Trends In Seasonal Precipitation Research Articles

Seasonal precipitation changes in the western Mediterranean Basin: The case of the Spanish mainland, 1916–2015

AbstractThis study examines the spatial and temporal variations in seasonal precipitation patterns across the Spanish mainland, within the western Mediterranean Basin, spanning the years 1916–2015. Utilizing the recently developed MOPREDAS_century database at a 10 × 10 km grid resolution, our analysis reveals predominantly negative trends in precipitation across the study area over the entire period, primarily driven by declines in spring precipitation, with lesser decreases in summer and winter. Notably, these trends exhibit complexity, manifesting as two distinct pulses occurring roughly at the outset and conclusion of the 20th century. However, upon employing a moving windows analysis, we find that since the mid‐1970s, seasonal precipitation trends have largely been nonsignificant. Spatially, the precipitation regime across 1916–2015 delineates three primary zones: a winter‐maximum zone in the north, an autumn‐maximum zone along the eastern coast, and a transition from winter‐maximum to spring‐maximum towards the western and inland regions. Noteworthy shifts in this spatial distribution are evident over the four 25‐year intervals examined. Initially, during 1916–1940, winter, autumn and spring regimes occupied 44.1%, 24.2% and 31.7% of the land, respectively. Subsequently, in the periods 1941–1965 and 1966–1990, winter dominance expanded to over 50% of the grid area, while spring varied between 34.7% and 25.5%, and autumn decreased notably to 12.4% and 13.5%. Lastly, significant alterations occurred in the final period of 1991–2015, with winter coverage decreasing to 33.7%, spring to 15.8% and autumn expanding to 50.1% of the grid area. In summary, the prevalent winter and spring regimes at the dawn of the 20th century have transitioned towards an autumn‐dominated regime, particularly in much of the central and western Spanish mainland, with these shifts possibly linked to the evolving precipitation trends. These findings contribute novel insights, particularly pre‐1950, and align with published results post‐1950 across the Mediterranean, particularly in its western regions. Furthermore, they suggest a potential connection between changes in the spatial distribution of seasonal precipitation regimes and temporal variations in the primary moisture sources over the study area.

A GIS-Based Assessment of Flood Hazard through Track Records over the 1886–2022 Period in Greece

This paper addresses the riverine flood events that have occurred in Greece over the last 136 years (i.e., during the 1886–2022 period), focusing, amongst others, on the case of urban floods. The flood record of various sites of the country has been collected and analyzed to determine their spatial and temporal distribution. Greece is a country where flood data and records are very scarce. Therefore, as there is not an integrated catalog of Greek floods spanning from the 19th century to recently, this is the first attempt to create an integrated catalog for Greece. The sources used include published papers, local and regional newspapers and public bodies (mainly the Ministry of Environment and Energy and the official websites of Greek municipalities). Additionally, the main factors responsible for their occurrence have been issued, regarding the country’s climatic, geological and geomorphological setting, as well as human interventions. In addition, the atmospheric circulation driving factors of floods are assessed via an unsupervised neural network approach (i.e., Self-Organizing Maps). Based on the results of this research, an online GIS-based database has been created, depicting the areas that have been struck by riverine floods in Greece. By clicking a flood event in the online database, one can view several characteristics, depending on data availability, such as duration and height of the rainfall that caused them and number of fatalities. Long-term trends of mean and extremes seasonal precipitation also linked to the spatial distribution of floods. Our analysis shows that urban floods are a very large portion of the overall flood record, and they mainly occur in the two large urban centers, Athens and Thessaloniki, as well as near large rivers such as Pineios. Autumn months and mainly November are the periods with higher flood hazards, based on past records and cyclonic atmospheric circulation constitutes the principal driving factor. Our results indicate that a flood catalog at national level is of fundamental importance, as it can provide valuable statistical insights regarding seasonality, spatial distribution of floods, etc., while it can also be used by stakeholders and researchers for flood management and flood risk analysis and modelling.

