Precipitation Analysis Research Articles

Climatology of the global summer monsoon rainy seasons: Revisited from a high-resolution satellite climate data record

Reliable information on the monsoon rainfall at finer spatiotemporal scales has always been crucial for applications in hydrometeorology, water resource management, disaster prevention, and assessment of numerical model outputs. Here, the spatial-temporal characteristics of the summer monsoon rainy seasons worldwide are revisited using a global, high-resolution, bias-corrected satellite rainfall climate data record. The Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) provides 0.25° rainfall estimates for the latitude band 60°S–60°N from 1983 to the near present. The global monsoon regimes are defined based on the annual rainfall range and the summer rainfall ratio. The onset, peak, and withdrawal of the rainy season are then determined using a concise yet pertinent rainfall parameter with universal objective criteria.Overall, six major summer monsoon regimes of the globe, the Asian Monsoon, Indonesian–Australian monsoon, North African monsoon, South African monsoon, North American and South American monsoon, are all reasonably represented by PERSIANN-CDR. The progression patterns of climatological onset, peak, and withdrawal phases of these monsoons are consistent with those reported by previous global and regional monsoon studies. Furthermore, compared with other coarser resolution satellite rainfall estimates such as the Climate Prediction Center Merged Analysis of Precipitation (CMAP), the present result is clearly in better agreement with that obtained from ground-based observations since it allows the determination of more detailed information associated with local-scale factors such as the sharp land-sea contrast, local surface heating, and topography effects. However, some “spots”, particularly over complex topography lacking ground truth validations, are revealed to have rainy season characteristics that differ substantially from those over the surrounding areas and have not been fully described by published literature. These distinct features need to be confirmed by further regional monsoon studies.

Optimization of phosphorus recovery using electrochemical struvite precipitation and comparison with iron electrocoagulation system.

A batch monopolar reactor was developed for total phosphorus (TP) recovery using electrochemical struvite precipitation. This study involves the optimization of factors using response surface methodology to maximize the TP recovery. The optimal parameters for this study were found to be a pH of 8.40, a retention time of 35 min, a current density of 300 A/m2 , and an interelectrode distance of 0.5 cm, resulting in 97.3% of TP recovery and energy consumption of 2.35 kWh/m3 . A kinetic study for TP removal revealed that at optimum operating conditions, TP removal follows second-order kinetics (removal rate constant(K) = 0.0117 mg/(m2 ·min)). The system performance was compared to the performance of an iron electrocoagulation system. The composition of the precipitate obtained during the optimal runs were analyzed using X-ray diffraction and EDS analysis. X-ray diffraction analysis of the magnesium precipitate revealed the presence of struvite as the only crystalline compound. PRACTITIONER POINTS: Electrochemical struvite precipitation has the potential to recover total phosphorus from anaerobic bioreactor effluent. Optimum conditions for phosphorus recovery was found at a pH of 8.4, retention time of 35 min, current density of 300 A/m2, and interelectrode distance of 0.5 cm. The quadratic model predicted complete (100 %) TP recovery under optimized conditions, whereas 97.3 % recovery was observed under experimental conditions. TP removal under optimum conditions followed second-order rate equation (removal rate constant(K) = 0.0117 mg/(m2 ·min)). XRD analysis of the precipitate revealed struvite as the only crystalline compound.

Toward a better understanding of uncertainty for satellite precipitation products over complex terrain with sparse rain gauge data

Satellite precipitation product quality is critical for various meteorological and hydrological applications. Products are subjected to more uncertainties in sparsely-gauged regions than in densely-gauged regions due to insufficient error correction. However, ground-truth-based validation cannot accurately quantify the spatially distributed uncertainty of satellite precipitation products over complex terrain with sparse rain gauge data. In this study, we explored a gauge-independent method, called the Three-Cornered Hat (TCH), to overcome the quantification issue and better understand the uncertainty of satellite precipitation products in such situations. Firstly, the reliability of the TCH method was explored over a topographically complex area. Then, the performance of the Soil Moisture TO RAIN-Advanced SCATterometer (SM2RAIN-ASCAT) and Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (GPM) mission (IMERG) in the Chuan-Yu region was evaluated using TCH, with the help of the China Merged Precipitation Analysis (CMPA) precipitation product as the third input. We found that: (1) The high consistency between error standard deviation (ESD) estimated by TCH and root mean square error (RMSE) estimated by ground-truth-based validation demonstrated that TCH is reliable for evaluating precipitation datasets over complex terrain; (2) The ESDs of SM2RAIN-ASCAT and IMERG had different spatial distributions, and the quality of IMERG was overall higher than that of SM2RAIN-ASCAT over a mountainous area; (3) IMERG performed better than SM2RAIN-ASCAT both at low (under 3000 m) and high elevations (over 3000 m) in most years, as well as for most main land cover types (woody savannas, mixed forests, and grasslands) in the study area. This method and these findings provide a new insight for better use of satellite precipitation products over complex terrain.

