Rainfall In May Research Articles

Specific Weather Factors Affecting the Incidence of Fire Blight in Korea from 2020 to 2023

Since its initial outbreak in Korea in 2015, fire blight has consistently emerged annually. Fire blight outbreaks usually begin in May, peak in June, and decline in July in Korea. In this study, we analyzed cases that exhibit a distinct pattern of disease occurrence based on yearly weather conditions from 2020 to 2023. In 2020, fire bight disease occurrence began in late May. Although the disease incidence started late by the low temperatures in April, which caused flowering period delayed, the incidence increased significantly due to the high risk of blossom infection. In 2021, the first outbreak began in late April because the flower infection started in early April. In 2022, despite the high blossom infection risk during the flowering period in April and the high incidence of fire blight in May, the incidence decreased sharply from June due to the low rainfall in May. In 2023, due to torrential rains and hail in late June, the incidence of fire blight increased even in July. Considering the weather factors that affect the increase of fire blight disease, it is suggested that control measures to prevent the fire blight infection should be carried out before and after wind-driven rains.

Landslide susceptibility assessment by implementing the analytical hierarchy process in GIS weight overlay tool: A case study of the Krupanj area in Western Serbia

The aim of this paper is to show the susceptibility to sliding in the Krupanj area. Intense rainfall in May 2014 triggered many landslides in western Serbia. The Krupanj area was particularly affected by this event. The material damage occurred affected the awareness of the importance of knowing the locations that are prone to sliding. Therefore, from 2014 to 2021, field research was carried out in the Krupanj area. During this period a large amount of landslide data were collected by engineering geological mapping. These data were used for susceptibility analysis. For present study the analytical hierarchy process (AHP) and weight overlay (WO) tool were used. Nine factors were used for susceptibility analysis: slope, aspect, curvature, elevation, lithology, distance from rivers, faults, boundary?s and land cover. In order to be able to make a comparison, all factors were evaluated using the Saaty scale, so that the weights of the individual factors were obtained. The weight values obtained by AHP were used in GIS tool. Final map was validated by ROC analysis. The validation results show accuracy of 77,1% (good) for model.

ФОРМУВАННЯ ПРОДУКТИВНОСТІ КВАСОЛІ ЗВИЧАЙНОЇ ЗАЛЕЖНО ВІД СОРТІВ, ІНОКУЛЯЦІЇ ТА УДОБРЕННЯ

Ріст і розвиток рослин квасолі прямо залежить від умов навколишнього середовища, основними складниками якого є температура повітря та ґрунту, освітленість, вологість, мінеральне живлення. Продуктивність рослин зумовлюється наявністю цих факторів, і чим більше вони відповідають біологічним особливостям культури, тим повніше реалізуються потенційні можливості сортів квасолі. Під час дослідження насіння квасолі звичайної перед сівбою обробляли різними штамами мікроорганізмів. Залежно від цього дещо змінювалися міжфазні періоди росту й розвитку рослин. Тривалість періоду «сівба – повна стиглість» у рослин квасолі сорту Ластівка, інокульованих різними штамами Rhizobium phaseoli, у середньому за період дослідження 2020–2022 рр. відрізнялася на 1–3 доби.

Water Cycles and Geothermal Processes in a Volcanic Crater Lake

Exploring how the hydrological and thermal conditions of a volcanic lake change in response to volcanic activity is important to identify the signs of a volcanic eruption. A water cycle system and a geothermal process in a crater lake, Okama, in the active Zao Volcano, Japan, were explored by estimating the hydrological and chemical budgets of the lake, and analyzing the time series of lake water temperature, respectively. In 2021, the lake level consistently increased by snowmelt plus rainfall in May–June, and then stayed nearly constant in the rainfall season of July–September. The hydrological budget estimated during the increasing lake level indicated that the net groundwater inflow is at any time positive. This suggests that the groundwater inflow to the lake is controlled by the water percolation into volcanic debris from the melting of snow that remained in the catchment. Solving the simultaneous equation from the hydrological and chemical budgets evaluated the groundwater inflow, Gin, at 0.012–0.040 m3/s, and the groundwater outflow, Gout, at 0.012–0.027 m3/s in May–September 2021. By adding the 2020 values of Gin and Gout evaluated at the relatively high lake level, it was found that Gin and Gout exhibit highly negative and positive correlations (R2 = 0.661 and 0.848; p < 0.01) with the lake level, respectively. In the completely ice-covered season of 15 December 2021–28 February 2022, the lake water temperature increased between the bottom and 15 m above the bottom at the deepest point, which reflects the geothermal heat input at the bottom. The heat storage change during the increasing water temperature was evaluated at a range of −0.4–5.5 W/m2 as the 10-day moving average heat flux. By accumulating the daily heat storage change for the calculated period, the water temperature averaged over the heated layer increased from 1.08 to 1.56 °C. The small temperature increase reflects a stagnant state of volcanic activity in the Zao Volcano. The present study could be useful to investigate how an active volcano responds to water percolation and geothermal heat.

