Rainfall Anomalies Research Articles

Estimating Rainfall Anomalies with IMERG Satellite Data: Access via the IPE Web Application

This study assesses the possibilities of the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG-GPM) to estimate extreme rainfall anomalies. A web application, the IMERG Precipitation Extractor (IPE), was developed which allows for the querying, visualization, and downloading of time-series satellite precipitation data for points, watersheds, country extents, and digitized areas. The tool supports different temporal resolutions ranging from 30 min to 1 week and facilitates advanced analyses such as anomaly detection and storm tracking, an important component for climate change study. To validate the IMERG precipitation data for anomaly estimation over a 22-year period (2001 to 2022), the Rainfall Anomaly Index (RAI) was calculated and compared with RAI data from 2360 NOAA stations across the conterminous United States (CONUS), considering both dry and wet climate regions. In the dry region, the results showed an average correlation coefficient (CC) of 0.94, a percentage relative bias (PRB) of −22.32%, a root mean square error (RMSE) of 0.96, a mean bias ratio (MBR) of 0.74, a Nash–Sutcliffe Efficiency (NSE) of 0.80, and a Kling–Gupta Efficiency (KGE) of 0.52. In the wet region, the average CC of 0.93, PRB of 24.82%, RMSE of 0.96, MBR of 0.79, NSE of 0.80, and KGE of 0.18 were computed. Median RAI indices from both the IMERG and NOAA indicated an increase in rainfall intensity and frequency since 2010, highlighting growing concerns about climate change. The study suggests that IMERG data can serve as a valuable alternative for modeling extreme rainfall anomalies in data-scarce areas, noting its possibilities, limitations, and uncertainties. The IPE web application also offers a platform for extending research beyond CONUS and advocating for further global climate change studies.

Changing Rainfall Patterns in the Northeastern South Kivu Region, Democratic Republic of the Congo: A Detailed Analysis Using CHIRPS Rainfall Data (1981–2023)

AbstractUnderstanding changes in rainfall patterns is vital for effective water resource management and agricultural planning in climate-sensitive regions. In Northeastern South Kivu, Democratic Republic of the Congo, limited knowledge of rainfall dynamics poses challenges for local climate assessments. This study analyzed rainfall patterns using the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) dataset from 1981 to 2023 to fill this knowledge gap. The findings revealed significant spatial and temporal changes in rainfall across the regions of Kabare, Bukavu, Kalehe, and Idjwi. Mean annual rainfall ranged from 1136.92 mm to 2048.85 mm, with coefficients of variation between 8.23% and 8.45%. Monthly rainfall fluctuations were substantial, ranging from 16 to 56.35%. Standardized rainfall anomalies indicated a shift from predominantly wet conditions in the 1980s to drier conditions in later decades, with over half the years from 1990 to 2023 recording below-average rainfall. Mann-Kendall trend analysis, supported by Innovative Trend Analysis (ITA), confirmed significant decreases in annual rainfall, with rates between − 3.53 to -5.72 mm/year. Additionally, rainfall intensity indices highlighted a decline in total annual precipitation, suggested fewer extreme events. Spatial variability was observed, with regions like Kalehe and Bukavu showed higher values for indices such as R95P and RX1day compared to Kabare and Idjwi. These results underscored the urgent need for adaptive strategies to mitigate water scarcity and manage changing rainfall patterns in the region.

Cross-Time-Scale Analysis of Year-Round Atmospheric Circulation Patterns and Their Impacts on Rainfall and Temperatures in the Iberian Peninsula