Extreme value analysis of precipitation and temperature over western Indian Himalayan State, Uttarakhand

Extreme value analysis of precipitation and temperature over western Indian Himalayan State, Uttarakhand

Investigating Drought and Flood Evolution Based on Remote Sensing Data Products over the Punjab Region in Pakistan

Over the last five decades, Pakistan experienced its worst drought from 1998 to 2002 and its worst flood in 2010. This study determined the record-breaking impacts of the droughts (1998–2002) and the flood (2010) and analyzed the given 12-year period, especially the follow-on period when the winter wheat crop was grown. We identified the drought, flood, and warm and cold edges over the plain of Punjab Pakistan based on a 12-year time series (2003–2014), using the vegetation temperature condition index (VTCI) approach based on Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data products. During the year 2010, the Global Flood Monitoring System (GFMS) model applied to the real-time Tropical Rainfall Measuring Mission (TRMM) rainfall incorporated data products into the TRMM Multi-Satellite Precipitation Analysis (TMPA) for the flood detection/intensity, stream flow, and daily accumulative precipitation, and presented the plain provisions to wetlands. This study exhibits drought severity, warm and cold edges, and flood levels using the VTCI drought-monitoring approach, which utilizes a combination of the normalized difference vegetation index (NDVI) with land surface temperature (LST) data products. It was found that during the years 2003–2014, the VTCI had a positive correlation coefficient (r) with the cumulative precipitation (r = 0.60) on the day of the year (D-073) in the winter. In the year 2010, at D-201, there was no proportionality (nonlinear), and at D-217, a negative correlation was established. This revealed the time, duration, and intensity of the flood at D-201 and D-217, and described the heavy rainfall, stream flow, and flood events. At D-233 and D-281 during 2010, a significant positive correlation was noticed in normal conditions (r = 0.95 in D-233 and r = 0.97 in D-281 during the fall of 2010), which showed the flood events and normality. Notably, our results suggest that VTCI can be used for drought and wet conditions in both rain-fed and irrigated regions. The results are consistent with anomalies in the GFMS model using the spatial and temporal observations of the MODIS, TRMM, and TMPA satellites, which describe the dry and wet conditions, as well as flood runoff stream flow and flood detection/intensity, in the region of Punjab during 2010. It should be noted that the flood (2010) affected the area, and the production of the winter wheat crop has consistently declined from 19.041 to 17.7389 million tons.

Analysis of precipitation and drought trends by a modified Mann–Kendall method: a case study of Lorestan province, Iran

Abstract In this study, to evaluate the trend of precipitation change, the Mann–Kendall method has been used. The studied area is Lorestan province located in the western part of Iran. To achieve this goal, time series of annual and monthly rainfall data were collected for different statistical periods. Moreover, in order to analyze the drought, the standard precipitation index and the non-parametric Mann–Kendall test were used. To predict the meteorological drought in this province, the monthly time series of the precipitation parameter was incorporated. The results showed that most parts of Lorestan province are facing an extreme drought and such conditions will happen again in the future. Furthermore, the amount of precipitation was predicted until 2032, and the trend of predicted precipitation data in the entire Lorestan province showed that there is a significant trend in most months. The results of the research on an annual scale showed that all stations have a significant negative trend at the level of 5%, which indicates the existence of a negative trend, or in other words, a decrease in irrigation in the studied stations. Therefore, according to the obtained results, it is necessary to plan water consumption in Lorestan province toward sustainable management.