Towards a Combined Physical and Social Evaluation of Climate Vulnerability in Coastal Urban Megacities

Coastal urban megacities across Asia face significant risks from climate change, including coastal flooding, high temperatures, urban heat island impacts and air pollution. These hazards are associated with negative impacts on infrastructure, communities and the environment. To identify the current intensity of climate change impacts in coastal urban megacities, an integrated evaluation method is needed. Firstly, the present study assesses the climate change impacts of Guangzhou, a Chinese coastal urban megacity, for both physical and social aspects. This study includes 60 years of time-series data for 1960–2020 to examine temperatures, precipitation, humidity and air pollution in Guangzhou city. At the same time, a survey was conducted between April and July 2022 in this megacity and collected the views of 336 people on climate change and its associated environmental impacts. Secondly, the Ganzhou city results are compared with existing data from similar nearby cities to evaluate the diverse climate change trends. Results show that during 1961-1990, the city received the most rainfall in May, reaching 283.6 mm. From 1990 to 2020, June recorded the highest rainfall of 356.6 mm and shows an increase of 73 mm during that period. The very severe monsoon season brought an increased risk of flooding. Results also revealed that the warmest month is July, and the coldest month is January, and both months showed increased temperatures of 0.60 ℃. Comparison results revealed that Guangzhou is not the only city which scored increased highest temperatures; other nearby cities including Heyuan, Shantou and Shaoguan also scored increased highest temperatures. The survey reveals that the majority of respondents (75%) perceived the increased frequency of extreme weather, including typhoons, heavy rainfall and multiple days of hot weather, such as higher temperatures and an increased number of hot days. In the responses to the questions related to the heat island effect, more than 80% of residents are aware of the existence of the heat island and its impacts. People believe that the primary causes of the urban heat island problem are industrial production and anthropogenic heat generated by the city. These results will be helpful to local and national policy and decision makers to revise and/or develop new strategies to improve the environment and quality of life in coastal megacities, particularly Ganzhou.

Joint Use of Optical and Radar Remote Sensing Data for Characterizing the 2020 Aniangzhai Landslide Post-Failure Displacement

The ancient Aniangzhai (ANZ) landslide in Danba County, Sichuan Province of southwest China was reactivated after a series of complex hazard events that occurred in June 2020. Since then, and until June 2021, emergency engineering work was carried out to prevent the further failure of the reactivated landslide. This study investigates the potential of joint use of time series Interferometric Synthetic Aperture Radar (InSAR) and optical pixel offset tracking (POT) to assess deformation characteristic and spatial-temporal evolution of the reactivated ANZ landslide during the post-failure stage. The relationships between sun illumination differences, temporal baseline of correlation pairs and the uncertainties were deeply explored. Surface deformation along the line-of-sight (LoS) direction was retrieved by the time series InSAR processing with the two Sentinel-1 datasets, revealing a maximum deformation rate up to 190 mm/year. The large horizontal displacements were also detected from the POT processing using 11 optical images acquired by the PlanetScope satellite (3 m spatial resolution), showing a significant increase of about 24 m between 24 June 2020 and 11 June 2021. The time series analysis from the InSAR and optical POT results revealed that the reactivated ANZ landslide body is gradually slowing down to a steady deformation status since its occurrence in August 2020, indicating the effectiveness of engineering work on the prevention of further landslide. A slight acceleration was detected from both InSAR and optical POT time series analysis between May 2021 and June 2021, which could be caused by the increased rainfall in May 2021.

