Diurnal Variation Characteristics Research Articles

Diurnal Variation in Summer Precipitation and the Characteristics of Precipitation Events in the Western Tarim Basin, China

The Tarim Basin in the western part of Northwest China (NWC) is the largest inland basin in the world and one of the most arid regions in the middle latitudes. In recent years, heavy precipitation events have occurred frequently in this region, especially in the western Tarim Basin (WTB), due to the climate change. Based on the hourly precipitation data from 2010 to 2022, the diurnal variation in summer precipitation and the characteristics of precipitation events with different durations in WTB have been analyzed. The results mainly show that (1) the diurnal variations in the precipitation amount (PA), precipitation frequency (PF) and precipitation intensity (PI) mainly present a unimodal pattern, but the times of maximum value do not coincide. The peak value of PA and PF appears between 01:00 and 03:00 BJT (Beijing Time), while the valley value appears around 18:00 BJT, yet the peak value of PI appears between 20:00 and 23:00 BJT with no obvious valley value. (2) There are some differences in the diurnal variation characteristics of precipitation among different summer months and different regions. (3) During the past decade, the precipitation structure in WTB has been continuously adjusted, and short-duration- and long-duration-precipitation-dominant periods appear alternately. On the whole, short-duration precipitation has been more frequent in summer, accounting for 70% of the total precipitation events and 40% of the total accumulated precipitation amount. These results can help us to better understand the refined physical characteristics of precipitation events and enhance our understanding of the local climate in the WTB under the background of climate change.

Time-dependent characteristics of analytical measurands.

Biological variation is a relevant component of diagnostic uncertainty. In addition to within-subject andbetween-subject variation, preanalytical variation also includes components that contribute to biological variability. Among these, daily recurring, i.e.,diurnal physiological variation is of particular importance, as it contains both a random and a non-random component ifthe exact time of blood collection is not known. We introduce four time-dependent characteristics (TDC) of diurnal variations for measurands to assess the relevance and extent of time dependence on the evaluation of laboratory results. TDC address (i)a threshold for considering diurnality, (ii) the expected relative changes per time unit, (iii) the permissible time interval between two blood collections at different daytimes within which the expected time dependence does not exceed a defined analytical uncertainty, and (iv) a rhythm-expanded reference change value. TDC and their importance will be exemplified by the measurands aspartate aminotransferase, creatine kinase, glucose, thyroid stimulating hormone, and total bilirubin. TDCs are calculated for four time slots that reflect known blood collection schedules, i.e.,07:00-09:00, 08:00-12:00, 06:00-18:00, and 00:00-24:00. The amplitude and the temporal location of the acrophase are major determinates impacting the diagnostic uncertainty and thus the medical interpretation, especially within the typical blood collection time from 07:00 to 09:00. We propose to check measurands for the existence of diurnal variations and, if applicable, to specify their time-dependent characteristics as outlined in our concept.

The importance of global synchronous observation for estimating oceanic chlorophyll-a

Over the last three decades, ocean color satellites have recorded continuous change in phytoplankton concentration, and in doing so, the satellites have helped marine remote sensing to become an emerging discipline. However, ocean color satellite has provided the state of global phytoplankton only around midday whereas phytoplankton have significant diurnal variation characteristics over an entire day-night cycle, which would lead to large estimation uncertainty in downstream products. A large global field observations show that the diurnal variation curves can be constructed as the sum of an exponential and a polynomial function. After correction with our diurnal variation curves, the intermission difference between MODISA and MODIST phytoplankton product could be decreased from 7.57% to 6%, which is critical to monitor the long-term changing trend with multi-mission data. When the satellite-recorded chlorophyll-a concentration is simply equal to a daily average value, it results in overestimating uncertainties of 16% and 54% for the northern and southern hemispheric oceans, respectively. Moreover, as a typical example of downstream product of the chlorophyll-a, the coverage of oligotrophic waters can oscillate 76% from day to night simulated from satellite images with our diurnal variation curves, further confirming the importance of global synchronous observation. The geostationary satellite might be an efficient regional tool for diurnal observation, but it must account for its limitations under the weak light conditions of early morning and late afternoon. In the real world, the effects of diurnal variations in ocean properties reach far beyond chlorophyll-a in the global oceans. We anticipate these quantitatively findings to be a starting point for quantitatively re-examining the proper application of ocean color products in scientific communication.

