Deficient Rainfall Research Articles

Assessing the impact of forest management and climate on a peatland under Scots pine monoculture using a multidisciplinary approach

Abstract. Assessing the scale, rate and consequences of climate change, manifested primarily by rising average air temperatures and altered precipitation regimes, is a critical challenge in contemporary scientific research. These changes are accompanied by various anomalies and extreme events that negatively impact ecosystems worldwide. Monoculture forests, including Scots pine (Pinus sylvestris L.) monocultures, are particularly vulnerable to these changes due to their homogeneous structure and simplified ecosystem linkages compared to mixed forests, making them more sensitive to extreme events such as insect outbreaks, droughts, fires and strong winds. In the context of global warming, forest fires are becoming extremely dangerous, and the risk of their occurrence increases as average temperatures rise. The situation becomes even more dramatic when fire enters areas of peatlands, as these ecosystems effectively withdraw carbon from the rapid carbon cycle and store it for up to thousands of years. Consequently, peatlands become emitters of carbon dioxide into the atmosphere. In this study, we aim to trace the last 300 years of historical development of a peatland situated in a Scots pine monoculture. Our focus is on the Okoniny (Jezierzba) peatland located within Tuchola Forest in northern Poland, one of the country's largest forest complexes. We delved into the phase when the peatland's surroundings transitioned from a mixed forest to a pine monoculture and investigated the impact of changes in forest management on the peatland vegetation and hydrology. Our reconstructions are based on a multi-proxy approach using pollen, plant macrofossils, micro- and macro-charcoal, and testate amoebae. We combine the peatland palaeoecological record with the dendrochronology of Pinus sylvestris to compare the response of these two archives. Our results show that a change in forest management and progressive climate warming affected the development of the peatland. We note an increase in acidity over the analysed period and a decrease in the water table over the last few decades that led to the lake–peatland transition. These changes progressed along with the strongest agricultural activity in the area in the 19th century. However, the 20th century was a period of continuous decline in agriculture and an increase in the dominance of Scots pine in the landscape as the result of afforestation. Dendroclimatic data indicate a negative effect of temperature on Scots pine and pressure from summer rainfall deficiency. Additional remote sensing analysis, using hyperspectral, lidar and thermal airborne data, provided information about the current condition of the peatland vegetation. With the application of spectral indices and the analysis of land surface temperature, spatial variations in peatland drying have been identified. Considering the context of forest management and the protection of valuable ecosystems in monocultural forests, the conclusions are relevant for peatland and forest ecology, palaeoecology, and forestry.

Assessing Drought Patterns in Al-Baha: Implications for Water Resources and Climate Adaptation

Due to growing water demands and changing hydro-meteorological variables brought on by climate change, drought is becoming an increasingly serious climate concern. The Al-Baha region of Saudi Arabia is the subject of this study because it is susceptible to both agricultural and meteorological droughts. This study investigates how climate change affects patterns of drought in Al-Baha by analyzing four drought indices (Agricultural Standardized Precipitation Index (aSPI), the Standardized Precipitation Index (SPI), the Rainfall Deficiency Index (RDI), and the Effective Reconnaissance Drought Index (eRDI)) for the years 1991–2022. Analysis of rainfall data was carried out to classify drought events according to their duration, frequency, and severity. Results showed that severe droughts occurred in 2009, 2010, 2012, 2016, and 2022, with 2010 being the worst year. Results also indicated a notable decrease in precipitation, which has resulted in extended dry spells. Several indices indicate that this tendency has significant ramifications for agriculture, particularly in areas where farming is a major economic activity. In addition, the possible occurrence of hydrological drought was also observed based on the negative values for the Reservoir Storage Index (RSI) in Al-Baha. Projections for the future under two Representative Concentration Pathways (RCPs) showed notable variations in temperature and precipitation. Both the RCP4.5 (low emission) and the RCP8.5 (high emission) projection scenarios indicate that drought conditions will likely worsen further. Depending on the emission scenario, it is projected to show a temperature increase of 1–2 °C, whereas the variability in precipitation projections indicates significant uncertainty, with a reduction change in the range of 1.2–27% between 2050 and 2100. The findings highlight the urgent need for proactive adaptation strategies, effective water resource management, and the development of sophisticated drought prediction tools. Addressing these challenges is crucial for sustaining agriculture and managing water scarcity in Saudi Arabia in the face of increasing drought risk.

