-shaped coastline in the formation of a tornadic mesovortex within monsoonal flows in this region.Part I primarily presents observational analyses of pre-storm environments and storm evolutions.The rotating storm developed in a lowshear environment(not ideal for a supercell)under the interactions of three air masses under the influence of the land–sea contrast,monsoon,and storm cold outflows.This intersection zone(or“triple point”)is typically characterized by local enhancements of ambient vertical vorticity and convergence.Based on a rapid-scan X-band phased-array radar,finger-like echoes were recognized shortly after the gust front intruded on the triple point.Developed over the triple point,they rapidly wrapped up with a well-defined low-level mesovortex.It is thus presumed that the triple point may have played roles in the mesovortex genesis,which will be demonstrated in Part II with multiple sensitivity numerical simulations.The findings also suggest that when storms pass over the boundary intersection zone in the PRD,the expected possibility of a rotating storm occurring is relatively high,even in a low-shear environment.Improved knowledge of such environments provides additional guidance to assess the regional tornado risk.

Assessment of the Spatio-Temporal Trends of Annual Extreme Temperature Indices over Tanzania during the Period of 1982-2022

Extreme weather and climatic phenomena, such as heatwaves, cold waves, floods and droughts, are expected to become more common and have a significant impact on ecosystems, biodiversity, and society. Devastating disasters are mostly caused by record-breaking extreme events, which are becoming more frequent throughout the world, including Tanzania. A clear global signal of an increase in warm days and nights and a decrease in cold days and nights has been observed. The present study assessed the trends of annual extreme temperature indices during the period of 1982 to 2022 from 29 meteorological stations in which the daily minimum and maximum data were obtained from NASA/POWER. The Mann-Kendall and Sen slope estimator were employed for trend analysis calculation over the study area. The analyzed data have indicated for the most parts, the country has an increase in warm days and nights, extreme warm days and nights and a decrease in cold days and nights, extreme cold days and nights. It has been disclosed that the number of warm nights and days is on the rise, with the number of warm nights trending significantly faster than the number of warm days. The percentile-based extreme temperature indices exhibited more noticeable changes than the absolute extreme temperature indices. Specifically, 66% and 97% of stations demonstrated positive increasing trends in warm days (TX90p) and nights (TN90p), respectively. Conversely, the cold indices demonstrated 41% and 97% negative decreasing trends in TX10p and TN10p, respectively. The results are seemingly consistent with the observed temperature extreme trends in various parts of the world as indicated in IPCC reports.

Assessing the Relationship between October-November-December Rainfall and Indian Ocean Dipole in Recent Decades over Tanzania Following the 2011 Abrupt Change

The present study explored how the Indian Ocean Dipole (IOD) influences October-November-December (OND) rainfall over Tanzania in recent decade following the 2011 abrupt change. The study spans 50 years, from 1973 to 2022. Notable abrupt changes were observed in 1976 and 2011, leading us to divide our study into two periods: 1976-2010 and 2011-2022, allowing for a close investigation into the existing relationship between OND IOD and OND rainfall and their associated large-scale atmospheric circulations. It was found that the relationship between OND IOD and OND rainfall strengthened, with the correlation changed from +0.73 during 1976-2010 to +0.81 during 2011-2022. Further investigation revealed that, during 1976-2010, areas that received above- normal rainfall during positive IOD experienced below-normal during 2011- 2022 and vice versa. The same pattern relationship was observed for negative IOD. Spatial analysis demonstrates that the percentage departure of rainfall across the region mirrors the standardized rainfall anomalies. The study highlights that the changing relationship between OND IOD and OND rainfall corresponds to the east-west shift of Walker circulation, as well as the north-south shift of Hadley circulation. Analysis of sea surface temperature (SST) indicates that both positive and negative IOD events strengthened during 2011-2022 compared to 1976-2010. Close monitoring of this relationship across different timescales could be useful for updating OND rainfall seasonal forecasts in Tanzania, serving as a tool for reducing socio-economic impacts.