A holistic approach for using global climate model (GCM) outputs in decision making

All human endeavours are affected by climate change and local weather, and 21st-century climate-change estimates will provide greater challenges. Therefore, numerical model-based climate projections (i.e., General Circulation Models – GCMs) are essential for making decisions about adaptation, mitigation, and resilience building to combat adverse climate impacts. However, these coarser resolution model projections have uncertainties resulting in significant doubts in decision-making, particularly in the local or regional domain. Thus, we suggest five principles for GCM use at local and regional scales to overcome uncertainties in decision-making. This study examines historical and projected precipitation from 44 GCMs, calculated under the Representative Concentration Pathways (RCP) 8.5 scenario considering regional, geographical, and temporal variability for establishing a decision-making support system based on the degree of confidence for nine diverse main river basins in tropical Sri Lanka as a case study. Each GCM confirmed the current climatic pattern in terms of wind vector and meridional wind patterns out of eight climate variables considered. GCM sensitivity varies geographically and temporally. An annual precipitation study is not enough to make climate change judgments because climate change signals change seasonally. Each basin's average annual precipitation was projected to likely increase over the near, middle, and far future (2025–2050, 2050–2075, 2075–2100, respectively); however, in the Mahaweli basin (MB), the largest basin neighboring most of the other basins, the annual precipitation was projected to extremely likely increase. Most of MB's surrounding basins show a more-likely-than-not decreasing precipitation tendency for inter-monsoon-1 in the future (2025–2100); however, MB shows a more-likely-than-not increasing trend. Our analysis shows that the southwest monsoon and inter-monsoon-2 are more likely than not or extremely likely to strengthen, whereas the northeast monsoon (NEM) and inter-monsoon-1 are more likely than not to weaken, excluding NEM in the near future. Here, we introduced a simple color-coded climate change (C4) matrix for decision-making that provides spatial, temporal, and seasonal climate change projections likelihood trends with current observed seasonal trends. Future projections indicate a swapping in seasonal precipitation trends between IM-1 and SWM for almost basins compared to the past. NEM appears to have a weakening influence on the majority of northeast-facing basins during the middle and far future. A simple detailed climate analysis chart may be more effective in communicating scientific messages to the scientific community and the key public actors who make decisions.

Assessing the skill of gridded satellite and reanalysis precipitation products over in East and Southern Africa

Validation of gridded precipitation products (GPP) increases the users’ confidence and highlights possible improvements in the algorithms to handle complex rain-forming processes. We evaluated the skill of three GGPs (CHIRPS-v2, CHELSA, and TerraClimate) in estimating the rain gauge observations and compared the precipitation trends derived from these products across the East and Southern Africa (ESA) region. We used Taylor diagrams and Kling-Gupta Efficiency (KGE) to assess the accuracy. A modified Mann-Kendal test and a Sen’s slope estimator were utilized to determine the trends’ significance and magnitude, respectively. The three GPPs had varied performance over temporal and altitudinal ranges. The skill of the three GPPs, at a monthly scale, was generally high but showed lower performance at elevations over 1500 masl, especially during the October-November-December (OND) season. The three GPPs performed equally well between the 1001 – 1500 masl elevation range. CHELSA-v2.1 was most accurate at 0-500 masl but had the lowest skill in both 501 – 1000 and above 1500 masl elevations, which caused over-estimation of the annual and seasonal precipitation trends over mountainous terrain and large inland water bodies. The quantified precipitation trends revealed high spatial-temporal variability. Generally, the skill and precipitation trends derived from CHIRPS-v2 and TC data showed substantial convergence except in Tanzania. Our results emphasize the importance of validating climate datasets to avoid error propagation in different models and applications. Moreover, we demonstrate that new or higher-resolution precipitation data are not always accurate since an algorithm update can introduce artifacts or biases.

