Rain Type Research Articles

Exploring the size-dependent dynamics of photosynthetic cells in rainwater: The influence of atmospheric variables and rain characteristics

The presence of microalgae in the atmosphere raises health and environmental concerns. Despite recent scientific advances, our knowledge of the origins and dynamics of photosynthetic cells in relation to atmospheric processes is limited due to a lack of empirical data. To address this gap, we conducted a one-year survey, collecting and analyzing rainwater samples. This study proposes to investigate the temporal dynamics of photosynthetic cells based on their size in combination with a unique dataset of variables of interest: type of rain and its characteristics, local meteorology, concentrations of inorganic chemical species, and long-range air mass transport. The analysis of the biochemical composition of rainwater, along with its correlation with the origin of air masses using ions as tracers, provides evidence of the long-range transport of photosynthetic cells. Additionally, our study reveals distinct removal mechanisms from the atmosphere for photosynthetic cells depending on their size. Our results suggest that convective events with high-intensity rainfall led to the efficient removal of medium-sized photosynthetic cells (4–15 μm) from the atmosphere. However, removal mechanisms for small (<4 μm) and large-sized cells (>15 μm) are not influenced by microphysical rainfall characteristics and seem to be governed by different atmospheric processes: dry deposition is proposed to be a significant mechanism for the removal of large-sized photosynthetic cells, while small-sized cells detected in rain are correlated with the horizontal wind speed and duration of rainfall, particularly during stratiform events. This implies that the removal of photosynthetic cells from the atmosphere is strongly influenced by environmental variables, which are expected to vary in response to global change. Therefore, it is crucial to enhance the monitoring of photosynthetic cells in relation to atmospheric processes and investigate the potential impact of the dissemination of genetic material from distant sources on recipient ecosystems.

Microphysical Characteristics of Cyclonic Rainfall: A GPM‐DPR Based Study Over the Arabian Sea

AbstractThe precipitation characteristics of tropical cyclone (TC) formed over the Arabian Sea during the onset phase of the Indian summer monsoon (i.e., late‐May and early‐June months) and in the post‐monsoon season were investigated during the period from 2014 to 2021 using the Global Precipitation Measurement (GPM) satellite level 2 V07 data. For the cyclonic precipitation, 2‐D frequency distribution between liquid water content (LWC) and non‐liquid water content, that is, ice water content (IWC) shows significant variation with the rain type and season. A large proportion of rain droplets are within the LWC (IWC) range of 0–800 (0–350) g/m2 for the stratiform precipitation of TCs in both seasons. The average value of the mass‐weighted mean diameter (Dm), for the stratiform and convective precipitation at 2 km above the mean sea level in the monsoon (post‐monsoon) season is 1.29 (1.27) mm and 1.47 (1.31) mm, respectively. A gradual decrease in the normalized intercept parameters (Nw) is found to occur with an increase in Dm, irrespective of cloud type and season. There is an enormously high concentration of supercooled liquid and ice particles observed above the melting layer during the convection precipitation in both seasons. In the stratiform cyclonic cloud, the contribution of the collision‐coalescence and breaking‐up process is about 36.62% (47.58%) and 52.52% (41.52%) during the monsoon (post‐monsoon) season. However, the collision‐coalescence process (63.45% in monsoon and 70.2% in post‐monsoon) is acting as dominating microphysical process in the convective precipitation as compared to the break‐up process.

Improving CINRAD Radar QPE Through GPM‐DPR Reflectivity Bias Correction

AbstractReflectivity bias of ground‐based weather radar (GR) is a common error source that can lead to biases in quantitative precipitation estimation (QPE). In this study, the Dual‐frequency Precipitation Radar onboard the Global Precipitation Measurement Mission Core Observatory (GPM‐DPR) is used to correct GR reflectivity bias. The reflectivity bias correction comprehensively considers variations in GR‐DPR reflectivity difference associated with radar frequency difference, data matching approach, precipitation type, GR orographic beam blockage, attenuation, and sample size. The criteria to perform a robust GR‐DPR comparison are presented. Disdrometer validation, based on eight typical rain events from April to August 2019, demonstrates that GPM‐DPR can effectively reduce GR reflectivity bias to ±1 dB. For the period from June to August 2021, the reflectivity correction method is applied to 17 operational GRs. The multiradar QPE shows a significant increase in correlation coefficient (from 0.62 to 0.71), and decreases in relative mean bias (from −0.28 to −0.19) and root mean square error (from 3.96 to 3.54 mm) compared to rain gauges. These results confirm that GPM‐DPR can effectively correct the reflectivity biases of a GR network and improve multiradar QPE accuracy and consistency.

