Rainfall In July Research Articles

Understanding the Forcing Mechanisms of the 1931 Summer Flood along the Yangtze River, the World’s Deadliest Flood on Record

Abstract The 1931 Yangtze River flood in eastern China, which had an associated death toll of over 2 million, is regarded as one of the world’s deadliest natural disasters on record. However, due to the lack of meteorological data before the 1950s, the causes of this event are rarely investigated. Here, we combine multiple lines of evidence from recently available historical observations, reanalysis datasets, and atmospheric general circulation model simulations driven by historical sea surface temperatures (SSTs) that cover the early twentieth century to reveal the physical mechanisms underlying this flood. We find that the flooding in 1931 along the Yangtze River valley was dominated by July rainfall. Although the rainfall totals in July 1931 were not the largest in history (ranking second over the past century), the totals exceeded those for many other pluvial years between 1951 and 2010 in terms of its persistence, which was associated with a steady western Pacific subtropical high (WPSH). The flooding resulted from the combined effects of tropical El Niño–related SST forcing and extratropical wave activities over the Eurasian continent. On the one hand, warm SST anomalies in the tropical Indian Ocean following an El Niño event led to the southwestward extension of the WPSH. On the other hand, the southward shift of the westerly jet due to extratropical wave activities prevented the normal northward movement of the WPSH typical in July. Additionally, the impact that the preceding springtime precipitation and soil moisture had on the summer flood of 1931 is also discussed.

Unprecedented July Rainfall in North China in 2021: Combined Effect of Atlantic Warming and Arctic Sea‐Ice Loss

AbstractRecord‐breaking July‐mean precipitation hit North China in 2021, resulting in huge economic losses and human casualties. The prevailing easterlies over the southern flank of a remarkable anomalous anticyclone centered over the Kuril Islands transported sufficient water vapor into North China, resulting in persistent downpours on the windward side of the North China Plain. The anomalous anticyclone was a portion of the Eurasian Rossby wave trains. The record‐high Atlantic sea surface temperature anomalies induced the Rossby wave trains, which ended with an anomalous anticyclone over the Kuril Islands; meanwhile, the record‐low sea‐ice concentration over the Laptev–East Siberian Seas reinforced the anomalous anticyclone. Therefore, the combined effect of Atlantic and Arctic thermal forcings caused the record‐breaking July‐mean rainfall in North China in 2021. Using these two boundary layer forcings as independent predictors to run a multiple regression model produced encouraging hindcasting skills.

Influencing factors in the stagnation of the Baiu front that induced heavy rainfall in July 2020 over Kyushu, Japan

The influencing factors of the long-term stagnation of the Baiu front that induced heavy rainfall in July 2020 over Kyushu, Japan, were examined. In July 2020, the position of the Baiu front from a weather chart at 130° E remained stationary over Kyushu for 20 days, and that was the longest from 2002 to 2021. By examining a certain index of the Yellow Sea High (YSH), which is a necessary condition for Baiu front stagnation near Kyushu, it was confirmed that in 2020, a positive high-pressure anomaly persisted over the Yellow Sea until the end of July. The YSH maintenance was due to the significant negative sea surface temperature (SST) anomaly over the Yellow Sea. The significant negative SST anomalies in the Yellow Sea were due to vertical mixing in ocean mixed layer in response to the strong winds of the extratropical cyclones. A rapid SST decrease ranging from 0.5 to 1.5 °C/day was repeatedly occurred by ocean mixed layer deepening in association with the passage of the extratropical cyclones. The anomalous long-term stagnation of YSH due to the negative SST anomalies could have caused the Baiu front to remain stagnant over Kyushu until the end of July.

Different Characteristics and Drivers of the Extraordinary Pakistan Rainfall in July and August 2022