Seasonal climate summary southern hemisphere (autumn 2020): another coral bleaching event for the Great Barrier Reef without an active El Niño

Austral autumn 2020, inclusive of the months March, April and May, followed a period of hot and dry conditions over summer that led to high bushfire risk in Australia due to a strong positive Indian Ocean Dipole. The autumn period was also warmer and drier than average overall with strong differences across the states. Notable exceptions were rainfall across New South Wales, Tasmania and Victoria, and rainfall associated with Tropical Cyclone Esther near the Pilbara and the Northern Territory Top End. Overall, Australia maximum mean temperatures were +0.65°C above average, with Western Australia in the top 10 recorded temperatures at +1.53°C above average. South-east Australian rainfall led to flooding and extinguished the remaining fires of the 2019–2020 bushfire season. The rainfall did not reach coastal regions of south-east Queensland where severe rainfall deficiencies persisted. Autumn 2020 was classified as neutral in terms of the El Niño–Southern Oscillation (ENSO) and marks the second time that the Great Barrier Reef has experienced mass coral bleaching due to elevated ocean temperatures in an ENSO neutral year. Elevated sea surface temperatures in the Coral Sea are largely attributed to a general warming trend in the region. Antarctic sea ice extent went from below average to close to average by the end of May 2020, aided by a positive Southern Annular Mode. At the end of autumn 2020, there were early signs of a La Niña event building, with negative temperature anomalies in the subsurface and cooling of sea surface temperatures along equatorial Pacific.

Impact of cloud properties and aerosols on the spatial distribution of Indian summer monsoon rainfall: A case study

Quantitative seasonal Indian summer monsoon (ISM) rainfall forecasting has been a challenge for the climate models as it is sensitive to cloud properties, which are modulated by large-scale dynamics. Proper understanding of the role of dynamics, aerosols, and cloud microphysical processes is important for the precipitation calculation in dynamical models. The all-India averaged seasonal ISM rainfall (ISMR) from June to September had been normal or above normal, however there were large spatial variations. Some meteorological subdivisions, the majority of which lie in the Gangetic Plains, received deficient seasonal rainfall during recent years 2022 and 2010. The quantitative seasonal prediction of the spatial distribution of ISMR from global coupled models (GCMs) has also shown a hard time for accurate spatial rainfall distribution. Four monsoon years (2022, 2021, 2011, and 2010) are considered, in which the country as a whole (all India land points) was ‘above normal’ or ‘normal’. However, in two specific years (2022 and 2010), some subdivisions received deficient rainfall (17% and 15% of the total area). We have used several datasets from the ground, and satellite observations, along with reanalysis products and computed climatology and anomalies for monsoon years of 2022 and 2010. The low-level wind and vertical velocity along with cloud microphysics played a pivotal role in the heterogeneous distribution of ISMR during 2022 and 2010 as compared to years 2021 and 2011. Here, we have demonstrated that the spatial heterogeneity of the positive and negative precipitation anomalies was consistent with cloud properties. Aerosols might have an impact on the cloud microphysical processes and modulate cloud properties and rainfall over different regions due to the availability of water vapor. Therefore, the inclusion of aerosol indirect effects in climate models is crucial for better interactions among dynamics, aerosol, and cloud microphysics. Proper representation of cloud droplet size distribution and microphysical conversion rates might be helpful for quantitative seasonal ISMR forecasting at a smaller spatial scale.