Single image deraining using scale constraint iterative update network

Rain streaks, which can be viewed as a type of noise, have the potential to destroy the structural integrity of objects within an image, leading to a dramatic degradation in the performance of advanced vision algorithms. Therefore, it is important to develop an effective deraining algorithm. There are three challenges in the current deraining task: First, it is difficult to separate rain streaks from the image background because of the complexity of rain types. Second, most of the existing methods use encoder–decoder-based structures, but the models are designed to be too bulky and inflexible to accommodate complex rain streaks. Third, many models perform the same operation for all rain types, which can reduce the generalizability of the model. To address these challenges, we propose a scale constraint iterative update network which divides the network structure into feature extraction block, multi-scale constraint block, and iterative update block. In the feature extraction block, the deep mixed attention is used to extract complex rain streak features, and the mixed convolution block is used to extract the background details. The multi-scale constraint block aggregates contextual features across different scales, while the Global GateUnit captures long-range dependencies. We followed a coarse-to-fine pipeline. In the iterative update block, the feature maps are updated based on features from different scales, gradually refining the image. The final optimized result is obtained by performing learnable up-sampling. During the whole iteration process, the parameters are shared to reduce the complexity of the model while maintaining the performance. Additionally, We also designed a dynamic inference mechanism, which dynamically selects the number of iterations for different types of rain streaks, effectively enhancing the generalization of the model. We conducted extensive experiments on synthetic and real-world rain datasets, as well as a raindrop dataset. The results of our experiments demonstrate that our method outperforms existing deraining methods in terms of effectiveness and generalization ability.

The Effect of Compost Combination on Growth and Yield of Three Varieties Shallot Plants (Allium ascalonicum L).

This experiment aims to determine the effect of the combination of compost on the growth and yield of plants of three varieties of shallots (Allium ascalonicum L). The experiment was carried out in Karangwangun Village, Babakan District, Cirebon Regency - West Java. The research period will be carried out from January to May 2023. The location is located at an altitude of 93 meters above sea level (asl), the soil type of Latosol and Regosol association, including rain type C (moderately wet). The experimental method used is using an experimental method with a Randomized Group Design (RAK) combination pattern, the treatment consists of two factors that are repeated three times. The first factor is compost which consists of three levels, namely compost 10 tons / ha, compost 15 tons / ha, and compost 20 tons / ha. While the second factor is varieties consisting of three levels, namely pancasona varieties, violetta varieties, and bima varieties. The main observation data were processed using linear model statistical tests, fingerprint analysis, and scott-knot group follow-up test analysis. To determine the correlation between the treatment and the growth and yield components of shallots, the correlation used is with the Product Moment correlation coefficient. The experimental results showed: (1) The combination of compost treatment and onion plant varieties had an effect on the weight of fresh bulbs per plot and the weight of dry tubers per clump, but did not affect plant height, number of leaves, number of saplings per clump, root volume, number of tubers per plant, diameter of tubers per plant, weight of fresh bulbs per plant, and weight of dry tubers per plot, (2) The highest dry tuber weight per plot was produced by a combination of compost treatment of 10 tons / ha and bima varieties of 3.85 kg / plot or equivalent to 10.26 tons / ha and was not significantly different from other treatment combinations, and (3) There was a significant correlation between plant height and the number of leaves aged 35 HST and 45 HST with seed weights per plot with weak and medium categories. However, there was no apparent correlation between plant height and leaf count aged 25 HST with seed weight per plot with very weak category.

