Total Rainfall Amount Research Articles

Increased rainfall frequency enhances dry seasonal soil mineral-associated organic carbon in a subtropical forest

Climate models predict longer and more severe droughts, and alterations in the frequency and intensity of rainfall events. However, how changing precipitation patterns affect soil organic carbon (SOC), particulate organic carbon (POC), and mineral-associated organic carbon (MAOC) remains unclear. Here, we conducted a three-year rainfall manipulation experiment with ambient rainfall as the control, removal of half the total rainfall amount with unaltered frequency (DRA), and increased rainfall frequency with the total amounts unchanged (IRF) in a subtropical forest. The results showed that the rainfall treatments did not change SOC content or fractions during the wet season. In the dry season, DRA significantly increased topsoil POC but did not change SOC or MAOC. IRF significantly increased POC and MAOC levels. The increased MAOC was associated with the newly formed binary complexes of Fe3+, Al3+, and Ca2+, and the adsorption/precipitation of reduced short-range-ordered Fe oxides, likely derived from the enhanced reductive dissolution in the IRF treatment. Our results suggest that changes in rainfall frequency affect organo-mineral interactions more profoundly relative to the rainfall amount and that these effects are season-dependent. Therefore, moisture-sensitive geochemical processes play an essential role in SOC stabilization in subtropical forests.

Bias correction of daily precipitation from climate models, using the Q‐GAM method

AbstractClimate models are useful tools for analyzing historical and projecting future climate conditions. However, the model results tend to differ systematically from observations, particularly for parameters with complex spatial and temporal distributions such as precipitation. A combination of quantile mapping and generalized additive models (GAMs) is presented and proposed as a new method (Q‐GAM) for the bias correction of daily precipitation. Q‐GAM is demonstrated by using data from five European stations with different climate characteristics. For each station, the closest continental grid point of a EURO‐CORDEX climate model was selected for bias correction. A bootstrapping experiment is presented with over 1000 repetitions of randomly splitting the historical period 1981 to 2005 into a calibration and evaluation period. The results for all stations reveal that Q‐GAM is a straightforward, accurate and computationally efficient method for the bias correction of precipitation. In particular, the method improves the frequency of dry days and the total annual rainfall amount. This outcome is robust across stations with varying climate characteristics and also to the choice of calibration and evaluation periods. Similar results are also obtained for other precipitation characteristics such as the 0.9 and 0.95 quantiles.

Assessment of nutrient differences in detached soil particles between cropland and revegetated abandoned land

AbstractCropland (CRL) abandonment is a worldwide phenomenon of land use change with significant impacts on agro‐ecosystems. This research attempts to deepen the analysis of the positive and negative effects arising by focusing on the changes in soil properties and the amount and composition of soil particles detached after several periods of rainfall and the resulting exported sediment that occurs in abandoned areas with natural revegetation compared to CRL. The study was carried out in an agroforestry catchment with a temperate climate, on which CRL and abandoned land with natural vegetation were compared. The soil was sampled along two representative hillslopes integrating elements of the landscape and land use/land covers. Sediments were collected after seven periods in which flood events were recorded during the period July 2016 to December 2017, using artificial‐lawn mats. Soil and sediment composition (texture, soil organic carbon [SOC] and nutrients [total nitrogen and total phosphorous]) under both land uses were assessed and compared and related to rainfall characteristics using principal component analysis. Nutrient enrichment factors in the sediments compared to soils were also evaluated. The results highlight that after abandonment, SOC increased significantly, reaching contents almost three times higher than in CRL. Consequently, soil erodibility decreased, resulting in substantially lower sediment generation after erosive rainfall events. On average, sediment generation was three times lower in abandoned areas than in CRL, despite their steeper slopes. Soil total nitrogen also increased on abandoned lands, reaching values about twice as high as those in CRL. However, total phosphorous content was almost twice as high in CRL than in abandoned land posing a potential risk for water due to higher erosion rates recorded in CRL. The results confirmed the association of phosphorous with smaller particles and also demonstrated the total phosphorous‐SOC link in abandoned land. Furthermore, the effect of rainfall intensity on phosphorous mobilisation was confirmed, whilst nitrogen losses were mainly related to the total amount of rainfall recorded. In a scenario of increasing extreme precipitation, both total amount and increased precipitation intensity may exacerbate water pollution problems following nutrient loss in cultivated areas. This research contributes to identifying the impacts on agroforestry systems within the current context of converting natural areas into cultivated land, whilst in other regions revegetated natural areas are developed from abandoned agricultural land.

