Evolution Of Rainfall Research Articles

Multi-scale characteristics of an extreme rain event in Shandong Province, produced by Typhoon Lekima (2019)

Super Typhoon Lekima (2019) is the fifth strongest typhoon to make landfall in mainland China since 1949. After its landfall, Typhoon Lekima moved northward along the coastline, resulting in an extreme rain event in Shandong Province that caused the highest precipitation in available meteorological records. A Weather Research and Forecasting (WRF) model simulation that properly produces the track and intensity of Typhoon Lekima and the spatio-temporal evolution of rainfall is used to analyze the multi-scale characteristics of the extreme rain event. The results show that different from the typhoon precipitation which occurred at low latitudes, the extreme rain event that occurred in mid-latitudes was influenced by the interactions of mid-latitude synoptic systems and typhoon circulation, especially with five mesoscale rainbands. The mid-latitude synoptic systems, mainly including the upper-tropospheric jet, the western North Pacific subtropical high, the mid-latitude trough, the low-level jets, and Typhoon Krosa (2019), allowed Typhoon Lekima to maintain its intensity after landfall and provided favorable kinematic, thermodynamic, and moisture conditions for the heavy rainfall in Shandong. Based on the evolution of the mesoscale rainbands, the extreme rain event can be divided into three stages. The first stage can be classified as distant rainfall, which was affected by two convective rainbands associated with boundary-layer processes. The second stage had the highest precipitation, featuring the formation of a frontal zone in Shandong, interacting with Typhoon Lekima. The third stage had weakened rainfall and was directly influenced by the spiral rainband of Typhoon Lekima.

VULNERABILITE DE LA PRODUCTION DU MANIOC AUX CHANGEMENTS CLIMATIQUES ET PRIORITE D’ADAPTATION DANS LES AGGLOMERATIONS FRONTALIERES BENIN-TOGO (VALLEE DU MONO, AFRIQUE DE L’OUEST)

In the south of the Mono Valley and in its Benin-Togo border towns, the production of cassava roots is hampered by fluctuating climatic conditions. It is in this context that this study is conducted, in order to analyze climatic variations and their impact on cassava production. Thus, climatological data (rainfall, temperature, relative humidity, potential evapotranspiration) and agricultural data (sown areas, yield and production of cassava) made it possible to characterize the major agroclimatic situations. Documentary research and field surveys formed the basis of the research methodology. In addition, data analysis reveals that the study area has a bimodal rainfall regime. The annual evolution of rainfall over the period 1988-2018 is marked by 45.16% of surplus years, 12.90% of normal years and 41.93% of deficit years. Therefore, the index of the deviation from the minimum value was calculated in order to see the years where the minimum need was not satisfied for certain years. In addition, an upward trend in average temperatures is noted with an average annual rate of 0.04°C/year. The linear correlations established between cassava yields and climatic parameters showed that there is no explicit linear relationship between cassava production and temperature and between cassava production and insolation. The rainfall and humidity dependence of cassava production are also low: 27% and 20% respectively. Thus, climatic parameters taken in isolation are not sufficient to explain agricultural yields. In addition, other factors could also play an inhibiting or enhancing role in yields. However, the producers have developed adaptation strategies in the face of climatic variability in the study area that deserve to be accompanied. KEYWORDS : Climate change, Cassava, Lower Mono Valley, border agglomeration, Benin and Togo

Evolution of Extreme Rainfall and Temperature Indices in the Nakambé Watershed at the Bagré Outflow (Burkina Faso)