Analysis of monthly average precipitation of Wadi Ouahrane basin in Algeria by using the ITRA, ITPAM, and TPS methods

Precipitation is one of the most significant components for the basin's hydrological cycle. Numerous features of a basin's water circulation may be affected by the chronological, geographical, and seasonal fluctuation of precipitation. It could be an important factor that influences hydrometeorological phenomena including floods and droughts. In this research, the innovative trend risk analysis (ITRA), innovative trend pivot analysis (ITPAM), and trend polygon star (TPS) methodologies of visualizing precipitation data are used to detect precipitation changes at six stations in Algeria's Wadi Ouahrane basin from 1972 to 2018. ITRA graphs show the direction of the precipitation trend (increasing-decreasing) and the trend risk class. Disparities in the polygons generated by the arithmetic mean and standard deviation ITPAM graphs demonstrate variations in precipitation seasonally and in the seasonal precipitation trends (increasing or decreasing) between sites. The TPS maps depict monthly variations in precipitation and highlight the autumn and spring transitions between the dry and wet seasons.

Observed trends and variability of seasonal and annual precipitation in Pakistan during 1960–2016

AbstractLong‐term precipitation monitoring plays a vital role in water resource management and disaster prevention and mitigation. This study assesses spatial and temporal trends in seasonal and annual precipitation in Pakistan between 1960 and 2016 at an interannual scale. The Mann–Kendall (MK) test, Sen's slope (SS) estimator, and Sequential Mann–Kendall (SQMK) test were employed to assess trends. Cluster analysis and L‐moment approach were used to identify the homogenous precipitation regions. In general, increasing precipitation trends between 1960 and 2016 were evident. Results indicated increasing precipitation in winter, autumn, summer and annual scale at the rates of 0.20, 2.18, 5.16, and 10.89 mm·decade−1, respectively. In spring, the precipitation trend shows a decreasing trend at −0.67 mm·decade−1. Moreover, a significant decreasing trend occurred in winter in southern Pakistan. The overall increasing trends were more noticeable between 1960 and 1988, compared to the declining precipitation during 1989–2016. SQMK analysis indicates a clear downward trend in most regions during 1989–2016, except in autumn. Annual precipitation has increased topographically except at 500 m and 1,500 m during 1960–2016 with a significant increase of 1.37 mm·decade−1 at elevation <250 m. Results indicate a negative correlation in SS test value with seasonal and annual precipitation with elevation and a positive correlation in winter. The seasonal and annual precipitation trends exhibit increasing and decreasing trends before and after 1990, respectively, in most subregions. The notable finding based on the outcomes of this study is that the whole country observed an increasing trend during 1960–1988, followed by a decreasing trend in during 1989–2016. This decreasing tendency is particularly pronounced between 1985 and 1995, except in autumn. Agriculture production is largely reliant on precipitation in many regions. So, a detailed study of the influence of monsoon trends and large‐scale climatic variability controls over Pakistan is vital for improved water resource management in the context of global warming and rising human activity. The results will help policy makers while establishing and updating water‐related initiatives and regulations.

Evaluation and projection of precipitation in Pakistan using the Coupled Model Intercomparison Project Phase 6 model simulations

AbstractThis study aimed to evaluate the performance of global climate models (GCMs) from the family of the Coupled Model Intercomparison Project Phase 6 (CMIP6) in the historical simulation of precipitation and select the best performing GCMs for future projection of precipitation in Pakistan under multiple shared socioeconomic pathways (SSPs). The spatiotemporal performance of GCMs was evaluated against the Climate Research Unit (CRU) data in simulating annual precipitation during 1951–2014, using the Taylor diagram and interannual variability skill (IVS). Moreover, the modified Mann–Kendall (mMK) and Sen's slope estimator (SSE) tests were employed to estimate significant trends in future precipitation for the period 2015–2100. Based on the comprehensive ranking index (CRI), the HadGEM3‐GC31‐MM model has the highest skill in simulating precipitation distributions followed by EC‐Earth3‐Veg‐LR, CNRM‐ESM2‐1, MPI‐ESM1‐2‐HR, CNRM‐CM6‐1, MRI‐ESM2‐0, CNRM‐CM6‐1‐HR, EC‐Earth3‐Veg, MCM‐UA‐1‐0, INM‐CM5‐0, KACE‐1‐0‐G, CAMS‐CSM1‐0, and HadGEM3‐GC31‐LL models. Furthermore, the projections of the best models ensemble mean (BMEM) showed that the study region will experience a substantial increase in precipitation under SSP3‐7.0 and SSP5‐8.5 but an indolent rise under SSP1‐2.6 and SSP2‐4.5 scenarios. The summer and annual precipitations exhibit a statistically significant increasing trend relative to the winter season under most scenarios. Moreover, the magnitude of monotonic trends in seasonal and annual precipitation progresses from low forcing scenario (SSP1‐2.6) to high forcing scenario (SSP5‐8.5). The findings of the study could provide a benchmark in selecting appropriate GCMs for future projection over a data scare region, like Pakistan. Moreover, the projected trends of future precipitation are crucial in devising adaption and mitigation actions towards sustainable planning of water resource management, food security, and disaster risk management.