Analysis of Changes of Extreme Temperature during June to August Season over Tanzania

Natural and human systems are exposed and vulnerable to climate extremes, which contributes to the repercussions of climate variability and the probability of disasters. The impacts of both natural and human-caused climate variability are reflected in the reported changes in climate extremes. Particularly at the local community levels in the majority of the regions, there is currently a dearth of information regarding the distribution, dynamics, and trends of excessive temperatures among the majority of Tanzanians. Over the years 1982-2022, this study examined trends in Tanzania’s extreme temperature over the June to August season. Based on the distinction between absolute and percentile extreme temperatures, a total of eight ETCCDI climate indices were chosen. Mann-Kendall test was used to assess the presence of trends in extreme climatic indices and the Sen’s Slope was applied to compute the extent of the trends in temperature extremes. The study showed that in most regions, there is significant increase of warm days and nights while the significant decrease of cold days and nights was evident to most areas. Moreover, nighttime warming surpasses daytime warming in the study area. The study suggests that anthropogenic influences may contribute to the warming trend observed in extreme daily minimum and maximum temperatures globally, with Tanzania potentially affected, as indicated in the current research. The overall results of this study reflect patterns observed in various regions worldwide, where warm days and nights are on the rise while cold days and nights are diminishing.

Regional Integrated Meteorological Forecasting and Warning Model for Geological Hazards Based on Logistic Regression

Information model is adopted to integrate factors of various geosciences to estimate the susceptibility of geological hazards. Further combining the dynamic rainfall observations, Logistic regression is used for modeling the probabilities of geological hazard occurrences, upon which hierarchical warnings for rainfall-induced geological hazards are produced. The forecasting and warning model takes numerical precipitation forecasts on grid points as its dynamic input, forecasts the probabilities of geological hazard occurrences on the same grid, and translates the results into likelihoods in the form of a 5-level hierarchy. Validation of the model with observational data for the year 2004 shows that 80% of the geological hazards of the year have been identified as ＂likely enough to release warning messages＂. The model can satisfy the requirements of an operational warning system, thus is an effective way to improve the meteorological warnings for geological hazards.

Polarimetric Meteorological Satellite Data Processing Software Classification Based on Principal Component Analysis and Improved K-Means Algorithm

With the increasing variety of application software of meteorological satellite ground system, how to provide reasonable hardware resources and improve the efficiency of software is paid more and more attention. In this paper, a set of software classification method based on software operating characteristics is proposed. The method uses software run-time resource consumption to describe the software running characteristics. Firstly, principal component analysis (PCA) is used to reduce the dimension of software running feature data and to interpret software characteristic information. Then the modified K-means algorithm was used to classify the meteorological data processing software. Finally, it combined with the results of principal component analysis to explain the significance of various types of integrated software operating characteristics. And it is used as the basis for optimizing the allocation of software hardware resources and improving the efficiency of software operation.

Editorial: Special issue on meteorological instruments

The earth we live in is a wonderful and complicated system,meteorology is a science of researching the earth and serving the public,so every country in the world is putting its attention on meteorological observation,and World Meteorological Organization always putting its emphasis on weather,climate

Development of Solar Spectroradiometer for Meteorological Observation

A newgeneration of solar spectroradiometer has been developed by CUST/JRSI to improve solarirradiance observation data under hyperspectral resolution. It is based on the grating spectroradiometer with a back-thinned CCD linear image sensor and is operated in a hermetically sealed enclosure. The solar spectroradiometer is designed to measure the solar spectral irradiance from300 nm to 1100 nm wavelength range with the spectral resolution of 2 nm( the full width at half maximum). The optical bench is optimized to minimize stray light. The Peltier device is used to stabilize the temperature of CCD sensor to 25℃,while the change of temperature of CCD sensor is controlled to ±1℃ by the dedicated Peltier driver and control circuit.