Large effects of fine and coarse aerosols on tropical deep convective systems throughout their lifecycle

Previous studies have shown that aerosols invigorate deep convective systems (DCS). However, the magnitude or even the existence of aerosol invigoration of DCS remains controversial. Here, we aimed to observationally quantify the full aerosol effects on DCS by tracking their entire lifecycle and spatial extent in tropical regions. We found that fine aerosols (FA) can invigorate DCS, making them taller and longer lived, and resulting in up to ×5 increase in total area and rainfall amount. In contrast, added coarse sea salt aerosols (CSA) over the ocean can inhibit the vertical development of DCS through enhancing warm rain formation, yet resulting in longer lived and extensive DCSs. Notably, combining FA and CSA generates the strongest aerosol invigoration effect at the concentrations of ~5 and ~80 μg/m³, leading up to ×10 increase in rainfall amount. Our results indicate that aerosols significantly redistribute convective precipitation and climate effects, greatly underestimated in previous studies.

Predicting flood stages in watersheds with different scales using hourly rainfall dataset: A high-volume rainfall features empowered machine learning approach

Accurate prediction of instantaneous high lake water levels and flood flows (flood stages) from micro-catchments to big river basins are critical for flood forecasting. Lake Carl Blackwell, a small-watershed reservoir in the south-central USA, served as a primary case study due to its rich historical dataset. Bearing knowledge that both current and previous rainfall contributes to the reservoirs' water body, a series of hourly rainfall features were created to maximize predicting power, which include total rainfall amounts in the current hour, the past 2 h, 3 h, …, 600 h in addition to previous-day lake levels. Notedly, the rainfall features are the accumulated rainfall amounts from present to previous hours rather than the rainfall amount in any specific hour. Random Forest Regression (RFR) was used to score the features' importance and predict the flood stages along with Neural Network – Multi-layer Perceptron Regression (NN-MLP), Support Vector Regression (SVR), Extreme Gradient Boosting (XGBoost), and the ordinary multi-variant linear regression (MLR) together with dimension reduced linear models of Principal Component Regression (PCR) and Partial Least Square Regression (PLSR). The prediction accuracy for the lake flood stages can be as high as 0.95 in R2, 0.11 ft. in mean absolute error (MAE), and 0.21 ft. in root mean square error (RMSE) for the testing dataset by the RFR (NN-MLP performed equally well), with small accuracy decreases by the other two non-linear algorithms of XGBoost and SVR. The linear regressions with dimension reductions had the lowest accuracy. Furthermore, our approach demonstrated high accuracy and broad applicability for surface runoff and streamflow predictions across three different-sized watersheds from micro-catchment to big river basins in the region, with increases of predicting power from earlier rainfall for larger watersheds and vice versa.

Changes in precipitation phases based on the multi-discrimination method in the Tibetan Plateau

Global warming is rapidly changing the precipitation structure, and the shift in precipitation phases is even more pronounced in the Tibetan Plateau (TP), a region sensitive to global climate change. The accuracy of precipitation phase discrimination is essential for studying precipitation variability. Based on the observed data from 112 meteorological stations in the study area obtained from the China Meteorological Administration (CMA) and the National Climatic Data Center (NCDC) before 1980, we compared and assessed six methods for distinguishing precipitation phases and the optimal method was determined to complete the precipitation phase data after 1980 in the study area. Subsequently, the changes in precipitation amount, intensity, and frequency were analyzed by classifying them into light, moderate, heavy, and extreme precipitation using the percentile threshold discrimination method. It found that the dynamic threshold temperature method (presented by Ding et al., 2014) was the most effective to distinguish precipitation phases in the TP, and its performance was further improved from 80.9% to 86.1% after using frequency intersection and probability guarantee methods. Precipitation was mainly concentrated in July. Meanwhile, the proportion of snowfall to total precipitation (S/P) was approximately 9%. From 1961 to 2020, the amount of total precipitation, rainfall and snowfall in the TP exhibited increasing trends, while the sleet demonstrated a persistent decline. Spatial and temporal heterogeneity existed in the changes of precipitation of different phases. The average single precipitation amount increased. Moreover, the changes in the amount and frequency of extreme precipitation were more pronounced. Increased frequency and amount of both rainfall and snowfall were distributed in the central and eastern parts of the study area with a more significant proportion. In contrast, the peripheral areas witnessed a decrease. The spatial distribution of frequency and amount of different precipitation intensities was comparable to that of the total precipitation. This study offers novel procedure into changes of precipitation phases at high altitudes, which will inform future research on climate change and water resource management.