Climate change is now a global phenomenon with serious implications for many countries. Like other countries in sub-Saharan Africa, Burkina Faso is also vulnerable to the extreme effects of climate change, although few studies have been carried out, even though several vital sectors, such as agriculture and the livestock, forestry are strongly affected. The objective of this work is to study the evolution of rainfall and temperature extremes in the Nakambé watershed at the synoptic stations of Ouagadougou, Ouahigouya and Pô. ClimPACT2 was used to calculate the extreme rainfall and temperature indices. The results show that cumulative rainfall above the 95th percentile (R95p) increases by 147.2 mm and 141.3 mm respectively in Ouahigouya and Ouagadougou. However, in Pô, a slight downward trend in the index (-0.17 mm) was observed. Cumulative extremely wet rainfall (R99p) is increasing at all stations. The frequencies of cold nights (TN10p) and cold days (TX10p) are decreasing while those of warm nights (TN90p) and warm days (TX90p) are increasing. The application of break detection tests to rainfall indices shows breaks in the time series. The PETTITT, HUBERT and LEE and HEGHINIAN tests show a break in 2008 for the PRCPTOT index in Ouagadougou with an excess of 20.8% from 2009 to 2018. With these same tests, a break is detected in 2006 in Ouahigouya on the same index followed by a 29.5% surplus

Short-term rainfall forecasting using cumulative precipitation fields from station data: a probabilistic machine learning approach

Rainfall nowcasting supports emergency decision-making in hydrological, agricultural, and economical sectors. However, short-term prediction is challenging because meteorological variables are strongly interconnected and rapidly change during an event. Since machine learning do not require any previous physical assumption, this study investigates their ability to provide reliable and quick forecasts. This paper proposes a machine learning model for probabilistic rainfall nowcasting at 10 min intervals for short lead times - from 30 min up to 6 h. The model employs cumulative rainfall fields from station data as inputs for a feed forward neural network to predict rainfall interval and the corresponding probability of occurrence. Cumulative rainfall depths from station data were used to overcome the lack of temporal memory of the feed forward neural networks. In this way, using only the current rain field as input, the model exploited pattern recognition techniques combining both temporal - cumulative rainfall depth - and spatial - cumulative rainfall field – information. Based on 359 rain events observed in an area of 1619 km2 in Southern Italy, 95 machine learning models were independently trained for 19 recording stations and for each target lead-time (30, 60, 120, 180 and 360 min). Comprehensive nowcasts verification was performed to analyse the reliability of probabilistic nowcasts using both continuous (RMSE and RAE) and categorical (POD, FAR and CSI) indicators. The performance of the models was also compared with the results of Eulerian Persistence. All the models produced consistent nowcasts and learnt the complex relationship describing space–time rainfall evolution. As expected, predictive accuracy gradually decreased as the lead-time increase, according to physically based models. Results showed that the use of both temporal and spatial information enables the model to predict short-term rainfall using only the current measurements as input, resulting in a rapid, easily replicable and convenient nowcasting approach. The procedure is an effective way to predict multi-step rainfall fields and is suitable for operational early warning system.

Warmer SSTs in the Equatorial Eastern Pacific Delay the Seasonal March of the Asian–Pacific Summer Monsoon Onset

Abstract This study investigates the impact of El Niño–Southern Oscillation (ENSO) on the seasonal evolution of the Asian–Pacific summer monsoon. The results show that during the summers when the SSTs in the equatorial eastern Pacific are above normal (i.e., during developing El Niño), the seasonal march of the Asian–Pacific summer monsoon is delayed. Specifically, the stepwise northeastward extension of the western North Pacific monsoon and the northward migration of East Asian and Indian monsoon are all delayed, resulting in rainfall deficiency in the western North Pacific and India, and more rainfall in the Yangtze River valley but less rainfall in North China due to the delayed northward migration and resultant prolonged rainy season in the Yangtze River valley. In addition, the seasonal march of the Asian upper-tropospheric westerly jet, which is mainly characterized by the northward migration during the monsoon development, is also delayed, concurrent with the delayed march of monsoonal rainfall. During La Niña summers, however, the seasonal march of the monsoon and Asian jet does not exhibit clear variations, suggesting asymmetrical impacts between El Niño and La Niña. Furthermore, we explain these variations in the seasonal evolution of rainfall and jet and the asymmetrical impacts between El Niño and La Niña through the variations in tropical tropospheric temperatures and the resultant changes in meridional temperature gradient. Significance Statement The seasonal march of the Asian–Pacific summer monsoon exhibits large spatial and temporal variations, but shows some regular features such as stepwise northward migrations. The impacts of ENSO on the seasonal evolution of the components of Asian–Pacific summer monsoon have been shown in previous studies. However, there have been remarkable uncertainties in the previous results, and more emphasis has been put on the impacts of preceding ENSO. This study starts from El Niño and La Niña summers to reduce uncertainty caused by defining the seasonal march of the monsoon, and includes the variations in circulations that correspond well to monsoonal rainfall, making the conclusions more reliable.