Hydro-meteorological characteristics of Chitral River basin at the peak of the Hindukush range

This paper presents the impact of mean maximum temperature on Chitral river basin situated at Chitral district and high altitude (>6000 m) peaks of the Hindukush range under changing climate in Pakistan. The analysis of Chitral River as one of the tributary of Kabul River—the second largest river of Pakistan—revealed that change in temperature has a profound influence on the snow/glacial melt in comparison to the mean monthly rainfall. This is because the studied river is faded by the snow and glacial melt and receives a lot of snowfall from winter (DecFeb) to pre-monsoon (April-May). In monsoon period (Jul-Sep), 30% of the time the discharge rate remains above the mean while 60% of the time the discharge is less than the mean in the pre-monsoon (April-May) period. It means that 10% of the time the discharge is in reach of 300% to 900% of the mean flow, showing a rise in water yield and river discharge rate due to increase in mean monthly maximum temperature. Due to this significant increase (p < 0.05), the glaciers start melting faster and disappear in early summer, hence, reducing their residency period to convert into ice. This shows the signals of changing climate transfer into hydrological changes in Pakistan. Our findings are important for agriculture, hydropower and water management sectors for future planning especially in dry season for sustainable food security and for operation of ydrological installations in the country.

Evaluation of Seasonal Changes in Temperature and Precipitation for Iran Five Provincial Centres during 1960-2017

Climate change is one of the key challenges of our era and it is a threat to sustainable development. Global warming has many meteorological consequences including rising air temperatures across the world. Undoubtedly, human activity has been one of the key factors to global warming followed by increased greenhouse gas emissions which will exacerbate changes in the Earth’s climate variables. So, any research work related to the climate around the world including Iran due to climate change may cause to better understand the cause and effect and make a better adaptation. This study investigates the regional warming in five meteorological stations in central provinces of Iran, based on seasonal changes in precipitation and temperatures over the period of 1960-2017 (study period). The seasonal drought severity based on Palmer index during 1960-2005 was used to monitor the drought intensity in the study areas which are in drought risk situation. The classification of drought severity using Palmer index shows the severe drought intensity in Arak, Qom, Semnan, Tehran and Isfahan respectively in all four seasons, especially during fall and summer. The slight changes in the coefficients of seasonal maximum, minimum and mean temperatures have been resulted. According to these results, the highest maximum (minimum) temperature rise has been calculated for Qom (Tehran) station during spring and winter (fall) seasons ~0.44°C (~0.67°C) in a decade during 1960-2017. However, the highest decrease in precipitation over Arak station has been calculated ~13.8 mm in a decade in winter during study period.

PM_(10)Observed at a Meteorological Station in Beijing:Historical Trend and Implications

Inhalable particles(PM_(10)),with aerodynamic equivalent diameters that are generally 10 micrometers or smaller,are basic pollutants in many areas,especially in northern China,and thus the pollution from PM_(10)inhalable particulate matter is a growing concern for public health.Independent long-term observations are necessary to evaluate the efficacy of PM_(10)reduction actions.Variations in the PM_(10)concentration from 2006 to 2017 at an observation station(NJ)in Beijing were recorded and analyzed.The average value±1 standard deviation of daily mean PM_(10)concentrations was 138.8±96.1μg m^(-3)for 1307 days(accounting for 34.7%of the total days),showing PM_(10)concentration exceeding the National Ambient Air Quality Standard(NAAQS)24-h average of 150μg m^(-3).Particulate concentration depended upon various meteorological conditions as also observed in this work:at low wind speed(<4 m s^(-1)),the concentrations of PM_(10) revealed a downward trend with-19μg m^(-3)per unit of wind speed,but when wind speed rose(>4 m s^(-1)),the values increased by 49μg m^(-3)per unit of wind speed.In Beijing,air masses from northwest China,especially from the Gobi Desert and other desert areas,had net contributions to long-range transport of natural dust,enhancing the PM_(10)concentrations by up to 29%.Overall,PM_(10)mass concentration showed a significant downward trend with-8.0μg/m3/yr from 2006 to 2017.Although with higher fluctuations in recorded data,similar downward trends derived from the government released data were also found at the nearby districts.The result delivered a proof of efficacy for the reduction actions recently adopted to limit PM_(10)concentrations in Beijing.Very significant difference of diurnal changes in PM_(10) concentrations was also found in two periods of 2006-2011 and 2012-2017,which might be due to the different contributions of fugitive dust.Nevertheless,further efforts,especially on controlling fugitive dust,should be planned as the PM_(10) concentration annual mean value(94μg m^(-3))in 2017 still exceeded the NAAQS standard.The results showed that there is still a long way to go to reduce PM_(10)in Beijing.

