Precipitation Variability Research Articles

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.

Role of Tropical Disturbances along the South Asian Monsoon Trough in the 2022 Pakistan Floods and the Implications for Interannual Variability

Abstract This study examined the atmospheric circulation patterns that were responsible for the severe flooding that occurred in Pakistan in 2022. It focused on the role of westward-propagating tropical disturbances (TDs) along the South Asian monsoon trough, which are associated with flood-related precipitation events. The study also investigated the interannual precipitation variation in Pakistan over 23 years from 2000 to 2022, using satellite-derived precipitation and atmospheric reanalysis. The results showed high precipitation in southern and central Pakistan, implying tropical influences. The precipitation was the highest in the past 23 years. The massive rainfall was brought by several TDs under the highest water vapor conditions, although a TD of South Asia climatologically tends to weaken before affecting Pakistan. Enhanced easterlies along the Indo-Gangetic Plain, part of the enhanced monsoon trough, supported high water vapor conditions over Pakistan. The high water vapor was also partly supported by the long-lasting active phase of the South Asian monsoon intraseasonal oscillation in 2022. Moreover, the La Niña condition increased moisture transport as a background. On an interannual time scale, the enhanced moisture flux over the Indo-Gangetic Plain resulted in higher precipitation over Pakistan, as occurred in 2022. These high (low) water vapor and precipitation can be partly explained by La Niña (El Niño). However, La Niña and El Niño may not control the TD activity over South Asia. Thus, for 2022, the high water vapor is somewhat empirically predictable, but the active TD activity can be coincidental. Significance Statement In 2022, Pakistan was hit by catastrophic flooding that affected 15% of the population. The analysis of the atmospheric circulation associated with the flooding indicates that weak but rain-bearing tropical disturbances played a significant role in flooding. Several tropical disturbances stayed or moved into Pakistan, bringing massive rainfall although, usually, they tend to weaken before hitting Pakistan. In the past 23 years, La Niña–related weather patterns have partly explained the year-to-year precipitation variation in Pakistan. However, in 2022, the unusually heavy flooding was due to the combined La Niña effect and tropical disturbance activity. Because it is still difficult to predict the seasonal tropical disturbance activity from La Niña, El Niño, and other climatic conditions, seasonal prediction of these floods remains challenging.

Surface energy and mass balance of Mera Glacier (Nepal, Central Himalaya) and their sensitivity to temperature and precipitation

Abstract The sensitivity of glacier mass balance to temperature and precipitation variations is crucial for informing models that simulate glaciers’ response to climate change. In this study, we simulate the glacier-wide mass balance of Mera Glacier with a surface energy-balance model, driven by in situ meteorological data, from 2016 to 2020. The analysis of the share of the energy fluxes of the glacier shows the radiative fluxes account for almost all the energy available during the melt season (May–October). However, turbulent fluxes are significant outside the monsoon (June–September). On an annual scale, melt is the dominant mass flux at all elevations, but 44% of the melt refreezes across the glacier. By reshuffling the available observations, we create 180 synthetic series of hourly meteorological forcings to force the model over a wide range of plausible climate conditions. A +1 (−1)°C change in temperature results in a −0.75 ± 0.17 (+0.93 ± 0.18) m w.e. change in glacier-wide mass balance and a +20 (−20)% change in precipitation results in a +0.52 ± 0.10 (−0.60 ± 0.11) m w.e. change. Our study highlights the need for physical-based approaches to produce consistent forcing datasets, and calls for more meteorological and glaciological measurements in High Mountain Asia.