High resolution dynamical downscaling of global products using spectral nudging for improved simulation of Indian monsoon rainfall

Societal wellbeing and risk management demand the evolution of rainfall during the Indian summer monsoon (ISM) at various spatio-temporal scales. The ISM rainfall (ISMR) is simulated for 1982–2018 using the Weather Research and Forecasting (WRF) model at 15 km grid-spacing by forcing with ERA5 reanalysis data. Two experiments are conducted without spectral-nudging (NSN) and with spectral-nudging (SN) in which the wind and temperature fields are updated. The seasonal mean rainfall over India and its homogeneous regions has realistically captured in SN experiment with less root mean square error (4.5 mm day−1) and high correlation (0.62) than the NSN run (6.0 mm day−1 and 0.35), with significant improvements in the first 60-days' simulation. Very-light, light, moderate, and heavy rain categories are well detected in the SN in 5 homogeneous regions out of 6. About 57–89% of years match the observed contribution of these rainfall categories in the SN experiment's seasonal rainfall, while 21–54% in the NSN. Better simulation of moderate rain from SN run in 24 years leads to improved contribution to the seasonal rainfall. NSN runs mostly underestimate the rainrate contribution in recent years. High threat scores (0.2–0.6) for these rainfall categories indicate the consistent performance of SN run in all monsoon months than the NSN (0.1–0.45). The SN could capture the interannual variability of observed ISMR, which aids in detecting the normal, excess, and deficit years at ∼75%, ∼86%, and ∼ 70% rate with high threat scores (0.60, 0.55, and 0.58, respectively), unlike NSN run. The SN experiment is superior in capturing frequent rainfall in extreme years, improving performance at monthly and seasonal scales. While NSN mainly underestimates rainfall in all extreme years. Thus, the study highlights the importance of spectral-nudging to high-resolution downscaling for improved long-range simulations.

Long-Term Evolution of Rainfall and Its Consequences on Water Resources: Application to the Watershed of the Kara River (Northern Togo)

The Kara River watershed (KRW), northern Togo, is facing climate-change impacts that have never been clearly characterized. Six decades of rainfall data (1961–2020) from six measuring stations ideally distributed across the watershed were used in this study. The flow records from two stations situated in contrasting locations on the KRW were also used. Statistical tests were conducted to assess the spatial and temporal variability of the rainfall and to detect tendencies within these meteorological series. The water balance method and calculation of the dry-off coefficient and of the groundwater volume drained by rivers allowed evaluating the impact of climatic evolution on surface flow and on groundwater volumes during the six decades studied. The results showed contrasting spatiotemporal variability of rainfall (and of aquifer recharge) over the watershed with a decreasing tendency upstream and an increasing one downstream. At the same time, the water volume drained by the aquifer to sustain the river’s base flow decreased from −22% to −36% depending on the measuring station. These results constitute a decision-making tool for Togolese water resource managers and are of primary importance for characterizing the fate of water resources worldwide in regions subject to severe droughts.