Seasonal variations in precipitation microphysics over East China based on GPM DPR observations

The disdrometer-observed raindrop size distribution (DSD) in East China has been shown to vary across seasons and rainfall types. In this study, as an extensive research, the seasonal variations of vertical structures and associated microphysical processes of precipitation were investigated using nine-year measurements of dual-frequency precipitation radar on board the Global Precipitation Measurement satellite. The spatial distribution and vertical profiles of the reflectivity factor (Ze), mass-weighted mean diameter (Dm), and generalized intercept parameter (Nw) showed different magnitudes of variability among seasons (and rain types). Generally, the collisional-coalescence process was dominant for sufficient raindrop growth in convective precipitation, followed by the breakup of melted large ice particles. Summer convective precipitation exhibited typical monsoonal features with the largest Ze and Dm values, whereas extremely weak winter convective precipitation exhibited stratiform-like characteristics. For stratiform precipitation, the major microphysical processes were competitive between the breakup and coalescence processes during different seasons. In contrast, collisional coalescence was predominant in the shallow convective precipitation throughout the year. The distribution of rainfall and DSD parameters with respect to storm top height also varied. Specifically, the storm (convective core) top converged around the upper (middle) troposphere during extreme rainfall, indicating moderate convection where Dm reached its maximum with moderate log10Nw. Warm-rain processes also play an important role in raindrop growth. Moreover, the discrepancies between the extreme rainfall and the highest echo top suggest a weak linkage between the heaviest rainfall and tallest storms. This study provides a comprehensive picture of the seasonal variability in precipitation microphysics in East China.

A Preliminary Analysis of Typical Structures and Microphysical Characteristics of Precipitation in Northeastern China Cold Vortexes

The northeastern China cold vortex (NCCV) is the main weather system affecting Northeast China. Based on the precipitation products from the dual-frequency precipitation radar (DPR) onboard the Global Precipitation Measurement core observatory (GPM) satellite, the precipitation structures and microphysical properties for different rain types in 6432 NCCVs from 2014 to 2019 were studied using dynamic composite analysis. Our results show that the precipitation in NCCVs is dominated by stratiform precipitation. Regions with high stratiform and convective precipitation frequency have a comma shape. The growth mechanism of precipitation particles changes at ~4 km in altitude, the lower particles grow through collision (more pronounced in convective precipitation), and the upper hydrometeors grow through the Bergeron process. Additionally, the precipitation structures and microphysical properties exhibit great regional variations in NCCVs. The rainfall for all rain types is the strongest in the southeast region within an NCCV, mainly characterized by higher near-surface droplet concentration, while precipitation events occur more frequently in the southeast region for all rain types. There are active rimming growth processes above the melting layer for convective precipitation in the western region of an NCCV. In the southeast region of an NCCV, the collision growth of droplets in both types of precipitation is the most obvious.

Minor impacts of rain on methane flux from hemiboreal, boreal, and subarctic lakes

Methane (CH4) emissions (FCH4) from northern freshwater lakes are not only significant but also highly variable in time and one driver variable suggested to be important is precipitation. Rain can have various, potentially large effects on FCH4 across multiple time frames, and verifying the impact of rain on lake FCH4 is key to understand both contemporary flux regulation, and to predict future FCH4 related to possible changes in frequency and intensity of rainfall from climate change. The main objective of this study was to assess the short-term impact of typically occurring rain events with different intensity on FCH4 from various lake types located in hemiboreal, boreal, and subarctic Sweden. In spite of high time resolution automated flux measurements across different depth zones and covering numerous commonly types of rain events in northern areas, in general, no strong impact on FCH4 during and within 24 h after the rainfall could be observed. Only in deeper lake areas and during longer rain events FCH4 was weakly related to rain (R2 = 0.29, p < 0.05), where a minor FCH4 decrease during the rain was identified, suggesting that direct rainwater input, during greater rainfall, may decrease FCH4 by dilution of surface water CH4.Overall, this study indicates that typical rain events in the studied regions have minor direct short-term effects on FCH4 from northern lakes and do not enhance FCH4 from shallow and deeper parts of lakes during and up to 24-h after the rainfall. Instead, other factors such as wind speed, water temperature and pressure changes were more strongly correlated with lake FCH4.