The response of soil carbon mineralization losses to changes in rainfall frequency is seasonally dependent in an estuarine saltmarsh

Altered rainfall distribution patterns resulting from climate change have substantial effects on soil carbon (C) cycling in terrestrial ecosystems particularly in water-limited regions. However, how rainfall redistribution affects soil C mineralization (CO2 and CH4 fluxes) in humid regions such as of the coastal saltmarshes remain unclear. We conducted mesocosm experiments in an estuarine saltmarsh in the Yellow River Delta of China, where we simulated three rainfall frequency scenarios (high-frequency, medium-frequency and low-frequency) with the same total rainfall amount in the dry and wet seasons, respectively. Soil CO2 and CH4 fluxes were measured before and after rain frequency treatment during a 40-day period for each season. The decrease in rainfall frequency significantly reduced the mean soil CO2 and CH4 fluxes during the dry season, but had no effect on either flux during the wet season. The seasonal variation in the response of soil C mineralization to rainfall frequency changes could be explained by the changes in antecedent soil water and salinity conditions, soil C substrate, microbial activities and diversity. Thus, the effects of changes in rainfall frequency on soil C mineralization are regulated by season, and should be considered when predicting the future C balance of coastal wetland ecosystems. Furthermore, the shift in precipitation frequency distribution towards increasing heavy rainfall events during the dry season in this region will have a great effect on soil C losses, potentially feeding back into the soil C budget and stability in this estuarine saltmarsh.

Numerical Analysis of Seepage Field Response Characteristics of Weathered Granite Landslides under Fluctuating Rainfall Conditions

The threat and destructiveness of landslide disasters caused by extreme rainfall are increasing. Rainfall intensity is a key factor in the mechanism of rainfall-induced landslides. However, under natural conditions, rainfall intensity is highly variable. This study focuses on the Fanling landslide and investigates the effects of varying rainfall intensity amplitudes, rainfall durations, and total rainfall amounts on landslide behavior. Three experimental groups were established, and ten rainfall conditions were simulated numerically to analyze the seepage field response of the landslide under fluctuating rainfall conditions. The results indicate that (1) there are positive correlations between the final pore pressure and both the amplitude and duration of rainfall intensity; (2) the pore water pressure response in the upper slope changes significantly, initiating deformation; and (3) the total rainfall amount is the most direct factor affecting the pore pressure response and landslide deformation. Compared to long-term stable rainfall, short-term fluctuating rainstorms are more likely to trigger landslides. These findings enhance our understanding of landslide mechanisms under fluctuating rainfall, providing valuable insights for disaster prevention and mitigation.

Impact of Atlantic multidecadal variability on rainfall intensity distribution and timing of the West African monsoon

