Search

The Sierra Nevada and Southern Cascades—California's snowy mountains—are primary freshwater sources and natural reservoirs for the states of California and Nevada. These mountains receive precipitation overwhelmingly from wintertime storms including atmospheric rivers (ARs), much of it falling as snow at the higher elevations. Using a seven-decade record of daily observed temperature and precipitation as well as a snow reanalysis and downscaled climate projections, we documented historical and future changes in snow accumulation and snowlines. In four key subregions of California's snowy mountains, we quantified the progressing contribution of ARs and non-AR storms to the evolving and projected snow accumulation and snowlines (elevation of the snow-to-rain transition), exploring their climatology, variability and trends. Historically, snow makes up roughly a third of the precipitation affecting California's mountains. While ARs make up only a quarter of all precipitating days and, due to their relative warmth, produce snowlines higher than do other storms, they contribute over 40% of the total seasonal snow. Under projected unabated warming, snow accumulation would decline to less than half of historical by the late twenty-first century, with the greatest snow loss at mid elevations (from 1500 to 3300 m by the mountain sub-regions) during fall and spring. Central and Southern Sierra Nevada peaks above 3400 m might see occasionally extreme snow accumulations in January–February resulting entirely from wetter ARs. AR-related snowlines are projected to increase by more than 700 m, compared to about 500 m for other storms. We discuss likely impacts of the changing climate for water resources as well as for winter recreation. [ABSTRACT FROM AUTHOR]

The Three-River Headwater Region (TRHR) has undergone significant hydrological changes and affects the water resources security in the local and downstream areas. We use multiple observational precipitation product, as well as the ERA5 reanalysis dataset to investigate the precipitation variations over the TRHR during the rainy season from 1990 to 2020, and to analyze the contributions of local evaporation and remote water vapor transport to the precipitation and its variations. The precipitation shows a significant increasing trend (17.8 mm decade−1). The precipitation variability (PV) is larger at daily scale and smaller at interannual scale. The spatial distribution of PV varies on different timescales, which reflects the different dominant regimes driving the moisture transport. The mean precipitation in the TRHR is predominantly contributed by western and southern moisture influxes, and the increasing trend of these influxes (10.8 kg s−1 decade−1) determines the precipitation increase. Local evaporation provide about 6% of water vapor for the precipitation, while it has little influence on the precipitation change. The anomalous precipitation in wet and dry years is mainly controlled by the atmospheric circulation over the Tibetan Plateau, which regulates the southwestern moisture transport towards the TRHR. Additionally, the precipitation during 1990–2020 increases by about 3.9% compared to that during 1960–1989. It is related to the higher conversion ratio of water vapor influxes to precipitation and larger evaporation over the TRHR. These findings improve our understanding of the precipitation variations in the TRHR and provide insights for policy makers to optimize water resources management to cope with the global climate change. [ABSTRACT FROM AUTHOR]

Flooding events associated with extreme precipitation have had large impacts in Norway. It is well known that these heavy precipitation events affecting Norway (and other parts of Europe) are strongly associated with atmospheric rivers (ARs). We assess trends in Norwegian AR characteristics, and the influence of AR variability on extreme precipitation in Norway. We first evaluate the ability of a high-resolution global climate model (EC-Earth) to simulate ARs, compared to ERA-Interim. We evaluate the EC-Earth simulated relationship between ARs and extreme precipitation in western Norway, compared to the observed relationship. We find that EC-Earth is able to simulate well the statistics of AR events and the related precipitation. The intensity and frequency of ARs making landfall in Norway both increase by the end of the century and we find a shift in seasonality of AR events in the future period. In two regions on the west coast, the majority of winter precipitation maxima are associated with AR events (> 80% of cases). Next we assess the influence of AR variability on extreme precipitation. A non-stationary extreme value analysis indicates that the magnitude of extreme precipitation events in these regions is associated with AR intensity. Indeed, the 1-in-20 year extreme event is 17% larger when the AR-intensity is high, compared to when it is low. There is little influence of specific humidity on the variability of extreme precipitation after all variables are de-trended. Finally, we find that the region mean temperature during winter AR events increases in the future. In the future, when the climate is generally warmer, AR days will tend to make landfall when the temperature is above the freezing point. The partitioning of more precipitation as rain, rather than as snow, can have severe impacts on flooding and water resource management. [ABSTRACT FROM AUTHOR]