Climatology of Orographic Precipitation Gradients Over High Mountain Asia Derived From Dynamical Downscaling

AbstractWithin High Mountain Asia (HMA), the annual melting of glaciers and snowpack provides vital freshwater to populations living downstream. Precipitation over HMA can directly affect the freshwater availability in this region by altering the mass balance of glaciers and snowpack. However, available reanalyses and downscaling simulations lack the resolution required to understand important glacier‐scale variations in precipitation. This study aimed to determine the current characteristics of orographic precipitation gradients (OPG) by curve‐fitting daily precipitation as a function of elevation from a 15‐year, 4‐km grid spaced Weather Research and Forecasting (WRF) model simulation focused on the Himalayan, Karakoram, and Hindu‐Kush mountain ranges. To facilitate precipitation curve‐fitting, the WRF model grid points were separated into regions of similar orientation, referred to as facets. Akaike Information Criterion‐corrected values and an F‐test p‐value identified the need for a curvature term to account for a varying OPG with elevation. Regions with similar seasonal variability were found using ‐means clustering of the monthly mean OPG coefficients. The central Himalayan slope's intra‐seasonal variability of OPG depended on synoptic scale conditions, in which cyclonically‐forced heavy‐precipitation events produced strong sublinear increases in precipitation with elevation. Initial testing of precipitation estimates using monthly coefficients showed promising results in downscaling daily WRF precipitation; the daily mean absolute error at each grid point had a lower magnitude than the daily mean precipitation total, on average. Results provide a physically‐based context for machine learning algorithms being developed to predict OPG and downscale precipitation output from global climate models over HMA.

Performance Evaluation of CMIP6 Climate Model Projections for Precipitation and Temperature in the Upper Blue Nile Basin, Ethiopia

The projection and identification of historical and future changes in climatic systems is crucial. This study aims to assess the performance of CMIP6 climate models and projections of precipitation and temperature variables over the Upper Blue Nile Basin (UBNB), Northwestern Ethiopia. The bias in the CMIP6 model data was adjusted using data from meteorological stations. Additionally, this study uses daily CMIP6 precipitation and temperature data under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios for the near (2015–2044), mid (2045–2074), and far (2075–2100) periods. Power transformation and distribution mapping bias correction techniques were used to adjust biases in precipitation and temperature data from seven CMIP6 models. To validate the model data against observed data, statistical evaluation techniques were employed. Mann–Kendall (MK) and Sen’s slope estimator were also performed to identify trends and magnitudes of variations in rainfall and temperature, respectively. The performance evaluation revealed that the INM-CM5-0 and INM-CM4-8 models performed best for precipitation and temperature, respectively. The precipitation projections in all agro-climatic zones under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios show a significant (p < 0.01) positive trend. The mean annual maximum temperature over UBNB is estimated to increase by 1.8 °C, 2.1 °C, and 2.8 °C under SSP1-2.6, SSP2-4.5, and SSP5-8.5 between 2015 and 2100, respectively. Similarly, the mean annually minimum temperature is estimated to increase by 1.5 °C, 2.1 °C, and 3.1 °C under SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. These significant changes in climate variables are anticipated to alter the incidence and severity of extremes. Hence, communities should adopt various adaptation practices to mitigate the effects of rising temperatures.

Assessing long-term water storage dynamics in Afghanistan: An integrated approach using machine learning, hydrological models, and remote sensing

Assessment of Terrestrial Water Storage (TWS) components is crucial for understanding regional climate and water resources, particularly in arid and semi-arid regions like Afghanistan. Given the scarcity of ground-based data, this study leverages remote sensing datasets to quantify water storage changes. We integrated Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-on (GRACE-FO) data with WaterGap, Global Land Water Storage (GWLS), Catchment Land Surface Model (CLSM), and climate variables (precipitation, temperature, potential evapotranspiration) using artificial neural networks (ANN) and random forests (RF). Additionally, Ice, Cloud, and Land Elevation Satellite (ICESat-1,2) data were utilized to estimate glacier mass changes. Seasonal trend decomposition using Loess (STL) was applied to assess TWS changes from 2003 to 2022. Our methodology reveals a high correlation (R = 0.90–0.97) between reconstructed and observed TWS anomalies across Afghanistan's major basins. Glacier mass decreased by −0.59 and −1.17 Gt/year during 2003–2009 and 2018–2022, respectively, while overall TWS declined by −2.46 Gt/year. The HRB experienced the largest TWS loss (−1.47 Gt/year), primarily due to groundwater depletion (−1.18 Gt/year). These findings underscore the importance of our approach for assessing water resources, providing vital insights for sustainable management under a changing climate in a data-scarce country.