Climate change adaptation strategies among smallholder farmers in Senegal’s semi-arid zone: role of socio-economic factors and institutional supports

In dryland agricultural systems, developing appropriate climate-smart technology (CST) options is important to adapt agriculture to climate change and transition toward sustainability, as well as increasing productivity and incomes. This study examines the impact of socio-economic and institutional support on community responses to climate change and the impact of changes in three selected regions of Senegal (Meouane, Thiel, and Daga Birame), which fall within different rainfall gradients. It captures community perceptions of climate change, compares them to long-term meteorological data, and identifies site-specific response strategies. Communities are randomly selected from a list of communities within the target sites. We used a two-stage stratified sampling method to select sample households. First, purposive sampling was conducted to select at least six (6) villages as a cluster within each rainfall gradient. Likewise, the selection of households in each cluster was based on the main value chains of crops grown in the study area, namely groundnut, millet, black pea, and livestock. A total of 145 households participated in this study. Data from surveys conducted during the 2022 post-harvest season were analyzed using descriptive statistics and logit models. The analysis found that smallholders have a comprehensive understanding of climate indicators, including annual rainfall, shortened crop seasons, and rising temperatures, compared to historical data trends. Additionally, the results highlight how farmers view the negative impacts of seasonal rainfall deficiencies (72%), delayed start of the growing season (88%), frequent dry spells (68%), and longer dry spells (76%), which ultimately lead to decreased grain and fodder yields. The logit model also highlights the importance of socio-economic and institutional factors such as access to credit, extension services, agricultural experience, frequency of interaction with extension workers, and access to government subsidies. These factors play a crucial role in farmers’ decision to adopt CST. Given the specificity of community contexts, these insights have important implications for guiding policymakers and making it easier to reduce climate risk among smallholder farmers.

Fuzzy comparison of drought vulnerability based on the analytical hierarchy process

The vulnerability represents the level to which any ecosystem experiences impairment due to natural distress. One such distress is drought, a prolonged phase of deficient rainfall that causes the depletion of water resources. The possibility of the influences of drought principally depends on the vulnerability of the affected area. The predominantly arid climate of Pakistan and the dependence of its economy on agriculture make it vulnerable to climate change. Rahim Yar Khan and Tharparkar have similar environmental conditions, but Tharparkar experiences more droughts. Vulnerability factors observed by the two districts among the regions are different even with similar climate conditions. The system vulnerability to drought was observed for two districts by using the analytical hierarchy process (AHP) and drought vulnerability index (DVI). The drought vulnerability index (DVI) was used to assess the meteorological, agricultural, hydrological, and socio-economic indicators to build the hierarchy for these inconsistence factors and evaluate the most vulnerable and affecting cause among the meteorological, agricultural, hydrological, and socio-economic indicators. The selected measures specify the hypotheses and the relativity of the indicators to the overall vulnerability of the system. The evaluated weights for each variable are derived from the analytical hierarchy process by comparing the variables of the selected indicators. Due to different meteorological, agricultural, and socio-economic conditions, the weights for the DVI were not the same in both study districts, i.e., Rahim Yar Khan and Tharparkar. The classification of vulnerability depending upon the drought vulnerability index with AHP suggests that the DV indexation is favorable in assessing the regional drought vulnerability. The drought vulnerability assessment of Tharparkar indicates that Tharparkar is highly vulnerable to drought, i.e., DVI = 0.066, as it is highly dependent on irrigation resources for its agriculture and livestock. The unavailability of hydrological resources has increased the drought vulnerability of the Tharparkar, which corresponds to a high level of agricultural damage due to droughts. However, the district of Rahim Yar Khan with developed irrigation resources has a lower drought vulnerability index (DVI = 0.011). It is necessary for Tharparkar to establish countermeasures to mitigate the drought vulnerability through the development of water resources. Future studies are needed to be focused on more indicators for assessing particular drought vulnerability issues in order to reduce the drought vulnerability of Tharparkar.