Assessing Impacts of Flood and Drought over the Punjab Region of Pakistan Using Multi-Satellite Data Products

The Punjab region of Pakistan faced significant losses from flash flooding in 2010 and experienced a multiyear drought during 1998–2002. The current study illustrates the drought and flood conditions using the multi-satellite data products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) as well as the TRMM Multi-satellite Precipitation Analysis (TMPA) satellites with high-quality resolution in the region of Punjab during 2010–2014. To determine the drought and flood events, we used the Vegetation Temperature Condition Index (VTCI) drought monitoring approach combined with the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) to identify the warm and cold edges (WACE) in the provision of soil moisture as well as the VTCI imagery using the MODIS-Aqua data products. We assessed the 2010 flood effect on the four years (2011–2014) of drought conditions during winter wheat crop seasons. The obtained VTCI imagery and precipitation data were utilized to validate the drought and flood conditions in the year 2010 and the drought conditions in the years 2011–2014 during the winter-wheat-crop season. It is worth mentioning that over the four years (2011–2014) of the Julian day~D-041 year, the VTCI shows a stronger link with the accumulative precipitation anomaly (r = 0.77). It was found that for D-201 during the 2010 flood was the relationship was nonlinear, and in D-217, there was a negative relationship which revealed the flood timing, duration, and intensity. For D-281, a correlation (r = 0.97) was noted during fall 2010, which showed the drought and flood extreme conditions for the winter-wheat-crop season in the year 2010–2014. In regard to 2010, the Global Flood Monitoring System (GFMS) model employs the TRMM and TMPA data products to display the study region during the 2010 flood events and validate the VTCI results. This study’s spatial and temporal observations based on the observed results of the MODIS, TRMM, and TMPA satellites are in good agreement with dry and wet conditions as well as the flood runoff stream flow and flood intensity. It demonstrates the flood events with high intensity compared with the normality of flood with the complete establishment of flood events and weather extremes during the year of 2011–2014, thereby highlighting the natural hazards impacts. Our findings show that the winter wheat harvest was affected by the 2010 monsoon’s summer high rain and floods in the plain of Punjab (Pakistan).

Microstructural analysis of phase precipitation during high temperature creep in AISI 310 stainless steel

Stainless steels subjected to constant load at high temperature, such as under creep conditions, are known to develop microstructural changes including precipitation of distinct phases. The present work investigated the quantitative precipitation process in an AISI 310 stainless steel creep-tested at 650, 675 and 700 °C under a constant load corresponding to a stress of 100 MPa. The microstructural evolution was evaluated by transmission electron and scanning electron microscopies as well as X-ray diffraction and microhardness. Even after a short time of 2 h at 675 °C, Cr23C6 precipitates were nucleated inside grains. After 140 h of creep test at 700 °C, both Cr23C6 and sigma phase were found in the grain boundaries. A quantitative analysis revealed that sigma phase emerged with 2.4 vol.% at 675 °C after 22 h to an increasing volume of 15.0 vol.% at 650 °C. A microhardness increase was associated with the presence of Cr23C6 and sigma phase. After 1231 h at 650 °C a microhardness decrease was attributed to coalescence and growth of Cr23C6 precipitates.

Investigation of the mechanism of nickel hydroxide formation from nickel nitrate

Nickel hydroxides are widely used as electrochemically active substances in alkaline batteries and hybrid supercapacitors; they can be used for electrocatalysis, in electrochemical sensors, and as pigments. Knowledge of the formation mechanism of nickel hydroxides is necessary for developing and optimizing targeted synthesis methods. The thermal effects of processes in the formation of nickel hydroxide from nitrate were studied by the calorimetry method. The mechanism of precipitate formation was investigated by the method of simultaneous potentiometric (with a glass universal electrode) and conductometric titration. The nickel content in the samples obtained at the determined NaOH/Ni2+ ratios was investigated by the chemical method of trilonometry after preliminary dissolution. Calorimetric investigations showed that the reaction of nickel nitrate with NaOH was exothermic with ΔНreaction=‒28328.5 J/mol. The exothermic nature of the NaOH dilution process was revealed with ΔНdilution =‒2454 J/mol. According to the results of potentiometric titration, the formation of a basic salt of the NiOHNO3 type was not detected. Analysis of the results of conductometric titration revealed a two-stage chemical mechanism for the formation of nickel hydroxide from nitrate. At the first stage, which had a high rate, due to the liquid-phase reaction of the nickel cation with the hydroxyl anion, a primary precipitate of the composition Ni(OH)1.87(NO3)0.13 was formed. In the second stage, as a result of a slow topochemical reaction of the primary precipitate with hydroxyl anions, nitrate ions were displaced from the precipitate to form nickel hydroxide. These data are confirmed by the analysis of precipitate obtained at NaOH/Ni2+ ratios of 1.87 and 2.2: the Ni content was 52.95 % and 55.63 %, corresponding to the formulas Ni(OH)1.87(NO3)0.13∙0.68H2O and Ni(OH)2∙0.71H2O. This clearly indicated that the primary precipitate was nitrate-doped α-Ni(OH)2 and the final precipitate corresponded to the α-modification of nickel hydroxide