Precipitation variability and environmental change across late Quaternary glacial-interglacial cycles in lowland Central America: Insights from Lake Petén Itzá (Guatemala) sediments

Lowland Central America, a biodiversity hotspot in the northern Neotropics, is a region where the climate is influenced by the location and expansion-contraction of the Intertropical Convergence Zone (ITCZ) on seasonal to millennial timescales. Paleo-records from the Caribbean Sea and the eastern equatorial and subtropical Pacific Ocean illustrate the response of regional precipitation to fluctuations in global temperature, driven by glacial-interglacial cyclicity over the past 500 kyr. Here, we present a paleoclimate and paleoenvironment record from Lake Petén Itzá, lowland Guatemala, which spans the last ∼413 kyr. Sediment in the lake recorded lacustrine and terrestrial ecosystem responses to large-scale climate variability. Precipitation patterns during MIS11-9 (∼413-304 ka BP) align with the latitudinal position of the ITCZ, with superimposed effects from the strength of the Caribbean Low-Level Jet (CLLJ). A sediment hiatus, likely attributable to mass removal processes in the lake's shallower areas, spans the period from MIS8 (starting at 304 ka BP) to the end of MIS6 (at 149 ka BP). MIS6 was characterized by humid conditions, perhaps ascribable to a more southerly extension of cold fronts and intensification of the CLLJ. During MIS5, pronounced fluctuations among all sediment variables, accompanied by an abrupt decline in precipitation, may correspond with cold events inferred from North Atlantic Ocean sediment cores. Although discontinuous, the Lake Petén Itzá sediment record provides a window into late Quaternary climate and environmental change in lowland Central America.

Dryland state transitions alter trophic interactions in a predator-prey system.

Environmental change is expected to alter trophic interactions and food web dynamics with consequences for ecosystem structure, function and stability. However, the mechanisms by which environmental change influences top-down and bottom-up processes are poorly documented. Here, we examined how environmental change caused by shrub encroachment affects trophic interactions in a dryland. The predator-prey system included an apex canid predator (coyote; Canis latrans), an intermediate canid predator (kit fox; Vulpes macrotis), and two herbivorous lagomorph prey (black-tailed jackrabbit, Lepus californicus; and desert cottontail, Sylvilagus audubonii) in the Chihuahuan Desert of New Mexico, USA. We evaluated alternative hypotheses for how shrub encroachment could affect habitat use and trophic interactions, including (i) modifying bottom-up processes by reducing herbaceous forage, (ii) modifying top-down processes by changing canid space use or the landscape of fear experienced by lagomorph prey and (iii) altering intraguild interactions between the dominant coyote and the intermediate kit fox. We used 7 years of camera trap data collected across grassland-to-shrubland gradients under variable precipitation to test our a priori hypotheses within a structural equation modelling framework. Lagomorph prey responded strongly to bottom-up pulses during years of high summer precipitation, but only at sites with moderate to high shrub cover. This outcome is inconsistent with the hypothesis that bottom-up effects should be strongest in grasslands because of greater herbaceous food resources. Instead, this interaction likely reflects changes in the landscape of fear because perceived predation risk in lagomorphs is reduced in shrub-dominated habitats. Shrub encroachment did not directly affect predation pressure on lagomorphs by changing canid site use intensity. However, site use intensity of both canid species was positively associated with jackrabbits, indicating additional bottom-up effects. Finally, we detected interactions between predators in which coyotes restricted space use of kit foxes, but these intraguild interactions also depended on shrub encroachment. Our findings demonstrate how environmental change can affect trophic interactions beyond traditional top-down and bottom-up processes by altering perceived predation risk in prey. These results have implications for understanding spatial patterns of herbivory and the feedbacks that reinforce shrubland states in drylands worldwide.