Carving Drought Impact Over Purulia District, West Bengal, India

Purulia was the westernmost district of West Bengal (from 1956) and is drought-prone due to deficient rainfall, its undulating topography with rugged hilly terrains and its positioning near the Tropic of Cancer, the spatial evaluation of vulnerable and risk-prone places.
 The various impacts of drought, such as meteorological, hydrological, and agricultural, are assessed by considering the meteorological parameters, vulnerability, and risk levels. The fundamental factors impacting susceptibility and risk are recognised, and the drought years are analysed. The methodologies applied GIS technology, EREDAS, and secondary data were collected to analyse the type of drought. The intensities and types of droughts: a spatial analysis and relative vulnerability assessment of the Kashipur/ Purulia block by Remote Sensing and GIS. Analysis of pre- and post-monsoon meteorological and Agricultural drought.
 Agriculture is a climate-sensitive activity. The mechanism is to know the farmers, what crops to grow, when suitable, the climatic parameters, temperature, rainfall concentration, and seasonal hazards. A well-planned agriculture practice has been proposed, and an adequately calculated water budget, catchment treatment plan, and implementation of a perfect crop plan, seeds, manures, and pesticides are the weapons of the drought-hit Purulia/Kashipur farmers.

Using Calibrated Rainfall Forecasts and Observed Rainfall to Produce Probabilistic Meteorological Drought Forecasts

Most existing drought forecast systems rely only on observed or forecast rainfall, losing valuable context gained from considering both. The lack of a direct link between observed and forecast rainfall reduces the physical consistency of a system, motivating the development of a methodology that can directly link the two. The methodology developed in this study allows the comparison of the calibrated ensemble forecasts of rainfall totals from a dynamical climate model to observed rainfall deficiencies from a gridded rainfall analysis. The methodology is used to create a probabilistic product that forecasts the chance of entering meteorological drought, with lead times of one month (monthly forecast) and three months (seasonal forecast). Existing deficiency areas are included to facilitate analysis of how these areas are forecast to change. The performance of the developed methodology was verified using Percent Correct (PC), Brier Score (BS), and Relative Operating Characteristic (ROC) statistics. Analysis of the forecast plots was also completed visually. Forecast performance for areas with existing deficiencies as well as for non-deficiency areas was promising (PC rates of >79% and >97%, respectively). Although PC rates for observed deficiencies were low across most months, the mean forecast probability for these areas was 36%, indicating the system had value and outperformed climatology. A calibrated, coupled product like the one scoped in this study has not been explored and we note that it could be an invaluable tool for quantifying meteorological drought onset and persistence in Australia.

Evaluating Rainwater Harvesting Systems for Water Scarcity Mitigation in Small Greek Islands under Climate Change

Rainfall variability, exacerbated by climate change, poses significant challenges to water resource management, particularly in regions prone to intense droughts and floods. The Greek islands, characterized by poor water potential, face interannual water supply issues dating back to their earliest habitation. Rainwater harvesting (RWH) systems emerge as a promising solution to address water scarcity in these regions. This study simulates RWH systems for two small Greek islands, Fourni and Nisyros, representing similar rainfall regimes. Multiple scenarios are explored, and system reliability is assessed in light of simulated daily rainfall time series incorporating climate change projections. Utilizing eight low/medium (RCP 4.5) and eight high (RCP 8.5) emission scenarios over a future 35-year period, the study evaluates system reliability based on model parameters (collection area: 40 to 140 m2, rainwater tank volume: 5 to 30 m3, number of household members: 2, 3), with 30% coverage of total daily water demand (180 L/d). Negligible evapotranspiration effects are assumed due to closed-type tanks. Results indicate that the RWH system demonstrates high efficiency in general. The investigation for the future period revealed that the system’s performance varies, with instances where daily demand targets are not met, even with a 30 m3 tank. This research underscores the potential of RWH systems as a cost-effective “green” solution, particularly in regions with deficient rainfall regimes. It highlights the importance of localized water management strategies, reducing reliance on mainland water transportation, and assisting desalination unit operations. In conclusion, this study contributes to the assessment of RWH systems, demonstrating their viability as a sustainable water management solution in regions facing water scarcity, contingent on local rainfall conditions and system design parameters.