The unprecedented and long-lasting abnormal monsoon rainfall attacked Pakistan in the summer of 2022, causing severe flooding. This study investigated the sub-seasonal characteristics and mechanisms of this distinctively extreme precipitation event. The historical rainfall in July and August and extreme precipitation mainly occurred in northern Pakistan. Both the monthly rainfall in July and August 2022 and the extreme precipitation during the summer were far exceeding the historical record and involved unique spatial distribution. The rainfall in July 2022 is nationwide and mainly located in northern Pakistan, while the rainfall in August and extreme precipitation occurred in southern Pakistan. Different physical processes are responsible for the precipitation in July and August 2022. In July, the South Asian high (SAH) and Iranian high extended eastward. Meanwhile, the anticyclonic circulation anomalies occurred in northwestern Pakistan and the easterly winds enhanced in the south side of the Tibetan Plateau (TP), which strengthened water vapor transporting from the Bay of Bengal and cooperated with the cyclonic system over the Arabian Sea to enhance the precipitation over Pakistan. In August, the SAH further extended eastward and the Western Pacific Subtropical High extended westward to the TP. Meanwhile, the European blocking (EB) developed, and a deep trough appeared over northwestern Pakistan. This weakened the easterly flow along southern TP but enhanced the southerly flow accompanying the cyclone over the Bay of Bengal and the Arabian Sea, and thus guided the water vapor transporting to southern Pakistan and enhanced the precipitation. The extreme precipitation in July was mainly attributed to the unusually strong Indian monsoon, while the extreme precipitation in August was the result of a combination of the Indian monsoon and EB. The study provided important information about extreme precipitation in Pakistan, which will help policymakers take measures to deal with the effects of flooding.

Skilful Forecasts of Summer Rainfall in the Yangtze River Basin from November

Variability in the East Asian summer monsoon (EASM) brings the risk of heavy flooding or drought to the Yangtze River basin, with potentially devastating impacts. Early forecasts of the likelihood of enhanced or reduced monsoon rainfall can enable better management of water and hydropower resources by decision-makers, supporting livelihoods and major economic and population centres across eastern China. This paper demonstrates that the EASM is predictable in a dynamical forecast model from the preceding November, and that this allows skilful forecasts of summer mean rainfall in the Yangtze River basin at a lead time of six months. The skill for May–June–July rainfall is of a similar magnitude to seasonal forecasts initialised in spring, although the skill in June–July–August is much weaker and not consistently significant. However, there is some evidence for enhanced skill following El Niño events. The potential for decadal-scale variability in forecast skill is also examined, although we find no evidence for significant variation.

Impact assessment of climate change on water resources of the Kokcha watershed: a sub-basin of the Amu Darya river basin in Afghanistan

Abstract Climate change is one of the most concerning issues which mostly impacts water resources. This study aimed to investigate the Kokcha watershed under the effects of climate change. The study was performed utilizing the Soil and Water Assessment Tool (SWAT) considering the Representative Concentration Pathway (RCP4.5 and RCP8.5) scenarios in the periods of 2050–2059 and 2090–2099. The Model for Interdisciplinary Research on Climate (MIROC5) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) was used to prepare future climate data. The temperature indicated a rising of +2.47 and +2.85 °C in 2050–2069 considering RCP4.5, and +3.38 and +5.51 °C based on the RCP8.5 scenario through 2080–2099. Precipitation showed a −30 and −17.17% decrease based on RCP4.5, and a decrease of −9.28 and −4.52% considering RCP8.5 in the mentioned periods, respectively. The historical runoff peak shifted a month earlier with a −54.56 and −25.98% decrease considering RCP4.5 and a −29.18 and −6.45% based on the RCP8.5 scenario in the mid and end of the century accordingly. Alternatively, a second river flow peak takes shape due to rainfall in July. This study's result can be used to adapt water management to climate change in the Kokcha watershed and similar regions.

Large-scale background and role of quasi-biweekly moisture transport in the extreme Yangtze River rainfall in summer 2020

A severe flooding hit southern China along the Yangtze River in summer 2020. The floods were induced by extreme rains, and the associated dynamic and thermodynamic conditions are investigated using daily gridded rainfall data of China and NCEP-NCAR reanalysis. It is found that the June–July rainfall over the Yangtze River Basin (YRB) experienced pronounced subseasonal variation in 2020, dominated by a quasi-biweekly oscillation (QBWO) mode. The southwestward-moving anomalous QBWO circulation was essentially the fluctuation of cold air mass related to the tropospheric polar vortex or trough-ridge activities over the mid-high latitude Eurasian in boreal summer. The southwestward-transport of cold air mass from mid-high latitudes and the northeastward-transport of warm and moist air by the strong anomalous anticyclone over the western North Pacific provided important large-scale circulation support for the extreme rainfall in the YRB. The analysis of streamfunction of water vapor flux demonstrates that a large amount of water vapor eastward zonal transport from the Bay of Bengal and Indo-China and northward transport from the South China Sea provided the background moisture supply for the rainfall. The quasi-biweekly anomalies of potential and divergent component of vertically integrated water vapor flux played an important role in maintaining the subseasonal variability of rainfall in June–July of 2020. The diagnosis of moisture tendency budget shows that the enhanced moisture closely related to the quasi-biweekly fluctuated rainfall was primarily attributed to the moisture convergence. Further analysis of time-scale decomposition in the moisture convergence indicates that the convergence of background mean specific humidity by the QBWO flow and convergence of QBWO specific humidity by the mean flow played dominant roles in contributing to the positive moisture tendency. In combination with adiabatic ascent over the YRB induced by the warm temperature advection, the boundary layer moisture convergence strengthened the upward transport of water vapor to moisten the middle troposphere, favoring the persistence of rainfall during June–July. The vertical moisture transport associated with boundary layer convergence was of critical importance in causing low-level tropospheric moistening. By comparison, the horizontal moisture advection played a secondary important role in the quasi-biweekly oscillation of rainfall in June–July 2020.