Deciphering the Variations and Mechanisms of Global Land Monsoons during Marine Isotope Stage 3

Abstract Marine Isotope Stage 3 (MIS 3) is characterized by significant millennial-scale climatic oscillations between cold stadials and mild interstadials, which presents a valuable case for understanding hydrological response to abrupt climate change. Through a set of coupled model simulations, our results broadly show an antiphased interhemispheric change in land monsoonal precipitation during the present-day relative to MIS 3 interstadial and the stadial–interstadial transition, with a general decrease in the Northern Hemisphere but an increase in the Southern Hemisphere. The antiphased pattern is largely caused by the change in orbital insolation during the present-day relative to MIS 3 interstadial, whereas by the weakened Atlantic meridional overturning circulation during the interstadial–stadial transition. However, there are obvious discrepancies in precipitation response and underlying mechanisms among individual monsoon domains and across different periods. Based on the moisture budget analysis, we indicate that the dynamic factor mainly explains the decreased monsoonal rainfall in the Northern Hemisphere during the present-day relative to the MIS 3 interstadial, whereas the thermodynamic term is largely responsible for the increased precipitation in the Southern Hemisphere. In contrast, the dynamic factor plays an important role in the variation of precipitation over all the monsoon zones from the MIS 3 interstadial to stadial states, with the thermodynamic term mainly contributing to the decreased tropical monsoonal precipitation in the colder Northern Hemisphere. Our results help improve the understanding of global monsoon variations under intermediate glacial climate conditions and shed light on their behaviors under potentially rapid climate change in the future.

Assessing Trade-Offs and Synergies in Ecosystem Services within the Tianshan Mountainous Region

In managing ecosystem services (ESs), it is vital to understand and effectively regulate the trade-offs and synergies (ToSs) involved. This study investigates the Tianshan Mountains (TSMs), utilizing the InVEST (Integrated Valuation of ESs and Tradeoffs) model to evaluate ecosystem service changes from 2000 to 2020, while employing univariate linear regression to examine their spatiotemporal dynamics. Pearson correlation analysis was also conducted to assess how climatic variables (temperature and precipitation) and vegetation indicators (NDVI, normalized difference vegetation index) influence the overall ecosystem service benefits. The findings reveal notable spatial heterogeneity and dynamic shifts in ESs across the TSMs, with strong synergies observed between carbon storage (CS) and other services (such as habitat quality, HQ; soil conservation, SC; and water yield, WY), especially in areas experiencing increased vegetation. However, the connection between HQ and WY was comparatively weaker and occasionally exhibited negative correlations during specific periods, highlighting the intricate trade-offs among various services. The correlation analysis further showed that climate and vegetation changes significantly impact ecosystem service benefits, with declining precipitation and rising temperatures reducing these benefits, whereas higher NDVI was associated with improved service functions. Ultimately, this study emphasizes the necessity of recognizing and managing ToSs in ESs to promote sustainable regional ecosystem development.

On the present and future changes in Indian summer monsoon precipitation characteristics under different SSP scenarios from CMIP6 models

AbstractMonsoons are a vital part of the agriculture and economy of India which most of its population rely on for their livelihoods. It still is not clear how climate change will impact precipitation events over India due to the complexity of accurately modelling precipitation. Using twelve Coupled Model Intercomparison Project Six (CMIP6) models, we compared their performance to observed data taken from CRU as well as looking at the future changes in precipitation until the end of the twenty first century for the six precipitation homogenous regions over India. The individual models showed varying degrees of wet and dry biases and the ensemble mean of these models showed relatively lesser bias and improved spatial correlation. Out of 12 models, NorESM and MIROC6 models outperform other models in terms of capturing the spatial variability of precipitation over the Indian region. It is also found that due to lesser moisture transport from the adjoining seas represented through vertically integrated moisture transport (VIMT) analysis, there is consistent dry bias across the models. Further a comprehensive analysis of model performance across six homogeneous precipitation regions indicates that NorESM demonstrates better performance in the CNE and HR regions, EC-Earth excels in the PR, WC, and NE regions, while CMCC shows better performance specifically in the NW region compared to other models. Shared Socioeconomic Pathways (SSPs) were used for future projections and a slight increase in June, July, August, and September (JJAS) precipitation until the end of the century with SSP5-8.5 showing the largest increase. We found an increase in precipitation of 0.49, 0.74 and 1.4 mm/day under SSP1-2.6, SSP2-4.5 and SSP5-8.5 in the far future. The northeast region was shown to receive the largest increase in precipitation (2.9 mm/day) compared to other precipitation homogenous regions and northwest will experience largest shift in precipitation. Interestingly, the number of wet days is expected to increase in the northwest region implying more VIMT towards the region. Our results indicate that monsoon precipitation extremes across all the homogenous regions will increase into the future with a higher severity under fossil-fuelled development, although the models still show large biases lowering confidence in our results.