Abstract This study presents a framework to assess climate variability and change through atmospheric circulation patterns (CPs) and their link with regional processes across time scales. We evaluate the CP impacts on daily rainfall and maximum and minimum temperatures in the Iberian Peninsula using sea level pressure (SLP) during 1950–2022. Different sensitivity analyses are performed, employing multiple spatial domains and number of patterns. An optimal classification is found in midlatitudes, centered over the Mediterranean basin and covering part of the North Atlantic Ocean, which can identify atmospheric configurations significantly related to discriminated rainfall and temperature anomalies, with clear seasonal behavior. The temporal variability of CPs is studied across time scales showing, e.g., that transitions between patterns are faster in autumn and spring, and that CPs exhibit distinct temporal variability at intraseasonal, seasonal, interannual, and decadal scales, including significant long-term trends on their frequency. CPs influence temperature and precipitation variations throughout the year. The winter season exhibits the largest atmospheric circulation variability, while the summer is dominated by persistent high-pressure structures—the subtropical Azores high—leading to warm and dry conditions. Based on an interannual correlation analysis, some CPs are significantly associated with the North Atlantic Oscillation (NAO), stronger during winter, indicating the NAO modulation on the regional-to-local climatic features. Overall, this approach arises as a dynamic cross-time-scale framework that can be adapted to specific user needs and levels of regional detail, being useful to study climate drivers for climate change and to perform a process-based evaluation of climate models.

Advancing the Seasonal Outlook of the Wet Seasons of Florida

Abstract In this study, we introduce an ensemble approach to provide a probabilistic seasonal outlook of the length and seasonal rainfall anomaly of the wet season over Florida using the observed variations of the onset date of the season at the granularity of ∼10-km grid resolution (which is the spatial resolution of the observed rainfall data used for this work). The time series of daily precipitation at the grid resolution of NASA’s Global Precipitation Mission is randomly perturbed 1000 times to account for the uncertainty of synoptic to mesoscale variations on the diagnosis of the onset and demise date of the wet season. The strong covariability of the onset date with the seasonal length and seasonal rainfall anomaly of the wet season is then leveraged to provide the seasonal outlooks by monitoring the onset date of the wet season. This simple seasonal outlook is effective in predicting extreme tercile and even extreme pentile anomalies across Florida. We suggest that the proposed approach to the seasonal outlook of the wet season of Florida provides a viable alternative in the absence of strong external forcing like ENSO or tropical Atlantic variability that potentially limits the predictability of numerical climate models used for seasonal prediction. Significance Statement Earlier studies have shown that the seasonal prediction from the numerical climate models even at zero lead time has very limited prediction skills over the summer in Florida, which also coincides with the wettest part of the year. Florida’s wet season exhibits significant interannual variations, which exert its influence on water management decisions for subsequent drier seasons of the year. Therefore, strategies to improve this skill are highly relevant. We propose in this study that by monitoring the onset of the wet season variations, we can usefully provide a probabilistic seasonal outlook of the season over Florida. This is done by leveraging the observed linear relationships between the onset date variations with the length and the seasonal rainfall anomaly of the season. Furthermore, the outlook is provided at the spatial resolution of the observed dataset, which in this case is at 10-km grid resolution.

Unveiling the Urban Impact on Mesoscale Convective System Rainfall in the Pearl River Delta Urban Agglomeration Under Typical Synoptic Backgrounds

AbstractMesoscale convective systems (MCSs), the primary drivers of extreme rainfall over the Pearl River Delta (PRD) urban agglomeration, are strongly influenced by synoptic circulations and local geographical environments, including water bodies and topography. However, the urban impact on MCS rainfall under various synoptic backgrounds remain inadequately understood. Using a 20‐year high‐resolution MCS tracking database and self‐organizing map clustering, three typical backgrounds for MCSs, namely weak monsoon‐like, strong monsoon‐like, and low‐pressure system (Types‐1 to 3), impacting the PRD are identified. These backgrounds exhibit pronounced disparities in MCS tracks and temporal variations as well as rainfall distributions. Urban heat island (UHI) significantly alters the spatial patterns under Types‐1 and 2. Specifically, under weak UHI condition, MCS rainfall typically occurs offshore in the morning and shifts inland in the afternoon driven by the land‐sea breeze. However, UHI modifies the low‐level thermal structure, leading to anomalous convergence and instability, which causes morning rainfall to concentrate near coastal cities, while afternoon rainfall expands further inland to the northern rural region. Additionally, the strong southwesterly winds associated with Type‐2 enhance the interaction between topography and urban impact, resulting in even higher rainfall anomalies (+28.9%) over the northeastern region. The findings highlight the crucial role of urban impact and their synergistic effect with synoptic backgrounds and other land surface processes on MCSs.