A study of rain drop size distributions and associated rain microphysical processes over a subtropical station in the Northeast India

A study of rain Drop Size Distributions (DSDs) and associated microphysical processes is carried out during the premonsoon and monsoon seasons at Kohima (25.67° N, 94.08° E) in the Patkai hill range of the Northeast India. The study is carried out with the help of Micro Rain Radar (24.1 GHz). The rainfall is classified in three categories namely, Bright Band (BB), No Bright Band Low rain rate (R) i.e. 0.10 mm h−1< R ≤ 10 mm h−1 (NBBL) and No Bright Band High rain rate i.e. 10 mm h−1 <R ≤ 20 mm h−1 (NBBH). During the premonsoon and monsoon, for R ≤ 20 mm h−1, rainfall occurrence time constitute around 96% and 98% respectively, whereas rainfall accumulation constitute around 51%. and 72% respectively. The BB height is found to be lower during the premonsoon (∼2.2 km from surface level) compared to monsoon (∼3.6 km from surface level) season. The observational results suggest that, during the premonsoon as well monsoon seasons, BB rain is predominantly associated with collision–coalescence–breakup process with varying proportion, whereas NBBL and NBBH rain are predominantly associated with collision–coalescence process with varying proportion. In each season, collision-coalescence process is most dominant for NBBH type of rain. Seasonally, collision-coalescence process is found to be stronger during the premonsoon season. For the falling rain drops, there is a transition in the microphysical process from number controlled (collision-coalescence-breakup) to size-controlled (collision-coalescence) process with varying proportion. For each season, for R ≤ 10 mm h−1, larger rain drops are found for BB type of rain compared to NBBL rain. Overall, relatively larger raindrops are found to be associated with NBBH rain. Seasonally, larger drops are found during the premonsoon compared to the monsoon season. The rain DSDs and associated microphysical processes during the premonsoon are found to be associated with stronger convection compared to the monsoon season.

Variation characteristics of acid rain in Zhuzhou, Central China over the period 2011-2020

Zhuzhou was one of the most polluted cities in China with the serious acid rain. Due to the implementation of air pollution control measures from 2016 to 2018, the acid rain pollution in this city has reduced. In order to understand the recent situation, a comprehensive study on the acid rain was carried out from January 2011 to December 2020. The pH values during the study period varied from 3.3 to 7.5, with a volume-weighted mean value of 4.7. The predominant acidic components of the precipitation were SO42− and NO3−, accounting for 89.3% of the total anions. The ratio of non-sea-salt SO42− to NO3− showed a decreasing trend, revealing that the pollution type of acid rain changed from sulfuric acid type to sulfuric acid and nitric acid compound type. The correlation analysis (p < 0.05) showed that SO42− was positively correlated with NH4+, Ca2+, and Mg2+; hence, it predominated in precipitation as (NH4)2SO4, NH4HSO4, CaSO4, and MgSO4. Significant positive correlation of Ca2+ with Mg2+ shows that they may originated mainly from crust. Significant positive correlation between SO42− and F− and Cl− indicate that their source may be related to the non-ferrous metal smelting industry in Zhuzhou. Further correlation analysis shows that emissions from the non-ferrous metal smelting industry in the area have a large significant on SO42− and F− in precipitation, while Cl− may still be emitted from other anthropogenic sources.

Effects of acid rain and root exclusion on soil organic carbon in Cunninghamia lanceolata and Michelia macclurei plantations.

Acid rain is one of most serious environment problems in China. The types of acid rain have gradually transformed from sulfuric acid rain (SAR) to mixed acid rain (MAR) and nitric acid rain (NAR) in recent years. Roots are one source of soil organic carbon and play an important role in the formation of soil aggregates. However, the changes in acid rain type and the effect of root removal on soil organic carbon in forest ecosystems are poorly understood. In this study, we removed roots and simulated acid rain with different types (SO42-:NO3- ratio of 4:1, 1:1, and 1:4) for three years in Cunninghamia lanceolata (CP) and Michelia macclurei (MP) plantations to analyze the changes of soil organic carbon and physical properties and to measure the size and mean weight diameter (MWD) of aggregates. Results showed that root removal in C. lanceolata and M. macclurei remarkably reduced soil organic carbon pool by 16.7 % and 21.5%, and soil recalcitrant carbon by 13.5% and 20.0%, respectively. Root removal substantially decreased the MWD and proportion and organic carbon content of soil macroaggregates in M. macclurei, but not in C. lanceolata. Acid rain did not affect soil organic carbon pool and soil aggregate structures. Our results indicated that roots promote soil organic carbon stabilization and that their contribution to the stability of soil organic carbon varies with forest types. Moreover, soil organic carbon stabilization is not affected by different types of acid rain in the short term.