Abstract. Previous studies agree on an impact of the Atlantic multidecadal variability (AMV) on the total seasonal rainfall amounts over the Sahel. However, whether and how the AMV affects the distribution of rainfall or the timing of the West African monsoon is not well known. Here we seek to explore these impacts by analyzing daily rainfall outputs from climate model simulations with an idealized AMV forcing imposed in the North Atlantic, which is representative of the observed one. The setup follows a protocol largely consistent with the one proposed by the Component C of the Decadal Climate Prediction Project (DCPP-C). We start by evaluating model's performance in simulating precipitation, showing that models underestimate it over the Sahel, where the mean intensity is consistently smaller than observations. Conversely, models overestimate precipitation over the Guinea coast, where too many rainy days are simulated. In addition, most models underestimate the average length of the rainy season over the Sahel; some are due to a monsoon onset that is too late and others due to a cessation that is too early. In response to a persistent positive AMV pattern, models show an enhancement in total summer rainfall over continental West Africa, including the Sahel. Under a positive AMV phase, the number of wet days and the intensity of daily rainfall events are also enhanced over the Sahel. The former explains most of the changes in seasonal rainfall in the northern fringe, while the latter is more relevant in the southern region, where higher rainfall anomalies occur. This dominance is connected to the changes in the number of days per type of event; the frequency of both moderate and heavy events increases over the Sahel's northern fringe. Conversely, over the southern limit, it is mostly the frequency of heavy events which is enhanced, thus affecting the mean rainfall intensity there. Extreme rainfall events are also enhanced over the whole Sahel in response to a positive phase of the AMV. Over the Sahel, models with stronger negative biases in rainfall amounts compared to observations show weaker changes in response to AMV, suggesting that systematic biases could affect the simulated responses. The monsoon onset over the Sahel shows no clear response to AMV, while the demise tends to be delayed, and the overall length of the monsoon season enhanced between 2 and 5 d with the positive AMV pattern. The effect of AMV on the seasonality of the monsoon is more consistent to the west of 10∘ W, with all models showing a statistically significant earlier onset, later demise, and enhanced monsoon season with the positive phase of the AMV. Our results suggest a potential for the decadal prediction of changes in the intraseasonal characteristics of rainfall over the Sahel, including the occurrence of extreme events.

Comparing Different Coupling and Modeling Strategies in Hydromechanical Models for Slope Stability Assessment

The dynamic interaction between subsurface flow and soil mechanics is often simplified in the stability assessment of variably saturated landslide-prone hillslopes. The aim of this study is to analyze the impact of conventional simplifications in coupling and modeling strategies on stability assessment of such hillslopes in response to precipitation using the local factor of safety (LFS) concept. More specifically, it investigates (1) the impact of neglecting poroelasticity, (2) transitioning from full coupling between hydrological and mechanical models to sequential coupling, and (3) reducing the two-phase flow system to a one-phase flow system (Richards’ equation). Two rainfall scenarios, with the same total amount of rainfall but two different relatively high (4 mm h−1) and low (1 mm h−1) intensities are considered. The simulation results of the simplified approaches are compared to a comprehensive, fully coupled poroelastic hydromechanical model with a two-phase flow system. It was found that the most significant difference from the comprehensive model occurs in areas experiencing the most transient changes due to rainfall infiltration in all three simplified models. Among these simplifications, the transformation of the two-phase flow system to a one-phase flow system showed the most pronounced impact on the simulated local factor of safety (LFS), with a maximum increase of +21.5% observed at the end of the high-intensity rainfall event. Conversely, using a rigid soil without poroelasticity or employing a sequential coupling approach with no iteration between hydromechanical parameters has a relatively minor effect on the simulated LFS, resulting in maximum increases of +2.0% and +1.9%, respectively. In summary, all three simplified models yield LFS results that are reasonably consistent with the comprehensive poroelastic fully coupled model with two-phase flow, but simulations are more computationally efficient when utilizing a rigid porous media and one-phase flow based on Richards’ equation.

Impacts of Climate Change and Regional Variations on Future Rainfall Patterns in Thailand by Downscaling Method

In this study, we investigated the impacts of climate change on rainfall patterns in Thailand using the downscaling method. The simulation data was obtained from the Weather Research and Forecasting (WRF) model, using the Community Earth System Model (CCSM) as a boundary condition. The characteristics of rainfall were analyzed in terms of the total annual rainfall, rainfall intensity, the number of days with heavy rain, and the total amount of rainfall in each season in the future compared to the base periods. It was found that the simulation of the climate in upper Thailand was consistent with the reanalysis values, with TCC ranging from 0.6 to 0.9. The simulated annual rainfall amount is underestimated throughout the country. There are indications that rainfall will increase in average and extreme terms in some regions, including the eastern region of the Northeast, the western side of the North, and the upper part of the West. In the southern part of the country, the overall rainfall indices are expected to decrease with low confidence in almost the entire region.