The Impact of Major Ecological Projects on the Water Yield of Mountain Basins, Northern China

Water yield, one of the most valuable and important ecological indicators, reflects the renewable capacity of regional water resources. The Taihang Mountains are a natural ecological barrier and an important source of water production for the North China Plain. Two large-scale projects involving returning farmland to forest and grassland have significantly changed the distribution of land use in the Taihang Mountains, and also affect the water production characteristics of the Taihang Mountains. Taking the Hutuo River Basin, a typical river in the Taihang Mountainous region, as the study area, the InVEST model is utilized to calculate the spatial and temporal changes in water yield capacity in the Hutuo River basin, and four scenarios were set to judge the impact of different ecological projects on the water yield of the mountainous watershed of the Hutuo River. The results showed that the water yield in the five study periods was 218.58–376.44 mm. The interannual variations in both precipitation and water yield of the study area in the last decade were large. The water yield is mainly concentrated in the northeast region of the upper reaches of the basin, and the smallest is the northwest and central regions of the upper reaches. The water yield in each year in the study area is mainly less than 400 mm, accounting for more than 60% of the study area, and the water yield has shown a large regional expansion in the past 10 years. Grassland has the largest water yield capacity of all land use types, and climate change has basically no effect on the water yield capacity of different land use types. The ecological project of returning farmland to forestland has a negative impact on the water yield capacity, whereas the water yield capacity increases after returning farmland to grassland. The water conservancy project of river training has a negative impact on the water yield capacity of the Hutuo River mountainous basin. The research results provide theoretical data for judging the relationship between vegetation restoration and water yield in mountainous watersheds, a scientific basis for evaluating the implementation effect of major projects, and strong data support for water resource management in the North China Plain.

Reconstruction of temperature and hydroclimate in Serling Co (Central Tibet) since the last deglaciation

Understanding the past climatic conditions and their possible driving mechanism can contribute to better constrain future climate projection, and to provide potential insights into the disputed Holocene temperature variations. In this study, we quantitatively reconstruct the mean annual air temperature (MAAT) of Serling Co since 17.3 cal kyr BP using a novel terrestrial thermometer (ring index of OH-GDGTs, RI-OH), and reconstructed the hydroclimatic evolutionary history in combination with n-alkanes and their associated proxies. Our temperature records indicate that Serling Co experienced a period of reduced temperatures during the Younger Dryas event, approximately 6 °C cooler than the present conditions. Subsequently, there was a rapid warming phase, leading to peak temperatures in the early Holocene, roughly 5.5 °C warmer than the modern MAAT, followed by a protracted cooling trend during the subsequent middle and late Holocene. The temperature and hydroclimate trends at Serling Co exhibit a synchronized evolutionary pattern since the last deglaciation, featuring an optimal hydrothermal combination in the early Holocene. This period witnessed the peak productivity of terrestrial and aquatic ecosystems, followed by a gradual decline. Summer insolation emerges as a primary controlling factor for temperature variations, with Indian Summer Monsoon intensity and internal climate system variability exerting dominance over atmospheric moisture and precipitation variations in the region.

Reassessing water resource challenges in a changing climate in the Kagera transboundary river basin, Tanzania