The California-Nevada 1997 New Year's flood was an atmospheric river (AR)-driven rain-on-snow (RoS) event and remains the costliest in their history. The joint occurrence of saturated soils, rainfall, and snowmelt generated inundation throughout northern California-Nevada. Although AR RoS events are projected to occur more frequently with climate change, the warming sensitivity of their flood drivers across scales remains understudied. We leverage the regionally refined mesh capabilities of the Energy Exascale Earth System Model (RRM-E3SM) to recreate the 1997 New Year's flood with horizontal grid spacings of 3.5 km across California, with forecast lead times of up to 4 days, and across six warming levels ranging from pre-industrial conditions to + 3.5 ∘ C. We describe the sensitivity of the flood drivers to warming including AR duration and intensity, precipitation phase, intensity and efficiency, snowpack mass and energy changes, and runoff efficiency. Our findings indicate current levels of climate change negligibly influence the flood drivers. At warming levels ≥ 1.7 ∘ C, AR hazard potential increases, snowpack nonlinearly decreases, antecedent soil moisture decreases (except where the snowline retreats), and runoff decreases (except in the southern Sierra Nevada where antecedent snowpack persists). Storm total precipitation increases, but at rates below warming-induced increases in saturation-specific humidity. Warming intensifies short-duration, high-intensity rainfall, particularly where snowfall-to-rainfall transitions occur. This study highlights the nonlinear tradeoffs in 21st-century RoS flood hazards with warming and provides water management and infrastructure investment adaptation considerations. [ABSTRACT FROM AUTHOR]

Originating in the Tianshan Mountains in arid Central Asia, the natural discharge change of the Naryn River is strongly affected by climate change. As the main source of water for the region, this river is crucial to both the natural environment and the socio-economic development. To extend the discharge record and better understand past and future changes in Naryn River discharge, we developed four tree-ring width chronologies and analyzed the relationship between tree growth and discharge. The resulting reconstruction dates back to 1753 and has an R2 of 0.374 (1939–2017). Interannual discharge variations of the Naryn River indicate that 1917 was the driest year of the past 265 years, while 1956 was the wettest. The record also indicates that the majority of extreme flood years occurred in the past century; prior to about 1900 C.E., the discharge of the Naryn River was relatively stable. Since 1900 C.E., discharge volume has gradually increased, as has discharge variability. At decadal time scales, the 2010s are notable for the frequency of major floods, whereas the 1910s were the driest. Between the 1870s and the 1910s, the Naryn River experienced a period of low discharge that continued for nearly half a century. The discharge of the Naryn River over the past 265 years appears to vary over quasi-periods of 60, 21, 11, and 2-4 years, which are driven by large-scale climate systems. [ABSTRACT FROM AUTHOR]

Inland-penetrating atmospheric rivers (ARs) affect the United States Southwest and significantly contribute to cool season precipitation. In this study, we examine the results from an ensemble of dynamically downscaled simulations from the North American Regional Climate Change Assessment Program (NARCCAP) and their driving general circulation models (GCMs) in order to determine statistically significant changes in the intensity of the cool season ARs impacting Arizona and the associated precipitation. Future greenhouse gas emissions follow the A2 emission scenario from the Intergovernmental Panel on Climate Change Fourth Assessment Report simulations. We find that there is a consistent and clear intensification of the AR-related water vapor transport in both the global and regional simulations which reflects the increase in water vapor content due to warmer atmospheric temperatures, according to the Clausius-Clapeyron relationship. However, the response of AR-related precipitation intensity to increased moisture flux and column-integrated water vapor is weak and no significant changes are projected either by the GCMs or the NARCCAP models. This lack of robust precipitation variations can be explained in part by the absence of meaningful changes in both the large-scale water vapor flux convergence and the maximum positive relative vorticity in the GCMs. Additionally, some global models show a robust decrease in relative humidity which may also be responsible for the projected precipitation patterns. [ABSTRACT FROM AUTHOR]

Winter precipitation (PR) characteristics in western United States (WUS) related to atmospheric river (AR) landfalls are examined using the observation-based PRISM data. The observed AR-related precipitation characteristics are in turn used to evaluate model precipitation data from the NASA MERRA2 reanalysis and from seven dynamical downscaling simulations driven by the MERRA2. Multiple metrics including mean bias, Taylor diagram, and two skill scores are used to measure model performance for three climatological sub-regions in WUS, Pacific Northwest (PNW), Pacific Southwest (PSW) and Great Basin (GB). All model data well represent the winter-mean PR with spatial pattern correlations of 0.8 or higher with PRISM for the three sub-regions. Higher spatial resolutions and/or the use of spectral nudging generally yield higher skill scores in simulating the geographical distribution of PR for the entire winter. The PRISM data shows that the AR-related fraction of winter PR and associated daily PR PDFs in each region vary strongly for landfall locations; AR landfalls in the northern WUS coast (NC) affect mostly PNW while those in the southern WUS coast (SC) affect both PSW and GB. NC (SC) landfalls increase the frequency of heavy PR in PNW (PSW and GB) but reduce it in PSW (PNW). All model data reasonably represent these observed variations in the AR-related winter PR fractions and the daily PR PDFs according to AR landfall locations. However, unlike for the entire winter period, no systematic effects of resolution and/or spectral nudging are identified in these AR-related PR characteristics. Dynamical downscaling in this study generally yield positive added values to the MERRA2 PR in the AR-related PR fraction for most sub-regions and landfall locations, most noticeably for PSW by NU-WRF. The downscaling also generate positive added value in p95 for PNW, but negative values for PSW and GB due to overestimation of heavy precipitation events. [ABSTRACT FROM AUTHOR]