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.

Advanced optimisation in pilot-scale trial and emergency pre-treatment design to produce safe drinking water

Following severe drought in 2018-19, bushfires in late 2019, and three successive extreme rain events between 2020 and 2022, the water quality in Warragamba Dam, the largest water source in Sydney, has significantly deteriorated. This resulted in a turbidity of >110 NTU and a true colour of >100 CU420, representing a significant increase of suspended particles and natural organic matter respectively in raw water, after heavy rainfall in July 2022. Through advanced testing and optimisation at the pilot-scale contact filtration plant and designing an emergency pre-treatment strategy, Sydney Water was able to produce safe drinking water (turbidity <0.20 NTU) from full-scale Water Filtration Plants (WFPs) that have contact filtration technology, to avoid potential severe impacts on 85% of Sydney’s water supply and ensure drinking water met Australian Drinking Water Guidelines, while water quality remained outside the design envelope of the plants. The novel optimisation in a pilot-scale contact filtration plant for increased suspended particles (turbidity) and natural organic matter (true colour) in raw water caused by extreme events is discussed in this paper. The increase of true colour and dissolved organic carbon (DOC) represents a significant increase of natural organic matter (NOM) in the raw water due to extreme events. The characterisation of DOC of raw water and its impact on the contact filtration water treatment process is also discussed in this paper.

Weather Conditions and Biostimulants Influence Nitrogen Acquisition from Different Sources by Soybean Plants

This study aimed to determine the influence of weather conditions (air temperature, precipitation and insolation) on the quantity of nitrogen taken up by soybean plants whose cultivation included an application of two biostimulants: Asahi and Improver, which have been approved for sale. An isotopic dilution method was used which involved an application of mineral fertilisers enriched with the isotope 15N (5%) to detect the quantity of nitrogen fixed from the atmosphere, acquired from the soil and taken up from the fertiliser. Microplots of 1 m2, organised to form larger units, were planted with soybean. The impact of meteorological conditions on the amount of nitrogen fixed by plants as influenced by the experimental biostimulants was estimated using regression trees based on the C&RT algorithm in STATISTICA 13.3. This procedure yielded regression trees which revealed that, irrespective of the test biostimulant, the quantity of nitrogen fixed from the atmosphere was mainly influenced by the air temperature in July, as indicated by the first and most significant branching of the tree. The poorest fixation of atmospheric nitrogen in plants was observed when the average 24-h air temperature in July was higher than 20.9 °C, the quantities being 20.61, 31.33 and 30.49 kg, respectively, in the control, Asahi- and Improver-treated plots. The superior nitrogen uptake from fertiliser, from 10.64 (for the control) to 14.98 kg (in the Improver-amended units), was found when the air temperatures recorded in July and June did not exceed, respectively, 20.9 and 13.15 °C, and the daily rainfall in July was up to 5.65 mm. The regression tree model associated with the quantity of nitrogen acquired by soybean plants from soil indicates that, just like atmospheric nitrogen and nitrogen taken up from fertiliser, the average daily air temperature in July was the major factor determining the first branching of the tree. When this temperature went beyond 20.9 °C, the lowest uptake of nitrogen from soil was found for control plants.