Multi-scale remote sensing retrieval model for land surface emissivity and its impact on land surface temperature estimation

ABSTRACT As a fundamental parameter of the surface radiation process, land surface emissivity (LSE) is the most direct factor affecting the land surface temperature (LST) retrieval accuracy. Based on the measured data from 2017 to 2023, the characteristics of LSE changes were analysed, different timescale LSE retrieval models were developed, and the impact of LSE on pixel scale observational LST acquisition was evaluated by using unmanned aerial vehicle (UAV) remote sensing images. The results show that with changes in atmospheric environmental conditions, the LSE changes are relatively less pronounced at 3.99 µm and 4.02 µm in the mid-infrared band and at 10.8 µm and 11.8 µm in the thermal infrared band than in the other bands. At the timescale above day, the LSE is significant correlation with the normalized differential vegetation index (NDVI). Vegetation is the main parameter that dominates the LSE change under heterogeneous underlying surfaces. On a daily timescale, LSE exhibits typical diurnal variation characteristics, and the amplitude of diurnal variation is influenced mainly by shallow soil water and heat conditions. The developed LSE model based on Fengyun-4A (FY-4A) satellite remote-sensing data can effectively reproduce the daily variation characteristics of LST and avoid the ‘jumping’ phenomenon that may occur in the NDVI threshold method. The root-mean-square error (RMSE) between the retrieved LST and in situ data is reduced to 3.78°C, and the retrieval accuracy is better than that of the published LST product. When using UAVs to obtain pixel-scale LSTs, dry bare soil is more sensitive to LSE. When the LSE increases from 0.95 to 1.0, the average LST obtained by the UAV deviates by approximately 1.0°C. This study preliminarily provides some spatiotemporal variation patterns of LSE and lays a foundation for the later-modified LST retrieval algorithms.

Evaluation and correction of wind energy forecast in Yangjiang

Wind power generation is one of the most promising new energy sources. It is important to study effective short-term wind speed forecasting methods. In this paper, the CMA-GD model is applied to forecast the wind speed over South China in four typical months (January, April, August, and October) in 2022. Taking Longyue Wind Farm in Yangjiang as an example, the simulated wind speed and wind direction are evaluated based on the observation of this station at four heights (10 m, 30 m, 50 m, and 70 m). The results show that the CMA-GD model has a good effect on forecasting the next day’s 24 h wind speed of Longyue Wind Farm. Overall, the correlation coefficients (R) between forecast and observation are 0.77-0.81, and the root-mean-square errors (RMSE) are 1.80-2.08 m·s-1. With the increase in altitude, the simulation effect is a little better. For different months, the R is as follows: October>August>April>January, and the RMSE and mean absolute error (MAE) are as follows: October>January>August>April. For diurnal variation, the wind speed simulation effect in the night is better than that in the day. Due to the influence of the subtropical monsoon climate and local mountain microclimate in April and August, there are some deviations in the wind speed simulation during 4-8 p.m. The difference in wind direction between forecast and observation are as follows: August<January<October<April, the average wind direction differences are between 2-17°, with little difference in the vertical direction. After the forecast wind speed is corrected by the random forest (RF) algorithm, the R of wind speed at each height is 0.92, and RMSEs are 1.07-1.27 m·s-1. The revised wind speed forecast has the same diurnal variation characteristics as the observation, indicating that the random forest algorithm can effectively reduce the model forecast error.