Discussion on the Relationship between Debris Flow Provenance Particle Characteristics, Gully Slope, and Debris Flow Types along the Karakoram Highway

Debris flow, the most extensive and most severe geological hazard along the Karakoram Highway, frequently blocks the Karakoram Highway. Based on the methods of field measurement, indoor statistical analysis and theoretical research, this paper discusses the relationship between the four types of debris flow along the Karakoram Highway. The four types are the rain type, the rain glacier type, the glacier ice lake break type and the freeze–thaw type, and their particle characteristics and gully slope are also considered in the discussion. The results are as follows: (1) The provenance particle size of debris flow is controlled by the type of debris flow. Generally, the provenance average particle equivalent diameter of the debris flow induced by the glacier ice lake type is relatively small, followed by the freeze–thaw type and glacier ice lake break type, and the equivalent diameter of the debris flow induced by the rain type is relatively large; (2) The gully slope coefficient of the debris flow C along the Karakoram Highway is greater than 1, and it increases with the increase in gully slope α, that is, the larger C is, the steeper the gully slope will be; (3) The gully slope coefficient C and the average particle equivalent diameter D of the four types of debris flow are distributed in the ellipse with them as the axis. This ellipse quantitatively describes the relationship between the gully slope of the four types of debris flow and the corresponding provenance particle characteristics. This paper analyzes the formation and causes of debris flow along the Karakoram Highway. It accurately understands the scientific connotation of debris flow formation in the surface matrix layer and improves the diversity, stability, and sustainability of the ecosystem. The paper also proposes ideas and suggestions for promoting the ecological protection and restoration of the Karakoram Highway. Therefore, the research has a certain theoretical significance and practical application value for the appropriate selection and rational design of the debris flow prevention projects along the China–Pakistan Highway.

Estimation of rain parameters for microwave backscattering model using PSO

The intention of the geophysical modelling of rain is to provide a better explanation for the effect of rainfall to the microwave backscattering and thus to interpret radar measurements. However, in the model, physical characteristic of raindrops should be estimated primarily and accurately by considering observation system, measurements and suitable rain rate retrieval algorithms to calculate backscattering coefficients from rainfall. In this study, a geophysical microwave backscattering model of rain type precipitation over sea surface is constructed by using Particle Swarm Optimization (PSO) algorithm in the multilayered Vector Radiative Transfer (VRT) model to estimate vertical profile of rain by using GPM DPR data. Rain column is partition into sublayers and for each sublayer, physical properties of raindrops such as drop radius, water volume fraction or layer thickness are estimated by using PSO to provide the best fit with measurements by searching within certain limits defined by rain rate. Backscattering coefficients from entire rain is provided by the solution of VRT equations via Matrix Doubling Method to consider multilayer effect. Results show that, vertical profile of rain parameters can be estimated accurately for moderate /high rain rates (up to 11–12 mm/h) by using presented model.

Characteristics of Raindrop Size Distributions in the Southwest Mountain Areas of China According to Seasonal Variation and Rain Types

The precipitation and raindrop size distribution (RSD) characteristics of the four seasons and different rain types were studied using a PARSIVEL2 raindrop disdrometer set in the southwest mountain areas of China from 2019 to 2021. The seasonal precipitation in the southwest mountain areas was mainly stratiform rain. The peaks of the RSD were about 1–2 orders of magnitude higher than those in the plains. The convective rain in spring and autumn was very close to the ocean-like convective mass. The local shape–slope (μ–Λ), radar reflectivity–rain rate (Z–R), and kinetic energy–rain rate (KE–R) relationships were further derived, and the diversity of these relationships was mainly due to the variability of the RSDs. In addition, the differences in the RSD characteristics between the top and the foot of the mountain during a typical precipitation process in the summer of 2020 were further compared. It was found that the number density of the small particles at the top of the mountain was higher than that at the foot of the mountain due to the broken large raindrops caused by the high wind speed, while the high evaporation rate, strong convective available potential energy (CPAE), and water vapor content at the foot of the mountain could strengthen the RSD, making the number density of the large raindrops at the foot of the mountain higher than that at the top.