Using Remote Sensing to Study Impact El Niño Southern Oscillation on Reservoir Level at Murum and Bakun Dam Hydropower, Sarawak

In the years 2015 and 2016 has happened El Niño phenomenon was one of the three worst in history that has been happened since 1908. The El Niño phenomenon is usually related to the drought in Southeast Asia, Asia Pacific, and the Caribbean. This study analyses the impact of El Niño in the year 2015/2016 on rainfall at Bakun and Murum Hydropower using the technique of remote sensing. Global Precipitation Measurement (GPM) satellite was applied to understanding, the impact of 2015/2016 El Niño on rainfall at Bakun and Murum Hydropower. The results of this study show that drought conditions are widespread have reduced the total amount of rainfall and reservoir level and led to unusually low lake levels in Bakun and Murum reservoirs. Better understand the hydrological response and the complexity of different methods. The study found the rainfall decrease 20 until 30 % from normal during neutral and reduced 25 until 30 meters above sea level the reservoir water level at Murum and Bakun dam during the El Niño 2015/2016. The impact approach can support the design of more adaptive management strategies for specific areas.

Microclimatic Variation in Miri Region (NW Borneo): Inference from Rainfall and Temperature Trends, Isotopic Signature and Air Mass Movement

Trend analysis is frequently utilised to identify the changes in meteorological and hydrologic time series data, such as rainfall and temperature. The variations in the intensity, rainfall pattern and temperature have gradually changed globally. Hence, in this study, an attempt was made to analyse the decadal rainfall and surface air temperature data to understand the microclimatic variations in the Miri coastal region of NW Borneo. A data series of records for daily total rainfall amount and daily surface temperature of 11 years from 2010 to 2021 was studied and analysed. In addition, representative rainwater and groundwater samples were collected and analysed for hydrochemical parameters and oxygen and hydrogen isotopes. A detailed literature review was carried out on rainfall patterns in Malaysia, which was used for the comparative study. Interpretation of results shows that the northeast monsoon (NEM) contributed a higher total rainfall rate with lower daily mean surface air temperature over the years compared to the southwest monsoon (SWM). The recorded data for rainfall amounts in SWM for the month of May, July, August and September were higher, particularly for the years 2010 and 2020. During NEM, a higher rainfall amount was recorded in the month of January for several years. February month has always been among the driest month in NEM, and September has been the wettest month throughout the year during SWM. The isotopic values of rainwater indicate a similar moisture source to the regional precipitation trend. Groundwater isotopes reveal the low water-rock ratio of retrograde exchange between water and primary silicate minerals in the aquifer. The moisture source of the precipitation was contributed from both oceanic and continent, affecting the rainfall intensity in this region. This study is a crucial outcome to determine the potential impacts of microclimatic variations on the rainfall patterns in the Miri coastal region.

Effects of rainfall pattern and soil surface roughness on surface–subsurface hydrological response and particle size distribution of red soil slope

Water erosion is strongly affected by rainfall pattern and soil surface roughness (SSR), the available information is inadequate to understand the influences of both on erosion processes and mechanisms. Four simulated rainfall patterns as constant (CR), increasing (IR), decreasing (DR), and rising-falling (RFR) with the same total rainfall amount (180 mm) and duration (180 min) were designed and applied to two soil surface conditions (smooth and rough) with the slope gradient of 15°. The response and generation of surface flow were positively correlated with the initial rainfall intensity of different rainfall patterns. The surface flow generation ranked as: DR > CR > RFR > IR, and the subsurface flow was the opposite. The CR pattern produced the lowest sediment yield, which was around 46.7% of the average soil loss for the varying-intensity rainfall patterns. SSR significantly promoted surface flow generation and sediment production under varying-intensity rainfall patterns, the surface flow coefficient and soil loss rate of the rough surface were 0.6%–13.1% and 3.20–11.27 g m−2 min−1 higher than that of the smooth surface. SSR inhibited the transport of sand particles and promoted the enrichment of clay particles. Under constant and variable rainfall patterns, the average content of clay particles of the rough surface was 2.8% and 0.9% more than that of the smooth surface, respectively. SSR could decrease fine particles and increase coarse particles in the eroded sediment, but only functioned under the rainfall patterns with lower initial rainfall intensity. Through comprehensively considering the effects of rainfall pattern and SSR, the stream power was the best hydraulic parameter for predicting the soil loss rate. The results are beneficial to the investigation of soil erosion in agricultural sloping farmland caused by natural rainfall events.