Interdecadal Variations in the Seasonal Cycle of Explosive Growth of Southern Hemisphere Storms with Impacts on Southern Australian Rainfall

Interdecadal variations, since the middle of the 20th century, in the seasonal cycle of Southern Hemisphere extratropical synoptic scale weather systems, are studied and related to associated anomalies in Southern Australian rainfall over south-west Western Australia (SWWA) and southeast Australia (SEA). A data-driven method is employed in which atmospheric fluctuations, specified from 6-hourly lower-tropospheric reanalysis data, are spectrally analysed in space and time to determine the statistics of the intensity and growth rates of growing and decaying eddies. Extratropical storms, blocking and north-west cloud band weather types are investigated in two frequency bands, with periods less than 4 days and between 4 and 8 days, and in three growth rate and three decay rate bins. Southern Australian rainfall variability is found to be most related to changes in explosive storms particularly in autumn and winter. During the first 10 years of the Australian Millennium Drought (AMD), from 1997 to 2006, dramatic changes in rainfall and storminess occurred. Rainfall declines ensued over SEA in all seasons, associated with corresponding reductions in the intensity of fast-growing storms with periods less than 4 days. These changes, compared with the 20-year timespans of 1949 to 1968 and 1975 to 1994, also took place for the longer duration of 1997 to 2016, apart from summer. Over SWWA, autumn and winter rainfall totals have decreased systematically with time for each of the 10-year and 20-year timespans analysed. Southern Australian rainfall variability is also found to be closely related to the local, hemispheric or global features of the circulation of the atmosphere and oceans that we characterise by indices. Local circulation indices of sea level pressure and 700 hPa zonal winds are good predictors of SWWA and SEA annual rainfall variability particularly in autumn and winter with vertical velocity generally less so. The new Subtropical Atmospheric Jet (SAJ) and the Southern Ocean Regional Dipole (SORD) indices are found to be the most skilful non-local predictors of cool season SWWA rainfall variability on annual and decadal timescales. The Indian Ocean Dipole (IOD) and Southern Oscillation Index (SOI) are the strongest non-local predictors of SEA annual rainfall variability from autumn through to late spring, while on the decadal timescale, different indices dominate for different 3-month periods.

Predictability of the 2020 Strong Vortex in the Antarctic Stratosphere and the Role of Ozone

AbstractThe Antarctic vortex of October–December 2020 was the strongest on record in the satellite era for the season in the mid‐ to lower stratosphere. However, it was poorly predicted by the Australian Bureau of Meteorology's operational seasonal climate forecast system of that time, ACCESS‐S1, even at a short lead time of a month. Using the current operational forecast system, ACCESS‐S2, we have, therefore, tried to find a primary cause of the limited predictability of this event and conducted forecast sensitivity experiments to understand the potential role of ozone in the event and its associated anomalies of the Southern Annular Mode (SAM) and rainfall over south–eastern Australia and western Patagonia. Here, we show that the 2020 strong vortex event did not follow the canonical dynamical evolution seen in previous strong vortex events in spring but suddenly appeared as a result of the record‐low upward propagating wave activity in September 2020. The ACCESS‐S2 forecasts significantly underestimated the negative wave forcing in September even at zero lead time, irrespective of the ozone configuration, therefore falling short in predicting the record strength of the polar vortex in late spring 2020. Nevertheless, ACCESS‐S2 with prescribed realistic ozone that had large anomalies in the Antarctic stratosphere significantly better predicted the strong vortex and the subsequent positive SAM and related rainfall anomalies over south–eastern Australia and western Patagonia in the austral summer of 2020–21. This highlights the potentially important role of ozone variations for seasonal climate forecasting as a source of long‐lead predictability.