Investigation on Variability, Broader Types and Patterns of Daily and Sub-daily Rains Using Satellite Sub-Daily Rainfall Records based in Western Indian Province

The present study was conducted during 2021 at middle Gujarat. The objectives of the study remained inclined towards the challenging task, where limited observed rainfall records (daily and sub-daily both) were utilized to project corresponding regional design hyetographs for providing the design hyetographs at similar ungauged sites in the region. This script explores suitability, appropriateness and end efficacies of blended (ground based as well as remotely sensed) precipitation data attained for a data deprived region, which was ultimately utilized to derive location specific rainfall curves adopting satellite based observed rainfall records. A set of representative type curves on rainfall (daily &amp; sub-daily) for study region were conceived, which could be potentially utilized for better rainfall-runoff modelling even under purely ungauged scenarios. Voluminous precipitation data retrieved via GPM (IMREG) satellite precipitation products was endeavoured and used to create values envelope of design curves for use in ungauged situations. 21 years of daily &amp; sub-daily rainfall records (2000–2020) were thoroughly examined and used to retrieve valid understanding towards annual, monthly, daily and even hourly based variability of rainfall across six different stations as adopted in the study. The net magnitude of dispersals in all the derived sets of mass curves/Hyetographs were worked out and suitably compared across 6 specific locations as well as their categorization in terms of storm depths, storm durations and peak rain intensities which could be of high practical importance for water resource planners other relevant research and development.

Relationships between lightning occurrence and summer precipitation characteristics over china observed by GPM core observatory

The relationships between lightning occurrence and precipitation properties observed from the Dual-frequency Precipitation Radar and the Microwave Imager onboard the core observatory of the Global Precipitation Measurement Mission over China are investigated. The results indicate that lightning precipitation features (LPFs) typically account for <11% of the total precipitation features (PFs) over China, with the convective rain types accounting for ∼40%. The LPFs are more organized with wider spanning areas over Eastern China than Western China, and embedded with wider areas of convective cores than the non-lightning PFs. The probability of lightning (POL) increases linearly with the near-surface rain rate, liquid water path (LWP), and non-liquid water path (NLWP), while increases exponentially with the equivalent reflectivity factor (Ze). The precipitation profiles reveal that the maximum Ze values at higher altitudes are more sensitive to lightning occurrence than the ones at lower altitudes. The POL reaching above 80% mainly occurs when the areas of Ze above 20 dBZ or 30 dBZ exceed specific thresholds above the melting layer, while also occurs below the melting layer for the areas of Ze above 40 dBZ. The established precipitation parameter threshold-based lightning delineation scheme reveals that the maximum or minimum precipitation properties within PFs perform better than the mean ones in discriminating lightning. Furthermore, there is a great regional variance in the optimum thresholds of lightning delineation by precipitation properties over four typical regions of China. Overall, the present study may be helpful in the future prediction and nowcasting of lightning storms in numerical models.

Analysis and Correction of Precipitation Observation Error in Henan Province

Accurate precipitation data is the basis for studying regional hydrological cycle and climate change, and correcting the precipitation observation error can effectively improve its accuracy. Therefore, based on the daily observation data (including snow and rain types) of 111 meteorological stations in Henan Province from 1960 to 2017, the precipitation observation error correction equation obtained from the precipitation error comparison observation experiment conducted in the Urumqi River Basin of China in the International Cooperation Project on Solid Precipitation Observation carried out by the World Meteorological Organization in 1980 was used to systematically correct the dynamic loss, wetness loss and trace loss of precipitation at 111 meteorological stations from 1960 to 2017. The main conclusions are: (1) The absolute error of each season decreases from south to north, the average absolute error in summer is the largest, 47.30mm, and the winter is the smallest; while the relative error is the opposite, the largest in winter and the smallest in summer. (2) The absolute error of the average annual precipitation in the entire region is above 60mm, gradually increasing from north to south, and the error in most areas is 70-160mm; The relative error varies little from region to region, and the error range is 10%-16%. (3) The average annual rainfall before the correction was 761.92mm, and the average annual rainfall after the correction was 881.1mm, and the corrected value was 119.18mm. There was a decreasing trend in rainfall before and after the correction from 1960 to 2017, but the trend of reduction in the revised rainfall series was greater than that in the measured series.

What modulates the impacts of acid rain on the allelopathy of the two Asteraceae invasives?

