Contribution Of Rainfall Research Articles

The contribution of non‐tropical cyclone vortices to the rainfall of the Philippines

AbstractWeaker disturbances than tropical cyclones (TCs) such as tropical depressions and cold surges can significantly induce heavy rainfall and flooding events over the Philippines. However, the analysis of these disturbances including their rainfall contributions are often neglected in previous studies. As the first attempt to address this research gap, this study investigates the rainfall contribution of non‐TC vortices over the Philippines from 1979 to 2020. Only those rainfall‐producing non‐TC vortices that formed and appeared within a 500‐km radius from the Philippine coastline were examined in this study. A total of 7,686 non‐TC vortex days (50% of the total days during the analysis period) were identified. The mean rainfall contribution of these non‐TC vortices was found to be highest over the northeastern Mindanao Island (80–90% of the mean daily rainfall) and lowest over the central and western regions of Luzon Island (50–60%). Seasonal analysis of the occurrence frequency of these vortices shows that they are most frequent during the December–February (DJF) season. In this season, the rainfall contribution may increase to 50–80% of the mean daily rainfall over the whole country, while in the other seasons, the rainfall contribution may only increase to as much as 60%. Higher frequency of extreme rainfall days associated with these non‐TC vortices were also found during the DJF season. The frequency of occurrence and percentage rainfall contribution of these non‐TC vortices in relation to the different phases of the Boreal Summer Intraseasonal Oscillation (BSISO) during boreal summer (June–October) and the Madden–Julian Oscillation (MJO) during boreal winter (December–April) were also examined. Higher frequency and percentage rainfall contribution over the country were found during Phases 4–6 of both the BSISO and MJO, during which their respective active convections transition from the Maritime Continent to the western North Pacific.

X-band polarimetric radar QPE for urban hydrology: The increased contribution of high-resolution rainfall capturing

Increased population is exposed to urban flooding as a result of climate change. Flood early warning can largely reduce the loss of life and asset, while how detailed rainfall information is enough has always been a critical issue in achieving robust flood forecasting. Previous analysis has been limited by lacking high-resolution rainfall observation or a spatially-matched urban hydrological model. This study couples mature modeling technologies with comprehensive hydro-meteorological measurement, that is comprised of X-band polarimetric radar (75 m, 3 min), weather stations, and hydrometric stations, and this study further attempts to understand the rainfall spatial resolution effects and critical resolutions from a multi-scale perspective (e.g. block, district, and catchment scales). The results show that coarser resolutions always lead to underestimation of peak flows, even exceeding 40 % in the case of adopting 10 km rainfall data at the block scale. But such damping effects on discharge simulation can be largely attenuated with increased hydrological scale. In general, spatial resolutions of higher than 500 m, and 10 km are needed to obtain accurate simulation results (i.e. keep the relative bias within 20 %) at district and catchment scales, while at least 300 m for the block scale. In conclusion, refined rainfall forcing contributes to better simulation of peak flows in urban hydrological modeling, but the required rainfall spatial resolution changes with the scale of hydrological application. These findings help to better achieve the balance between rainfall observation cost and flood simulation accuracy.

Spatiotemporal trends in daily and subdaily rainfall extremes and return levels in Turkey

AbstractIn this study, we present the long‐term daily and subdaily station data of annual extreme rainfall (1970–2015) and the trend analyses in rainfall regimes in Turkey. Trends in 5, 10, 15, and 30 min, 1, 2, 6, 12, and 24 hr of extreme rainfall in seven different rainfall regimes are estimated through nonparametric tests. The trends in return levels (2, 20, and 100 years) are defined by an appropriate three‐parameter generalized extreme value distribution and are evaluated in the climatological context of rainfall regimes. Overall, from 5‐min to 2‐hr durations, magnitudes of trends in extreme rainfall constantly increase in all rainfall regimes, which may be attributed to the intensified contribution of convective rainfall as a response to warming. Trend analysis of return levels reveals that, compared with 2‐year return levels, low‐probability high‐impact extreme rainfall events generally have the lowest estimated median trends until 30‐min to 2‐hr range. A shift in the magnitudes of trends occurs generally at 30‐min and 1‐hr durations; trends of rare intense events increase at the expense of less intense extreme rainfall. Thus, the intensification of 1–2‐hr extreme rainfall events can arise from both the increasing trends of more common events in shorter rainfall durations and from the increase in the trends of low‐probability high‐impact extreme rainfall events at this range. Moreover, explicitly in continental rainfall regimes, increases in the magnitudes of the trends in 30‐min to 2‐hr duration range are accompanied by various declines in 6–24‐hr duration range. Although coastal regimes generally have increasing trend values from 5‐min to 24‐hr durations, in northern and southern clusters, changes occur in the variability of extreme rainfall and the trend values of rarer (20‐ and 100‐year return periods) extreme rainfall exhibit increases in 6–12‐hr range.