Convection-permitting modeling strategies for simulating extreme rainfall events over Southeastern South America

A set of six convection-permitting (CP) domain configurations were implemented to perform 72-hour long simulations of three extreme precipitation events over Southeastern South America (SESA). The goal of the study is to determine the most adequate configuration for reproducing not only the rainfall evolution and intensity, but also the synoptic triggering mechanisms that led to these extreme events, taking into account the trade-off between model performance and computational cost. This study assesses the impact of (1) the horizontal resolution in the CP domain, (2) the horizontal resolution of the driver domain, (3) the size of both CP and driver domains and (4) the nesting strategy (one-step versus two-step nesting). Each simulation was performed with the Weather Research and Forecasting model driven by the ERA-Interim reanalysis. For each event and domain configuration, a 6-member physics ensemble is built, making a total of 36 simulations for each event. No significant differences were found between the 4 km and 2.4 km CP ensembles. Increasing the horizontal resolution of the driver domain from 20 km to 12 km introduced only subtle differences. Increasing the size of the CP domain improved the model performance, probably because of better resolved topography and, hence, better resolved synoptic environment. The results in this study reveal that the one-step nesting CP ensemble at 4 km horizontal resolution covering an area of \(29^\circ\)x \(21^\circ\) (lon-lat) arises as the optimal domain configuration among these tested to simulate extreme precipitation events over SESA.

Comparative analyses of the heavy rainfall associated with landfalling tropical cyclones SOULIK (1307) and MARIA (1808) with similar routes

Different rainfall evolutions associated with landfalling tropical cyclones (TCs) SOULIK (1307) and MARIA (1808) are analyzed before and after they made landfalls in Fujian province based on reanalysis data of the ERA5 and CMORPH data. The two TCs shared similar tracks, motion speed as well as landing points, but showed different asymmetric features of rainfall intensities and locations relative to routes. The results primarily exhibited the discrepancy of the inland rainfall distributions between the two TCs and the related influence factors. The constant torrential rain over land with the maximum on the left of the storm track associated with SOULIK was attributed to favorable dynamical conditions. The northeasterly outflow of SOULIK was reinforced by the easterly wave in upper-level, which induced strong divergence along with the distinct ascending motions by suction effect. The strong ambient VWS broke the warm core structure of SOULIK, which pointed to south-southwest direction relevant to the strong northeasterly wind at 200 hPa, and further caused a more asymmetric rainfall pattern on the left of TC track. Besides, a cold intrusion was observed south of SOULIK in mid-levels, enhancing convective instability coincident with the alternating circumstance of cold and warm advections from the lower layer to the upper layer over south of SOULIK, which further intensify the precipitation on the left of TC track. Simultaneously, the meridional moisture convergence owing to the enhanced southerly wind at lower level played a key role in the maintenance of severe rainfall south of SOULIK. Comparatively, the 48-h accumulated rainfall over land associated with MARIA was much weaker than that associated with SOULIK, and the maximum is on the northern side. The strong convergence in the lower level induced by the predominant easterly winds interacting with coastal terrains, as well as the distinct divergence coincident with the upper level jet in the southern part of the South Asia High (SAH), provide favorable dynamical conditions for the maximum rainfall north of MARIA. Simultaneously, the strong westerlies over the South China Sea, together with the eastern cyclonic system over the Northwest Pacific, create favorable moisture conditions for the rainfall on the northern side of MARIA. Results presented in this study provides an improved predictive understanding of physical mechanism dictating storm rainfall evolution from landfalling TCs, especially those with similar tracks

The Spatiotemporal Evolution of Rainfall Extremes in a Changing Climate: A CONUS‐Wide Assessment Based on Multifractal Scaling Arguments