Cluster landslides and associated damage in the Dima Hasao district of Assam, India due to heavy rainfall in May 2022

Cluster landslides and associated damage in the Dima Hasao district of Assam, India due to heavy rainfall in May 2022

Productivity of Short-Rotation Poplar Crops: A Case Study in the NE of Romania

In Romania, the productivity of the new clones of hybrid poplar has not been tested in recent years. This case study aims to fill a gap on the productivity map of the new poplar clones, estimating, by biomass measurements, the productivity of two clones (AF2 and AF8) with different planting densities (from 1333 trees·ha−1 to 2667 trees·ha−1). The short-rotation woody crops (SRWCs) were established in homogeneous conditions, in North-East (NE) Romania and the northern part of Suceava County. Using a specifically developed method, biomass production was estimated using destructive methods, with 190 poplar trees being harvested, measured, and weighed to compute the accumulated biomass for each growing season The biomass production of the crops with 1667 trees·ha−1 planting density highlighted significant differences in productivity in favour of the AF2 clone after five growing seasons. The crops shared similar annual growth patterns, and the stem biomass represents approximately 73–80% of the total biomass of the trees. The second research question concerning planting density influence on productivity showed fluctuations of biomass accumulations at different planting densities (1333 trees ha−1, 1667 trees ha−1 and 2667 trees ha−1) for a 5-year rotation. The outcomes emphasized the influence of the annual weather conditions—primarily the rainfall in May–June—on poplar growth, showing that productivity also depends on the genotype, density and biotic disturbances.

Seasonal Prediction for May Rainfall over Southern China Based on the NCEP CFSv2

In this study, we assess the prediction for May rainfall over southern China (SC) by using the NCEP CFSv2 outputs. Results show that the CFSv2 is able to depict the climatology of May rainfall and associated circulations. However, the model has a poor skill in predicting interannual variation due to its poor performance in capturing related anomalous circulations. In observation, the above-normal SC rainfall is associated with two anomalous anticyclones over the western tropical Pacific and northeastern China, respectively, with a low-pressure convergence in between. In the CFSv2, however, the anomalous circulations exhibit the patterns in response to the El Niño-Southern Oscillation (ENSO), demonstrating that the model overestimates the relationship between May SC rainfall and the ENSO. Because of the onset of the South China Sea monsoon, the atmospheric circulation in May over SC is more complex, so the prediction for May SC rainfall is more challenging. In this study, we establish a dynamic-statistical forecast model for May SC rainfall based on the relationship between the interannual variation of rainfall and large-scale ocean-atmosphere variables in the CFSv2. The sea surface temperature anomalies (SSTAs) in the northeastern Pacific and the central-eastern equatorial Pacific, and the 500-hPa geopotential height anomalies over western Siberia in previous April, which exert great influence on the SC rainfall in May, are chosen as predictors. Furthermore, multiple linear regression is employed between the predictors obtained from the CFSv2 and observed May SC rainfall. Both cross validation and independent test show that the hybrid model significantly improve the model's skill in predicting the interannual variation of May SC rainfall by two months in advance.

Close Linkage of the South China Sea Summer Monsoon Onset and Extreme Rainfall in May over Southeast Asia: Role of the Synoptic-Scale Systems

Abstract Based on multiple datasets and methods, this study reveals a close relation between the South China Sea summer monsoon (SCSSM) onset and the occurrence frequency of extreme rainfall over Southeast Asia (including the Indochina Peninsula, Hainan Island, and the Philippines) in May. Specifically, an early SCSSM onset tends to be accompanied by a higher chance of extreme rainfall over Southeast Asia, while a late SCSSM onset is likely to coincide with less heavy rainfall in May. It is suggested that the amplitude of tropical synoptic-scale systems may play an important role in the linkage between the SCSSM onset and the extreme rainfall over Southeast Asia. Accompanying an early SCSSM onset, anomalous cyclonic circulation appears over the SCS and Philippine Sea, which tends to increase the quantity of midtroposphere moisture via moisture advection and Ekman pumping. Besides, the barotropic energy conversion (from mean kinetic to eddy kinetic energy) associated with this anomalous cyclone will facilitate the development of the synoptic-scale systems. The vertical easterly wind shear accompanying an early SCSSM onset will confine the synoptic-scale wave train to the lower troposphere, which is also favorable for its growth. Once these synoptic-scale systems develop, the baroclinic process (from eddy available potential energy to eddy kinetic energy) will further promote their development. As such, the intensity of synoptic-scale systems is much stronger in early than late SCSSM onset years. The increased moisture and vigorous synoptic-scale systems further lead to an increase in the occurrence of extreme rainfall over Southeast Asia.

