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.

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.

Observing the air-sea turbulent heat flux on the trajectory of tropical storm Danas

Tropical cyclones constitute a major risk for coastal communities.To assess their damage potential,accurate predictions of their intensification are needed,which requires a detailed understanding of the evolution of turbulent heat flux(THF).By combining multiple buoy observations along the south north storm track,we investigated the THF anomalies associated with tropical storm Danas(2019)in the East China Sea(ECS)during its complete life cycle from the intensification stage to the mature stage and finally to its dissipation on land.The storm passage is characterized by strong winds of 10-20 m/s and a sea level pressure below 1000 hPa,resulting in a substantial enhancement of THF.Latent heat(LH)fluxes are most strongly affected by wind speed,with a gradually increasing contribution of humidity along the trajectory.The relative contributions of wind speed and temperature anomalies to sensible heat(SH)depend on the stability of the boundary layer.Under stable conditions,SH variations are driven by wind speed,while under near-neutral conditions,SH variations are driven by temperature.A comparison of the observed THF and associated variables with outputs from the ERA 5 and MERRA 2 reanalysis products reveals that the reanalysis products can reproduce the basic evolution and composition of the observed THF.However,under extreme weather conditions,temperature and humidity variations are poorly captured by ERA 5 and MERRA 2,leading to large LH and SH errors.The differences in the observed and reproduced LH and SH during the passage of Danas amount to 26.1 and 6.6 W/m^(2) for ERA 5,respectively,and to 39.4 and 12.5 W/m^(2) for MERRA 2,respectively.These results demonstrate the need to improve the representation of tropical cyclones in reanalysis products to better predict their intensification process and reduce their damage.

Regional Climate Damage Quantification and Its Impacts on Future Emission Pathways Using the RICE Model

This study quantified the regional damages resulting from temperature and sea level changes using the Regional Integrated of Climate and Economy(RICE)model,as well as the effects of enabling and disabling the climate impact module on future emission pathways.Results highlight varied damages depending on regional economic development and locations.Specifically,China and Africa could suffer the most serious comprehensive damages caused by temperature change and sea level rise,followed by India,other developing Asian countries(OthAsia),and other high-income countries(OHI).The comprehensive damage fractions for China and Africa are projected to be 15.1%and 12.5%of gross domestic product(GDP)in 2195,with corresponding cumulative damages of 124.0 trillion and 87.3 trillion United States dollars(USD)from 2005 to 2195,respectively.Meanwhile,the comprehensive damage fractions in Japan,Eurasia,and Russia are smaller and projected to be lower than 5.6%of GDP in 2195,with cumulative damages of 6.8 trillion,4.2 trillion,and 3.3 trillion USD,respectively.Additionally,coastal regions like Africa,the European Union(EU),and OHI show comparable damages for sea level rise and temperature change.In China,however,sea level-induced damages are projected to exceed those from temperature changes.Moreover,this study indicates that switching the damage modules on or off affects the regional and global emission trajectories,but the magnitude is relatively small.By 2195,global emissions under the experiments with all of the damage modules switched off,only the sea level damage module switched on,and only the temperature damage module switched on,were 3.5%,2.3%and 1.2%higher than those with all of the damage modules switched on,respectively.

Assessment of ECMWF’s Precipitation Forecasting Performance for China from 2017 to 2022

This study used the China Meteorological Administration(CMA)three-source fusion gridded precipitation analysis data as a reference to evaluate the precipitation forecast performance of the European Centre for Medium-Range Weather Forecasts(ECMWF)model for China from 2017 to 2022.The main conclusions are as follows.The precipitation forecast capability of the ECMWF model for China has gradually improved from 2017 to 2022.Various scores such as bias,equitable threat score(ETS),and Fractions Skill Score(FSS)showed improvements for different categories of precipitation.The bias of light rain forecasts overall adjusted towards smaller values,and the increase in forecast scores was greater in the warm season than in the cold season.The ETS for torrential rain more intense categories significantly increased,although there were large fluctuations in bias across different months.The model exhibited higher precipitation bias in most areas of North China,indicating overprediction,while it showed lower bias in South China,indicating underprediction.The ETSs indicate that the model performed better in forecasting precipitation in the northeastern part of China without the influence of climatic background conditions.Comparison of the differences between the first period and the second period of the forecast shows that the precipitation amplitude in the ECMWF forecast shifted from slight underestimation to overestimation compared to that of CMPAS05,reducing the likelihood of missing extreme precipitation events.The improvement in ETS is mainly due to the reduction in bias and false alarm rates and,more importantly,an increase in the hit rate.From 2017 to 2022,the area coverage error of model precipitation forecast relative to observations showed a decreasing trend at different scales,while the FSS showed an increasing trend,with the highest FSS observed in 2021.The ETS followed a parabolic trend with increasing neighborhood radius,with the better ETS neighborhood radius generally being larger for moderate rain and heavy rain compared with light rain and torrential rain events.