Elevation-Dependent Trends in Precipitation Observed over and around the Tibetan Plateau from 1971 to 2017

The Tibetan Plateau (TP) are regions that are most sensitive to climate change, especially extreme precipitation changes with elevation, may increase the risk of natural disasters and have attracted attention for the study of extreme events in order to identify adaptive actions. Based on daily observed data from 113 meteorological stations in the Tibetan Plateau and the surrounding regions in China during 1971–2017, we calculated the annual total precipitation and extreme precipitation indices using the R ClimDex software package and explored elevation-dependent precipitation trends. The results demonstrate that the annual total precipitation increased at a rate of 6.7 mm/decade, and the contribution of extreme precipitation to total precipitation increased over time, and the climate extremes were enhanced. The annual total, seasonal precipitation, and precipitation extreme trends were observed in terms of elevation dependence in the Tibetan Plateau (TP) and the surrounding area of the Tibetan Plateau (TPS) during 1971–2017. There is growing evidence that the elevation-dependent wetting (EDWE) is complex over the TP. The trends in total precipitation have a strong dependence on elevation, and the EDWE is highlighted by the extreme precipitation indices, for example, the number of heavy precipitation days (R10) and consecutive wet days (CWD). The dependence of extreme precipitation on elevation is heterogeneous, as other extreme indices do not indicate EDWE. These findings highlight the precipitation complexity in the TP. The findings of this study will be helpful for improving our understanding of variabilities in precipitation and extreme precipitation in response to climate change and will provide support for water resource management and disaster prevention in plateaus and mountain ranges.

Projecting climate change in South America using variable‐resolution Community Earth System Model: An application to Chile

AbstractWe introduce variable‐resolution enabled Community Earth System Model (VR‐CESM) results simulating historical and future climate conditions at 28 km over South America and 14 km over the Andes. Three 30‐year simulations are performed: a historic (1985–2014), a near future (2030–2059), and an end‐century (2070–2099) simulation under the RCP8.5 scenario. Historic results compare favourably to several temperature and precipitation reanalysis products, though local biases are present, particularly during austral summer. Future simulations highlight broad warming patterns (+3–6°C by end‐century) and heterogeneous precipitation responses across South America that qualitatively agree with prior modelling efforts. Our results reveal that the interaction between temperature and precipitation changes produce shifts in several Köppen–Geiger climates. Notable changes include the near‐elimination of the Andean Tundra or Alpine climates, a 15% decrease in Tropical Rainforests and a Tropical Savannah expansion of 20%. To provide a regionally focused analysis of projected climate change and to illustrate the benefits of variable resolution modelling, we analyse changes in the magnitude and trend in seasonal and daily temperature and precipitation in Chile. We also examined several metrics [e.g., snow water equivalent (SWE), temperatures on wet days, and days below 0°C] to evaluate potential impacts of climate change on the Chilean cryosphere between the end‐of‐century and historic periods, finding wide‐ranging indications of cryospheric decline. These changes are interpreted through reductions in the timing (1–2.5 months earlier peak SWE) and magnitude (200–1,000 mm SWE decreases) of water stored as snow in the Andes, a 10–30% decrease in number of cool season wet days with temperatures below 1°C, and 50–200 fewer days (annually) with minimum temperatures below 0°C. Our aim in producing a high‐resolution dataset of climate projections from VR‐CESM is to support analyses of climate change throughout South America but especially in vulnerable montane regions and to provide additional results for comparison with previous, ongoing, and upcoming modelling efforts.