Diurnal Variation Characteristics of Raindrop Size Distribution Observed by a Parsivel2 Disdrometer in the Ili River Valley

The diurnal variation characteristics of raindrop size distribution (RSD) in the Ili River Valley are investigated in this study, using the RSD data from May to September during 2020-2021 collected by a Parsivel2 disdrometer in Zhaosu. Significant diurnal variations (02–07, 08–13, 14–19, and 20-01 local standard time (LST)) of precipitation and RSD in Zhaosu are revealed during the rainy seasons. Precipitation mainly occurs in the late afternoon and early evening. A higher concentration of small raindrops is observed in the morning, whereas more mid-size and large raindrops are observed in the afternoon. The RSD exhibits diurnal differences between different rainfall rate classes; the diurnal difference of RSD is more pronounced in the case of high rainfall rates. Stratiform precipitation can occur at any time of the day, yet convective precipitation mainly occurs during the late afternoon and early evening. The RSD of stratiform rainfall shows a similar distribution over the four time periods. For convective rainfall, the concentration of small raindrops is the highest (lowest) over 02–07 (14–19) LST, while the highest (lowest) concentration of medium and large drops is observed over 14–19 (02–07) LST. Convective rain in the Ili River Valley over 14–19 LST can be characterized as the continental convective cluster, while in the rest time of the day, it is neither in the maritime cluster nor in the continental cluster. The empirical relationships between the radar reflectivity factor and rainfall rate (Z-R) for stratiform and convective rain types are also derived. The purpose of this study is to advance our understanding of precipitation microphysics in arid mountainous region.

High-resolution diurnal variation mechanism of oxygen and acid environments at the water–sediment interface during cyanobacterial decomposition

Changes in the oxygen and acidic environments of water caused by algal blooms in lakes aggravate the uncertainty of the eutrophication process, profoundly influencing water ecosystems and lake biogeochemical cycles. This study aimed to detail the mechanisms of benthic oxygen and acid processes by determining high-resolution and high-quality chemical gradients and acquiring heterogeneous data for diurnal changes in dissolved oxygen (DO)/pH at the water–sediment interface (SWI) during different stages of algal degradation. Planar optode (PO) systems were used to obtain dynamic two-dimensional (2D) images of DO/pH at a laboratory microcosm interface. The benthic gradient and diurnal variation of DO/pH at the SWI were jointly regulated by the photosynthesis/respiration and migration behaviors of algae, through their influence on the water–carbon chemistry. The DO/pH at the SWI showed unique diurnal variation characteristics at different stages of algal degradation; however, characteristics consistent with the diurnal variation in photosynthesis were limited to the algal growth period. The increase in DO/pH during the daytime resulted from O2-rich and carbonate hydrolysis, to compensate for the reduction in CO2 saturation caused by algal photosynthesis. Nocturnal DO/pH decreased owing to O2 depletion and H+ release, because of increased water CO2 content from algal respiration. When photosynthesis and respiration were inhibited, or not smooth, DO/pH showed a limited increase with uncertainty. The sediment was not completely anaerobic, and DO/pH penetrated to −20 mm and even to the bottom of the interface (−40 mm) as a result of algal migration, whereas DO was exhausted and high pH areas transferred to sediments following algal decay. Sediments acted as storage pools in alkaline environments, which posed a potential risk for water eutrophication. The trajectory of algal activity at the SWI was highly consistent with the dynamic variation in DO/pH. Our findings provide new insights for in situ tracking and early prediction of algal blooms, and can be used to formulate a theoretical basis for the mechanism of eutrophication processes and for exploring new algal control technologies.

Diurnal variation characteristics and meteorological causes of autumn ozone in the Pearl River Delta, China