Rainfall‐runoff responses and hillslope moisture thresholds for an upland tropical catchment in Eastern Madagascar subject to long‐term slash‐and‐burn practices

AbstractSlash‐and‐burn agriculture is an important driver of tropical forest loss and typically results in a mosaic of land uses. However, there is little quantitative information about the hydrological effects of long‐term slash‐and‐burn agriculture and how such mosaics affect the rainfall‐runoff response at the catchment scale. We monitored streamflow responses at two points along a perennial stream in a 31.7 ha catchment in eastern Madagascar that was monitored previously between 1963 and 1972. Land cover in 2015 consisted of degraded grasslands, shrub and tree fallows at various stages of regrowth (64%), eucalypt stands for charcoal production (30%), and rice paddies and wetlands in the valley‐bottom (3%). For the majority (60%) of the events during the study period, the ratio between the total amount of stormflow and rainfall was <3%, suggesting that for these events runoff was generated in the valley‐bottom only. Events for which an antecedent soil moisture storage plus rainfall (ASI + P) threshold was exceeded had much higher stormflow ratios (up to 50%), indicating that a certain wetness was required for the hillslopes to contribute to stormflow. Stable isotope sampling for four small to moderate events indicated that stormflow was dominated by pre‐event water. Total stormflow and annual water yield in 2015 were higher than in the 1960s, despite much lower rainfall in 2015. We attribute these differences to changes in soil physical properties caused by the repeated burning and loss of top‐soil, which has resulted in a reduction in the depth to the impeding layer. The changed runoff‐processes (less infiltration, more saturation‐excess overland flow) thus affect local water resources.

Regional Drought Analysis with Standardized Precipitation Evapotranspiration Index (SPEI): Gediz Basin, Turkey

In this study, regional drought analysis was performed with the Standard Precipitation Evapotranspiration Index (SPEI) and L moments techniques by using the monthly average temperature and monthly total rainfall amounts collected from five sites in the Gediz basin in Turkey. Using the monthly average temperatures, the potential evapotranspiration (PET) amounts obtained by the Thornthwaite method and the monthly total rainfall amounts are divided into 5 different reference periods as 1, 3, 6, 9 and 12 months. Expressing the difference between rainfall and potential evapotranspiration amounts, the water balance (Di) series shows that almost all of the 9 and 12 months periods suffers from water deficiency and the 3 months period is water excessive. After determining the distributions that provide the best adaptation to the water balance series, according to the SPEI values obtained, near-normal conditions prevailed in all sites, while moderate and severe arid and humid conditions sometimes occur, while extremely humid and arid conditions are rarely seen. In the regional drought analysis using L moment techniques with the SPEI values obtained, a region of 5 sites was accepted and the irregularity and heterogeneity measures showed that the basin was acceptable homogeneous. SPEI values are generally the best fit generalized extreme values (GEV) for 1 and 3 months periods, generalized normal (GNO) for 6 months period, generalized logistics (GLO) for 9 months period, Pearson type 3 (PE3) distributions for 12 months period. According to the regional SPEI values for reference periods, it has been found near-normal in 1.11, 1.25 and 2 years, moderately humid in 1.04 years, very humid conditions for 1.01 and 1.02 years, moderately dry in 4 and 5 years, severe arid in 10 years, and extremely dry conditions in 20 and longer periods.

Land–Sea Distribution of Ground Precipitation in Mediterranean Storms

The Mediterranean basin is traditionally a hotspot where copious amounts of water vapor at low- and mid-tropospheric levels often favor atmospheric instability and the deepening of storms, leading to intense rainfall events with consequent flash floods. Moreover, this region includes sharp land–sea transitions, narrow maritime areas, and mountain chains which enhance convective precipitation. In this study, radar precipitation data were used to investigate the spatial distribution of rainfall swaths for seven severe cyclones originating over the Mediterranean Sea which produced intense flash inundation events along the western coast of Italy in the last decade (2011–2020). Based on 5 min precipitation amounts gridded at a 1 km spatial resolution, the temporal evolution of these storms displays a curvilinear path moving from sea to inland. Results show that more than half of the total precipitation for the analyzed events occurred on sea, and the total amount of storm rainfall over the marine surface exceeded that over land in four events out of the seven. Since the coastline strongly affects the rainfall pattern, we analyzed the land–sea discontinuity, which is a key factor controlling the spatial distribution of storm rates through their trajectory, where a small shift in precipitation target might smooth ground effects and mitigate flood impacts.