Correlations between the hydrological regime and the morphodynamic processes in the Gilort river basin

This study highlights the relationship between the dynamics of the hydrological regime in a river basin and the morphodynamic potential that appears in the context of increasing frequency and intensity of current climatic phenomena. Climate change characterized by the high frequency and intensity of torrential rains and floods, especially in the last decade, with a maximum amplitude in the summer months (June-July), alternating with periods of drought have brought to a series of geomorphological changes in the Gilort river basin. These processes are amplified by the high degree of fragmentation of the relief, by the presence of springs that feed the hydrographic network and by the important rainfall contribution to the formation of river flows. In the high mountainous area of the basin, there are a series of debris flows that have been triggered in the last ten years, during torrential rains and exceptional floods, by major changes in the land cover and by the transport of materials in the drainage section. At the exit of the mountain, the longitudinal profile of the river changes radically with the decrease of the slope, so that most of the coarse alluvium is deposited in the riverbed in the sectors of the contact depressions at the foot of the mountain. At the contact between the mountains and the Subcarpathian Depression, due to a pronounced decrease of the riverbed slope, the phenomenon of bed aggradation occurs. In this study, all these geomorphological processes are explained from the perspective of hydrological and climatic influence combined with changes in land cover.

Evaluation of IMERG Satellite Precipitation over the Land–Coast–Ocean Continuum. Part II: Quantification

Abstract To understand and manage water systems under a changing climate and meet an increasing demand for water, a quantitative understanding of precipitation is most important in coastal regions. The capabilities of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) V06B product for precipitation quantification are examined over three coastal regions of the United States: the West Coast, the Gulf of Mexico, and the East Coast, all of which are characterized by different topographies and precipitation climatologies. A novel uncertainty analysis of IMERG is proposed that considers environmental and physical parameters such as elevation and distance to the coastline. The IMERG performance is traced back to its components, i.e., passive microwave (PMW), infrared (IR), and morphing-based estimates. The analysis is performed using high-resolution, high-quality Ground Validation Multi-Radar/Multi-Sensor (GV-MRMS) rainfall estimates as ground reference at the native resolution of IMERG of 30 min and 0.1°. IMERG Final (IM-F) quantification performance heavily depends on the respective contribution of PMW, IR, and morph components. IM-F and its components overestimate the contribution of light rainfall (<1 mm h−1) and underestimate the contribution of high rainfall rates (>10 mm h−1) to the total rainfall volume. Strong regional dependencies are highlighted, especially over the West Coast, where the proximity of complex terrain to the coastline challenges precipitation estimates. Other major drivers are the distance from the coastline, elevation, and precipitation types, especially over the land and coast surface types, that highlight the impact of precipitation regimes.

The Application of an Artificial Neural Network to Quantify Anthropogenic and Climatic Drivers in Coastal Phytoplankton Shift

The overlapping effect of anthropogenic activities and climate change are major drivers for a shift in coastal marine phytoplankton biomass. Linear regression analyses are not sufficient to detect the nonlinear relationship between complex environmental factors and phytoplankton shift. Here, an Artificial Neural Network (ANN) model is applied to quantify the relative contribution of pearl oyster farming, temperature and rainfall on phytoplankton increases in Cygnet Bay, Australia. The result shows that increased oyster farming ranks among the most important factors for phytoplankton increases, with a relative importance of 54% for diatoms and 74% for dinoflagellates; temperature plays a second important role with a positive impact on diatoms (relative importance of 25%) but a negative impact on dinoflagellates (relative importance of 19%); rainfall is the least important which enhances diatom biomass only (relative importance of 21%). Our ANN analysis provides a useful approach for quantifying the complex interrelationships affecting phytoplankton shift.