This study investigates the diurnal variation of ozone (O3) in the Pearl River Delta (PRD) during autumn from 2016 to 2021, focusing on the main O3 modes and their relationship with meteorological conditions. Utilizing K-means clustering, four patterns of O3 variation were identified: Cluster 1 (extremely low O3), Cluster 2 (close to autumn average), Cluster 3 (abnormally high O3 at night), and Cluster 4 (extremely high O3). In Cluster 1, the PRD was situated on the northwest side of the western Pacific subtropical high (WPSH), resulting in increased cloud cover, weakened radiation, and the lowest O3 growth rate during the day, with weak nighttime changes. Cluster 2 presents O3 changes under normal autumn conditions, closely resembling the autumn average. In Cluster 3, the PRD was located between continental high pressure and the low-pressure system over the South China Sea. The enhanced horizontal pressure gradient led to an increase in the horizontal wind speed, promoting the formation of a low-level jet (LLJ). The LLJ caused decoupling between the residual layer and stable boundary layer at night, leading to increased surface O3 concentration and a higher background O3 concentration before sunrise the next day. In Cluster 4, favorable meteorological conditions for O3 generation and accumulation were created by the influence of the WPSH and peripheral tropical cyclones. O3 rapidly increased during the day, reaching extremely high values in the afternoon, with an exceedance rate of 80 %. Comparing the four diurnal patterns and their meteorological conditions highlights the significance of meteorological processes in O3 variations.

Diurnal Variation Characteristics of Summer Precipitation over the Northern Slope of the Tianshan Mountains, Xinjiang, Northwest China: Basic Features and Responses to the Inhomogeneous Underlying Surface

The diurnal variation characteristics of precipitation in summer (June–August) during the period of 2015–2019 over the Northern Slope of the Tianshan Mountains (NSTM) was analyzed using hourly simulated data from Nanjing University’s real-time forecasting system (WRF_NJU) with 4 km resolution, Automatic Weather Station (AWS) data, and the ERA5-Land data through using methods such as the Rotated Empirical Orthogonal Function (REOF) and Coefficient of Variation (CV). The results show that the diurnal variation pattern of the precipitation over the NSTM simulated by WRF_NJU aligns closely with that of the observational AWS data, and it captured spatial distribution, peak values, and the times of precipitation reasonably well. The hourly precipitation amount (PA), precipitation frequency (PF), and precipitation intensity (PI) all show characteristics of being greater in the afternoon to nighttime than from early morning to noon, and the diurnal variations of precipitation in this region are significantly influenced by altitude. The PA, PF, and PI peak over the southern edge of the Junggar Basin (JB) below 1000 m occurred at around 2200 Local Solar Time (LST). In contrast, peak PA over the mountainous regions above 3000 m occurred at around 1500 LST. Further analysis with REOF and CV indicated that the difference in diurnal variations of precipitation between the mountainous regions and the JB is most pronounced likely due to the topographical influences. The peak PA over the mountainous regions mainly occurred at around 1500 LST, while that of the JB occurred at around 0100 LST. High CV regions for PI are predominantly found over the area near the central JB and the middle Tianshan mountains, whereas high CV regions for the PF are located in the central and northern parts of Urumqi and Changji. In addition, different land surface categories exhibit distinct patterns of diurnal precipitation variation, i.e., the forests, grasslands, and water bodies exhibit their peak PA in the period from early morning to noon, while the impervious surfaces, croplands, and barren lands exhibit their peak PA in the period from afternoon to nighttime.

Long-term observations of NO2 using GEMS in China: Validations and regional transport

In 2019, South Korea launched the Geostationary Environment Monitoring Spectrometer (GEMS) to observe trace gases with an hourly temporal resolution. Compared to previous payloads on polar-orbiting satellites, the GEMS payload has significant advantages in detecting the diurnal variation characteristics of NO2. However, there is still a lack of ground-based validations regarding the overall accuracy of GEMS in the Chinese region. In this study, we conducted a systematic ground validation of GEMS NO2 data in China for the first time. We validated the accuracy of GEMS NO2 data in four typical pollution regions in China, namely the Beijing-Tianjin-Hebei region (JJJ), the Yangtze River Delta region (YRD), the Pearl River Delta region (PRD), and the Sichuan Basin region (SCB), based on MAX-DOAS and CNEMC data. The averaged correlations using the two datasets for validation were 0.81 and 0.57, respectively, indicating a high level of accuracy for the data in China. Using the GEMS seasonal averaged NO2 data, we studied the distribution of NO2 levels in the four regions. We found that the highest NO2 in all four regions occurred during winter with concentrations of 1.84 × 1016 molecules cm−2, 1.59 × 1016 molecules cm−2, 1.58 × 1016 molecules cm−2 and 9.47 × 1015 molecules cm−2, respectively. The distribution of NO2 was closely related to the terrain. Additionally, we observed a significant underestimation issue with TROPOMI, exceeding 30 % in many regions. Based on MAX-DOAS, we investigated the vertical distribution of NO2 in the four regions and found that NO2 was mainly concentrated below 0.5 km. with the HNU station having the lowest concentration, averaging only 2.12 ppb, which was approximately 41 % of the highest concentration recorded at the CQ station. Furthermore, we conducted a study on regional and cross-regional transport using a combination of MAX-DOAS and GEMS data. We found that the transport flux of NO2 could increase by over 500 % within 1 h, making a significant contribution to local NO2 concentrations. The joint observations of GEMS and MAX-DOAS will provide reliable data support for NO2 research and control in China, making a substantial contribution to environmental protection and sustainable development.