Spatio-temporal characteristics of rainfall and drought conditions are using the different drought indices with geospatial approaches in Karnataka state

Karnataka state drought conditions are assessed via drought indices. Over the past several decades, several indices of drought (DI) have been developed and presented, although some of them are region-specific and have problems regarding their applicability to other climatic circumstances. Additionally, choosing the best DI time step to illustrate the drought condition is difficult because of the DIs' various time steps. The study compares the Standardized Precipitation Index (SPI), Statistical Z-Score, China Z-Index (CZI), Rainfall Anomaly Index (RAI), and Rainfall Departure (RD) to determine which one is most appropriate for the districts of the Karnataka state that are prone to both dry and rainy conditions. This study has pointed out that the best drought indices are SPI and RD, and the least accountable drought indice is China Z index. Droughts were most common in 22 districts in 2009, which represent around 70.97% of the state's landmass. In comparison with the rest of the districts, the Ramanagara district noticed the worst drought conditions in 2003, with rainfall reaching 92.47 mm and SPI -3.68, RAI-6.04, MCZI -2.39, and Z score −2.62. Overall, the results of the study will aid in the organization and improvement of drought, flood, agriculture, and water resource management approaches in the state.

Attributions of Rainfall Anomalies to Weather Systems and Their Spatial and Temporal Variabilities: A Case Study of Victoria in Southeast Australia

ABSTRACTAttributions of rainfall anomalies to weather systems and their spatio‐temporal variability in Victoria, southeast Australia are investigated with a multimethod weather type dataset and two popularly used gridded daily rainfall datasets for the period 1979–2015. The rainfall anomalies before, during and after the Millennium Drought (1997–2009) are compared to quantify the temporal variability of rainfall responses to weather type changes. The results show: (1) Three weather systems (Front, Cyclone and Thunderstorm) and their combinations contribute 89% of total rainfall; (2) Contributions of weather types to rainfall vary from month to month with winter season rainfall coming from more diverse weather types than summer rainfall; (3) The contributions of weather types to rainfall in three periods show temporal variabilities and there is a clear shift of contribution pattern after the Millennium Drought, such as front‐thunderstorm (FT) is now the largest contributor to rainfall compared with cyclone‐frontal‐thunderstorm (CFT) before and during the Millennium Drought; (4) A seasonal shift in the post‐drought period is found with higher rainfall in February and March and lower rainfall in September and October. The increased rainfall in February mainly results from Front–Thunderstorm (FT) and Thunderstorm‐only (TO), while rainfall declines in September from all weather types; (5) Several rainfall characteristics that are important for streamflow generation, such as rainfall intensity, probability of rainfall occurrence, number of rainfall days and the maximum daily rainfall, do depend on the weather types; (6) The results are similar with different rainfall datasets, but differences do exist, especially at the local scale. The conclusions of this study are drawn from an Australian case study but have implications for other regions to investigate the attributions of rainfall characteristic changes to weather systems.

Contrasting Rainfall Anomaly Patterns Over South America Related to Central and Eastern Atlantic Niño Modes

ABSTRACTThe present study examines the effects of the central Atlantic Niño (CAN) and eastern Atlantic Niño (EAN) events on the seasonal precipitation in South America (SA) during the 1951–2020 period. For the CAN during the summer and autumn, an interhemispheric sea surface temperature (SST) dipole mode induces an anomalous thermally direct circulation in the 10° N–10° S band and is the main factor causing precipitation anomaly patterns with a dipole structure between northern (negative) and northeastern (positive) SA. For winter and spring, the SST pattern featuring a South Atlantic dipole induces meridional and zonal anomalous circulations, which are the mechanisms causing positive precipitation anomalies in tropical SA to the north of 20° S. In contrast, for the EAN, the precipitation anomaly patterns show large areas with anomalous dryness, particularly during summer, autumn, and spring. For summer and autumn, the east–west SST anomaly gradient in the equatorial Atlantic and the associated sea level pressure (SLP) anomalies induce equatorial westerlies and a regional Walker cell with descending motions in most tropical SA, where large areas with anomalous dryness are noted. During spring, a northward SST gradient in the tropical Atlantic induces a meridional cell with descending motions in the 0°–10° S band; meanwhile, the westward SST gradient in the equatorial Atlantic and tropical South Atlantic induces a zonal circulation with descending motions over northeastern and eastern Brazil. These descending motions extend the anomalous dryness over a large area. For the EAN events, the east–west SST gradient and the associated east–west circulation in the South American/Atlantic region are crucial elements to modulate precipitation variability in SA. Therefore, the CAN and EAN events induce distinct precipitation anomaly patterns in SA due to distinct associated regional circulation patterns. The results presented here have not been discussed before and might have relevant implications for climate monitoring and modelling studies.