Characteristics of Precipitation at Haha-jima, Ogasawara (Bonin) Islands in Comparison with Those at Chichi-jima

Given the lack of studies on the characteristics of precipitation at Haha-jima, Ogasawara (Bonin) Islands, they are investigated using daily precipitation data from AMeDAS Haha-jima (August 30, 2007-December 31, 2020) and the Oki-mura Water Supply Branch of Ogasawara Village (January 1, 1978-December 31, 2017). A regression equation is produced to estimate daily precipitation at AMeDAS using data at Oki-mura for each month; then, they are applied to estimate daily precipitation at AMeDAS from January 1, 1978 to August 29, 2007. The monthly precipitation analysis for the period from January 1978 to December 2020 reveals that precipitation in February at Haha-jima decreased with a 5% significance level. In contrast, precipitation in September at Chichi-jima increased with a 5% significance level. A comparison between the histograms of daily precipitation on both islands in the former (1978-1999) and latter (2000-2020) periods reveals that in February 2000-2020, precipitation of 10-19 mm/day class on both islands decreased, along with a decrease of 20-29 mm/day class at Haha-jima. During the period September 2000-2020, the maximum daily precipitation on both islands surpassed previous records, and precipitation of 70-89 mm/day class increased on both islands. Most of the heavy daily precipitation occurred either during the approach or the passage of a tropical depression or a typhoon.

TREND ANALYSIS ON CLIMATE VARIABILITY IN KATHMANDU VALLEY

The study of temperature and rainfall spatiotemporal dynamics is critical for assessing climate change. The current changes are distinctly more rapid and not due to natural causes but by anthropogenic activities. Various studies suggest that Kathmandu is one of the urbanized and polluted cities in Nepal. The main objective of this study was to assess the trend of climate in Kathmandu. This study was based on climatic data. It utilized the data from the Department of Hydrology and Meteorology between 1991- 2020 based on Pani-Pokhari stations. Similarly, secondary data were collected from relevant literature including reports, journals, websites, and publications. linear regression analysis was performed to determine the climatic variability of the study area. The result showed that the year-wise precipitation trend was increasing at the rate of 0.07mm per year with rainfall distribution in the month of July. The seasonal trend analysis of precipitation shows that the rainfall was increasing during Monsoon and Winter while decreasing in the case of Pre-monsoon and Post- monsoon. There was an increase in both the minimum and maximum temperature at the rate of 0.0424°C/year and 0.1047°C/year respectively. The average temperature increased in the Summer and Winter seasons. Both maximum temperatures, as well as minimum temperatures, were increasing. Though the change is small, it takes no time to turn into a big one and create a serious impact on different sectors. So, immediate adaptive, as well as mitigating measures, should be taken to reduce the impacts of climate change in Kathmandu valley.

Long-term spatio-temporal variability and change in rainfall over Ghana (1960–2015)

Assessment of the change in the characteristics of precipitation for more than half a century (1960–2015) is important for determining the extent of climate change on the country Ghana, and more specifically, the Northern Savannah Agro-ecological Zone (NSAZ). This is because the change in the attributes of rainfall has a direct impact on the quality of livelihood and is crucial not only for the sustenance of natural systems but also for agriculture productivity and the supply of food. The analysis involved the determination of the Daily Precipitation Analysis (Annual Total precipitation, Number of wet days, Number of dry days, Number of wet spells, and Number of dry spells) for the period and trend analysis using Mann-Kendall test and Sen's slope estimation. The following climate extreme indices; R10mm, R20mm, R25mm, CDD, CWD, PRCPTOT, SDII were also computed to assess the level of change in rainfall characteristics for the country. It is observed that Inter-annual, decadal changes and the general trend in Total precipitation (PRCPTOT) show a decline which is higher for the country than for the NSAZ. On the other hand, NSAZ has a higher variability observed in terms of the standard deviation and the coefficient of Variation (CoefVar). There is a general drying up of the climate evident in the decline in rainfall amount (PRCPTOT) and intensity (SDII), and this pattern exhibits a latitudinal decrease from the south (5°N) to the north (11°N). We observe the decrease in PRCPT from latitude 4°N up to latitude 10°N with some exceptional years of increases, however, from latitude 10.3°N up to 11°N, there is a steep increase in the driest part of the country especially to the north east. SDII is the only precipitation indices which have a positive and significant relationship with the AMO for both national and Zone. All other indices have Negative and insignificant values of the relationship AMO. NAO has a negative correlation with all the Precipitation indices except CDD and Dry days. This indicates that as NAO increases, PRCPTOT, Wet days, CWD, R10mm, R20mm, R25mm, and SDII decreases, or vice versa.