Phenological Water Balance Applications for Trend Analyses and Risk Management

The overarching goal of this work is to develop and demonstrate methods that support effective agro-pastoral risk management in a changing climate. Disaster mitigation strategies, such as the Sendai Framework for Disaster Risk Reduction (SFDRR), emphasize the need to address underlying causes of disaster risk and to prevent the emergence of new risks. Such assessments can be difficult, because they require transforming changes in meteorological outcomes into sector-specific impact. While it is common to examine trends in seasonal precipitation and precipitation extremes, it is much less common to study how these trends interact with crop and pasture water needs. Here, we show that the Water Requirement (WR) component of the widely used Water Requirement Satisfaction Index (WRSI) can be used to enhance the interpretation of precipitation changes. The WR helps answer a key question: was the amount of rainfall received in a given season enough to satisfy a crop or pasture's water needs? Our first results section focuses on analyzing spatial patterns of climate change. We show how WR values can be used to translate east African rainfall declines into estimates of crop and rangeland water deficits. We also show that increases in WR, during recent droughts, has intensified aridity in arid regions. In addition, using the PWB, we also show that precipitation increases in humid areas of western east Africa have been producing increasingly frequent excessive rainfall seasons. The second portion of our paper focuses on assessing temporal outcomes for a fixed location (Kenya) to support drought-management scenario development. Kenyan rainfall is decreasing and population is increasing. How can we translate this data into actionable information? The United Nations and World Meteorological Organization advise nations to proactively plan for agro-hydrologic shocks by setting aside sufficient grain and financial resources to help buffer inevitable low-crop production years. We show how precipitation, WR, crop statistics, and population data can be used to help guide 1-in-10 and 1-in-25-year low crop yield scenarios, which could be used to guide Kenya's drought management planning and development. The first and second research components share a common objective: using the PWB to translate rainfall data into more actionable information that can inform disaster risk management and development planning.

Regional and Seasonal Precipitation and Drought Trends in Ganga–Brahmaputra Basin

Satellite-based precipitation products can be a better alternative of rain gauges for hydro-meteorological studies in data-poor regions. This study aimed to evaluate how regional and seasonal precipitation and drought patterns had changed in the Ganga–Brahmaputra Basin between 1983 and 2020 with PERSIANN-CDR precipitation data. The spatial pattern of winter drought, monsoon drought, and Standardized Precipitation Index (SPI) calculated for different time scales were evaluated using principal component analysis. Ganga–Brahmaputra is one of the most populated river basins that flows through different geographical regions. Rain gauges are heterogeneously distributed in the basin due to its complex orography, highlighting the significance of gridded precipitation products over gauge observations for climate studies. Annual and monthly precipitation trends between 1983 and 2020 were evaluated using the original and modified Mann–Kendall trend test, and annual precipitation in the basin was found to be declining at a rate of 5.8 mm/year. An increasing trend was observed in pre-monsoon rainfall, whereas precipitation exhibited a decreasing trend for other months. Results of the Pettitt test showed precipitation time series was inhomogeneous and changepoint occurred around 2000. Decreasing trends of SPI indicated increasing frequency and intensity of drought events. Winter drought showed a clear spatial pattern in the basin; however, SPIs calculated for different time scales and monsoon drought had complex spatial patterns. This study demonstrates the applicability of satellite-based PERSIANN-CDR precipitation data in climate research in the Ganga–Brahmaputra Basin.

Gross Discrepancies between Observed and Simulated Twentieth-to-Twenty-First-Century Precipitation Trends in Southeastern South America