Inter-Model Spread in Representing the Impacts of ENSO on the South China Spring Rainfall in CMIP6 Models

A major challenge for climate system models in simulating the impacts of El Niño–Southern Oscillation (ENSO) on the interannual variations of East Asian rainfall anomalies is the wide inter-model spread of outputs, which causes considerable uncertainty in physical mechanism understanding and short-term climate prediction. This study investigates the fidelity of 40 models from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) in representing the impacts of ENSO on South China Spring Rainfall (SCSR) during the ENSO decaying spring. The response of SCSR to ENSO, as well as the sea surface temperature anomalies (SSTAs) over the tropical Indian Ocean (TIO), is quite different among the models; some models even simulate opposite SCSR anomalies compared to the observations. However, the models capturing the ENSO-related warm SSTAs over TIO tend to simulate a better SCSR-ENSO relationship, which is much closer to observation. Therefore, models are grouped based on the simulated TIO SSTAs to explore the modulating processes of the TIO SSTAs in ENSO affecting SCSR anomalies. Comparing analysis suggests that the warm TIO SSTA can force the equatorial north–south antisymmetric circulation in the lower troposphere, which is conducive to the westward extension and maintenance of the western North Pacific anticyclone (WNPAC). In addition, the TIO SSTA enhances the upper tropospheric East Asian subtropical westerly jet, leading to anomalous divergence over South China. Thus, the westward extension and strengthening of WNPAC can transport sufficient water vapor for South China, which is associated with the ascending motion caused by the upper tropospheric divergence, leading to the abnormal SCSR.

Climatic and hydrological variability in the Oued Lakhdar watershed (Central High Atlas, Morocco)

Abstract The results of this study highlighted significant changes in hydroclimatic conditions over the period studied. Annual rainfall shows significant variability, with years such as 1996 characterised by exceptional humidity, while others, such as 2017, stand out for their particularly marked drought. This variation can be quantified using the Rainfall Anomaly Index (RAI), providing crucial information for water resource management. Temperatures also show seasonal fluctuations, oscillating between hot summers and cold winters. In particular, 2017 was exceptionally warm, while 2011 was unusually cold. In terms of river flows, there has been considerable variability, with some years showing high flows (e.g. 2011) and others with very low flows (e.g. 1990). However, the general trend towards an increase in flow from the 2010 onwards is notable (Sgat station). The RCV index, which classifies years according to surplus or deficit, highlights the predominance of deficit years. In addition, the Monthly Flow Coefficient (MFC) allows us to subdivide the hydrological regime into periods of high and low water. These results highlight the importance of monitoring hydro-climatic conditions for effective management of water resources and the implementation of measures to adapt to climate change.

Temporal variability of spatial patterns of correlations between summer rainfall and the Oceanic Niño Index in the Pampean region