Statistical Analysis of Rainfall Data: A Case Study of Georgetown, Guyana

Rainfall is a key component for designing of many engineering projects, including canals, bridges, culverts, and road drainage systems. This research will provide useful information to water resource planners, farmers, and urban engineers for analysis of water availability and for building appropriate engineering structures. In order to calculate the appropriate input value for the design and analysis of engineering structures as well as for crop planning, a thorough statistical study is required. The Botanical Gardens raingauge station in Georgetown was selected for analysis as Georgetown experiences frequent floods. The mean, standard deviation and coefficient of variation, skewness and kurtosis of monthly and annual rainfall for a 30 year period were analyzed. According to the computed data, the rainfall pattern is unpredictable, as demonstrated by the coefficient of variation. The variability in rainfall for May, June and July are (38%, 35% and 37%) respectively are much lower than the other months. An analysis of the average monthly rainfall data shows a bi-modal yearly rainfall pattern. Various plotting position formulae and probability distribution functions were used to analyze the return period of the yearly rainfall. It was determined that the Chegodayev technique provides the best fit distribution for yearly rainfall data using the plotting position method, whilst the Gumbel’s Extreme Distribution yields the highest value for rainfall for various return periods using the probabilistic methods. Chegodayev technique also provides the best fit annual one day maximum rainfall for the plotting position methods The Chegodayev technique projects that rainfall for 5, 10, 50, 100 and 150 year return period are 2668.31 mm, 3024.23 mm, 3850.65 mm 4206.56 mm and 4414.76 mm whilst Gumbel’s Extreme Distribution projects rainfall of 2761.54 mm, 3090.30 mm, 3813.85 mm, 4119.73 mm and 4298.10 mm respectively for the same periods. It should be noted that the result from the plotting position formulae are usually good for small extrapolations as errors increases with the amount of extrapolations.

The Henan extreme rainfall in July 2021: Modulation of the northward-shift monsoon trough on the synoptic-scale wave train

The synoptic-scale wave train is a dominant pattern of the synoptic variability over the tropical western Pacific and usually affects the extreme weather over South China and Southeast Asia. Whether it could extend its influence and contribute to the Henan extreme rainfall in July 2021 still needs to be unraveled. We found that during the Henan extreme rainfall days a positively synoptic-scale vorticity disturbance dominated Henan province, China, which was embedded in the synoptic-scale wave train that originated from the western North Pacific. Moreover, the propagating pathway of this synoptic-scale wave train located northward and was likely modulated by the latitudinal location change of the monsoon trough over the western North Pacific. A northernmost displacement of the monsoon trough in July 2021 (∼23.2°N) would facilitate the synoptic-scale wave train to propagate farther northwestward via shifting the related barotropic conversion northward. Therefore, the synoptic-scale wave train from the tropics could reach Henan, provide the necessary lifting forcing, and supply abundant water vapor associated with the anomalous southerly for the occurrence of Henan extreme rainfall event. The results implicate that the pre-existing synoptic-scale wave train regulated by the location of the monsoon trough may be a potential precursor for heavy rainfalls in northern Central China.

Differences in colonization strategies of three common pioneer woody species in post mining heaps.

Willow (Salix caprea), birch (Betula pendula) and aspen (Populus tremula) are common pioneer woody species, however little is known about colonization strategies in large-scale disturbances. Here we have compared the strategies of establishment of these pioneer woody species in unreclaimed sites on a large (1957ha) spoil heap in Czechia. For all species, seedlings numbers peaked in the 17 year old (successional age - time since overburden heaping) plot, suggesting that initial soil development promotes seedling establishment while covering of the surface by litter and organic layers reduces the establishment of pioneer species. The proportion of willow decreased from the edge of the heap and analysis of the age structure suggests that willow establishment was correlated with the presence of older willows in the vicinity of willows of certain ages (13 and 23 years being particularly important). The proportion of birch increased with its distance from the heap edge, and it is correlated with suitable weather conditions in the year of establishment, mainly July rainfall. Aspen proportion does not change significantly with its distance from the heap edge and year of establishment. It correlates with the number of trees in both surrounding and climatic conditions. Detailed analysis of young trees shows that vegetative propagation by root suckers (offspring) is rare in birch. In willow they represent about half of the trees while in aspen all of the young trees were root suckers derived from older aspen trees. This indicates a different colonization strategy of individual species. Birch is capable of long-distance seed transfer, which establishes most of the population, and its establishment is highly influenced by climatic conditions. Willow spreads massively over a short distance, and its establishment is highly influenced by the presence of 21-23 year old willow individuals in the vicinity. Only few scattered trees are able to establish at longer distances, where they can later spread locally by seeds. Aspen spreads over a long distance in low numbers but when some trees are established it spreads massively locally by clones.