AbstractSoutheastern South America (SESA; encompassing Paraguay, southern Brazil, Uruguay, and northern Argentina) experienced a 27% increase in austral summer precipitation from 1902 to 2019, one of the largest observed trends in seasonal precipitation globally. Previous research identifies Atlantic multidecadal variability and anthropogenic forcing from stratospheric ozone depletion and greenhouse gas emissions as key factors contributing to the positive precipitation trends in SESA. We analyze multimodel ensemble simulations from phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP) and find that not only do Earth system models simulate positive SESA precipitation trends that are much weaker over the historical interval, but some models persistently simulate negative SESA precipitation trends under historical forcings. Similarly, 16-member ensembles from two atmospheric models forced with observed historical sea surface temperatures never simulate precipitation trends that even reach the lower bound of the observed trend’s range of uncertainty. Moreover, while future twenty-first-century projections from CMIP6 yield positive ensemble mean precipitation trends over SESA that grow with increasing greenhouse gas emissions, the mean forced response never exceeds the observed historical trend. Preindustrial control runs from CMIP6 indicate that some models do occasionally simulate centennial-scale trends in SESA that fall within the observational range, but most models do not. Results point to significant uncertainties in the attribution of anthropogenically forced influences on the observed increases in precipitation over SESA while also suggesting that internal decadal-to-centennial variability of unknown origin and not present in state-of-the-art models may have also played a large role in generating the twentieth-to-twenty-first-century SESA precipitation trend.

Trends in Arctic seasonal and extreme precipitation in recent decades

Daily precipitation data from the European Centre for Medium-Range Weather Forecasts (ERA-Interim) from 1979 to 2016 are analyzed to determine the trends in seasonal and extreme precipitation across the pan-Arctic and estimate the contributions to the trends from the dynamic (e.g., changes in circulation patterns) and thermodynamic processes (e.g., sea ice melt–water vapor feedback) and their interactions. The trends in the seasonal total precipitation are generally consistent with the trends in the occurrence of seasonal extreme precipitation. Although the trends vary considerably in direction and magnitude across the pan-Arctic and the seasons, more regions experience a statistically significant positive trend than negative trend, particularly in autumn and winter seasons and over areas of the Arctic Ocean and the northern North Atlantic. Statistically significant negative trends are mostly found in areas of northern Eurasian and North America. The thermodynamic processes account for more than 85% of the total trends, with the rest of the trends explained by the dynamic processes (e.g., changes in circulation patterns) and the interaction between dynamic and thermodynamic processes.

Annual and seasonal precipitation trends and their attributions in the Qinling Mountains, a climate transitional zone in China

In this study, annual and seasonal precipitation trends and their connection with large-scale climate indices in the Qinling Mountains (QMs) were investigated using the innovative trend analysis (ITA), based on observed monthly precipitation data between 1959 and 2016 from 32 meteorological stations. The results indicated a declining trend in annual precipitation in the QMs. Seasonally, a decreasing trend was also observed in spring and autumn, while increasing trends were observed in summer and winter. Spring and autumn precipitations significantly contributed to this observed decline in annual precipitation. More importantly, both low and high values indicated a declining trend, which would have a significant influence on ecology and livelihood in the QMs. Additionally, the results of wavelet coherence showed that annual precipitation is strongly associated with the East Asian Summer Monsoon Index (EASMI), Southern Oscillation Index (SOI), South Asian Summer Monsoon Index (SASMI), South China Sea Summer Monsoon Index (SCSMI), and Southwest Australian Circulation Index (SWACI). However, its relationship with the North Atlantic Oscillation (NAO) and West African Summer Monsoon Index (WASMI) was insignificant, and seasonally, EASMI had negative effects on the precipitation in each season. It was also observed that spring and autumn precipitations were more sensitive to SOI than SWACI, while SASMI had a strong positive relationship with winter precipitation, and SCSMI was more negatively related to autumn and winter precipitation. This study will provide scientific basis for precipitation forecast, prevention, and mitigation of flood in the future.

Influence of climate change on river discharges over the Sava River watershed in Bosnia and Herzegovina

The paper examines changes in air temperature, precipitation, and river discharges on seasonal and annual scale over the Sava River watershed in Bosnia & Herzegovina during the period 1961–2016. Based upon data gathered from 11 meteorological stations and 3 hydrological stations, hydroclimatic variables trends were established by utilizing the nonparametric Mann-Kendall test and the nonparametric Sen’s slope estimator. The results show significant positive seasonal and annual trends (expect for autumn, during which upward trends were insignificant) in air temperature, whereas both positive and negative insignificant seasonal and annual precipitation trends are shown where determined for the entire watershed. Most prominent upward trends in air temperature were found in summer and afterwards in winter and spring, indicating a pronounced warming tendency over the Sava River watershed. Trends in river discharge displayed a negative tendency in all seasons. Nevertheless, a majority of estimated trends of river discharges were weak and statistically insignificant. Throughout the year, river discharges showed significant positive correlation with precipitation, whilst connection with air temperature was mostly significant and negative. The study results suggest that climate is an important factor affecting river regimes, as well as that changes in river discharges are reflecting recent abrupt changes in climatic variables.