A Potential Seasonal Predictor for Summer Rainfall over Eastern China: Spring Eurasian Snowmelt

Abstract The hydrological effect of snow over Eurasia is important for regulating regional and global climate through affecting land–atmosphere energy exchange. Based on observational and reanalysis datasets, this study investigates the effect of spring Eurasian snowmelt on the following summer rainfall over eastern China during the period of 1979–2018. The results show that a substantial meridional dipole pattern of summer rainfall anomalies over eastern China is closely associated with the preceding spring snowmelt anomalies over Eurasia, especially over remote Siberia. Excessive snowmelt anomalies over Siberia in spring could result in a wetter local soil condition from spring until the following summer, thereby increasing latent heat fluxes and reducing local surface temperature, and vice versa. Then, the anomalous summer surface cooling over Siberia increases the meridional gradient of temperature between the Eurasian midlatitudes and high latitudes, which intensifies the Eurasian atmospheric baroclinicity and motivates the eddy‐induced geopotential height responses along with the significant wave propagations spreading from the Eurasian high latitudes to Lake Baikal. As a result, excessive spring snowmelt anomalies over Siberia tend to be accompanied with an anomalous anticyclone circulation to the east of Lake Baikal and an anomalous cyclonic circulation over southeastern China in the following summer. This could lead to a meridional dipole pattern of summer rainfall anomalies over eastern China, with deficient rainfall over northern China and slightly excessive rainfall over southern China. The present findings highlight the lagged effect of spring Eurasian snowmelt on summer climate over eastern China, with implications for the regional seasonal climate prediction. Significance Statement Frequent summer droughts and floods over eastern China cause serious damage to the regional economy and society. This study reveals an important effect of spring Eurasian snowmelt anomalies on the following summer rainfall anomalies over eastern China. Through affecting the local land–atmosphere energy exchange and regulating the remote atmospheric circulation, excessive spring Eurasian snowmelt anomalies could induce a substantial meridional dipole pattern of summer rainfall anomalies over eastern China, with deficient rainfall over northern China and excessive rainfall over southern China, and vice versa. Therefore, this work identifies spring Eurasian snowmelt as a potential seasonal predictor for summer rainfall over eastern China, which is home to more than a billion people. This is important for the local livelihood, including agriculture, water resources, ecosystems, human health, and economies.

Rainfall trends and spatiotemporal patterns of meteorological drought in Menna watershed, northwestern Ethiopia

Understanding the spatiotemporal patterns of drought is crucial for planning, disaster preparedness, vulnerability assessment, impact evaluation, and policy formulation to mitigate drought-induced effects. The purpose of this study was to assess rainfall trends and spatiotemporal patterns of meteorological drought using geospatial techniques in Menna watershed. The Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) rainfall, and station-based observed rainfall were the datasets used. The station-based rainfall was used to confirm the accuracy of CHIRPS rainfall data. The Mann-Kendall (MK) test and Sen's slope estimator were utilized to assess trends and ascertain the extent of change. To characterize meteorological droughts, percent of normal (PN), standardized anomaly index (SAI), and standardized precipitation index (SPI) were computed during the crop growing seasons (2000–2022). The validation result confirmed a strong agreement between the observed and CHIRPS rainfall data (R2 = 0.88). Based on the MK test, an increasing trend has been observed in annual (3.7 mm/year) and belg (3.4 mm/year) rainfall, which was significant at p < 0.05. But the kiremt season was slightly decreasing (−0.7 mm/year). The PN, SAI, and SPI values detected that 2002, 2004, 2009, 2011, 2014, 2015, and 2019 were drought years in the area. Even only 1.4, 0.2, and 0.5% of the watershed were free from drought in 2009, 2014, and 2015, respectively, due to extremely high rainfall deficiency. Conversely, 2001, 2010, and 2016 were notable for having the highest amounts of rainfall compared to the other years. Generally, the region could be classified as an area highly susceptible to meteorological drought in northwestern Ethiopia. There was no even a single year free from drought in the entire study period. To that extent, about 86% of it had repeatedly encountered extreme rainfall deficit (7–23 times) during the study period. Thus, the population has always been repeatedly smashed down by the frequent droughts. To tackle existing challenges and mitigate upcoming risks, continual droughts monitoring and implementation of efficient early warning systems are vital for the region.