Causes of extreme 2020 Meiyu-Baiu rainfall: a study of combined effect of Indian Ocean and Arctic

A record-breaking Meiyu-Baiu rainfall hit East Asia in June–July 2020. The warm Indian Ocean (IO) has been identified as a primary cause, but it cannot explain the heavy rainfall in July, a striking characteristic of the 2020 Meiyu-Baiu rainfall. A remarkable retreat of Arctic sea ice in the late spring and early summer of 2020 also promoted Meiyu-Baiu rainfall by favoring North Asian blockings and cold air outbreaks. However, its importance compared with IO warming is unclear. Our result shows that the abundant moisture supply to the 2020 Meiyu-Baiu rainfall mainly stems from anomalous meridional wind convergence, while the excessive ascending motions are due to warm advection tied to enhanced mid-troposphere westerlies. AGCM experiments are used to examine the relative importance of IO warming and Arctic sea ice anomalies. In June, IO warming is responsible for the atmospheric circulation anomalies around the Meiyu-Baiu region and accounts for ~ 75% of the Meiyu-Baiu rainfall anomalies, despite the Arctic sea-ice loss explaining most circulation anomalies over Eurasian high latitudes. In July, both IO warming and Arctic sea-ice loss are necessary for meridional convergence, enhanced westerlies, and thus the heavy rainfall over the Meiyu-Baiu region. Their effects are interdependent rather than additive. Strong IO warming is rarely observed alongside severe Arctic sea-ice loss before 2020 because of their discordant interannual variations. In the future, the combined effects of IO warming and Arctic sea-ice loss on the Meiyu-Baiu rainfall may become more pronounced as their long-term trends continue.

Spatial non-stationary characteristics between grass yield and its influencing factors in the Ningxia temperate grasslands based on a mixed geographically weighted regression model

Spatial models are effective in obtaining local details on grassland biomass, and their accuracy has important practical significance for the stable management of grasses and livestock. To this end, the present study utilized measured quadrat data of grass yield across different regions in the main growing season of temperate grasslands in Ningxia of China (August 2020), combined with hydrometeorology, elevation, net primary productivity (NPP), and other auxiliary data over the same period. Accordingly, non-stationary characteristics of the spatial scale, and the effects of influencing factors on grass yield were analyzed using a mixed geographically weighted regression (MGWR) model. The results showed that the model was suitable for correlation analysis. The spatial scale of ratio resident-area index (PRI) was the largest, followed by the digital elevation model, NPP, distance from gully, distance from river, average July rainfall, and daily temperature range; whereas the spatial scales of night light, distance from roads, and relative humidity (RH) were the most limited. All influencing factors maintained positive and negative effects on grass yield, save for the strictly negative effect of RH. The regression results revealed a multiscale differential spatial response regularity of different influencing factors on grass yield. Regression parameters revealed that the results of Ordinary least squares (OLS) (Adjusted R2 = 0.642) and geographically weighted regression (GWR) (Adjusted R2 = 0.797) models were worse than those of MGWR (Adjusted R2 = 0.889) models. Based on the results of the RMSE and radius index, the simulation effect also was MGWR > GWR > OLS models. Ultimately, the MGWR model held the strongest prediction performance (R2 = 0.8306). Spatially, the grass yield was high in the south and west, and low in the north and east of the study area. The results of this study provide a new technical support for rapid and accurate estimation of grassland yield to dynamically adjust grazing decision in the semi-arid loess hilly region.

Evaluation of WRF Cumulus Parameterization Schemes for the Hot Climate of Sudan Emphasizing Crop Growing Seasons

High spatiotemporal resolution climate data are essential for climate-related impact studies. The Weather Research and Forecasting (WRF) model is widely used to downscale climate data for different regions with regional-specific physics configurations. This study aimed to identify robust configurations of the WRF model, especially cumulus parameterization schemes, for different climatic zones of Sudan. We focused on wet season (June–September) rainfall and dry season (November–February) temperature, which are determinants of summer crop and irrigated wheat yields, respectively. Downscaling experiments were carried out to compare the following schemes: Betts–Miller–Janjic (BMJ), improved Kain–Fritch (KFT), modified Tiedtke (TDK), and Grell–Freitas (GF). Results revealed that the BMJ performed better for wet season rainfall in the hyper-arid and arid zones; KFT performed better for rainfall in July and August in the semi-arid zone where most summer crops are cultivated. For dry season temperature, the BMJ and TDK outperformed the other schemes in all three zones, except that the GF performed best for the minimum temperature in December and January in the arid zone, where irrigated wheat is produced, and in the semi-arid zone. Specific parameterization schemes therefore need to be selected for specific seasons and climatic zones of Sudan.