Precipitation trends over the southern Andean Altiplano from 1981 to 2018

This study undertakes a spatio-temporal assessment of the annual and seasonal precipitation trends over the Desaguadero-Poopó (DP) system in Bolivia for the period 1981–2018. Given the insufficient spatial density of meteorological stations in the study, the high-spatial resolution Climate Hazards group Infrared Precipitation with Stations (CHIRPS) satellite product was used. CHIRPS precipitation data was validated against 7,636 gauge measurements and used to map the spatial distribution of precipitation trends. In addition, the temporal changes in the onset, duration and average intensity of the wet season were explored. Results showed a good, statistically significant agreement between CHIRPS data and onsite records of monthly precipitation at the pixel and regional scales. The spatio-temporal precipitation assessment revealed that statistically significant increases in annual precipitation (2–6 mm yr−1) occurred in two zones at the north and north-western part of the DP system. Only the southern part showed decreasing precipitation trends at a rate of −1 mm yr−1 while the central part did not show significant changes. Overall, a general increasing trend of about 2.5 mm yr−1 was observed for the entire DP system during the 38-year study period, with the months of December and February showing the highest significant increases. The analysis of the onset and cessation times of the rainy season indicated a statistically significant decrease in its duration at a rate of −0.4 day yr−1 and an increment of the average precipitation intensity. Our results reveal trend in the temporal concentration of precipitation in a water scarce region, which highlights the need for the management of the resource, so it can meet societal and environmental demands throughout the year.

International Environmental Conflict Management in Transboundary River Basins

Despite signing a bilateral water treaty in 1973, water utilization in the Hirmand River Basin (HRB) has been a source of dispute between Iran and Afghanistan for many decades. While Iran accuses Afghanistan of depriving it of the Hirmand water due to dam construction in the upper basin, Afghanistan assures that it enforces the treaty. An evident reduction of the Hirmand River flow to Iran in recent years is fully attributed by Afghanistan to a reduction in precipitation in the basin. Although Iran disagrees and remains unconvinced by this line of reasoning. A fundamental lack of trust in collected and shared hydrological data has hindered dialog between the two neighbors. To address this issue, this study investigates the use of remote sensing information, as an independent source of data, for fact-finding in a highly disputed transboundary river basin. For this purpose, historical data (34 years) from two satellite precipitation products, PERSIANN-CDR and CHIRPS, were used to understand if precipitation characteristics and, subsequently, rainfall-runoff regimes have changed in the HRB. Results reveal that the frequency and amount of heavy precipitation have been increasing over the mountainous areas. The total amount of precipitation has been increasing significantly. The intensity of heavy precipitation, however, has been decreasing over the basin. In the upper basin, the duration of the wet period has increased, although the share of wet months in annual precipitation has been decreasing. In the lower basin, trends in seasonal and annual precipitation and most of the indices are insignificant, indicating water availability issues cannot be attributed to the changes in precipitation in the downstream area itself. These results can be used as an integral part of mutual fact-finding and trust-building exercise that supports water diplomacy to promote environmental cooperation between Iran and Afghanistan.