Comparison and Verification of Coherent Doppler Wind Lidar and Radiosonde Data in the Beijing Urban Area

As a new type of wind field detection equipment, coherent Doppler wind lidar(CDWL) still needs more relevant observation experiments to compare and verify whether it can achieve the accuracy and precision of traditional observation equipment in urban areas. In this experiment, a self-developed CDWL provided four months of observations in the southern Beijing area. After the data acquisition time and height match, the wind profile data obtained based on a Doppler beam swinging(DBS) five-beam inversion algorithm were compared with radiosonde data released from the same location. The standard deviation(SD) of wind speed is 0.8 m s^(–1), and the coefficient of determination R~2 is 0.95. The SD of the wind direction is 17.7° with an R~2 of 0.96. Below the height of the roughness sublayer(about 400 m), the error in wind speed and wind direction is significantly greater than the error above the height of the boundary layer(about 1500 m). For the case of wind speeds less than 4 m s^(–1), the error of wind direction is more significant and is affected by the distribution of surrounding buildings. Averaging at different height levels using suitable time windows can effectively reduce the effects of turbulence and thus reduce the error caused by the different measurement methods of the two devices.

Wind farms increase land surface temperature and reduce vegetation productivity in the Inner Mongolia

Wind power has been developing rapidly as a key measure to mitigate human-driven global warming.The under-standing of the development and impacts of wind farms on local climate and vegetation is of great importance for their rational use but is still limited.In this study,we combined remote sensing and on-site investigations to identify wind farm locations in Inner Mongolia and performed landscape pattern analyses using Fragstats.We explored the impacts of wind farms on land surface temperature(LST)and vegetation net primary productivity(NPP)between 1990 and 2020 by contrasting these metrics in wind farms with those in non-wind farm areas.The results showed that the area of wind farms increased rapidly from 1.2 km2 in 1990 to 10,755 km2 in 2020.Spatially,wind farms are mainly clustered in three aggregation areas in the center.Further,wind farms increased nighttime LST,with a mean value of 0.23℃,but had minor impacts on the daytime LST.Moreover,wind farms caused a decline in NPP,especially over forest areas,with an average reduction of 12.37 GC/m^(2).Given the impact of wind farms on LST and NPP,we suggest that the development of wind farms should fully consider their direct and potential impacts.This study provides scientific guidance on the spatial pattern of future wind farms.

Influence of Irregular Coastlines on a Tornadic Mesovortex in the Pearl River Delta during Monsoon Season.Part II:Numerical Experiments

As demonstrated in the first part of this study(Part I),wind-shift boundaries routinely form along the west coast of the Pearl River Delta due to the land-sea contrast of a“trumpet”shape coastline in the summer monsoon season.Through multiple numerical simulations,this article(Part II)aims to examine the roles of the trumpet-shaped coastline in the mesovortex genesis during the 1 June 2020 tornadic event.The modeling reproduced two mesovortices that are in close proximity in time and space to the realistic mesovortices.In addition to the modeled mesovortex over the triple point where strong ambient vertical vorticity was located,another mesovortex originated from an enhanced discrete vortex along an airmass boundary via shear instability.On the fine-scale storm morphology,finger-like echoes preceding hook echoes were also reproduced around the triple point.Results from sensitivity experiments suggest that the unique topography plays an essential role in modifying the vorticity budget during the mesovortex formation.While there is a high likelihood of an upcoming storm evolving into a rotating storm over the triple point,the simulation's accuracy is sensitive to the local environmental details and storm dynamics.The strengths of cold pool surges from upstream storms may influence the stretching of low-level vertically oriented vortex and thus the wrap-up of finger-like echoes.These findings suggest that the trumpet-shaped coastline is an important component of mesovortex production during the active monsoon season.It is hoped that this study will increase the situational awareness for forecasters regarding regional non-mesocyclone tornadic environments.

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.

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.