Effect of sudden stratosphere warming on characteristics of medium-scale traveling ionospheric disturbances in the Asian region of Russia

Based on the data from the oblique-incidence sounding radio path network at mid- and subauroral latitudes of the Asian region in Russia, we investigated features of medium-scale traveling ionospheric disturbances (MS TID) within the 2016 winter and spring seasons. We revealed characteristic diurnal variations in the occurrence probability and recording time of MS TIDs along different-orientation paths. We analyzed the effect of the 2016 February minor sudden stratosphere warming (SSW) and the 2016 March final warming on the MS TID characteristics in the Asian region of Russia.

Application of Machine Learning Techniques to Improve Multi-Radar Mosaic Precipitation Estimates in Shanghai

In this study, we applied an explainable machine learning technique based on the LightGBM method, a category of gradient boosting decision tree algorithm, to conduct a quantitative radar precipitation estimation and move to understand the underlying reasons for excellent estimations. By introducing 3D grid radar reflectivity data into the LightGBM algorithm, we constructed three LightGBM models, including 2D and 3D LightGBM models. Ten groups of experiments were carried out to compare the performances of the LightGBM models with traditional Z–R relationship methods. To further assess the performances of the LightGBM models, rainfall events with 11,483 total samples during August-September of 2022 were used for statistical analysis, and two heavy rainfall events were specifically chosen for the spatial distribution evaluation. The results from both the statistical analysis and spatial distribution demonstrate that the performance of the LightGBM 3D model with nine points is the best method for quantitative precipitation estimation in this study. Through analyzing the explainability of the LightGBM models from Shapley additive explanations (SHAP) regression values, it can be inferred that the superior performance of the LightGBM 3D model is mainly attributed to its consideration of the rain gauge station attributes, diurnal variation characteristics, and the influence of spatial offset.

Diurnal Variation Characteristics of Summer Precipitation and Related Statistical Analysis in the Ili Region, Xinjiang, Northwest China

The diurnal variation characteristics and basic statistical features of summer precipitation (from June to August) in the Ili region from 2015 to 2019 were investigated based on 4 km resolution Weather Research and Forecasting model simulation data from Nanjing University (WRF_NJU). The results show that the overall diurnal variation characteristics of precipitation (DVCP) reflected by the WRF_NJU data were consistent with respect to the observations and reanalysis data. The total precipitation pattern exhibited high (low) values on the east (west), with higher (lower) values over the mountainous (valley) area. Hourly precipitation amount (PA), precipitation frequency (PF), and precipitation intensity (PI) show similar diurnal variation characteristics, with peaks occurring at around 1700 LST in the mountainous area and around 2000 LST in valleys. Furthermore, moderate to intense precipitation contributes up to 87.88% of the total precipitation. The peaks in the mountainous area occur earlier than the valleys, while the peaks in western part of the valleys occur earlier than the eastern part. The PA peaks over the valleys and slopes occurred from the evening to early morning and from the afternoon to evening, respectively. In addition, the rotated empirical orthogonal function (REOF) analysis implied that the DVCP exhibits distinct differences between mountainous and valleys, and peak precipitation occurs during the evening in basin– and wedge–shaped areas, while the mountain peaks and foothill regions exhibit semi–diurnal variation characteristics. Among several basic meteorological factors, the vertical velocity (VV) and water vapor mixing ratio (WVMR) provided major contributions to the DVCP in both areas with high and low coefficients of variation, and the WVMR (VV) probably played a more significant role in mountainous (valleys) areas.