Runoff Variation and Influencing Factors in the Kuye River Basin of the Middle Yellow River

In recent decades, due to climate change and human activities, the hydrological processes of many rivers in the world have undergone significant changes. As an important part of the water cycle, it is of great practical significance to identify the causes of runoff change for water resource management and planning. Taking the Kuye River and its tributaries, the Wulanmulun River and Beiniuchuan River as examples, the trend change in runoff was investigated by the Mann-Kendall trend test and mutation analysis, and the contribution of influencing factors of runoff change was quantitatively evaluated by the Budyko framework. The results showed that the annual runoff depth of the Kuye River basin and its tributaries, the Wulanmulun River basin and Beiniuchuan River basin, showed a significant decreasing trend from 1960 to 2014 (p < 0.01), and the decreasing rates were 1.03 mm/a, 1.24 mm/a and 1.50 mm/a, respectively. The abrupt change point of runoff depth in the Kuye River basin and its upstream Beiniuchuan River basin occurred in 1996, while that in the Wulanmulun River basin, another tributary, occurred in 1992. In the Kuye River basin, Beiniuchuan River basin and Wulanmulun River basin, the contributions of underlying surface change to runoff change were 89.03, 89.54, and 95.42%, respectively, followed by the contribution of rainfall, and the contribution of potential evapotranspiration to runoff change was the lowest. The change in the underlying surface (the Grain for Green Project and coal mining) is the main factor causing the decrease in runoff in the Kuye River basin.

Localized recharge processes in the NE Mekong Delta and implications for groundwater quality

Understanding recharge in the Mekong Delta is critical for the delta's groundwater resources, and requires the investigation of recharge processes at the local scale. In this study of the north eastern area of the Mekong Delta, time-series of environmental tracer data (δ18O, δ2H, major ions and 3H) and markers of rural pollution (NH4 and NO3) were used to highlight localized recharge and impacts on groundwater quality. Results highlighted new hydrological insights into recharge processes, including that the Pleistocene aquifer receives recent recharge (< 60 years), predominantly during high rainfall months (> 100 mm/month). However, due to shallow clay layers there are significant spatial variations in these recharge processes, which were observed in the seasonal fluctuation of groundwater δ18O values in groundwater. Wet season δ18O changes ranged from below analytical uncertainty (≤ 0.10 ‰) to up to 0.56 ‰, and the calculated fraction of rainfall contribution to the aquifer is ≤5 % to 16 %. Rainfall recharge via the acrisol soils results in low groundwater EC (20–55 μS/cm), acidic groundwater (pH 3.6–5.6), and may also have resulted in the low groundwater NO3 concentrations (≤ 5.3 mg NO3/L) at many sites due to adsorption, therefore delaying not reducing NO3 contamination. Site specific variations in nitrogen processes includes increased NO3 (to 29.7 mg/L) from fertiliser transfers or nitrification, and increased NH4 (to 1.4 mg/L) likely due to the recharge of irrigation waters. Unlike other recharge areas across the northern Mekong Delta, this north-eastern region provides a groundwater resource unaffected by arsenic contamination. Therefore, these results should inform on priority areas for protection from further contamination by rural anthropogenic activities.

An Integrated Hydrological Modelling Approach to Evaluate the Capacity of Keenjhar Lake by Using STELLA

Due to overexploitation and lower rainfall rates, it is essential to study the detailed water balance of the Keenjhar lake by considering the climate change impacts and higher water demands linked with the population growth. A hydrological model of Keenjhar Lake is developed based on a system dynamic approach using STELLA (Structural Thinking and Experiential Learning Laboratory with Animation). The model (STELLA) developed in the current research study comprises the following three sub-systems: population, water supply, and water demand. The hydrological and climate data for the period of seventeen years (2000–2016) is used in the current study. The monthly water budget of the Keenjhar Lake is determined by inflow components such as rainfall and the Kalri-Baghar Feeder (K.B.F) (upper) and outflow components such as evaporation, the K.B. Feeder (lower), and the Keenjhar-Gujju (K.G) canal from the lake. The water balance results revealed that the contribution of direct rainfall and the annual inflow components to the lake are 22.03% and 77.91%, respectively. Whereas the evaporation, outflow to K.B.F lower and water abstraction to the K.G. Canal constituted about 5.78%, 92.55%, and 1.57% of the total annual outflow from the lake, respectively. Moreover, the annual inflow components of the water budget of the lake showed a declining trend while the outflow components (water abstraction) intimated an increasing trend. The study results also acknowledged that the demand for water can increase from 3 × 1010 ft3/yr up to 1.2 × 1011 ft3/yr by the year 2050 (influence of overdrawing of water due to population growth), and water supply may decrease to 9.066 × 1010 ft3 (rainfall depletion due to climate change). A detailed water balance explains the main water loss components and will help in developing better water management practices and well-informed policy decisions.