Statistical Analysis of Thirty-Year Rainfall Variability in Udaipur District, Rajasthan, India

The rainfall variability for the Udaipur district for thirty years (1991–2020) was statistically analysed in this study. The linear regression (parametric) and Mann–Kendall (non-parametric) trend test along with precipitation indices performed using rainfall data collected from 9 rain gauge stations situated in different parts of the Udaipur district, Rajasthan, India. An increasing trend was found between the months March to November in the Udaipur district, indicating that total annual rainfall has increased in these months during the study period. About 85.20% of the total annual rainfall is occurred due to the southwest monsoon during the rainy season. The PCI (21.74 to 57.92) and CV (11.04 to 21.23) values show the high-nonuniformity and less rainfall variability, respectively. The SRA values for each year have been greater than -0.84 (no drought category) during the study period. The rainfall deficiency took place only four out of 30 years of the study period, 1995, 1999, 2000, and 2002, which fall under the category of large deficiency. The values of the wetness index indicate that during the study period,2006 was the wettest year due to the maximum rainfall (Wi = 179.07) while 2000 was the driest year due to the minimum rainfall (Wi = 54.26). Total annual rainfall has increased in the last three decades, which shows the need for implementation of all necessary plans by the government for proper rainwater utilization and management to prevent future natural disasters like floods.

Interannual variations of westward extension area of western Pacific subtropical high and its relationship with precipitation in East Asia

The western Pacific subtropical high (WPSH) is viewed as an important part of the East Asian summer monsoon system and its western boundary location significantly affects regional weather and climate. Based on characteristics of the WPSH western boundary in boreal summer, this study proposes a new index of WPSH, the westward extension area (WEA) index, defined as the area enclosed by the 587 dagpm contour in the region (10°–50°N, 105°–130°E), which can reasonably describe the area variations of WPSH when approaching and landing coastal regions. Compared with the canonical area index of WPSH, the WEA index can more effectively represent the WPSH-associated atmospheric circulation, water vapor transport, and convective activities in the boreal-summer East Asia-northwestern Pacific. A big WEA index significantly indicates flood in the middle reaches of Yangtze River basin and drought in South China. The WEA of WPSH has a significant connection with precipitation in Maritime Continent, due to the convection-circulation interaction in Philippine Sea. There, the WPSH-related sea surface temperature (SST) cooling and rainfall deficiency can excite Rossby waves, which induces the anomalous anticyclone development and the westward stretching and intensifying of WPSH that in turn further reduces rainfall in Philippine Sea. Moreover, the WEA index is significantly modulated by the preceding El Niño-type and tropical Indian Ocean SST anomalies, which may provide a highly predictable indicator of the continental precipitation in East Asia.

Evaluating crop water stress through satellite-derived crop water stress index (CWSI) in Marathwada region using Google Earth Engine

Accurate information of crop water requirements is essential for optimal crop growth and yield. Assessing this information at the appropriate time, particularly during the vegetative and reproductive stages when water demand is highest, is crucial for successful crop production. Our study cantered on the drought-prone Marathwada region, specifically targeting the years 2015 to 2020, encompassing the challenging drought year of 2015 and the favourable year of 2020. The crop water stress was detected using crop water stress (CWSI) index and compared with normalized difference vegetation index (NDVI) and normalized difference wetness index (NDWI) derived from satellite data. Our findings reveal a negative correlation between the CWSI and satellite derived vegetation indices NDVI and NDWI. Notably, the NDWI index exhibits stronger alignment with CWSI compared to NDVI. The correlation demonstrates particular robustness during drought or deficient rainfall years such as 2015, 2017, and 2019, while weaker correlations are observed in 2016, 2018, and 2020. Moreover, these correlations display variations across different areas within distinct rainfall zones.