Most of the allelopathic studies have focused on the independent allelopathy of one invasive plant, but have ignored the co-allelopathy of the two invasives. The variations in the type of acid rain can modulate the invasiveness of invasives via the changes in the allelopathy. Thus, it is vital to elucidate the allelopathy of invasives, particularly the co-allelopathy of the two invasives, under acid rain with different types, to illuminate the mechanisms driving the co-invasion of two invasives under diversified acid rain. However, little progress has been finished in this aspect presently. This study aimed to evaluate the co-allelopathy of two Asteraceae invasives Solidago canadensis L. and Erigeron annuus L. treated with acid rain with different nitrogen-to-sulfur ratios on seed germination and seedling growth of the horticultural Asteraceae species Lactuca sativa L. via a hydroponic experiment. Aqueous extracts of the two Asteraceae invasives generated obvious allelopathy on L. sativa. S. canadensis aqueous extracts caused stronger allelopathy. There may be an antagonistic effect for the co-allelopathy of the two Asteraceae invasives. Nitric acid at pH 5.6 weakened the allelopathy of the two Asteraceae invasives, but the other types of acid rain strengthened the allelopathy of the two Asteraceae invasives. The allelopathy of the two Asteraceae invasives increases with the increasing acidity of acid rain, but the allelopathy of the two Asteraceae invasives decreases with the increasing nitrogen-to-sulfur ratio of acid rain. Accordingly, the species number of invasives, and the acidity and type of acid rain modulated the impacts of acid rain on the allelopathy of the two Asteraceae invasives.

Hypothetical Ground Radar-Like Rain Rate Generation of Geostationary Weather Satellite Using Data-to-Data Translation

This study proposes a deep-learning-based data-to-data (D2D) translation framework to simulate a radar-like retrieval of rainfall rates using the advantages of spatial coverage and temporal resolution of geostationary (GEO) satellite observation. The D2D method comprises normalization and denormalization in pre- and post-processing and an adversarial learning structure for an inter-domain conversion between physical values of data such as albedo and brightness temperature (BT) unlike the image-to-image translation using digital number values in image data. The GEO-KOMPSAT-2A (GK2A) and radar hybrid surface rainfall (HSR) datasets over the Korean Peninsula from September 2019 to September 2021 were used as the source and target domains for training and testing the D2D model. The constructed D2D model for ground radar-like rainfall generation was validated using the ground radar-observed rainfall data and compared to the GK2A rainfall rate (RR), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS), and Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) rainfall products. The D2D model exhibited excellent performance for various rain types in the study area compared to the GK2A RR, PERSIANN-CCS, and IMERG data. Consequently, the D2D model can provide valuable and accurate radar-like rainfall intensity and distribution data with a high temporal resolution and complementary rainfall information over lands and oceans without radar observation.

Interdisciplinary strategy to assess the impact of meteorological variables on the biochemical composition of the rain and the dynamics of a small eutrophic lake under rain forcing

Abstract. We present an interdisciplinary investigation of the links between the macro and microphysical properties of rain, the biochemical composition of rain, meteorological parameters, and their impacts on the phytoplankton dynamics of a mountain lake. In order to document this interdisciplinary scientific question, Lake Aydat in the French Massif Central mountains was fitted with a set of high-resolution atmospheric radars, a disdrometer, and a precipitation collector in 2020. In parallel, the lake was monitored via sensors and water sampling. To illustrate the potential of this novel experimental setup, we present a case study of a rain event that occurred in September 2020 and during which, three contrasting sub-periods were identified based on the type of rain (convective or stratiform). Using our high-temporal resolution monitoring, we show that the origin of the air mass mainly influences the chemical composition of the rain, which depends on the rain type. In contrast, the photosynthetic cell concentration in the rain is mainly influenced by meteorological variables, predominantly below-cloud scavenging. The very low concentrations of photosynthetic cells found in rain events cannot directly impact the lake's phytoplankton abundance. In contrast, the rain rate directly impacted the lake's thermal stratification during the convective event. The response of the phytoplankton depends on the genus and, interestingly, three cyanobacteria, Microcystis, Coelomoron, and Merismopedia, showed a systematic response to rain events with a sudden decrease in abundance at the lake surface immediately after rain events. In contrast, the abundance of green algae (Elakatothrix), picocyanobacteria (Synechocystis and Synechococcus), and diatoms (Asterionella and Melosira) gradually increased following the rain events, but with a lower intensity compared to the cyanobacteria species. These different phytoplankton responses to the same rainfall event could play a key role in phytoplankton dynamics in the temperate zone. Our results highlight the importance of high-frequency and time resolution monitoring of both atmosphere and lake to better understand the adaptive strategies of cyanobacteria following rain events.