Study on the benef its of meteorological services for industries in China

It is very important to analyze and evaluate the benefi ts of meteorological services for policy decision-making and taking precautions against meteorological disasters.In this study,a model for evaluating the benef its of meteorological services for industries is constructed,with the combining method of dose-response and contingency assessment,and also absorbing other countries' experience.According to this model,and referring to the practical value of the contribution of meteorological services to typical enterprises,experts calculated the benef its of meteo-rological services for every industry.By applying this model,and taking the evaluation framework of "to determine which industries are meteorology-sensitive" - "to evaluate the benefi ts of meteorological services" - "to get the total benef its of meteorological service",evaluation and analysis on the total benef its of meteorological services was done with case study.According to this study,the annual mean benef its of meteorological services are known as no less than 279.3 billion yuan(cost excluded) in present national economical environment.

Analysis of Essential Meteorological Elements Surrounding Typhoon Sinlaku by Unmanned Aerial Vehicle

In this paper, a successful flight with an unmanned aerial vehicle (UAV) surrounded Typhoon Sinlaku on 15 Sept., 2008 and the preliminary analysis of all the collected data during the observation period has been presented. It is the first time to adopt surrounding method to observe typhoon in mainland of China. During the 3 h field campaign, the flight altitude is about 500 m to observe the essential meteorological elements in boundary layer of typhoon. The average temperature is 22.57&#176C and ranged from 21.50&#176C to 25.80&#176C, while about the relative humidity, the maximum is 100%, the minimum is 80.60% and the average is 97.98%. As for the wind, the average wind speed is 19.68 m/s and the maximum is 30.03 m/s. The typhoon center is a warm structure, the closer to the center, the higher the temperature is and the lower the wind speed is. In conclusion, the mini-UAV has the capability to observe the boundary layer of typhoon.

Super Typhoon Hinnamnor(2022)with a Record-Breaking Lifespan over the Western North Pacific

Super Typhoon Hinnamnor(2022)was a rare and unique western North Pacific typhoon,and throughout its lifespan,it exhibited all of the major features that pose current challenges in typhoon research.Specifically,during different stages of its lifespan,it experienced a sudden change of track,underwent rapid intensification,interacted and merged with another vortex,expanded in size,underwent rapid weakening,produced a strong cold wake,exhibited eyewall replacement,and underwent extratropical transition.Therefore,a timely identification and review of these features of Hinnamnor(2022),as reported in this article,will help update and enrich the case sets for each of these scientific issues and provide a background for more in-depth mechanistic studies of typhoon track,intensity,and structural changes in the future.We also believe that Hinnamnor(2022)can serve as an excellent benchmark to quickly evaluate the overall performance of different numerical models in predicting typhoon’s track,intensity,and structural changes.

Statistical Downscaling Retrieval of Land Surface Temperature in an Area with Complex Landforms in the Eastern Qinling Mountains of China Based on Sentinel-2/3 Satellite Data

The study of land surface temperature(LST)is of great significance for ecosystem monitoring and ecological environmental protection in the Qinling Mountains of China.In view of the contradicting spatial and temporal resolutions in extracting LST from satellite remote sensing(RS)data,the areas with complex landforms of the Eastern Qinling Mountains were selected as the research targets to establish the correlation between the normalized difference vegetation index(NDVI)and LST.Detailed information on the surface features and temporal changes in the land surface was provided by Sentinel-2 and Sentinel-3,respectively.Based on the statistically downscaling method,the spatial scale could be decreased from 1000 m to 10 m,and LST with a Sentinel-3 temporal resolution and a 10 m spatial resolution could be retrieved.Comparing the 1 km resolution Sentinel-3 LST with the downscaling results,the 10 m LST downscaling data could accurately reflect the spatial distribution of the thermal characteristics of the original LST image.Moreover,the surface temperature data with a 10 m high spatial resolution had clear texture and obvious geomorphic features that could depict the detailed information of the ground features.The results showed that the average error was 5 K on April 16,2019 and 2.6 K on July 15,2019.The smaller error values indicated the higher vegetation coverage of summer downscaling result with the highest level on July 15.