The dynamic shifts in climatic patterns, particularly alterations in precipitation, have significantly impacted water resource availability and accessibility. These climate-induced changes affect hydrological processes, encompassing runoff, groundwater replenishment, water demand, and biophysical patterns within river basins. This study seeks to unravel the multifaceted implications encountered and challenges in water resource management within the river basin. It employed a survey-based approach for data collection, including Key informant interviews (KI), consultation methods and documentary reviews. The study utilized Statistical Package for the Social Sciences (SPSS) and Microsoft Excel for quantitative analysis and thematic synthesis for qualitative insights, including local community perspectives. The findings reveal substantial fluctuations in precipitation, protracted droughts, severe flooding, and other climatic extremes. The observed annual mean rainfall of 832 mm, with a standard deviation of 248, a standard error of 361, and a skewness of −945, accentuates the pronounced variability in mean precipitation, exhibiting a declining trend indicative of climatic shifts (R2 = 0.1797 and P = 0.002). The challenges are limited access to hydrological and meteorological data, undermining prediction accuracy, infrastructure planning, and response strategies for water resource allocation and management. The absence of unified approaches, influenced by the politics of riparian states, feeble coordination, conflicting sectoral policies, and ambiguous priorities, hinders effective transboundary water resource management. The study addresses these complexities and advocates for institutionalizing robust water management strategies that capitalize on existing resources and foster innovative capacities among critical stakeholders. Central to these efforts is harmonizing and enforcing policies, regulations, and laws governing water use, coupled with a concerted focus on inclusive governance to ensure the sustainability of water resource management. Such effort entails synchronized strategies, programs, plans, and livelihood practices underpinned by active stakeholder involvement in pivotal facets of water resources management.

ВЛИЯНИЕ ИЗМЕНЕНИЯ КЛИМАТА НА ПАСТБИЩНЫЕ ЭКОСИСТЕМЫ АТЫРАУСКОЙ ОБЛАСТИ РЕСПУБЛИКИ КАЗАХСТАН

Grasslands are an important and vulnerable resource among many ecosystems that occupy a large part of the earth's surface. These ecosystems are constantly exposed to various climatic factors, and climate change is becoming one of the main threats to them. Pastures occupy 9612.9 thousand hectares of the territory of Atyrau oblast, which is 81% of the total territory. These lands are an important source for livestock breeding. In this paper we assessed the potential impact of climate change on pasture ecosystems of Atyrau oblast of the Republic of Kazakhstan. The spatial and temporal variability of precipitation for 30 years (1992-2022) was investigated using meteorological data. The fluctuations of precipitation amount in vegetation period (April - September) for 1992-2022 were determined. Multiyear series of average annual air temperature and precipitation during vegetation vegetation period were analysed and their predicted cyclic fluctuations for the next two years were modelled. Degradation points of pasture ecosystems were identified by counting 622 points in 1992, 585 points in 2002, 412 points in 2012 and 387 points of former and current cattle stands in 2022 through Google Earth map. The heat and moisture availability of the growing season of pasture plants under climate change was predicted. The results of this study show how increasing temperature, decreasing precipitation, and management history affect pasture quality, and highlight the important role of vegetation of rangeland ecosystems. The results can be used in the process of establishing effective rangeland management practices, mechanisms for adaptation of rangeland vegetation or ecosystems to climate change.

Changes in Climatological Variables at Stations around Lake Erie and Lake Michigan

Climatological variables undergo changes over time, and it is important to understand such dynamic changes at global, regional, and local levels. While global and regional studies are common in the study of climate, such studies at a local level are not as common. The aim of this article is to study temporal changes in precipitation, snowfall, and temperature variables at specific stations located on the rims of Lake Erie and Lake Michigan. The identification of changes is carried out by applying change-point analysis to precipitation, snowfall, and temperature data from Buffalo, Erie, and Cleveland stations located on the rim of Lake Erie and at Chicago, Milwaukee, and Green Bay stations located on the rim of Lake Michigan. We adopt mainly the Bayesian information criterion (BIC) method to identify the number and locations of change points, and then we apply the generalized likelihood ratio statistic to test for the statistical significance of the identified change points. We follow this up by finding 95% confidence intervals for those change points that were found to be statistically significant. The results from the analysis show that there are significant changes in precipitation, snowfall, and temperature variables at all six rim stations. Changes in precipitation show consistently significant increases, whereas there is no similar consistency in snowfall increases. Temperature increases are generally quite sharp, and they occur consistently around 1985. Overall, upon combining the amounts of changes from all six stations, the average amount of change in annual average temperature is found to be 0.96 °C, the average percentage of change in precipitation is 16%, and the average percentage of change in snowfall is 17%. The changing local climatic conditions identified in the study are important for local city planners, as well as residents, so that they can be well prepared for changing climatic scenarios.