The Argentinean Pampean region is essential for global food security, known for its extensive production of soybeans, corn, and wheat. The November to January (NDJ) trimester is critical for rainfed summer crops, as precipitation during this period directly affects soil moisture and crop yields. The El Niño-Southern Oscillation (ENSO), particularly its Oceanic Niño Index (ONI), plays a crucial role in influencing precipitation patterns in this region. This study investigates the spatial correlation between the ONI and NDJ precipitation from 1990 to 2021 sing a 20-year sliding window approach. We conducted Pearson correlation and cluster analyses to identify regions with consistent ONI-precipitation relationships. Our findings reveal notable temporal variability, with a general decrease in correlation strength since the window 1995–2014. This decline is likely driven by changes in ENSO dynamics and the influence of other climate variability modes, highlighting the need to consider factors modulating the ONI-precipitation relationship. Notably, the addition of the strong 2015 El Niño, which exhibited inconsistent precipitation behaviour compared to previous strong El Niño events such as 1997, contributed to this weakening. While the 1997 El Niño brought widespread positive rainfall anomalies, the 2015 event was marked by weaker and even negative precipitation anomalies in part of the region. This difference mirrors similar patterns reported in other parts of South America, such as Ecuador and Coastal Peru, and may be linked to a poleward shift in the jet streams during the 2015/2016 El Niño. The results underscore the complexity of ENSO's impact on regional climate and highlight the need for adaptive agricultural planning. By enhancing the understanding of ONI-precipitation dynamics, this study aims to improve long-term climate predictions and support sustainable agricultural practices in the Pampean region.

How unusual was Australia's 2017–2019 Tinderbox Drought?

Australia’s Murray-Darling Basin experienced three consecutive years of meteorological drought across 2017–2019, collectively named the ‘Tinderbox Drought’. Rainfall deficits during the three-year drought were most pronounced in the Australian cool season (April to September). Deficits in both the cool season and annual total rainfall were unprecedented in the instrumental record. However, the instrumental record provides just one of a range of equally plausible climate trajectories that could have occurred during this period. To determine if the Tinderbox Drought was outside this range, we used observational data from prior to the onset of the drought to construct Linear Inverse Models (LIMs) that emulate the stationary statistics of Australian rainfall and its connection to global sea surface temperature (SST) anomalies. Overall, we find that rainfall deficits were most unusual in the northern Murray-Darling Basin, and during the final year of the drought. The global SST anomalies observed during the first two years of the Tinderbox Drought, particularly the cool anomalies in the central tropical Pacific and western Indian Ocean, are not typically associated with low rainfall across the Murray-Darling Basin. In terms of single-year rainfall anomalies, the only aspect of the Tinderbox Drought that was beyond the range of the LIMs was annual-total rainfall over the northern Murray-Darling Basin during 2019. This coincided with an extreme positive Indian Ocean Dipole event that was also beyond the range of the LIMs. When considered in terms of basin-wide rainfall over the full three years, rainfall deficits during the Tinderbox Drought were beyond the LIM range in terms of both cool-season and annual-total rainfall. This suggests an anthropogenic contribution to the severity of the drought—likely exacerbated by the 2019 extreme positive Indian Ocean Dipole event.

Spatiotemporal climate variability and food security implications in the Central Ethiopia Region

Studies focusing on the spatiotemporal distribution of climatic parameters and meteorological drought are of paramount significance for countries like Ethiopia, where climate change and variability cause major losses to rain-dependent agriculture. In this study, the National Meteorology Institute of Ethiopia provided an Enhanced National Climate Services (ENACTS) dataset at a spatial resolution of approximately 4 km by 4 km over 38 years (1981–2018) was used to study climate trends, spatiotemporal variability, and meteorological drought in the Central Ethiopia Region. Coefficient of variation (CV), Standardized Rainfall Anomaly (SRA), Standardized Precipitation Index (SPI), Mann-Kendall trend test, and Sen's slope were used for the analysis. The findings suggest that Belg rainfall (also known as "small-rain") varied greatly in space and time over the study area, with area-averaged CV of 29 % and pixel-level CVs ranging from 63 to 93 %. The average precipitation during Belg experienced a 15 % decrease from 2000 to 2019 compared to the preceding two decades, from 1981 to 1999. The maximum temperature has increased significantly during the Annual, Belg, and Bega seasons. The SPI and SRA showed that there have been multiple drought episodes with rising negative rainfall anomalies, with a drought occurring every 2.9 years during the Kiremt (also called "big rain", spanning from June to September) and Belg seasons. The growing negative rainfall anomaly, high CV, and highly significant increase in mean maximum temperature during the Belg season is concerning for food security and poverty eradication. The notable rise in rainfall during the June (sowing period) and November (harvesting period) also hurts crop production during the main cropping season. Thus, developing appropriate adaptation strategies and policies oriented toward climate-resilient agriculture is crucial to meet the global sustainable development goals (SDGs) and Africa Union's Agenda 2063.