CAIPEEX: Indian Cloud Seeding Scientific Experiment

Abstract The demand for effective methods to augment precipitation over arid regions of India has been increasing over the past several decades as the changing climate brings warmer average temperatures. In the fourth phase of the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX IV), a scientific investigation was conducted over a rain-shadow region of the Western Ghats mountains in India. The primary objective was to investigate the efficacy of hygroscopic seeding in convective clouds and to develop a cloud seeding protocol. CAIPEEX IV followed the World Meteorological Organization (WMO) recommendations in a peer-reviewed report with physical, statistical, and numerical investigations. The initial results of the campaign in the monsoon period of 2018 and 2019 with two instrumented aircraft, a ground-based dual-polarization C-band radar, a network of rain gauges, radiosondes, and surface aerosol measurements are reported here. The hygroscopic seeding material was detected in cloud droplets and key cloud microphysical processes in the seeding hypothesis were tracked. The formidable challenges of assessing seeding impacts in convective clouds and the results from 150 seed and 122 no-seed samples of randomized experiments are illustrated. Over 5,000 cloud passes from the airborne campaign provided details about the convective cloud properties as the key indicators for a seeding strategy and the evaluation protocol. The experimental results suggest that cloud seeding can be approached scientifically to reduce uncertainty. The results from this study should interest the scientific community and policymakers concerned with climate change’s impact on precipitation and how to mitigate rainfall deficiencies.

Assessing the impact of precipitation on hardrock aquifer system using standard precipitation index and groundwater resilience index: a case study of Purulia, West Bengal, India.

Groundwater stored in the aquifers provides water security during natural hazards, e.g. clean water access during floods and droughts. Groundwater drought, a phenomenon closely linked with rainfall (climate) variability, is less researched, especially in India. This study aims to detect precipitation and groundwater droughts and comprehend the groundwater response to long-term precipitation trends (25years). As a case study, the drought-affected and groundwater-depleted Purulia district in West Bengal, India, which is a part of the Chotanagpur plateau, was selected. Precipitation and groundwater droughts (in aquifer types of shallow, moderate and deep) are detected using the Standard Precipitation Index (SPI) and Groundwater Resilience Index (GRI). During the 25 yearstudy period (1996-2020),Purulia had 13 (52%) rainfall deficiency years, with an annualaverage rainfall of 1382 mm. SPI detected four severe droughts and the most severe occurring in 2010-2011 (1.50). GRI found that aquifermedium had a 71% [Formula: see text] conditions and are the most resilient and aquiferdeep experienced maximum extreme drought events and is the most stressed. The cross-correlationcoefficients (CCCs) between rainfall and groundwater is moderate in deep, shallow, and medium aquifers, with CCCs - 0.43, - 0.59, and - 0.49, respectively. Positive CCCs are found for seasonal lags of - 3, - 4, and - 7. The study found that during the monsoon, average depth to groundwater level is 1 - 4m and it drops to 8-10m during the lean period, more than 85% of wells are vulnerable to extreme droughts (SPI > 1.5), aquifer's response to rainfall is aquifershallow > aquifermoderate > aquiferdeep, and aquifer's may be arranged as aquifermoderate > aquifershallow > aquiferdeep depending on their drought resistance. This study, with the use of statistical tools and long term data, will aid in the management of groundwater at varying depthsby creating basis forunderstanding the groundwater response to rainfall events.

Bathymetric modelling for long-term monitoring of water dynamics of Ramsar-listed lakes using inundation frequency and photon-counting LiDAR data

Accurate information on lake bathymetry and water dynamics is crucial for comprehending the intricate ecological processes in wetland ecosystems, which in turn can inform effective conservation and management strategies. However, obtaining such information can be challenging, particularly in remote areas with limited data. This study presents a way to leverage inundation frequency and ICESat-2 photon-counting LiDAR data to develop bathymetric models for Ramsar-listed lakes in a semi-arid region of Australia. Based on developed bathymetric models, monthly time series of water areas, levels and volumes were derived, providing a long-term view of the water dynamics of the two lakes from1987-2021. This is the first time that such detailed bathymetry and long-term water dynamics have been established for Ramsar-listed lakes in Australia's Outback. The findings of this study provide the most up-to-date information on the long-term trends of the Ramsar-listed lakes in the region and highlight the lakes’ prolonged dry spells when drought conditions prevailed through much of the 2000s and the 2010s as denoted by rainfall deficiencies and high evaporation. The outcome of this study serves as a valuable baseline for understanding the historical and ongoing status of these Ramsar-listed lakes in a warming and drying climate and contributes to the development of strategic plans to fulfill international obligations for wetland protection under the Ramsar Convention.