Modeling the response of sesame (Sesamum indicum L.) growth and development to climate change under deficit irrigation in a semi-arid region

The future climate outlook was based on a combination of CCMs based on three Representative Concentration Pathway (RCP) scenarios including RCP 2.6, RCP 4.5 and RCP 8.5 for the future period of 2021–2051. The results showed an increase of the average Tmax in June, July and August (averaged by 1.8°C compared to the observed period) and a decrease in rainfall in May to September (averaged by 30.76 mm compared to the observed period under all three scenarios. Estimation of phenological stages of sesame under different scenarios showed that with increasing Tmax in April and May, the beginning of flowering, grain filling and physiological maturity was accelerated, also with increasing temperature from June to August the duration of the phenological stages was decreased. The effect of deficit irrigation (DI, supplying of 50% plant water requirement) on sesame phenological stages was not significantly different from full irrigation (FI). Simulation of canopy cover evolution (CC) and dry matter accumulation using the AquaCrop model revealed that the length of the late-season and the mid-season stages, have the greatest liability to be changed under the future climate change. Under the studied scenarios, the beginning of sesame growing season will accelerate from 9 to 11 days, which makes possible delayed sowing of sesame. The average of biomass (B) produced under three scenarios in DI and FI conditions were 17920 and 17241 kg ha-1, and the average of grain yield (GY) was 2905 and 3429 kg ha-1, respectively, which shows an increase by 31.5% and 28.7% of B, 18.4% and 39.5% of GY, compared to the observations (year 2016). The results revealed that under the future climate (except for RCP8 scenario), DI strategy can be used without reducing the GY of sesame due to the very little reduction (1.2%) in GY under DI compared to FI.

High Rainfall May Induce Fungal Attack of Hemlock Woolly Adelgid (Hemiptera: Adelgidae) Leading to Regional Decline.

Hemlock woolly adelgid (HWA; Adelges tsugae Annand (Hemiptera: Adelgidae)) is the cause of widespread mortality of Carolina and eastern hemlock (Tsuga caroliniana Engelmann and T. canadensis (L.) Carrière) throughout the eastern United States (U.S.). Since its arrival in the northeastern U.S., HWA has steadily invaded and established throughout eastern hemlock stands. However, in 2018, anecdotal evidence suggested a sharp, widespread HWA decline in the northeastern U.S. following above-average summer and autumn rainfall. To quantify this decline in HWA density and investigate its cause, we surveyed HWA density in hemlock stands from northern Massachusetts to southern Connecticut and analyzed HWA density and summer mortality in Pennsylvania. As native fungal entomopathogens are known to infect HWA in the northeastern U.S. and rainfall facilitates propagation and spread of fungi, we hypothesized high rainfall facilitates fungal infection of aestivating nymphs, leading to a decline in HWA density. We tested this hypothesis by applying a rain-simulation treatment to hemlock branches with existing HWA infestations in western MA. Our results indicate a regional-scale decline and subsequent rebound in HWA density that correlates with 2018 rainfall at each site. Experimental rain treatments resulted in higher proportions of aestivating nymphs with signs of mortality compared to controls. In conjunction with no evidence of increased mortality from extreme winter or summer temperatures, our results demonstrate an indirect relationship between high rainfall and regional HWA decline. This knowledge may lead to better prediction of HWA population dynamics.

Effects of harvest intervals and seeding rates on dry matter yield and nutritive value of alfalfa cultivars.