Changes in the dynamical, thermodynamical and hydrometeor characteristics prior to extreme rainfall events along the southwest coast of India in recent decades

Extremes in rainfall have links with atmospheric dynamics, thermodynamics, and deep cloud properties. Employing station-based gridded rainfall data, analysis product of sea surface temperature (SST), reanalysis product of dynamic/thermodynamic parameters and remotely sensed cloud properties, we demonstrate the features and evolution of rainfall extremes over the southwest coast of India (8–14°N, 75–77.5°E) during monsoon season. Analysis of the frequency and total amount of extreme rainfall reveals that the northwest coast (14–20°N) typically serves as the central node for the precipitation extremes. However, linear trends in rainfall extremes are remarkably different across the northwest and southwest coasts of India. Specifically, we noted a marked decrease in extreme rain events between 14 and 16°N along the northwest coast, while at the same time, the southwest coast emerges as a hot spot for extreme rain events. Results suggest that the evolution of rainfall extremes on the southwest coast is linked to the warming of the south-central Arabian sea (AS), enhanced SST gradient between north and south AS, and low pressure over the Bay of Bengal (BoB) four days before the event day. Under the influence of these factors, moisture-laden winds shift from the northwest coast to the southwest coast of India. Three days before the extreme precipitation, the BoB low-pressure centre advances westward and eventually merges with the trough of low along the west coast on the event day and creates a considerable increase in the mid-tropospheric vorticity. Meteorological conditions on extreme rainfall days over the southwest coast are portrayed by a significant reduction of sea level pressure, an intense flow of low-level jets from the Arabian sea and a cyclonic vortex at mid-troposphere. These elements favour a substantial rise in moist static energy (MSE) throughout the troposphere, leading to deep convective clouds with copious ice content and extreme rainfall over the southwest coast.

Changing Trends in Temperatures and Rainfalls in the Western Pacific: Guam

Pacific islands have always been at the front of the great challenge of climate change. In this study, Mann–Kendall’s tau-based slope estimator was implemented to detect statistical trends in daily maximum and minimum temperatures of 2 stations and daily rainfalls at 14 stations over Guam for the period of 1953–2021, respectively, with 17 climate change detection indices. Mann–Kendall tests were implemented to the detection indices with respect to different time frames (i.e., annual, two-seasonal, and four-seasonal). The p-values from Mann–Kendall tests were used to determine the strength of trends, and Sen’s slopes were applied for the magnitudes of trends. The temperature trend analysis results indicate that Guam’s climate is getting warmer year by year. The increasing magnitudes of a seasonal maximum of daily maximum temperatures during the dry season are 0.036 °C/year for the dry season and 0.025 °C/year for the wet season at Anderson Airforce Base, while 0.031 °C/year and 0.023 °C/year for the dry and wet seasons at Guam International Airport. Trend analyses for temperatures have indicated that temperature during April through June has been increasing rapidly compared to other seasons. Strong trends in seasonal total rainfall amounts and the number of wet days were observed from July through December. The increasing trends in extreme rainfall indices during January–March and July–September periods would aggravate water quality due to the more sediments since important ecological reserve areas and coral reef areas are linked to watersheds in southern Guam.

Understanding and Reducing Warm and Dry Summer Biases in the Central United States: Improving Cumulus Parameterization

Abstract Most climate models still suffer large warm and dry summer biases in the central United States (CUS). As a solution, we improved cumulus parameterization to represent 1) the lifting effect of small-scale rising motions associated with Great Plains low-level jets and midtropospheric perturbations by defining the cloud base at the level of condensation, 2) the constraint of the cumulus entrainment rate depending on the boundary layer depth, and 3) the temperature-dependent cloud-to-rainwater conversion rate. These improvements acted to (i) trigger mesoscale convective systems in unfavorable environmental conditions to enhance total rainfall amount, (ii) lower cloud base and increase cloud depth to increase low-level clouds and reduce surface shortwave radiation, (iii) suppress penetrative cumuli from shallow boundary layers to remedy the overestimation of precipitation frequency, and (iv) increase water detrainment to form sufficient cirrus clouds and balanced outgoing longwave radiation. Much of these effects were nonlocal and nonlinear, where more frequent but weaker convective rainfall led to stronger (and sometimes more frequent) large-scale precipitation remotely. Together, they produced consistently heavier precipitation and colder temperature with a realistic atmospheric energy balance, essentially eliminating the CUS warm and dry biases through robust physical mechanisms.