The Representation of Soil Moisture-Atmosphere Feedbacks across the Tibetan Plateau in CMIP6

Thermal processes on the Tibetan Plateau (TP) influence atmospheric conditions on regional and global scales. Given this, previous work has shown that soil moisture–driven surface flux variations feed back onto the atmosphere. Whilst soil moisture is a source of atmospheric predictability, no study has evaluated soil moisture–atmosphere coupling on the TP in general circulation models (GCMs). In this study, we use several analysis techniques to assess soil moisture-atmosphere coupling in CMIP6 simulations including: instantaneous coupling indices; analysis of flux and atmospheric behaviour during dry spells; and a quantification of the preference for convection over drier soils. Through these metrics we partition feedbacks into their atmospheric and terrestrial components.Consistent with previous global studies, we conclude substantial inter-model differences in the representation of soil moisture–atmosphere coupling, and that most models underestimate such feedbacks. Focusing on dry spell analysis, most models underestimate increased sensible heat during periods of rainfall deficiency. For example, the model-mean bias in anomalous sensible heat flux is 10 W m−2 (≈25%) smaller compared to observations. Deficient dry-spell sensible heat fluxes lead to a weaker atmospheric response. We also find that most GCMs fail to capture the negative feedback between soil moisture and deep convection. The poor simulation of feedbacks in CMIP6 experiments suggests that forecast models also struggle to exploit soil moisture–driven predictability. To improve the representation of land–atmosphere feedbacks requires developments in not only atmospheric modelling, but also surface processes, as we find weak relationships between rainfall biases and coupling indexes.

‘The Long, Continued Dry’

Droughts are a canonical feature of Australian history and climate, and Australia’s paleoclimate and colonial past is dotted with extended periods of low rainfall. The Federation Drought was one such period. The result of a series of El Niño events, it parched much of Australia between 1895 and 1903 and remains one of the most significant and prolonged periods of rainfall deficiency since European colonisation. It also coincided with, and fuelled, a substantial increase in press coverage of the weather. In this article we examine reportage of the Federation Drought through two newspapers from the Victorian city of Bendigo: The Bendigo Advertiser and The Bendigo Independent. We identify themes that have persisted in drought coverage to the present day, highlighting the role the press has played in shaping how communities and policy makers have understood and managed the extremities of Australia’s climate. We also offer insights into the evolution of current drought reportage and the perspectives it enables or silences.

Relationship Between the Aerosol Loadings Over the Bay of Bengal and the Arabian Sea in the Early Summer and Asian Monsoon Rainfall Anomalies, and the Role of SST Anomalies in the Indian Ocean

AbstractTwo relatively long‐term satellite aerosol products during 1983–2020 and 2000–2020 are employed to investigate interannual relationships between anomalous aerosol loadings over the Bay of Bengal (BoB) and Arabian Sea (AS) in the early summer and Asian monsoon rainfall anomalies. It is shown that increased aerosol loading (IAL) over the BoB is primarily attributed to an intensified upstream aerosol transport by anomalous subtropical westerly winds and coincides with local sea surface temperature (SST) cooling due to intensified prevailing wind and the aerosol dimming effect, and vice versa. A deficient rainfall in India tends to concur with a BoB IAL while excessive rainfall with an AS IAL in May and June. In June, a BoB IAL coincides with significantly deficient rainfall in the southwestern China‐Huaihe River Basin primarily linked to an anomalous cyclone off the coast of Southeast China. Meanwhile a related overturning of Walker Circulation is identified to be driven by the contrast of anomalous convective activity between the southeastern Indian‐BoB and the South China Sea‐Philippine Sea. An AS IAL is associated with air warming in North India due to an elevated aerosol semi‐direct effect and remote forcing that reinforces the meridional air temperature gradient. The IAL over the respective BoB and AS in June are both preceded by cold SST anomalies in the western Indian Ocean that can be traced back to the preceding winter, but the corresponding atmospheric circulations driving aerosol‐monsoon interactions differ distinctly. The above aerosol‐monsoon relationships are sustained primarily during 2000–2020 and vague during 1983–2020.