precipitation trends
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Abstract Northern Hemisphere Land monsoon precipitation (NHLM) exhibits multidecadal variability, decreasing over the second half of the 20st century and increasing after the 1980s. We use a novel combination of CMIP6 simulations and several large ensembles to assess the relative roles of drivers of monsoon precipitation trends, analyzing the effects of anthropogenic aerosol (AA), greenhouse gas (GHG) emissions and natural forcing. We decomposed summer global monsoon precipitation anomalies into dynamic and thermodynamic terms to assess the drivers of precipitation trends. We show that the drying trends are likely to be mainly due to increased AA emissions, which cause shifts of the atmospheric circulation and a decrease in moisture advection. Increases in GHG emissions cause monsoon precipitation to increase due to strengthened moisture advection. The uncertainty in summer monsoon precipitation trends is explored using three initial condition large ensembles. AA emissions have strong controls on monsoon precipitation trends, exceeding the effects of internal climate variability. However, uncertainties in the effects of external forcings on monsoon precipitation are high for specific periods and monsoon domains, and due to differences in how models simulate shifts in atmospheric circulation. The effect of AA emissions is uncertain over the northern African monsoon domain, due to differences among climate models in simulating the effects of AA emissions on net shortwave radiation over the North Atlantic Ocean.

The investigation of regional vulnerability to extreme hydroclimatic events (e.g., floods and hurricanes) is quite challenging due to its dependence on reliable precipitation estimates. Better understanding of past precipitation trends is crucial to examine changing precipitation extremes, optimize future water demands, stormwater infrastructure, extreme event measures, irrigation management, etc., especially if combined with future climate and population projections. The objective of the study is to investigate the spatial-temporal variability of average and extreme precipitation at a sub-regional scale, specifically in the Southern Mid-Atlantic United States, a region characterized by diverse topography and is among the fastest-growing areas in North America. Particularly, this work investigates past precipitation trends and patterns using the North American Land Data Assimilation System, Version 2 (NLDAS-2, 12 km/1 h resolution) reanalysis dataset during 1980–2018. Both parametric (linear regression) and non-parametric (e.g., Theil-Sen) robust statistical tools are employed in the study to analyze trend magnitudes, which are tested for statistical significance using the Mann-Kendall test. Standard precipitation indices from ETCCDI are also used to characterize trends in the relative contribution of extreme events to precipitation in the area. In the region an increasing trend (4.3 mm/year) is identified in annual average precipitation with ~34% of the domain showing a significant increase (at the 0.1 significance level) of +3 to +5 mm/year. Seasonal and sub-regional trends are also investigated, with the most pronounced increasing trends identified during summers along the Virginia and Maryland border. The study also finds a statistically significant positive trend (at a 0.05 significance level) in the annual maximum precipitation. Furthermore, the number of daily extremes (daily total precipitation higher than the 95th and 99th percentiles) also depicts statistically significant increases, indicating the increased frequency of extreme precipitation events. Investigations into the proportion of annual precipitation occurring on wet days and extremely wet days (95th and 99th percentile) also indicate a significant increase in their relative contribution. The findings of this study have the potential to improve local-scale decision-making in terms of river basin management, flood control, irrigation scheme scheduling, and stormwater infrastructure planning to address urban resilience to hydrometeorological hazards.

The Mediterranean is one of the regions of the world where human-induced climate warming is expected to have large impacts on water and environmental resources. To predict shifts in the current climate system, more regional climate records, including seasonal-to-century scale variability spanning longer than the instrumental periods, are needed. To help fill this gap, we provide a reconstruction of autumn precipitation variations for the Central Pyrenees range since 1500 Common Era (CE) using the varved sediments of Lake Montcortès. To assess the suitability of the calcite sublayer width of the sediments of this lake as a proxy for precipitation anomalies, we performed an analysis and smoothing of the temporal structure of the width series, calibration of the new series with the available instrumental climate records, calculation of a transfer function and testing and comparison of the reconstructed series against available empirical data.The prediction model was statistically robust and showed that the climatic signal was captured in the calcite sublayers. The reconstruction provides the first estimations of regional autumn precipitation shifts in the Central Pyrenees at annual resolution, since 1500 CE. Pronounced interdecadal shifts in precipitation were noticeable; no increasing nor decreasing linear trends or periods of extreme precipitation events were identified. The reconstructed precipitation anomalies suggest a decrease in rainfall during the coldest phase within the coldest period of the Little Ice Age and also during the 20th century, probably associated to current Global Warming. Correlations between autumn precipitation and the North Atlantic Oscillation, Western Mediterranean Oscillation and Southern Oscillation indices were weak to moderate. A potential relationship with the Atlantic Multidecadal Oscillation pattern is suggested. The reconstructed autumn precipitation trends are coherent with other palaeohydrological reconstructions in similar Mediterranean settings, and consistent at a regional level.