AbstractGiven the rapidly changing climate, accurate spatiotemporal information on the evolution of extreme rainfall events is required for flood risk assessment and the design of resilient infrastructure. Consequently, various research efforts have focused on investigating the appropriateness of various parametric and non‐parametric approaches in modeling the observed changes in the frequency of extreme rainfall over time. Yet, the assumption of stationarity, or the change of model parameters when accounting for nonstationary rainfall, may magnify estimation uncertainty of rain rates associated with low exceedance probabilities. Moreover, the use of climate model results may yield inconclusive outcomes, given the existence of epistemic uncertainties in the frequency of extreme events developing on smaller spatial scales or over complex terrain. Herein, we employ a parametric approach based on multifractal scaling arguments, along with high‐resolution (4‐km) hourly precipitation estimates covering a 40‐year period over CONUS, to derive Intensity‐Duration‐Frequency curves and investigate the spatiotemporal evolution of extreme rainfall over a wide range of characteristic temporal scales and exceedance probability levels. Considering the robustness of the multifractal models even when fitted to short rainfall records, we uniquely apply the framework to sequential 10‐year segments of data, where the rainfall process can be reasonably assumed stationary. The obtained results reveal that existing infrastructure may be severely impacted by the intensification of precipitation extremes due to climate change, with the observed trends being significantly influenced by the topography and rainfall climatology of each region, while depending on the averaging durations and return periods of interest.

Evolution of warm season intense rainfall in Yaan against a cold-anomaly background

This study investigates the rainfall characteristics during intense rainfall over Yaan against a cold-anomaly background, aiming to refine the understanding of different kinds of rainfall events across complex terrain. Hourly rain gauge records, ERA5 reanalysis data and the black body temperature of cloud tops derived from FY-2E were used. The results show that against a cold-anomaly background, the regional rainfall events (RREs) in Yaan exhibit west-to-east propagation, which is different from the north-to-south evolution of warm RREs. The middle and upper troposphere is dominated by a negative geopotential height anomaly corresponding to the cold anomaly. The cyclonic circulation at the higher level associated with the negative geopotential height anomaly bends the high-level jet to the south, forming a divergent zone over the Tibetan Plateau (TP) and guiding mid-level systems to move eastward. The cyclonic circulation at the mid-level produces a wind shear zone over the TP, generating anomalous vorticity that continuously moves eastward and develops to influence the rainfall over Yaan. The cold Yaan RREs are closely related to the TP low-pressure systems (both vortex and shearline). The anomalous vorticity over the TP can influence the local vortex over the eastern periphery of the TP at a distance mainly by the horizontal advection of anomalous vorticity by the mean flow and then enhance the local vortex mainly by anomalous convergence when it moves near Yaan.

Impact of rainfall trends on flood in Agnéby watershed

The aim of this study is to analyse the spatio-temporal evolution of hydro-rainfall variables in the Agnéby watershed in a disturbed climatic context. Rainfall data from the stations of Arrah, Bongouanou, M’Batto, Akoupé, Céchi, Agboville, Adzopé, Sikensi, Abidjan Airport and Dabou as well as hydrometric data from the stations of Agboville, Offoliguié, M’Bessé and Guessiguié were used. The methodological approach is based on the application of independence and trend tests and spatio-temporal analysis of daily rainfall maxima, duration of consecutive rainfall events, number of rainfall events above a threshold and daily flow maxima. The hypothesis of independence justified the relevance of the choice of variables. The trend test showed the dynamic upward evolution of extreme rainfall and the decrease in the duration of consecutive rainy episodes, in the number of rainy episodes and in the flows feeding the main watercourse. Moreover, spatial analysis of daily maximum rainfall amounts above 120 mm, consecutive maximum rainfall amounts above 160 mm and Gumbel rainfall amounts above 190 mm indicated heavy rainfall in the southern part of the watershed. However, a decrease in rainfall is recorded in the areas covered by the stations of Arrah, Bongouanou, M’Batto, Ce chi and Akoupé. An increase in the flood flow calculated from the Generalized Extreme Value (GEV) between 76.60 m3∙s–1 and 225.70 m3∙s–1 is presented in the main river. The spatio-temporal variation in annual rainfall heights showed a high rainfall in the southern part of the watershed with a decrease in rainfall over the decades (1976–1985 and 1996–2005) followed by an increase over the decades (1986–1995 and 2006–2015). Despite the general decrease in rainfall, extreme rainfall has become frequent, causing flooding in the watershed.