Maturation process of alfalfa (Medicago sativa L.) could be prevented by the reduction of lignin content in terms of conventional breeding or transgenic technology. Alfalfa could exhibit higher leaf/stem ratio, with a concern of yield loss. The objective of this study was to compare forage yield and nutritive value of low lignin alfalfa and two reference varieties subjecting to two harvest intervals and three seeding rates. The experimental design was a randomized complete block in a split-split plot arrangement with four replicates, where harvest intervals (28-day and 35-day) were assigned to whole plots, seeding rates were subplots, and varieties were sub-subplots. The weighted mean nutritive value was applied to two production years of 2016 and 2017. Hi-Gest 360 (low lignin alfalfa) provided similar yield potential and increased nutritive value compared to two reference varieties. Over a two-year production period, alfalfa harvested at every 28-day interval provided more economic returns than those at 35-day interval. For the seeding year and first production year, five cuts made by the 28-day interval produced more yield than four cuts by the 35-day interval. Due to limited rainfall in May 2017, a sharp drop of the first cutting overturned the advantage of the five-cut system. Shorter intervals between harvests generally increased crude protein (CP) concentrations. The differences of relative feed value (RFV) between two harvest intervals tended to be great during the first and second cuttings. Overall, harvest interval had a large effect on nutritive value and a more significant effect on alfalfa dry matter yield than variety selection. Seeding rate did not affect alfalfa yield and nutritive value.

Natural and Managed Grasslands Productivity during Multiyear in Ex-Arable Lands (in the Context of Climate Change)

Ex-arable land-use change is a global issue with significant implications for climate change and impact for phytocenosis productivity and soil quality. In temperate humid grassland, we examined the impact of climate variability and changes of soil properties on 23 years of grass productivity after conversion of ex-arable soil to abandoned land (AL), unfertilized, and fertilized managed grassland (MGunfert and MGfert, respectively). This study aimed to investigate the changes between phytocenosis dry matter (DM) yield and rainfall amount in May–June and changes of organic carbon (Corg) stocks in soil. It was found that from 1995 to 2019, rainfall in May–June tended to decrease. The more resistant to rainfall variation were plants recovered in AL. The average DM yield of MGfert was 3.0 times higher compared to that in the AL. The DM yields of AL and MG were also influenced by the long-term change of soil properties. Our results showed that Corg sequestration in AL was faster (0.455 Mg ha−1 year−1) than that in MGfert (0.321 Mg ha−1 year−1). These studies will be important in Arenosol for selecting the method for transforming low-productivity arable land into MG.

ВЛИЯНИЕ АВТОТРАНСПОРТНОГО ЗАГРЯЗНЕНИЯ НА РОСТ ЛЕСНЫХ КУЛЬТУР ЛИСТВЕННИЦЫ ЕВРОПЕЙСКОЙ

The results of an 18-year monitoring of the growth of European larch (Larixdecidua Mill.) in the zone of influence of the Moscow Ring Road (MKAD), one of the largest highways in the European part of Russia with a load of about 9 thousand cars per hour, are presented. The studies have been carried out on three trial plots located at 15, 35 and 100 m (control) from the highway. The morphometric parameters of European larch were determined 4, 8 and 18 years after planting four-year-old seedlings. Significant inhibition of European larch growth near the MKAD was revealed by height, trunk diameter, and crown parameters. The largest negative impact of the MKAD on its growth was manifested in the first 4 years after the creation of forest crops. The area of influence of the motorway on larch stands is about 40 m. Dendrochronological analysis of larch wood has showed that the total annual growth in the control section is significantly higher than in the area near the highway. Moreover, the growth of early wood in the area near the Moscow Ring Road is on average 23% higher than in the control one, the growth of late wood in the control area exceeds the growth in the area near the Moscow Ring Road by 34%. An analysis of the radial increment of European larch wood has showed that the growth of early wood is most closely related to the total amount of rainfall in May, June and July (correlation coefficient r = 0.33), of late wood to the amount of heat in August and September (r = - 0.44)

Precipitação em Maringá-PR: estatísticas descritivas, tendência de longo prazo e probabilidade de eventos extremos diários