AbstractThis study provides a long-term (1891–2014) global assessment of precipitation trends using data from two station-based gridded datasets and climate model outputs evolved through the fifth and sixth phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively). Our analysis employs a variety of modeling groups that incorporate low- and high-top level members, with the aim of assessing the possible effects of including a well-resolved stratosphere on the model’s ability to reproduce long-term observed annual precipitation trends. Results demonstrate that only a few regions show statistically significant differences in precipitation trends between observations and models. Nevertheless, this pattern is mostly caused by the strong interannual variability of precipitation in most of the world regions. Thus, statistically significant model-observation differences on trends (1891–2014) are found at the zonal mean scale. The different model groups clearly fail to reproduce the spatial patterns of annual precipitation trends and the regions where stronger increases or decreases are recorded. This study also stresses that there are no significant differences between low- and high-top models in capturing observed precipitation trends, indicating that having a well-resolved stratosphere has a low impact on the accuracy of precipitation projections.

Drought has become a recurrent phenomenon in Algeria in the last few decades. Significant drought conditions were observed during the late 1980s and late 1990s. The agricultural sector and water resources have been under severe constraints from the recurrent droughts. In this study, spatial and temporal dimensions of meteorological droughts in the Wadi Mina basin (4900 km2) were investigated to assess vulnerability. The Standardized Precipitation Index (SPI) method and GIS were used to detail temporal and geographical variations in drought based on monthly records for the period 1970–2010 at 16 rainfall stations located in the Wadi Mina basin. Trends in annual SPI for stations in the basin were analyzed using the Mann–Kendall test and Sen’s slope estimator. Results showed that the SPI was able to detect historical droughts in 1982/83, 1983/84, 1989/90, 1992/93, 1993/94, 1996/97, 1998/99, 1999/00, 2004/05 and 2006/07. Wet years were observed in 1971/72, 1972/73, 1995/96, 2008/09 and 2009/10. Six out of 16 stations had significant decreasing precipitation trends (at 95% confidence), whereas no stations had significant increasing precipitation trends. Based on these findings, measures to ameliorate and mitigate the effects of droughts, especially the dominant intensity types, on the people, community and environment are suggested.

AbstractPastoral people in rangelands worldwide are experiencing uncertainty due to a combination of climatic, economic, and political stressors. Our study seeks to create a full view of the drivers, impacts, and adaptations to change for livestock herders in rural Mongolia, making use of herder traditional knowledge and select instrumental data. Interview respondents described undesirable trends in livestock herds, pasture, wildlife, and their livelihoods in three sites in northern, central, and eastern Mongolia from 1995 to 2015, including decreased lake levels. There was more agreement for precipitation trends than for temperature. We developed a systems model based on herder descriptions of the sequence and prominence of interacting drivers of change. Finally, we describe measures herders are taking to adapt to these changes, such as more frequent livestock movement. We present a transdisciplinary view of social-ecological change and applications for more regionally focused governance in an era of climate uncertainty.

The paper aims to provide an overview of the most important parameters (the occurrence, frequency and magnitude) in Vojvodina Region (North Serbia). Monthly and annual mean precipitation values in the period 1946–2014, for the 12 selected meteorological stations were used. Relevant parameters (precipitation amounts, Angot precipitation index) were used as indicators of rainfall erosivity. Rainfall erosivity index was calculated and classified throughout precipitation susceptibility classes liable of triggering soil erosion. Precipitation trends were obtained and analysed by three different statistical approaches. Results indicate that various susceptibility classes are identified within the observed period, with a higher presence of very severe rainfall erosion in June and July. This study could have implications for mitigation strategies oriented towards reduction of soil erosion by water.