Tectonic and Orbital Imprints in the Redox History of Japan Sea Since the Pliocene

AbstractOxygen content in the deep ocean plays a vital role in biogeochemical processes and has significant impacts on the global carbon cycle. The Japan Sea is a semiclosed basin with only shallow water connection to the Western North Pacific, and its redox history has been sensitively affected by tectonic and climatic changes in the past. Studies of paleo‐redox changes in the Japan Sea focused on the tectonic and orbital scales since the Pliocene remain scarce to date. Here, we present two high‐resolution paleo‐redox records during the last 4 Ma at IODP Sites U1425 and U1430 drilled in the Japan Sea. Our authigenic U (uranium) and U/Al records suggest remarkable changes of Japan Sea redox history from relatively oxic to periodic oxic‐anoxic conditions at ∼1.7 Ma. This was mainly caused by the restricted input of North Pacific oxygen‐rich water due to the uplift of northeastern Japan during late Pliocene and early Pleistocene, and opening of the Tsushima Strait and the periodic intrusion of Tsushima Warm Current following sea level change during glacial‐interglacial cycles since ∼1.7 Ma. Orbital changes of Japan Sea redox history suggest the existence of a long eccentricity cycle of 400 ka associated with East Asian summer monsoon rainfall evolution throughout the last 4 Ma. Changes of the amplitude of sea level and inflow of Tsushima Warm Current combined with the East Asian monsoon evolution produced eccentricity and obliquity cycles in Japan Sea redox environment after ∼1.7 Ma, as well as a transition from relatively oxic to anoxic conditions during glacials before and after Middle Pleistocene Transition.

Effect of rainfall characteristics on the sewer sediment, hydrograph, and pollutant discharge of combined sewer overflow

Significant management needs raised in urban sewer system to facilitate urban resilience to rainstorm. The work investigated the effects of temporal evolution of rainfall on hydrograph and pollutant discharge of CSO over an intensive observation period of 12 months, with special attention to differences in temporal scale for supporting management decision making. The characteristics of rainfall in different temporal scales helped overflow-risk identification and assessment. Prolonged dry seasons over 112 days in the CSO monitored year 2018 increased the sediment buildup in the pipes. The built sediment was mostly flushed out to overflow (and the treatment facility) by initial rainfall during 47 h. Following CSO hydraulics and pollutant discharge follows initial peak patterns which responded to rainfall patterns. Results of Redundancy analysis and network analysis showed that the combined effects of rainfall, urbanization, and sediments as “CSO troika” are the driving forces for CSO pollutants in the long-term. The improved characterization of CSO events and the associated pollutants has refined our understanding of how overflow hydrograph and pollutant discharge responds to rainfall temporally, which methodology supported decision making in the combining source/process control with terminal management for facilizing urban resilience.

The Asymmetric Precipitation Evolution in Weak Landfalling Tropical Cyclone Rumbia (2018) Over East China

The rainfall in landfalling TC is not always correlated with the storm intensity. Some weak landfalling TCs could bring extremely heavy rainfall during and after landfall. Such extreme events are very challenging to operational forecasts and often lead to disasters in the affected regions. Tropical storm Rumbia (2018) made its landfall in Shanghai with weak intensity but led to long-lasting and increasing rainfall to East China. The asymmetric rainfall evolution of Rumbia during and after its landfall was diagnosed based on the fifth generation European Centre for Medium-Range Weather Forecasting (ECMWF) reanalysis (ERA5) data, the tropical cyclone (TC) best-track data, and rainfall observations from China Meteorological Administration (CMA). Results showed that Rumbia was embedded in an environment with a deep-layer (300–850 hPa) southwesterly vertical wind shear (VWS). The maximum rainfall mostly occurred downshear-left in its inner-core region and downshear-right in the outer-core region. The translation of Rumbia also contributed to the rainfall distribution to some extent, especially prior to and just after its landfall. The strong southwesterly-southeasterly summer monsoon flow transported water vapor from the tropical ocean and the East China Sea to the TC core region, providing moisture and convective instability conditions in the mid-lower troposphere for the sustained rainfall even after Rumbia moved well inland. The results also showed that the low-level convective instability and the deep-layer environmental VWS played an important role in deepening the inflow boundary layer and the redevelopment of the secondary circulation, thus contributing to the heavy rainfall in the northeast quadrant of Rumbia after its landfall. However, further in-depth studies are recommended in regard of the rainfall evolution in the weak TCs. This study further calls for a continuous understanding of the involved physical processes/mechanisms that are responsible for the extreme rainfall induced by landfalling TCs, which can help improve the rainfall forecast skills and support damage mitigation in the future.