Observational and Mechanistic Analysis of a Nighttime Warm-Sector Heavy Rainfall Event Within the Subtropical High over the Southeastern Coast of China

In August 2021,a warm-sector heavy rainfall event under the control of the western Pacific subtropical high occurred over the southeastern coast of China.Induced by a linearly shaped mesoscale convective system(MCS),this heavy rainfall event was characterized by localized heavy rainfall,high cumulative rainfall,and extreme rainfall intensity.Using various observational data,this study first analyzed the precipitation features and radar reflectivity evolution.It then examined the role of environmental conditions and the relationship between the ambient wind field and convective initiation(CI).Furthermore,the dynamic lifting mechanism within the organization of the MCS was revealed by em-ploying multi-Doppler radar retrieval methods.Results demonstrated that the linearly shaped MCS,developed under the influence of the subtropical high,was the primary cause of the extreme rainfall event.High temperatures and humidity,coupled with the convergence of low-level southerly winds,established the environmental conditions for MCS develop-ment.The superposition of the convergence zone generated by the southerly winds in the boundary layer(925-1000 hPa)and the divergence zone in the lower layer(700-925 hPa)supplied dynamic lifting conditions for CI.Additionally,a long-term shear line(southerly southwesterly)offered favorable conditions for the organization of the linearly shaped MCS.The combined effects of strengthening low-level southerly winds and secondary circulation in mid-upper levels were influential factors in the development and maintenance of the linearly shaped MCS.

Impacts of Increasing Model Resolutions and Shortening Forecast Lead Times on QPFs in South China During the Rainy Season

This study investigated the impacts of increasing model resolutions and shortening forecast lead times on the quantitative precipitation forecast(QPF)for heavy-rainfall events over south China during the rainy seasons in 2013-2020.The control experiment,where the analysis-forecast cycles run with model resolutions of about 3 km,was compared to a lower-resolution experiment with model resolutions of about 9 km,and a longer-term experiment activated 12 hours earlier.Rainfall forecasting in the presummer rainy season was significantly improved by improving model resolutions,with more improvements in cases with stronger synoptic-scale forcings.This is partially attributed to the improved initial conditions(ICs)and subsequent forecasts for low-level jets(LLJs).Forecasts of heavy rainfall induced by landfalling tropical cyclones(TCs)benefited from increasing model resolutions in the first 6 hours.Forecast improvements in rainfall due to shortening forecast lead times were more significant at earlier(1-6 h)and later(7-12 h)lead times for cases with stronger and weaker synoptic-scale forcings,respectively,due to the area-and case-dependent improvements in ICs for nonprecipitation variables.Specifically,significant improvements mainly presented over the northern South China Sea for low-level onshore wind of weak-forcing cases but over south China for LLJs of strong-forcing cases during the presummer rainy season,and over south China for all the nonprecipitation variables above the surface during the TC season.However,some disadvantages of higher-resolution and shorter-term forecasts in QPFs highlight the importance of developing ensemble forecasting with proper IC perturbations,which include the complementary advantages of lower-resolution and longer-term forecasts.

Climatic Indices’ Analysis on Extreme Precipitation for Tanzania Synoptic Stations