Assessing Heavy Precipitation Risk Associated with Tropical Cyclones in China

Abstract Tropical cyclone precipitation (TCP), accounting for some of the most extreme rainfall events, can lead to severe flooding and landslides, which often occur together as compound natural hazards during a tropical cyclone landfall. The impact due to TCP is largely associated with its intensity and spatial extent as the storm approaches landfall. Yet it is not entirely clear how TCP intensity and spatial extent vary from one tropical cyclone to another. In this study, we employ an advanced geostatistical framework to determine the TCP intensity and spatial extent along cyclone tracks for different cyclone categories, defined using the wind speed and tropical cyclone lifetime maximum intensity (LMI) at each track point (“point intensity-LMI”). The results show that when a tropical cyclone with an LMI of a supertyphoon makes landfall and has weakened to tropical storm strength it usually produces the most intense rainfall and covers the largest spatial extent. The total TCP amount estimated using the varying spatial extent helps to determine more accurately the amount of seasonal rainfall that is from tropical cyclones in China. We also determined the rainfall trend from 1951 to 2019 for TCP and found that when compared with the inland stations the historical TCP rainfall trend in those stations near the coastline of China is significantly increasing. Significance Statement Heavy rainfall caused by tropical cyclones has caused huge direct or indirect economic losses in the coastal areas of China. This impact is particularly significant when the rainfall intensity is high and the area of heavy rainfall is extensive. Here we investigate the rainfall intensity and spatial extent by classifying and comparing the different types of tropical cyclones impacting China with varying intensities. To do this, we group the tropical cyclone tracks of the western North Pacific Ocean during the last seven decades according to the strength of wind speed across the cyclone tracks. We found that the largest areas and heaviest intensities of rainfall occur when a supertyphoon has weakened to a tropical storm at landfall. When considering all tropical cyclones and their rainfall contribution to rainfall over land stations, we found that tropical cyclone rainfall has become heavier in most coastal areas of China.

Analysis of water balance and hydrodynamics of Lake Beseka, Ethiopia

Abstract This study aims to calculate the water balance, interaction with irrigation water inflow, and hydrodynamics of Lake Beseka by a spreadsheet-based model using climatic, hydrological, multi-temporal satellite images, groundwater, and lake chemistry data. The rainfall for the catchment was estimated as 558.4 mm/year, whereas the mean evaporation was computed as 2,214 mm/year by the Penman method. The annual direct rainfall contribution to the lake was found to be 25.84 MCM (million cubic meters) with a runoff inflow in the catchment area of 37.2 MCM. This balance pointed to the mean evaporation of 108.2 MCM/year in the lake indicating that the water inflow was greater than the outflow. A major cause for the rise of the lake level was the drainage of excess irrigation water toward the lake, mainly from the Fentale Irrigation Farm. The average increment of the groundwater level in the area was 12 cm/year from 2010 to 2014. From 1998 to 2014, the electrical conductivity was reduced by 25.6%, and calcium was increased by 96%. The study outlined that appropriate irrigation drainage should be implemented in the catchment to ensure the balance between the rainfall, infiltration, and surface runoff to optimize economic and social welfare in the area.