Impact of Subglacial Freshwater Discharge on Pine Island Ice Shelf

AbstractSatellite‐based estimates of ice shelf melt rates reach 200 m close to the grounding line of Pine Island Glacier, in West Antarctica. However, ocean simulations have not yet been able to reproduce such high melt rates, even with high‐resolution models. Here, we use a regional model of Pine Island ice shelf cavity and study the impact of subglacial freshwater discharge on simulated ice shelf melt rates and ocean circulation in the cavity. We show that subglacial freshwater discharge substantially enhances ice shelf melting close to the grounding line, successfully simulating high ice shelf melt rates suggested by observations. The buoyant mixture of glacial meltwater plume rises to 27.4 isopycnal surfaces, following topographically constrained current, and spreads into mid‐depths at the ice shelf front. The role of freshwater discharge is likely to remain unchanged over the coming decades given the projected evolution of runoff and rainfall over Pine Island basin.

Space-Time Assessment of Extreme Precipitation in Cuba between 1980 and 2019 from Multi-Source Weighted-Ensemble Precipitation Dataset

Precipitation extremes such as heavy rainfall and floods are of great interest for climate scientists, particularly for small islands vulnerable to weather phenomena such as hurricanes. In this study, we investigated the spatio-temporal evolution of extreme rainfall over Cuba from 1980 to 2019, separating the dry and rainy periods. In addition, a ranking of extreme precipitation events was performed, which provides the number of events, the area affected, and a ranking of their magnitude by considering the magnitude of anomalies. The analysis was conducted using daily data from the multi-source weighted-ensemble precipitation (MSWEPv2). In determining the extreme precipitation ranking, the daily extreme precipitation anomaly was calculated with respect to the 95th percentile climatological distribution, giving a measure of the rarity of the event for each day and each grid point. For a more detailed analysis regarding the ranking, a separation was made by regions applying the K-mean methodology. The months belonging to the rainy period of the year presented the highest amount of precipitation above the 95th percentile compared to results obtained for the dry period. Of the six months belonging to the cyclonic season, in five of them Cuba was affected, directly or indirectly, by a tropical cyclone. The years 1982–83 and 1998 presented the highest-ranking value for the dry and rainy periods, respectively. Moreover, a trend analysis revealed an increase in the trend of occurrence of extreme events and a decrease in the percentage of the area affected. The analysis by regions showed a similar behavior to that carried out for all of Cuba. It was found that the warm phase of the ENSO events influenced approximately ~22% of the occurrence of extreme events for both periods.