Este artigo buscou apresentar uma visão geral sobre a precipitação registrada na Estação Climatológica Principal de Maringá (ECPM), no período de 1980 a 2018. Quatro objetivos delinearam a pesquisa: i) obtenção de estatísticas descritivas; ii) avaliação de tendências de longo prazo; iii) avaliação da distribuição de probabilidade da precipitação diária, e iv) análise dos dias consecutivos com chuvas. Além do padrão geral dos períodos úmido e seco, observou-se máximos locais de precipitação em maio e outubro. As tendências de longo prazo foram avaliadas por meio da análise de regressão linear, não se identificando tendências estatísticas significativas. Entretanto, por meio do teste de médias, verificou-se que os anos mais recentes (2013 a 2018) foram mais chuvosos do que o restante da série (1980 a 2012). A distribuição gama foi a que apresentou o melhor ajuste entre os dados analisados e a distribuição teórica. Observou-se que em maio, setembro e outubro os volumes diários estimados são superiores aos observados no restante do ano. O período com maior número de dias consecutivos de chuva é entre outubro a março. Por outro lado, os maiores volumes por evento acontecem nesses meses e em maio e setembro. Embora tenham acumulados mensais menores do que nos meses de verão, nas estações do outono e da primavera ocorrem chuvas diárias expressivas, cujos extremos são maiores do que no verão. Essa característica relaciona-se à atuação intensificada de sistemas atmosféricos de baixa pressão, principalmente cavados e sistemas frontais precoces ou tardios.

Medium-Term Rainfall Forecasts Using Artificial Neural Networks with Monte-Carlo Cross-Validation and Aggregation for the Han River Basin, Korea

In this study, artificial neural network (ANN) models were constructed to predict the rainfall during May and June for the Han River basin, South Korea. This was achieved using the lagged global climate indices and historical rainfall data. Monte-Carlo cross-validation and aggregation (MCCVA) was applied to create an ensemble of forecasts. The input-output patterns were randomly divided into training, validation, and test datasets. This was done 100 times to achieve diverse data splitting. In each data splitting, ANN training was repeated 100 times using randomly assigned initial weight vectors of the network to construct 10,000 prediction ensembles and estimate their prediction uncertainty interval. The optimal ANN model that was used to forecast the monthly rainfall in May had 11 input variables of the lagged climate indices such as the Arctic Oscillation (AO), East Atlantic/Western Russia Pattern (EAWR), Polar/Eurasia Pattern (POL), Quasi-Biennial Oscillation (QBO), Sahel Precipitation Index (SPI), and Western Pacific Index (WP). The ensemble of the rainfall forecasts exhibited the values of the averaged root mean squared error (RMSE) of 27.4, 33.6, and 39.5 mm, and the averaged correlation coefficient (CC) of 0.809, 0.725, and 0.641 for the training, validation, and test sets, respectively. The estimated uncertainty band has covered 58.5% of observed rainfall data with an average band width of 50.0 mm, exhibiting acceptable results. The ANN forecasting model for June has 9 input variables, which differed from May, of the Atlantic Meridional Mode (AMM), East Pacific/North Pacific Oscillation (EPNP), North Atlantic Oscillation (NAO), Scandinavia Pattern (SCAND), Equatorial Eastern Pacific SLP (SLP_EEP), and POL. The averaged RMSE values are 39.5, 46.1, and 62.1 mm, and the averaged CC values are 0.853, 0.771, and 0.683 for the training, validation, and test sets, respectively. The estimated uncertainty band for June rainfall forecasts generally has a coverage of 67.9% with an average band width of 83.0 mm. It can be concluded that the neural network with MCCVA enables us to provide acceptable medium-term rainfall forecasts and define the prediction uncertainty interval.