Exploring perceived relationships between weather, climate and mental health: biometeorological perspectives of healthcare practitioners.

Over the last decade, there has been an increase in research examining the influence of weather and climate in mental health caseloads. Variations in temperature, sunshine hours, cloud cover, precipitation and extreme weather events have been statistically linked to diagnoses and increases in hospital admissions for several mental health conditions. This study aimed to explore whether mental health practitioners perceive there to be a link between mental health and daily, seasonal, or inter-annual shifts in various climate variables in South Africa, and the timing and causal mechanisms thereof. Semi-structured interviews were conducted with 50 practicing healthcare practitioners, and the data was analysed using thematic analysis. The findings of this research show that all 50 participants were aware of the link between weather, climate and mental health, primarily through their awareness of seasonal affective disorder. Of the 50 participants, 38 participants could explain the aetiology of seasonal affective disorder. Participants perceived sunlight and temperature to exert an influence on mental health. All 50 participants perceived exposure to sunlight to exert a positive influence on several mental health conditions. Of the 50 participants, 36 participants perceived increases in temperature to exert an adverse effect on mental health symptomology. A minority of 11 participants perceived precipitation to influence mental health conditions such as seasonal affective disorder, bipolar disorder, and substance abuse disorder. Participants' perceptions of the influence of precipitation on mental health provided a unique potential explanation of this relationship, which, at the time of writing, has not been discussed in formal research.

Tillage and cover cropping influence phosphorus dynamics in soil and water pools

AbstractWinter cover crops (CCs) have the potential to reduce phosphorus (P) loss by temporarily fixing P into CC biomass. A field experiment with no‐tillage (NT) and conventional tillage (CT) was used to study the ability of different CC species planted after corn (Zea mays L.) and soybean (Glycine max L.) harvests to reduce the P availability in soil solution. The effect of three crop rotations (corn–no CC–soybean–no CC [C–S], corn–cereal rye (Secale cereale)–soybean–hairy vetch (Vicia villosa) [C–R–S–HV], corn–cereal rye–soybean–oats (Avena sativa)+ radish (Raphanus sativus L.) [C–R–S–OR]) and two tillage (NT and CT) treatments was determined on soil available P and soil solution P content through pan (A horizon) and tension (100‐cm depth) cup lysimeters. The experiment was set up as a randomized complete block design with tillage as a split factor with three replicates. Over the study period, incorporating hairy vetch in C–R–S–HV rotation reduced the Mehlich‐3 P content in soil by 26%–29% compared to the C–S and C–R–S–OR rotation. Both CC rotations (C–R–S–HV and C–R–S–OR) were effective in reducing dissolved reactive P (DRP) concentration in pan and tension cup lysimeters compared to the C–S in both CT and NT systems. However, these results varied with CC species grown and seasonal variability in precipitation. A significantly lower DRP load with crop rotation and tillage treatments was observed mainly during the CC growing season. During the study period, crop rotations with reduced labile soil P content and DRP loss were ranked in an order of C–R–S–HV > C–R–S–OR > C–S. Overall, this study showed that CCs have the potential in both CT and NT systems to significantly reduce P in soil and soil solution, and these effects are resilient to a wide range of precipitation conditions.

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.

An intrinsic low-frequency atmospheric mode of the Indonesian-Australian summer monsoon

AbstractDeep convection in the Indo-Pacific warm pool is vital in driving global atmospheric overturning circulations. Year-to-year variations in the strength and location of warm pool precipitation can lead to significant local and downstream hydroclimatic impacts, including floods and droughts. While the El Niño-Southern Oscillation (ENSO) is recognized as a key factor in modulating interannual precipitation variations in this region, atmospheric internal variability is often as important. Here, through targeted atmospheric model experiments, we identify an intrinsic low-frequency atmospheric mode in the warm pool region during the austral summer, and show that its impact on seasonal rainfall is comparable to ENSO. This mode resembles the horizontal structure of the Madden-Julian Oscillation (MJO), and may play a role in initiating ENSO as stochastic forcing. We show that this mode is not merely an episodic manifestation of MJO events but primarily arises from barotropic energy conversion aided by positive feedback between convection and circulation.