Like other countries in East Africa, Tanzania has been affected by extreme precipitation incidences both socially and economically. Determining the trend and variability features of extreme precipitation in the country is crucial. This study used data from 28 meteorological stations for 1981-2020 period to give an annual and seasonal analysis of the patterns of 10 ETCCDI’s extreme precipitation indices over the regions. At annual scale, the results showed that increasing trends had high frequency percentage than the decreasing ones, collecting about 76% in total. The decreasing trend was approximately 24%, and most of the stations with increasing percentage in trend are concentrated in Northern coast, Central, West, North-eastern highlands and Lake Victoria Basin. Most of the stations depicted negative trend are concentrated over Southern region. This highlights that extreme precipitation events have increased over the country for the period 1981-2020. At seasonal scale, during October to December (OND);the patterns of extreme precipitation climatic indices except R99p, showed positive significant increasing trend over Lake Victoria Basin and some Western parts of the country. In general, spatial patterns indicate decrease of precipitation over most parts of the country during OND. The seasonal average time series depicted non-significant positive trend during March to April (MAM) season, except for Consecutive Wet Days (CWD) which showed non-significant decreasing trend. Over the highest mountain in Africa, Kilimanjaro;the study has revealed significant decrease in Annual total-wet Precipitation (PRCPTOT), the number of heavy (very heavy) days of precipitation R10 mm (R20 mm) and Consecutive Wet Days (CWD) during MAM season. While the maximum one-day precipitation amount (RX1 day) was observed to decrease significantly over the Mountain during OND season. The result is very important in risk assessment and preparedness perspective in planning climate change mitigation and adaptations for different sectors like Tourism, Agriculture, Water and Energy.

Evaluation of the Global and Regional Assimilation and Prediction System for Predicting Sea Fog over the South China Sea

In the South China Sea, sea fog brings severe disasters every year, but forecasters have yet to implement an effective seafog forecast. To address this issue, we test a liquid-water-content-only(LWC-only) operational sea-fog prediction method based on a regional mesoscale numerical model with a horizontal resolution of about 3 km, the Global and Regional Assimilation and Prediction System(GRAPES), hereafter GRAPES-3 km. GRAPES-3 km models the LWC over the sea, from which we infer the visibility that is then used to identify fog. We test the GRAPES-3 km here against measurements in 2016 and 2017 from coastal-station observations, as well as from buoy data, data from the Integrated Observation Platform for Marine Meteorology, and retrieved fog and cloud patterns from Himawari-8 satellite data. For two cases that we examine in detail, the forecast region of sea fog overlaps well with the multi-observational data within 72 h. Considering forecasting for0–24 h, GRAPES-3 km has a 2-year-average equitable threat score(ETS) of 0.20 and a Heidke skill score(HSS) of 0.335,which is about 5.6%(ETS) and 6.4%(HSS) better than our previous method(GRAPES-MOS). Moreover, the stations near the particularly foggy region around the Leizhou Peninsula have relatively high forecast scores compared to other sea areas.Overall, the results show that GRAPES-3 km can roughly predict the formation, evolution, and dissipation of sea fog on the southern China coast.

Warm-Season Diurnal Variations of Total, Stratiform, Convective, and Extreme Hourly Precipitation over Central and Eastern China

Diurnal variations in amount, frequency and intensity of warm-season hourly precipitation(HP) at seven levels, which are defined as HP 0.1, 0.5, 1, 5, 10, 20 and 50 mm, are revealed based on no less than 30 years of hourly rain-gauge observations at national stations over central and eastern China(CEC). This study investigates the variations, relationships, differences and similarities of total, stratiform, convective and extreme HP over the entire CEC and various subregions. Results indicate that the variations in the amount and frequency of HP at the seven levels over the entire CEC all display a bimodal feature. For various regions, the variations of total HP mostly feature two peaks, while convective HP mainly occurs in the late afternoon and determines the diurnal variation of total HP intensity. On the basis of the primary peak time periods of HP frequency at all levels over different subregions, the variations can be classified into three main categories: late-afternoon primary peak, nocturnal primary peak, and time-shifting primary peak. However, the variations over some coastal regions like the Liaodong Peninsula, the Shandong Peninsula, and the coastal regions of Guangdong, distinctly differ from those over their corresponding larger regions. Overall, the normalized diurnal variation amplitude of amount and frequency increases with the increasing HP intensity; convective precipitation can be represented by HP 10 mm; and the intensity of HP 50 mm is slightly larger during the nighttime than during the daytime over the entire CEC. In northern China, diurnal variation in HP 5 mm can represent well that in convective precipitation.