A novel quantitative analysis for diurnal dynamics of Ulva prolifera patch in the Yellow Sea from Geostationary Ocean Color Imager observation

IntroductionIn the last decade, the outbreak of large-scale green tides caused by Ulva prolifera has continuously occurred in the Yellow Sea. Satellite remote sensing techniques have been widely used to monitor the distribution area and duration of green tides due to their advantages of their large-area synchronous observation. Ulva prolifera in the Yellow Sea is mainly distributed in bands or large patches during its flourishing stage. Previous studies have rarely reported the quantitative analysis of a single Ulva prolifera patch and its changes in the short term.MethodsConsidering the high temporal resolution of the Geostationary Ocean Color Imager (GOCI) sensor and the patchy distribution of Ulva prolifera floating on the sea surface, we developed a feasible method for monitoringUlva prolifera by performing clustering analysis with density-based spatial clustering of applications with noise (DBSCAN) to capture the diurnal variation characteristics of a single Ulva prolifera patch.ResultsThis new approach was used to extract informationfrom a single Ulva prolifera patch in the Yellow Sea in 2012 and 2017. The results showed that during the time of GOCI imaging, the tidal current was the main factor driving the drift of Ulva prolifera, and the drifting direction of Ulva prolifera was consistent with the direction of the local tidal current, with a coefficient of determination of 0.94.DiscussionBy changing the normalized difference vegetation index (NDVI) threshold, further more accurate atmospheric correction (AC) of GOCI data during the twilight periods was indirectly achieved. By comparing the areal change in the single patch before and after AC, we speculated that the daily change in signal intensity received by the GOCI sensor may be the main reason for the diurnal variation in the Ulva proliferacoverage area. The results showed the details of the diurnal variation in Ulvaprolifera patches in the dynamic marine environment, and the main reason that may cause this variation was speculated.

Diurnal Variation Characteristics of Clouds and Precipitation during the Summer Season in Two Typical Climate Regions of the Tibetan Plateau

Mêdog and Nagqu are two typical climate regions of the Tibetan Plateau, with different atmospheric conditions and local orography. This may lead to different diurnal variation patterns of clouds and precipitation. This paper investigates the diurnal variations of clouds and precipitation in Mêdog and Nagqu, using ground-based measurements from Ka-band cloud radar and a Particle Size and Velocity (PARSIVEL) disdrometer. High frequencies of cloud cover and precipitation occur from 23:00 local solar time (LST) to 05:00 LST in Mêdog, while low frequencies appear from 11:00 LST to 17:00 LST. The occurrence frequencies in Nagqu maintain high values from 13:00 LST to 21:00 LST. In terms of mean rain rate, heavier rainfall appears in the evening and at night in Mêdog, with peaks at 00:00 LST and 18:00 LST, respectively. In Nagqu, the heaviest rainfall occurs at 12:00 LST. In addition, the afternoon convective rainfall in Nagqu is characterized by a much higher concentration of large drops, which can be classified as continental-like. The morning rainfall has the lowest concentration of large drops and can be classified as maritime-like. Finally, the mechanisms of diurnal variations in the two regions are discussed. The diurnal cycle of clouds and precipitation in Mêdog may be associated with the nocturnal convergence of moisture flux and mountain–valley wind circulation. Diurnal variations in Nagqu have a high correlation with the diurnal cycle of solar radiation. The high nocturnal frequency of clouds and precipitation in the two regions at night is closely related to the convergence of moisture flux.