A Tale of Two Novembers: Confounding Influences on La Niña’s Relationship with Rainfall in Australia

Abstract Despite common background La Niña conditions, Australia was very dry in November 2020 and wet in November 2021. This paper aims to provide an explanation for this difference. Large-scale drivers of Australian rainfall, including El Niño–Southern Oscillation, Indian Ocean dipole, Southern Annular Mode, and Madden–Julian oscillation, were examined but did not provide obvious clues for the differences. We found that the absence (in 2020) or presence (in 2021) of an enhanced thermal wind and subtropical jet over the Australian continent contributed to the rainfall anomalies. In general, La Niña sets up warm sea surface temperatures around northern Australia, which enhances the meridional temperature gradient over the continent and hence thermal wind and subtropical jet. In November 2021, these warm sea surface temperatures, coupled with a persistent midlatitude trough, which advected cold air over the Australian continent, led to an enhanced meridional temperature gradient and subtropical jet over Australia. The enhanced jet provided favorable conditions for the development of rain-bearing weather systems across Australia. In 2020, the continent was warm, displacing the latitude of maximum meridional temperature gradient south of the continent, resulting in fewer instances of the subtropical jet over Australia, and little development of weather systems over the continent. We highlight that although La Niña tilts the odds to wetter conditions for Australia, in any given month, variability in temperatures over the continent can contribute to subtropical jet variability and resulting rainfall in ways which confound the normal expectation from La Niña. Significance Statement Forecasts of El Niño–Southern Oscillation are eagerly awaited, as the state of this climate driver has profound impacts on the likelihood of rainfall in regions around the world. While El Niño and La Niña do change rainfall likelihoods, the actual outcomes of these events are sometimes counter to expectation. This work explores one of the confounding factors to those expectations in the Australian context—the role of the meridional temperature gradient over the continent in modifying the storm track over Australia, which can disrupt the expected El Niño and La Niña teleconnections. We present case studies for two La Niña springs, highlighting that the Australian continent can help shape its own weather toward wetter or drier outcomes.

Seasonal, Decadal, and El Niño-Southern Oscillation-Related Trends and Anomalies in Rainfall and Dry Spells during the Agricultural Season in Central Malawi

As governments continue to address climate change when formulating policy, there remains a need to determine if such a change exists in the historical record to inform clear indices for monitoring the present climate for site-specific interventions. This study characterised trends and anomalies in rainfall and dry spells, providing local information often projected from satellites or regional data in data-scarce regions. From 1961 to 2007, daily rainfall records in Central Malawi were used to calculate indices for low-(Balaka), medium-(Bunda, Chitedze, KIA), and high-altitude (Dedza) sites, which were then subjected to Mann–Kendall’s, Cramer’s, and Spearman-Rho’s trend tests. Significant decreasing trends in terms of wet days and growing season length were evident across locations. Seasonal and extreme rainfall, dry spells, and inter-seasonal and near-decadal anomalies were not consistently or inevitably significant. Unexpectedly, rainfall anomalies were largest in Bunda and KIA, which have mild climatic regimes, while the lowest were in Balaka, a rainfall-averse zone. The relationship between El Niño-Southern Oscillation (ENSO) and extreme rainfall and dry spell events did not reach statistical significance. In conclusion, extreme precipitation and dry spell events show varied intensities and proportions rather than increased frequency. The disparate results largely justify the need for in-depth local-scale assessments for agroclimatic applications.