Typhoon, rainfall and trees jointly cause landslides in coastal regions

Typhoon-induced landslides are the primary natural hazard in hilly coastal regions of South East Asia and can potentially devastate coastal communities and infrastructure. They occur at approximately the same time as typhoon strikes, showing complex failure mechanisms under the coupled action of wind, rainfall and trees. Therefore, special assessments should be performed for such geohazards. Here we elucidated the general features of typhoon-induced landslides in southeast coastal China in terms of their geological characteristics, spatial and temporal distribution, and vegetation cover characteristics. We further established a framework to investigate their possible failure mechanisms coupled to wind, rainfall and trees. Specifically, the mechanical response of trees in a typhoon was estimated through a combination of the autoregressive method (AR) and a multi-degree-of-freedom tree swaying model, while the trees and rainfall contributions were determined by calculating the cohesion attributable to roots and the soil shear strength reduction caused by the water content variation. Our results suggest that the root reinforcement disappears when the sliding surface is below the root embedded depth, and the impact of wind load is significant during the slope stability analysis. The Force 14 wind (mean wind velocity up to 45 m/s) reduces the factor of safety (Fs) of the slope by 20% when blowing downhill, and its combined contribution with rainwater infiltration will lead to a higher risk of slope failures (Fs reduction of 45% at the base of the root-soil composite). Additionally, typhoon-induced shallow slope failures are prone to develop at the base of the root-soil composite or the rock-soil interface. Our model results suggest that the impacts of wind and vegetation on the generation of landslides during a typhoon can be significant and deserve more attention in hazard assessment studies.

Southeastern United States Hydroclimate During Holocene Abrupt Climate Events: Evidence From New Stalagmite Isotopic Records From Alabama

AbstractWe present new high‐resolution absolute‐dated stalagmite δ18O and δ13C records from Alabama, southeastern United States (SE US), spanning the last 12 thousand years (ka). A local relationship between annual rainfall amount and its amount‐weighed δ18O composition exists on interannual timescales, driven mostly by an amount effect during summer and spring seasons. Based on a novel quantitative interpretation of modern rainfall isotopic data, stalagmite δ18O variability is interpreted to reflect the relative contribution of summer and spring precipitation combined, relative to combined fall and winter precipitation. Precipitation amount in the SE US increases during an interval of 500 yr coeval with the Younger Dryas and during the 8.2 ka and Little Ice Age abrupt cooling events. High precipitation during these events reflects enhancement of spring and summer precipitation by 90% combined, relative to today's conditions, while the contribution of fall and winter rainfall remained unchanged or decreased slightly. Results from this study support model simulation results that suggest increased precipitation in the SE US during Atlantic Meridional Overturning Circulation (AMOC) slowdown/shutdown. In association with Northern Hemisphere mid‐latitude cooling from the Early to mid‐Holocene, annual precipitation in the SE US decreases, a pattern distinctive from that observed during abrupt cooling events related to AMOC shifts. Long‐term hydroclimate change in the SE US is likely sensitive to summer insolation reduction as inferred to have occurred in other tropical and subtropical regions. The dynamical link between AMOC shutdown and precipitation variability in the SE US remains to be examined.

The Effects of Plant and Soil Characteristics on Partitioning Different Rainfalls to Soil in a Subtropical Chinese Fir Forest Ecosystem

The climate-induced changes in soil water patterns pose a serious threat to subtropical plantations. Mixed species stands have been advocated as an efficient way to enhance ecosystem stability. However, little is known about their possible impact on the soil water-holding capacity in the subtropics. In this study, we employed a stable hydrogen isotope to assess the contribution of rainfall to soil water (CRSW) in a pure Chinese fir (Cunninghamia lanceolata) plantation and in two mixtures of Chinese fir with Cinnamomum camphora or with Alnus cremastogyne after three different magnitudes of rainfall events in subtropical China. Furthermore, we used structure equation modeling (SEM) to quantify the relative importance of vegetation and soil properties on the CRSW. The results indicated that the CRSW did not differ among these three Chinese fir plantations after light rainfall, whereas the CRSW of moderate and heavy rainfall to soil water were 15.95% and 26.06% higher in Chinese fir plantation with Cinnamomum camphora, and 22.67% and 22.93% higher in Chinese fir plantation with Alnus cremastogyne than that in the pure Chinese fir plantation, respectively. SEM analysis showed that the vegetation biomass and soil properties significantly affected the CRSW following light rainfall, but the soil properties were the most important factors influencing the CRSW under moderate and heavy rainfall. Our findings demonstrate that the mixed conifer–broad-leaved plantation is a more effective strategy for improving the soil water-holding capacity than the pure conifer plantation in subtropical regions, which is conducive to coping with the frequent seasonal droughts and extreme precipitation events.