Diverging identifications of extreme precipitation events from satellite observations and reanalysis products: A global perspective based on an object-tracking method

Extreme precipitation can trigger various natural hazards, causing catastrophic losses worldwide. As global warming accelerates, it is widely acknowledged that extreme precipitation will become more frequent and intense, calling for more accurate historical and projected precipitation estimation. Identifying extreme precipitation events is understudied particularly on the global scale, given that most studies only focus on pixel-by-pixel characteristics while ignoring the space-time continuity and evolution of extreme events. This study utilizes an object-based tracking method to track the precipitation system objects in time, extracting spatiotemporal attributes of precipitation events and investigates variable definitions of extremes for a better understanding of the performance of existing precipitation datasets. Five satellite and two reanalysis precipitation products (IMERG, GSMaP, PERSIANN-CCS, TRMM 3B42, CMORPH, ERA5, and ERA-Interim) are involved to investigate (1) the difference and similarity of those datasets in depicting the global pattern of extreme precipitation, (2) the impact of various definitions of extreme events, and (3) the trend of global extreme precipitation events. Results show that the object-based method can capture the motion of precipitation events. Different extreme definitions have a large impact on the distribution, trend, and features of extreme precipitation. The inter-comparison of extreme precipitation events from different products shows low correlation, indicating that accurately capturing the evolution of extreme events is still challenging. Reanalysis product-based analysis shows variable trends (magnitudes and signs) based on different attributes of precipitation objects and notable scale effect. Satellite precipitation products exhibit distinct inter-annual variability which could affect their hydrometeorological applications. In summary, this study leverages the object-based tracking method for comprehensive extreme precipitation analysis from the multi-dataset, multi-scale, and multi-definition perspectives, which can advance the understanding of the status and trend of global extreme precipitation.

A Meteorological Analysis from the Southern Slope of Mt. Everest, Nepal

Mt. Everest is the highest mountain in the world, with an elevation ending at 8848.86 m above sea level, providing unique opportunity for direct observation of the upper troposphere. Utilizing the data from recently established five automatic weather stations (AWSs) network along the Everest climbing route, as part of the National Geographic and Rolex Perpetual Planet Expedition to Mount Everest 2019, from June 2019 to May 2020, this study investigates the meteorological environment over the southern slope of the Mt. Everest. Precipitation, temperature, radiations (income and outgoing short wave and long wave radiation), wind speed and direction along with derived variables like Lapse Rate, Precipitation Gradient, 6.11 hPa Isoline, and zero-degree Isotherm are analyzed with the aim of understanding altitudinal variation. Precipitation is mainly concentrated in monsoon with highest in Phortse (530 mm). Analysis of temperature lapse rate shows the highest lapse rate (-5.6 ℃ km-1) in monsoon and lowest in post-monsoon (-7℃ km-1). The precipitation analysis reveals that the vertical and horizontal precipitation gradient for monsoon is -63 mm km-1 and is -8.6 mm km-1 however, during the post-monsoon, precipitation increased by 0.75mm km-1 and 4.6 mm km-1, respectively. Similarly, westerly winds dominate during winter in upper station while it’s nearly uniform for lower stations. Radiation, likewise, are highly correlated between the stations, with incoming shortwave being the highest in the upper station, South-Col. Both isoline and isotherm lines are observed at around 6000 m above sea level. The one-year data has revealed some of the interesting pictures of high-altitude meteorology, but long-term data with fewer data gaps should be required to confirm these patterns.