Influence of weather conditions, irrigation and plant age on yield and alpha-acids content of Czech hop (Humulus lupulus L.) cultivars

This study quantifies the effects of weather conditions, irrigation, and plant age on yield and alpha-acids content of Czech hop cultivars Saaz, Sládek, Premiant and Agnus in a 25-year long period, i.e., from 1993 to 2018. The yields of Czech hop cultivars were increasing for the first three years of plant age until they stabilized and then started to decline slightly for 15 to 20 years until they reached the optimal time for replanting. The highest alpha-acids content in hop cones was achieved in the first year of cultivation, followed by a logarithmic decline in the upcoming years. Rainfall was the most significant factor that positively influenced the yield of Saaz hops with correlations of r = 0.59 and 0.61 (P < 0.01) for total seasonal rainfall (April–August), 0.65 (P < 0.001) and 0.60 (P < 0.01) for daily rainfall above 3 mm, 0.37 (P < 0.05) and 0.58 (P < 0.01) for rainfall in May and 0.50 (P < 0.01) and 0.32 (P < 0.05) in July in the Saaz region and the Stekník farm, respectively. The yield of cultivars Sládek, Premiant and Agnus was not statistically influenced by the amount of precipitation, but there was a positive effect of irrigation level on yield increase with correlations 0.58 (P < 0.01), 0.55 and 0.49 (P < 0.05), respectively. High air temperatures during summer were the most significant factor that negatively influenced the alpha-acids content with the correlations ranging from –0.56 to –0.83. However, cv. Agnus showed a stable weather-independent alpha-acids content.

Individual and Combined Impacts of Tropical Indo-Pacific SST Anomalies on Interannual Variation of the Indochina Peninsular Precipitation

AbstractThis study documents interannual rainfall variations over the Indochina Peninsula (ICP) during the rainy season and individual and combined influences of tropical Indo-Pacific sea surface temperature (SST) anomalies. The rainfall variability is large along the west coast in May–June, along the west coast and over the eastern mountains in July–August, and along the central Vietnam coast in September–November. More rainfall in May–June, July–August, and October–November occurs in the La Niña decaying years, La Niña decaying years and/or El Niño developing years, and La Niña developing years, respectively. The May–June rainfall variation along the west coast is associated with equatorial central-eastern Pacific (EP), south Indian Ocean, and western North Pacific SST anomalies. The July–August rainfall variation along the west coast and over the eastern mountains is related to equatorial central Pacific and tropical southeastern Indian Ocean SST anomalies. The October–November rainfall variation along the central Vietnam coast is affected by EP and tropical western Indian Ocean SST anomalies. The EP and tropical western Indian Ocean SST influence is through anomalous Walker circulation. The south Indian Ocean SST influence is via cross-equatorial flows. The tropical southeastern Indian Ocean SST influence is via an anomalous cross-equatorial overturning circulation. The equatorial central Pacific and western North Pacific SST influence is via a Rossby wave–type response. The analysis illustrates the importance of combined effects of regional SST anomalies on the ICP precipitation variation in different stages of the rainy season. Numerical experiments with SST anomalies imposed in different regions confirm the combined effects of the Indo-Pacific SST anomalies on the ICP rainfall variation.

Bias Adjustment of Satellite Precipitation Estimation Using Ground-Based Observation: Mei-Yu Front Case Studies in Taiwan

The Global Satellite Mapping of Precipitation (GSMaP) was used to estimate the accumulated rainfall in May from the Mei-Yu front in Taiwan. Rainfall estimation from GSMaP during 2002–2017 were evaluated using more than 400 local gauge observations, collected from the Taiwan Central Weather Bureau (CWB). Studies have demonstrated that the GSMaP rainfall estimation estimates can be biased, depending on the target region, elevation, and season. In this experiment, we have evaluated GSMaP over three elevation ranges. The GSMaP systemic errors for each elevation range were identified and corrected using regression analysis. The results indicated that GSMaP estimation can be improved significantly through adjustment over three elevation ranges (elevation less than 50 m, elevation of 50–100 m, and elevation higher than 100 m). For these three elevation ranges, the correlation coefficient between the GSMaP estimations and CWB rainfall data was 0.76, 0.78, and 0.59, respectively. This indicated that the GSMaP estimation was more accurate for low-elevation regions than high-elevation regions. After the proposed approaches were employed to correct the errors, the bias errors were respectively improved by 5.64(13.7%), 7.33(38.4%) and 10.52(31.2%) mm for low-, mid- and high-elevation regions. This study demonstrated that the local correction approaches can be used to improve GSMaP estimation of Mei-Yu rainfall in Taiwan.