Composition Characteristics of Volatile Organic Compounds and Associated Contributions to Secondary Pollution in Shenyang Industrial Area in Summer

Based on the observation data of volatile organic compounds (VOCs) in the industrial area of Shenyang during the summer of 2019 and 2020, the composition characteristics and sources of VOCs were preliminarily studied. The ozone formation potential (OFP) and aerosol formation potential (AFP) of VOCs were also estimated using the max incremental reactivity (MIR) and aerosol formation coefficient (FAC) methods, respectively. The results showed that the average concentration of VOCs was 41.66 μg·m-3, and the proportions of alkanes, olefins, aromatics, and acetylene were 48.50%, 14.08%, 15.37%, and 22.05%, respectively. The top ten species of VOCs were primarily C2-C5 alkanes, also including acetylene, ethylene, and some aromatics, accounting for 69.25% of the total VOCs. VOCs showed obvious diurnal variation characteristics with a high concentration in the morning and evening (at 06:00 and 22:00) and a low concentration in the afternoon (11:00-16:00). According to the value of toluene/benzene (T/B) and isopentane/n-pentane, the atmosphere of the industrial area was mainly affected by vehicle exhaust emissions, solvent use, combustion sources, and LPG/NG. The total AFP of VOCs was up to 41.43×10-2 μg·m-3, and aromatics were the largest contributor. The total OFP of VOCs reached 117.59 μg·m-3, in which the alkenes contributed the most.

Wind Gust Parameters in the Lower Troposphere Based on Doppler Lidar Data

AbstractWind gusts are common small‐scale weather phenomena characterized by a rapid increase in wind speed over a short period of time. Wind gusts affect a wide range of interests, including aviation safety, wind energy and professional skiing, while strong gusts can also cause severe weather events and limit visibility. However, the characteristics of gusts in the lower troposphere are not yet well understood, especially at the top of the boundary layer. In this paper, the gust parameters in the lower atmosphere at different heights and their diurnal variation characteristics are examined based on Doppler lidar data from the gentle coastal topography of Shandong Province, China. The results show that all the gust parameters have distinct stratification characteristics, with significantly different diurnal variations below 400 m, between 400 and 1,200 m, and above 1,200 m (above the ground, same below). Wind gusts are considered to be the result of turbulent disturbances superimposed on the background airflow, and strong turbulence could cause the instantaneous winds to significantly deviate from the mean airflow. The magnitude of the peak gust is mainly controlled by the mean flow, but the gust factor, which is the ratio of the peak gust to the mean flow, is almost independent of the mean flow and has a strong positive correlation with the turbulence intensity. These results imply that gusts of different properties occur at varying altitudes, with differences depending on turbulence intensity and mean airflow, and provide an observational basis for studies of gust structure.

Research on the diurnal variation characteristics of ozone formation sensitivity and the impact of ozone pollution control measures in “2 + 26” cities of Henan Province in summer

Near-surface ozone pollution is becoming an increasingly serious air quality issue in China, especially in “2 + 26” cities (Beijing-Tianjin-Hebei and nearby cities). HN2 + 26 cities (“2 + 26” cities of Henan Province) are located in the south of “2 + 26” cities, with frequent and severe ozone pollution events in recent years. This study investigated the diurnal evolution characteristics of ozone formation sensitivity (OFS) of HN2 + 26 cities from May to September in 2021 by the innovative combination of Global Ozone Monitoring Experiment (GOME-2B) and Ozone Monitoring Instrument (OMI) satellite data, and assessed the impact of ozone pollution control measures (OPCMs) implemented from June 26 to July 1, 2021. The localized FNR (ratio of formaldehyde to nitrogen dioxide of satellite measurement) threshold (1.4–2.55) was established, and it was found that OFS in May–September 2021 was mainly in VOCs-limited regime in the morning (∼10:00), while transitional/NOx-limited regime in the afternoon (∼14:00). Three periods (before, during and after the OPCMs) were divided to evaluate the impact of OPCMs on OFS. It was indicated that OPCMs had no impact on the morning OFS, but had a significant impact on the afternoon OFS. Specifically, the OFS in two industrial cities Xinxiang (XX) and Zhengzhou (ZZ) shifted from transitional regime to NOx-limited regime after the OPCMs. We further investigated OFS differences between urban and suburban areas and found that OFS shift of XX only existed in urban areas, while that of ZZ existed in both urban and suburban areas. We compared their measures and found that it is effective to take hierarchical control measures on different levels of ozone pollution days to alleviate ozone pollution. This study provides an improved understanding of diurnal evolution characteristics of OFS and the impacts of OPCMs on it, which will provide a theoretical basis for formulating more scientific ozone pollution control policies.