Evaluation of Hourly Precipitation Characteristics from a Global Reanalysis and Variable-Resolution Global Model over the Tibetan Plateau by Using a Satellite-Gauge Merged Rainfall Product

High-resolution meteorological datasets are urgently needed for understanding the hydrological cycle of the Tibetan Plateau (TP), where ground-based meteorological stations are sparse. Rapid advances in remote sensing create possibilities to represent spatiotemporal properties of precipitation at a high resolution. In this study, the hourly precipitation characteristics over the TP from two gridded precipitation products, one from global reanalysis (the fifth generation of the European Center for Medium-Range Weather Forecasts atmospheric reanalysis of the global climate; ERA5) and the other is simulated by Global-to-Regional Integrated forecast SysTem (GRIST) global nonhydrostatic model, are compared against satellite-gauge merged precipitation analysis (China Merged Precipitation Analysis; CMPA) from 27 July to 31 August 2014, and a satellite-retrieved precipitation estimate from the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (IMERG) is also evolved. Two aspects are mainly focused on: the spatial distribution and the elevation dependence of hourly precipitation characteristics (including precipitation amount, frequency, intensity, diurnal variations, and frequency–intensity structure). Results indicate that: (1) The precipitation amount, frequency, and intensity of CMPA and IMERG decrease with altitude in the Yarlung Tsangpo river valley (YTRV), but increase at first and then decrease with altitude (except for intensity) in the eastern periphery of TP (EPTP). ERA5 performed well on the variation of precipitation amount with altitude (especially in EPTP), but poorly on the frequency and intensity. GRIST is the antithesis of ERA5, but they all overestimate (underestimate) the frequency (intensity) at all heights; (2) With increasing altitude, the diurnal phase of precipitation of CMPA and IMERG shifted from night to evening in the two sub-regions. IMERG’s diurnal phase is 1 to 3 h earlier than CMPA’s, and the discrepancy decreases (increases) as the altitude increases in YTRV (EPTP). The diurnal phase of precipitation amount and frequency in ERA5 and GRIST is significantly earlier than CMPA, and the frequency peaks around midday except in the basin. GRIST’s simulation of the diurnal variation in intensity at various altitudes is consistent with CMPA; (3) ERA5 and GRIST overestimate (underestimate) the frequency of weak (intense) precipitation, with ERA5’s deviance being the most severe. The deviations increased with altitude. These findings provide intensive metrics to evaluate precipitation in complex terrain and are helpful for deepening the understanding of simulated biases for further improving performance in high-resolution simulation.

Evaluation of the GPM IMERG product at the hourly timescale over China

More-accurate satellite-based precipitation data are required for the study of hydrological and meteorological phenomena in the face of the rapidly changing climate. In this study, we evaluated IMERG V06 Final Precipitation product (IMERG-F) of the Global Precipitation Measurement (GPM) mission based on China Merged Precipitation Analysis (CMPA) data at the hourly timescale for the period from 2008 to 2017. Results indicated the following: (1) The spatial distribution of precipitation is highly consistent between the CMPA and IMERG product. However, precipitation and precipitation frequency ratios in the IMERG data are both overestimated, by 0.1–0.3 mm/h and 5%–15%, respectively. IMERG product has better ability to estimate precipitation in the east and south of China than in the west of China. The precipitation error is larger during nighttime than daytime, while the frequency ratio error is smaller during nighttime than daytime. (2) The time of maximum precipitation is more consistent between the two products than the time of maximum frequency ratio. The time of maximum precipitation is later in the IMERG product than in the CMPA product in most regions except northwestern China, and the time of maximum frequency ratio is later in most regions. (3) Gauge density has a stronger influence on the mean error in precipitation than the mean error in frequency ratio. The findings of this study could help improve the accuracy of satellite precipitation at the hourly scale and help it become a more important tool in the field of hydrometeorology.