A CHANS Approach to Investigating Post-Disaster Recovery Potential in Rural Japan

Natural disaster recovery is a critical issue in rural Japan, yet repairing infrastructure, stabilising landscapes, and aiding those displaced is exceedingly expensive. Restoration of disaster affected landscapes mainly focuses on infrastructure repair, with less attention to socio-ecological activities pre- and post-disaster. The absence of integrated socio-ecological perspectives to disaster restoration creates missed opportunities for approaches more sensitive to local needs and resources. Coupled human and natural systems (CHANS) frameworks attempt to bridge social and natural sciences with the effect that interactions between human and natural systems can emerge that might not be apparent by studying them separately. However, application of CHANS frameworks in the context of natural disaster recovery in rural Japan is limited, and more consideration of the challenges is needed. The aim of this paper is to describe the design of a CHANS project and summarize lessons learned in applying this complex framework. The CHANS project comprised four graduate student projects investigating different topics related to landslide recovery and future disaster vulnerability after the Northern Kyushu Heavy Rainfall in July 2012 event in rural Japan. For lessons learned, we suggest CHANS projects to be designed as a nested hierarchy of research questions, aims, objectives, and hypotheses to enable deeper synthesis at a higher level. Despite limitations in the design of our CHANS project, triangulation of data enabled us to conclude meaningful findings. When faced with limited resources, it is impossible to design a complex study accounting for all relevant factors, but a CHANS approach can enable integrated socio-ecological insights and foster innovative solutions for improving resource management and cost-effectiveness of disaster recovery plans.

The Mesoamerican mid-summer drought: the impact of its definition on occurrences and recent changes

Abstract. The mid-summer drought, veranillo or canícula, is a phenomenon experienced in many areas, including Mexico, Central America, and the Caribbean. It generally is experienced as reduced rainfall in July–August, in the middle of the typical rainy season (May–September). Many past studies have attempted to quantify changes in mid-summer drought characteristics during the recent past or for future climate projections. To do this, objective definitions of a mid-summer drought's occurrence, strength, and duration have been developed by many researchers. In this effort we adopt a recent set of definitions and examine the impact of varying these on the characterization of mid-summer droughts and the detected changes over the past 4 decades. We find the selection of a minimum intensity threshold has a dramatic effect on the results of both the area considered as experiencing a mid-summer drought and the changes detected in the recent historical record. The intensity chosen can affect both the magnitude and direction of changes reported in the recent observed record. Further, we find that the typical mid-summer drought pattern may not be occurring during the time it has historically; whether examining past or future changes or developing improved seasonal forecasts, the non-stationarity of its timing should be accommodated.

Timely Event Attribution of Extreme Precipitation in Japan: An Example of Heavy Rainfall in July 2020

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).CORRESPONDING AUTHOR: Hiroaki Kawase, hkawase@mri-jma.go.jpA supplement to this article is available online (10.1175/BAMS-D-21-0192.2)

Roof water harvesting: A Case study

The study was conducted at Shri Ram college, Muzaffarnagar- 251001 located at 29° 28’N, 77°41’E at 272 meters MSL. The climate of Muzaffarnagar is subtropical characterized by much hot summer and cooler winter. The average temperature of the area is 24.2°C which range from 45°C to 0.9°C. The average rainfall of the area is 929 mm. The dries month is November with 8 mm of rain and highest rainfall in July with an average 261.4 mm. Shri Ram College is spread in more than 5.7 hac lands. For this study the roof of block B having 894.14 square meter area was selected. Based on last thirty years rainfall data (maximum 40 mm rain in a day) a rain water collecting well of 36 m3 was manufactured to store water. The study indicates that from 894.14 m2 catchment area 35.78 m3 water is generated which required almost 36 m3 well size for storing the water. The 9 feet depth of collecting well with 6 feet diameter was found appropriate if 40 mm rain in a day occurs. To drain out 36 m3 water stored on the roof of 894.14 m2 area 7 pipes of 10cm diameter required. The study also found that 3x4 feet size two siltation tank may be sufficient before the rain water enters into the collecting well. The 6 inch (15 cm) perforated pipe was found suitable to percolate the water into ground.