Changes in Secondary Inorganic Ions in PM2.5 at Different Pollution Stages Before and After COVID-19 Control

To investigate the change characteristics of secondary inorganic ions in PM2.5 at different pollution stages before and after COVID-19, the online monitoring of winter meteorological and atmospheric pollutant concentrations in Zhengzhou from December 15, 2019 to February 15, 2020 was conducted using a high-resolution (1 h) online instrument. This study analyzed the causes of the haze process of COVID-19, the diurnal variation characteristics of air pollutants, and the distribution characteristics of air pollutants at different stages of haze.The results showed that Zhengzhou was mainly controlled by the high-pressure ridge during the haze process, and the weather situation was stable, which was conducive to the accumulation of air pollutants. SNA was the main component of water-soluble ions, accounting for more than 90%. Home isolation measures during COVID-19 had different impacts on the distribution characteristics of air pollutants in different haze stages. After COVID-19, the concentration of PM2.5 in the clean, occurrence, and dissipation stages increased compared with that before COVID-19 but significantly decreased in the development stage. The home isolation policy significantly reduced the high value of PM2.5. The concentrations of NO2, SO2, NH3, and CO were the highest in the haze development stage, showing a trend of first increasing and then decreasing. The concentration of O3 was lowest in the pre-COVID-19 development stage but highest in the post-COVID-19 development stage. The linear correlation between[NH4+]/[SO42-] and[NO3-]/[SO42-] at different time periods before and after COVID-19 was strong, indicating that the home isolation policy of COVID-19 did not change the generation mode of NO3-, and the corresponding reaction was always the main generation mode of NO3-. The correlation between[excess-NH4+] and[NO3-] was high in different periods before COVID-19, and NO3- generation was related to the increase in NH3 or NH4+ in the process of PM2.5 pollution in Zhengzhou.

Spatiotemporal Variation Characteristics and Influencing Factors of Karst Cave Microclimate Environments: A Case Study in Shuanghe Cave, Guizhou Province, China

To systematically analyze the spatiotemporal heterogeneity, diurnal variation characteristics, and influencing factors of karst cave microclimate environments in Mahuang Cave, a cave in the Shuanghe Cave National Geological Park in Guizhou Province, China, was investigated. Monthly monitoring of meteorological and environmental parameters, such as wind speed, air pressure, humidity, and temperature indicators inside the cave and atmospheric temperature and precipitation outside the cave, was conducted from 2019 to 2021, as well as encrypted monitoring in August and December 2019. The results showed that: (1) The meteorological parameters of Mahuang Cave exhibited seasonal characteristics and cyclical interannual variation. Cave wind speed, relative humidity, and temperature were high in summer and autumn and lowest in winter, whereas cave air pressure was high in winter and low in summer. The atmospheric temperature outside the cave was the main controlling factor. (2) On a short time scale, the dewpoint and temperature of Mahuang Cave did not change significantly, and an abrupt change phenomenon occurred mostly around noon. The warm season was more sensitive than the cold season, and the closer to the entrance of the cave, the stronger the response. (3) In terms of spatial distribution, the overall microclimate factors of Mahuang Cave became increasingly stable and entered a constant state with the increasing depth of the cave passage. The related effects of cave morphology and structure, the physical environment of the cave passage, air movement, and groundwater dynamics were important factors leading to an abrupt change phenomenon in cave microclimates. Local meteorological conditions and cave geometry controlled the temporal variability and spatial heterogeneity of the cave microclimate environment.