Cell tracking of convective rainfall: sensitivity of climate-change signal to tracking algorithm and cell definition (Cell-TAO v1.0)

Abstract. Lagrangian analysis of convective precipitation involves identifying convective cells (“objects”) and tracking them through space and time. The Lagrangian approach helps to gain insight into the physical properties and impacts of convective cells and, in particular, how these may respond to climate change. Lagrangian analysis requires both a fixed definition of what constitutes a convective object and a reliable tracking algorithm. Whether the climate-change signals of various object properties are sensitive to the choice of tracking algorithm or to how a convective object is defined has received little attention. Here we perform ensemble pseudo-global-warming experiments at a convection-permitting resolution to test this question. Using two conceptually different tracking algorithms, Lagrangian analysis is systematically repeated with different thresholds for defining a convective object, namely minimum values for object area, intensity and lifetime. It is found that the threshold criteria for identifying a convective object can have a strong and statistically significant impact on the magnitude of the climate-change signal, for all analysed object properties. The tracking method, meanwhile, has no impact on the climate-change signal as long as the precipitation data have a sufficiently high temporal resolution: in general, the lower the minimum permitted object size is, the higher the precipitation data's temporal resolution must be. For the case considered in our study, these insights reveal that irrespective of the tracking method, projected changes in the characteristics of convective rainfall vary considerably between cells of differing intensity, area and lifetime.

Bivariate Analysis of Extreme Precipitation Using Copula Functions in Arid and Semi-Arid Regions

This study analyzed extreme precipitation events, using daily rainfall data for 1966–2015. A Mann–Kendall trend test was used to evaluate trends in extreme precipitation, copula functions were applied to compute the joint return periods of extreme events, and univariate and bivariate distributions were used to determine risk. The results showed that the decrease in consecutive wet days (CWD) was significant in the west and the northwest of Iran, while the consecutive dry days (CDD) index was increasing therein. The precipitation on more than the 90th percentile (P90) very wet days and annual number of days with precipitation less than the 90th percentile threshold (D90) indices followed similar patterns, with no significant trend in most parts of Iran, but at several stations in the north, west, and northwest, their decline was extreme. Furthermore, the increase of D10 (annual number of days with precipitation less than the 90th percentile threshold) and P10 (total precipitation of D10 of a year) was extreme in the wet regions of Iran, including the north, west, and northwest areas, and also part of the center. More than 50 percent of Iran experienced a low risk level, with a return period of extreme events (CWD, CDD) of more than 27.5 years, and the joint return periods of (D10, D90), (P10, P90), and (D10, P10) pairs were less than 100 years in most regions of Iran. Due to the increasing number of dry days in the north, west, and northwest of Iran, the drought risk increased. Based on the changes in extreme precipitation indices in recent years, the findings of this study will be useful for copula-based frequency analysis under a changing environment at regional and global scales.

Impacts of urban decline on local climatology: A comparison of growing and shrinking cities in the post-industrial Rust Belt

Cities such as Detroit, MI in the post-industrial Rust Belt region of the United States, have been experiencing a decline in both population and economy since the 1970's. These “shrinking cities” are characterized by aging infrastructure and increasing vacant areas, potentially resulting in more green space. While in growing cities research has demonstrated an “urban heat island” effect resulting from increased temperatures with increased urbanization, little is known about how this may be different if a city shrinks due to urban decline. We hypothesize that the changes associated with shrinking cities will have a measurable impact on their local climatology that is different than in areas experiencing increased urbanization. Here we present our analysis of historical temperature and precipitation records (1900–2020) from weather stations positioned in multiple shrinking cities from within the Rust Belt region of the United States and in growing cities within and outside of this region. Our results suggest that while temperatures are increasing overall, these increases are lower in shrinking cities than those cities that are continuing to experience urban growth. Our analysis also suggests there are differences in precipitation trends between shrinking and growing cities. We also highlight recent climate data in Detroit, MI in the context of these longer-term changes in climatology to support urban planning and management decisions that may influence or be influenced by these trends.

A review of durability improvement in concrete due to bacterial inclusions

Since the invention of industrially produced Portland cement in the nineteenth century, concrete has been the world’s most frequently used construction material. Because of the significant CO2 emissions produced during cement manufacture and concrete maintenance and repair costs, sustainably improving concrete durability has become a topic of concern. Bacterial self-healing is a unique method that uses CaCO3 precipitation to repair cracks in concrete, thereby improving the structure’s durability. This review highlights the effect of bacterial treatment on concrete durability. The permeation properties, water absorption, and mechanical properties are assessed. Emphasis is laid on the selection of bacteria and bacteria nutrients. The paper overviews the morphological analysis of CaCO3 precipitation by bacterial concrete. Despite the benefits of bacterial technology in concrete, numerous critical concerns remain unresolved. Further investigation on nutrients is required to develop a multi-nutrient system that will improve the efficiency of bacterial precipitation since a good combination of low-cost nutrients would reduce the total cost of bacterial concrete.