Biofouling initial succession on offshore artificial substrate under subtropical conditions

This study presents the initial stages of the macrofouling community on artificial substrate exposed to the offshore subtropical marine environment, and the contribution of depth (3 and 22m), exposure time (1-2-4-7-10-13-weeks), UV-radiation, rainfall, temperature, pH, salinity, water chlorophyll-a, and zooplankton supply to organism establishment. Steel substrates were placed horizontally on the structure of a pipeline monobuoy off the southern shore of Brazil (Tramandaí beach), and the ecological succession was monitored by six random removals per depth during the summer-autumn of 2011. Approximately 88.5% of the quantified settled individuals comprised fouling fauna and 11.5% vagile and sedentary fauna, although the taxa richness was higher for non-sessile invertebrates. Species richness and organism density up to four weeks were significantly higher at 3m-depth. After this period, a higher density of organisms was found at 22m, while during the whole study the species richness and diversity remained higher at 3m-depth. Zooplankton composition did not show a simultaneous temporal relationship with invertebrate recruitment at any depth; however, increasing the exposure time, the similarity between the planktonic and benthic communities also increased. Meroplankton, tychoplankton, and holoplankton were recorded on the substrates. This study showed that the depth of available substrates affects the macrofouling establishment, which is mainly associated with UV-radiation, exposure time, and ecological interspecific interactions.

A MESO-scale Rain gauge NETwork-MESONET over Mumbai: Preliminary results and applications

Mumbai, the compact megacity, the economic capital of India, is highly vulnerable to severe weather conditions, particularly related to the rainfall phenomenon. A MESO-scale rain gauge NETwork (MESONET) comprises 131 rain gauges scattered over the Mumbai metropolitan region is established to have instantaneous rainfall information. A real-time web-based rainfall data portal is set up as a public informative/awareness system that would help the public to cope with unanticipated situations caused by massive rainfall events. In this work, we provide the rationale of Mumbai MESONET and preliminary results from the observations during July–October 2019.High-resolution MESONET rainfall data are analyzed to examine the mean and associated small-scale spatiotemporal variability of rainfall over Mumbai. The results depict that the maximum contribution of rainfall is from low to moderate and heavy rainfall events. The prevalent occurrence of prolonged rainfall events of moderate to high intensity during mid-night and early morning hours is attributed to the diurnal variability of events duration. It is observed that heavy rainfall events (64–124 mm/day) occur at a sub-daily scale. Correlogram analysis of rainfall further reveals the good spatial coherence in the spatial variability of rainfall even at sub-daily scales.

Modeling and interpreting hydrological responses of sustainable urban drainage systems with explainable machine learning methods

Abstract. Sustainable urban drainage systems (SuDS) are decentralized stormwater management practices that mimic natural drainage processes. The hydrological processes of SuDS are often modeled using process-based models. However, it can require considerable effort to set up these models. This study thus proposes a machine learning (ML) method to directly learn the statistical correlations between the hydrological responses of SuDS and the forcing variables at sub-hourly timescales from observation data. The proposed methods are applied to two SuDS catchments with different sizes, SuDS practice types, and data availabilities in the USA for discharge prediction. The resulting models have high prediction accuracies (Nash–Sutcliffe efficiency, NSE, &gt;0.70). ML explanation methods are then employed to derive the basis of each ML prediction, based on which the hydrological processes being modeled are then inferred. The physical realism of the inferred hydrological processes is then compared to that would be expected based on the domain-specific knowledge of the system being modeled. The inferred processes of some models, however, are found to be physically implausible. For instance, negative contributions of rainfall to runoff have been identified in some models. This study further empirically shows that an ML model's ability to provide accurate predictions can be uncorrelated with its ability to offer plausible explanations to the physical processes being modeled. Finally, this study provides a high-level overview of the practices of inferring physical processes from the ML modeling results and shows both conceptually and empirically that large uncertainty exists in every step of the inference processes. In summary, this study shows that ML methods are a useful tool for predicting the hydrological responses of SuDS catchments, and the hydrological processes inferred from modeling results should be interpreted cautiously due to the existence of large uncertainty in the inference processes.