A Study of Two Impactful Heavy Rainfall Events in the Southern Appalachian Mountains during Early 2020, Part II; Regional Overview, Rainfall Evolution, and Satellite QPE Utility

Two heavy rainfall events occurring in early 2020 brought flooding, flash flooding, strong winds, and tornadoes to the southern Appalachian Mountains. Part I of the study examined large-scale atmospheric contributions to the atmospheric river-influenced events and subsequent societal impacts. Contrary to expectations based on previous work in this region, the event having a lower event accumulation and shorter duration resulted in a greater number of triggered landslides and prolonged downstream flooding outside of the mountains. One purpose of this study (Part II) is to examine the local atmospheric conditions contributing to the rather unusual surface response to the shorter duration heavy rainfall event of 12–13 April 2020. A second purpose of this study is to investigate the utility of several spaced-based QPE and vertical atmospheric profile methods in illuminating some of the atmospheric conditions unique to the April event. The embedded mesoscale convective elements in the warm sector of the April event were larger and of longer duration than of the other event in February 2020, leading to sustained periods of convective rain rates. The environment of the April event was convectively unstable, and the resulting available potential energy was sustained by relatively dry airstreams at the 700 hPa level, continuously overriding the moist air stream at low levels attributed to an atmospheric river.

Assimilation of FY-3D MWHS-2 Radiances with WRF Hybrid-3DVAR System for the Forecast of Heavy Rainfall Evolution Associated with Typhoon Ampil

AbstractA detailed investigation about the effects of the Microwave Humidity Sounder-2 (MWHS-2) radiances on board the Fengyun-3D (FY-3D) satellite is combined with developments within the Weather Research and Forecasting Data Assimilation (WRFDA) system and analyses on the evolution of the heavy rainfall associated with Typhoon Ampil during 23–24 July 2018. In the analysis field, the position of Typhoon Ampil is found out to be distinctly affected by the MWHS-2 assimilation. The experiment that assimilates MWHS-2 radiances through hybrid-3DVAR generates the best analysis with large increments around the typhoon, which contributes to the typhoon moving inland to the southwest. In the forecast fields, the MWHS-2 assimilation improves the rainfall in not only the accumulated amount, but also the evolution characteristics. The hybrid-3DVAR experiment reduces the RMSE of the rainfall amount, and enhances the spatial correlation and the fractions skill score of the rainfall evolution to the greatest extent, followed by the 3DVAR MWHS-2 experiment. As for the cause of the rainfall improvements, analyses suggest that it could be closely connected with the characteristics of the circulation structures related to the typhoon evolution. On one hand, the increases of the rainfall amount and intensities in the MWHS-2 assimilation experiments (previously underestimated) correspond to the strengthened typhoon structures with strong anomalies in both the upper-layer temperature and the lower-layer geopotential height. On the other hand, the better rainfall evolution in the hybrid-3DVAR experiment could be explained by its clearer evolution of the structure of typhoon under the effects of an approaching upper trough, and its smallest typhoon track errors around the middle time period.

Representation of Arabian Peninsula summer climate in a regional atmospheric model using spectral nudging

This study assesses the performance of the Weather Research and Forecasting (WRF) model in simulating the Arabian Peninsula summer climate for the period 2001–2016. The European Centre for Medium range Weather Forecast (ECMWF) reanalysis is downscaled using WRF without (CTRL) and with the Spectral Nudging (SPN) method. Our results suggest that the noticeable cold biases in surface temperatures (mean, minimum, and maximum) over the Arabian Peninsula in CTRL are significantly reduced in SPN. The seasonal patterns of surface pressure, cloud cover, lower and upper tropospheric circulation, and mid-tropospheric anticyclone are also simulated more realistically with SPN. The evaluation of mean vertical profiles of dynamical and thermo-dynamical features over the Arabian Peninsula further confirms the enhanced simulations with SPN with respect to CTRL. Though SPN captures better the observed evolution of rainfall compared to that of CTRL, it produces a positive rainfall bias over the Southwestern Arabian Peninsula. Stronger vertical motions associated with the local topography enhance the higher water vapor loading, condenses in the upper layers, and results in excess amount of rainfall in SPN. Furthermore, with SPN, WRF is further able to better simulate the synoptic features of heat waves. Overall, SPN enhances WRF simulation skill of the horizontal structures and vertical profiles of the Arabian Peninsula summer climate by enforcing a better balance between the small and large scale features and associated feedbacks.