The role of atmospheric circulation patterns in driving recent changes in indices of extreme seasonal precipitation across Arctic Fennoscandia

Extreme precipitation events (EPEs) have a major impact across Arctic Fennoscandia (AF). Here we examine the spatial variability of seasonal 50-year trends in three EPEs across AF for 1968–2017, using daily precipitation data from 46 meteorological stations, and analyse how these are related to contemporaneous changes in the principal atmospheric circulation patterns that impact AF climate. Positive trends in seasonal wet-day precipitation (PRCPTOT) are widespread across AF in all seasons except autumn. Spring (autumn) has the most widespread negative (positive) trends in consecutive dry days (CDD). There is less seasonal dependence for trends in consecutive wet days (CWDs), but the majority of the stations show an increase. Clear seasonal differences in the circulation pattern that exerted most influence on these AF EPE trends exist. In spring, PRCPTOT and CDD are most affected by the Scandinavian pattern at more than half the stations while it also has a marked influence on CWD. The East Atlantic/Western Russia pattern generally has the greatest influence on the most station EPE trends in summer and autumn, yet has no effect during either spring or winter. In winter, the dominant circulation pattern across AF varies more between the different EPEs, with the North Atlantic Oscillation, Polar/Eurasia and East Atlantic patterns all exerting a major influence. There are distinct geographical distributions to the dominant pattern affecting particular EPEs in some seasons, especially winter, while in others there is no discernible spatial relationship.

Application of Machine Learning to Attribution and Prediction of Seasonal Precipitation and Temperature Trends in Canberra, Australia

Southeast Australia is frequently impacted by drought, requiring monitoring of how the various factors influencing drought change over time. Precipitation and temperature trends were analysed for Canberra, Australia, revealing decreasing autumn precipitation. However, annual precipitation remains stable as summer precipitation increased and the other seasons show no trend. Further, mean temperature increases in all seasons. These results suggest that Canberra is increasingly vulnerable to drought. Wavelet analysis suggests that the El-Niño Southern Oscillation (ENSO) influences precipitation and temperature in Canberra, although its impact on precipitation has decreased since the 2000s. Linear regression (LR) and support vector regression (SVR) were applied to attribute climate drivers of annual precipitation and mean maximum temperature (TMax). Important attributes of precipitation include ENSO, the southern annular mode (SAM), Indian Ocean Dipole (DMI) and Tasman Sea SST anomalies. Drivers of TMax included DMI and global warming attributes. The SVR models achieved high correlations of 0.737 and 0.531 on prediction of precipitation and TMax, respectively, outperforming the LR models which obtained correlations of 0.516 and 0.415 for prediction of precipitation and TMax on the testing data. This highlights the importance of continued research utilising machine learning methods for prediction of atmospheric variables and weather pattens on multiple time scales.

A combined view on precipitation and temperature climatology and trends in the southern Andes of Peru

AbstractIn the southern Peruvian Andes, communities are highly dependent on climatic conditions due to the mainly rain‐fed agriculture and the importance of glaciers and snow melt as a freshwater resource. Longer‐term trends and year‐to‐year variability of precipitation or temperature severely affect living conditions. This study evaluates seasonal precipitation and temperature climatologies and trends in the period 1965/66–2017/18 for the southern Peruvian Andes using quality‐controlled and homogenized station data and new observational gridded data. In this region, precipitation exhibits a strong annual cycle with very dry winter months and most of the precipitation falling from spring to autumn. Spatially, a northeast–southwest gradient in austral spring is observed, related to an earlier start of the rainy season in the northeastern part of the study area. Seasonal variations of maximum temperature are weak with an annual maximum in austral spring, which is related to reduced cloud cover in austral spring compared to summer. On the contrary, minimum temperatures show larger seasonal variations, possibly enhanced through changes in longwave incoming radiation following the precipitation cycle. Precipitation trends since 1965 exhibit low spatial consistency except for austral summer, when in most of the study area increasing precipitation is observed, and in austral spring, when stations in the central‐western region of the study area register decreasing precipitation. All seasonal and annual trends in maximum temperature are larger than trends in minimum temperature. Maximum temperature exhibits strong trends in austral winter and spring, whereas minimum temperature trends are strongest in austral winter. We hypothesize, that these trends are related to precipitation changes, as decreasing (increasing) precipitation in spring (summer) may enhance maximum (minimum) temperature trends through changes in cloud cover. El Niño Southern Oscillation (ENSO), however, has modifying effects onto precipitation and temperature, and thereby leads to larger trends in maximum temperatures.