Moisture dynamic processes of the westward propagation of quasi-biweekly oscillation in Asian tropical summer monsoon rainfall

The quasi-biweekly oscillation (QBWO) is an important component of tropical monsoon variations. In this study, the QBWO rainfall demonstrates a westward propagation across the tropical Asian monsoon region, originating from the western North Pacific, passing through the South China Sea and the Bay of Bengal, and ultimately reaching the northwestern Indian Peninsula. Notably, the rainfall anomalies over the South China Sea precede those over the Bay of Bengal by one quarter of the QBWO life cycle. Enhanced (suppressed) rainfall is closely associated with significant positive (negative) specific humidity anomalies, primarily induced by meridional moisture transport at the lower levels, as revealed by a moisture budget analysis. Specifically, the alternating presence and westward movement of northerly anomalies on the eastern (western) flank of anticyclonic (cyclonic) circulation anomalies are responsible for transporting low-frequency moisture across tropical Asia, thereby instigating the westward propagation of QBWO rainfall. Thus, the multiscale interactions between atmospheric circulation and moisture play a pivotal role in the development of QBWO monsoon rainfall, and understanding the moisture dynamics of this rainfall development would provide useful information for subseasonal rainfall prediction in tropical Asia.

Diverse Responses of Strong Positive SST and Rainfall Indian Ocean Dipole Events under Greenhouse Warming

Abstract Recent research has shown that there is a projected increase in the frequency of strong positive Indian Ocean dipole (spIOD) events in terms of both sea surface temperature (SST) and precipitation. However, it is not clear whether the spIOD events defined by SST and precipitation, hereafter referred to as SST-spIOD and Pr-spIOD events, respectively, will increase at the same pace under greenhouse warming. Using climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and CMIP6 that can reasonably simulate the spIOD events, here we find that the occurrence of Pr-spIOD events increases much more than that of SST-spIOD events (+217% vs +77%) under the future high-emission scenario. The diverse response stems from a notably large increase in the spIOD events with strong rainfall but moderate SST anomalies (Pr-only spIOD), which is facilitated by a change in the local meridional Hadley circulation induced by land–sea thermal contrast in addition to the background mean-state SST warming. For the spIOD events with prominent anomalies in both rainfall and SST (concurrent spIOD), their occurrences are projected to increase, but their average SST amplitude is projected to weaken. The increased occurrence is associated with a westward-extended structural change induced by mean linear zonal advection feedbacks, while the weakened event-average SST amplitude results from a more stabilized atmosphere and coincides with the projected reduction in IOD SST skewness. Our results suggest that IOD-related mitigation strategies should consider the diverse responses of different kinds of spIOD events to greenhouse warming.

Strain variation and anomalous climate synergistically influence cholera pandemics.

Explanations for the genesis and propagation of cholera pandemics since 1817 have remained elusive. Evolutionary pathogen change is presumed to have been a dominant factor behind the 7th "El Tor" pandemic, but little is known to support this hypothesis for preceding pandemics. The role of anomalous climate in facilitating strain replacements has never been assessed. The question is of relevance to guide the understanding of infectious disease emergence today and in the context of climate change. We investigate the roles of climate and putative strain variation for the 6th cholera pandemic (1899-1923) using newly assembled historical records for climate variables and cholera deaths in provinces of former British India. We compare this historical pandemic with the 7th (El Tor) one and with the temporary emergence of the O139 strain in Bangladesh and globally. With statistical methods for nonlinear time series analysis, we examine the regional synchrony of outbreaks and associations of the disease with regional temperature and rainfall, and with the El Niño Southern Oscillation (ENSO). To establish future expectations and evaluate climate anomalies accompanying historical strain replacements, climate projections are generated with multi-model climate simulations for different 50-year periods. The 6th cholera pandemic featured the striking synchronisation of cholera outbreaks over Bengal during the El Niño event of 1904-07, following the invasion of the Bombay Presidency with a delay of a few years. Accompanying anomalous weather conditions are similar to those related to ENSO during strain replacements and pandemic expansions into Africa and South America in the late 20th century. Rainfall anomalies of 1904-05 at the beginning of the large cholera anomaly fall in the 99th percentile of simulated changes for the regional climate. Evolutionary pathogen change can act synergistically with climatic conditions in the emergence and propagation of cholera strains. Increased climate variability and extremes under global warming provide windows of opportunity for emerging pathogens.