Contributions of Seasonal Rainfall to Recent Trends in Cameroon’s Cotton Yields

Cotton yields in the Sudano-Sahelian region contribute to food security through their role in agricultural productivity. Daily precipitation data and cotton yield data were synthesized from nine agricultural regions obtained from the “Société de Développement du Coton (SODECOTON)”. The following seasonal rainfall indices—from Cameroon’s cotton zone—were mapped with geographic information systems for spatial analysis: wet season onset and retreat date, rainfall amount, number of rainy days, rainfall intensity (SDII), heavy-rainfall events (R95p), consecutive dry days (CDD), annual highest daily precipitation (Rx1day) and number of very heavy precipitation days (R20mm). Linear regressions were used as statistical tools for analysis. The strongest relationships were observed between cotton yields and the heavy-rainfall events, closely followed by seasonal rainfall amount. An increase in consecutive dry days (CDD) and heavy events, and a decreased seasonal rainfall amount, have a negative impact on cotton yield trends. Overall, the critical breakpoint analysis between cotton yields and all rainfall indices showed that the cotton yield was particularly negatively impacted before a 251 retreat date, 591 mm seasonal rainfall amount and 33 rainy days. By contrast, an onset date, rainfall intensity, heavy rainfall, CDD, Rx1day and R20mm of 127, 12.5 mm·day−1, 405 mm, 27 days, 67 mm and 22 days, respectively, were identified for an optimum cotton yield. These results can be used as information for agricultural activity and management, civil planning of economic activities and can also contribute to furthering our understanding of the management impacts on future food security.

Early warm-season mesoscale convective systems dominate soil moisture–precipitation feedback for summer rainfall in central United States

Land-atmosphere interactions play an important role in summer rainfall in the central United States, where mesoscale convective systems (MCSs) contribute to 30 to 70% of warm-season precipitation. Previous studies of soil moisture-precipitation feedbacks focused on the total precipitation, confounding the distinct roles of rainfall from different convective storm types. Here, we investigate the soil moisture-precipitation feedbacks associated with MCS and non-MCS rainfall and their surface hydrological footprints using a unique combination of these rainfall events in observations and land surface simulations with numerical tracers to quantify soil moisture sourced from MCS and non-MCS rainfall. We find that early warm-season (April to June) MCS rainfall, which is characterized by higher intensity and larger area per storm, produces coherent mesoscale spatial heterogeneity in soil moisture that is important for initiating summer (July) afternoon rainfall dominated by non-MCS events. On the other hand, soil moisture sourced from both early warm-season MCS and non-MCS rainfall contributes to lower-level atmospheric moistening favorable for upscale growth of MCSs at night. However, soil moisture sourced from MCS rainfall contributes to July MCS rainfall with a longer lead time because with higher intensity, MCS rainfall percolates into deeper soil that has a longer memory. Therefore, early warm-season MCS rainfall dominates soil moisture-precipitation feedback. This motivates future studies to examine the contribution of early warm-season MCS rainfall and associated soil moisture anomalies to predictability of summer rainfall in the major agricultural region of the central United States and other continental regions frequented by MCSs.

Evaluation of the Global Satellite Mapping of Precipitation (GSMaP) data on sub-daily rainfall patterns in Vietnam

This study aims to evaluate the performance of Global Satellite Mapping of Precipitation (GSMaP) data in observing the sub-daily rainfall patterns in Vietnam using synoptic gauge measurements considering seasonal variations in rainfall. Differences in the estimations of the three GSMaP products, including the standard version 7 (MVKv7) and two gauge-calibrated versions 6 and 7 (GAUv6 and GAUv7), were clarified based on rainfall characteristic parameters and statistical indices. The present study clarified that the contribution of sub-daily rainfall in Vietnam was higher during the afternoon than at other times, predominantly in the Central Highlands and Southern Plain, while it occurred most often during the evening to early morning in northern regions. Distinct regional features were also identified along the central coast. Most of the summer afternoon maximum fell in the western mountainous area, while the eastern coastal plain experienced an insignificant amount of rainfall. As rainfall characteristics varied with seasons and regions, the performance of GSMaP demonstrated this variation quite well compared to in-situ observations. However, GSMaP still exhibited high biases in rainy season and topographically heterogeneous areas, especially in the northern regions where sub-daily rainfall cycles had large variations. The standard GSMaP (MVK) product illustrated an afternoon peak better than the gauge-calibrated (GAU) product, which suggests that utilizing the MVK in the Central Highlands and Southern Plain and the GAU over central coastal regions would be appropriate when considering the characteristics of sub-daily precipitation.