Higher variability in rainfall and river discharge could be of major importance in landslide generation in the northwestern Argentine Andes. Annual layered (varved) deposits of a landslide dammed lake in the Santa Maria Basin (26°S, 66°W) with an age of 30,000 14C years provide an archive of precipitation variability during this time. The comparison of these data with present-day rainfall observations tests the hypothesis that increased rainfall variability played a major role in landslide generation. A potential cause of such variability is the El Niño/Southern Oscillation (ENSO). The causal link between ENSO and local rainfall is quantified by using a new method of nonlinear data analysis, the quantitative analysis of cross recurrence plots (CRP). This method seeks similarities in the dynamics of two different processes, such as an ocean–atmosphere oscillation and local rainfall. Our analysis reveals significant similarities in the statistics of both modern and palaeo-precipitation data. The similarities in the data suggest that an ENSO-like influence on local rainfall was present at around 30,000 14C years ago. Increased rainfall, which was inferred from a lake balance modeling in a previous study, together with ENSO-like cyclicities could help to explain the clustering of landslides at around 30,000 14C years ago. [ABSTRACT FROM AUTHOR]

Our results reveal long-term trends in ice out dates (1836-2013) for twelve lakes in Maine, New Brunswick and New Hampshire, in eastern North America. The trends are remarkably coherent between lakes (r = 0.462-0.933, p < 0.01) and correlate closely with the March-April (MA) instrumental temperature records from the region (r = 0.488-0.816, p < 0.01). This correlation permits use of ice out dates as a proxy to extend the shorter MA instrumental record (1876-2013). Mean ice out dates trended progressively earlier during the recovery from the Little Ice Age through to the 1940s, and gradually became later again through to the late 1970s, when ice out dates had returned to values more typical of the late nineteenth century. Post-1970's ice out dates resumed trending toward earlier dates, with the twenty-first century being characterized by the earliest ice out dates on record. Spectral and wavelet time series analysis indicate that ice out is influenced by several teleconnections including the Quasi-biennial Oscillation, El Niño-Southern Oscillation, North Atlantic Oscillation, as well as a significant correlation between inland lake records and the Atlantic Multidecadal Oscillation. The relative influence of these teleconnections is variable with notable shifts occurring after ~1870, ~1925, and ~1980-2000. The intermittent expression of these cycles in the ice out and MA instrumental record is not only influenced by absolute changes in the intensity of the various teleconnections and other climate drivers, but through phase interference between teleconnections, which periodically damps the various signals. [ABSTRACT FROM AUTHOR]

The spatio-temporal variations of the water budget components in the Amazon region are investigated by using a combination of hydrometeorological observations and moisture fluxes derived from the NCEP/NCAR reanalyses, for the period 1970-1999. The key new finding of this study identifies the major differences in the water balance characteristics and variability between the northern and southern parts of the basin. Our results show that there is a seasonality and interannual variability of the water balance that varies across the basin. At interannual time scales, anomalies in the water balance components in the northern Amazon region show relatively stronger links with tropical Pacific interannual variability. Over the entire region, precipitation exceeds evaporation and the basin acts as a sink of moisture (P>E). However, on some occasions the basin can act as a source for moisture (P

This paper provides a synoptic view of extreme monsoon floods on all the nine large rivers of South Asia and their association with the excess (above-normal) monsoon rainfall periods. Annual maximum flood series for 18 gauging stations spread over four countries (India, Pakistan, Bangladesh and Nepal) and long-term monsoon rainfall data were analyzed to ascertain whether the extreme floods were clustered in time and whether they coincided with multi-decade excess monsoon rainfall epochs at the basin level. Simple techniques, such as the Cramer's t-test, regression and Mann-Kendall (MK) tests and Hurst method were used to evaluate the trends and patterns of the flood and rainfall series. MK test reveals absence of any long-term tendency in all the series. However, the Cramer's t test and Hurst-Mandelbrot rescaled range statistic provide evidence that both rainfall and flood time series are persistent. Using the Cramer's t-test the excess monsoon epochs for each basin were identified. The excess monsoon periods for different basins were found to be highly asynchronous with respect to duration as well as the beginning and end. Three main conclusions readily emerge from the analyses. Extreme floods (>90th percentile) in South Asia show a tendency to cluster in time. About three-fourth of the extreme floods have occurred during the excess monsoon periods between ~1840 and 2000 AD, implying a noteworthy link between the two. The frequency of large floods was higher during the post-1940 period in general and during three decades (1940s, 1950s and 1980s) in particular. [ABSTRACT FROM AUTHOR]

Pan Third Pole (PTP) region includes Tibet Plateau (TP), Central Asia (CA) and Southeast Asia (SEA) and it is one of the places on earth that are most sensitive to climate change. Meanwhile, PTP origins a series of large rivers such as Yangtze River, Yellow River and Lancang-Mekong River, which feed millions of people downstream. Therefore, climate change in PTP has significant impact on livings and water supply of local residents. In this study, 16 model predictions from the Coupled Model Inter-comparison Project Phase 6 (CMIP6) and Climate Research Unit (CRU) observations are used to evaluate historical precipitation and temperature climatology changes in PTP region for the far (1901–1930), middle (1941–1970) and near history (1981–2010) respectively. In addition, Bayesian model averaging (BMA) approach is applied to obtain the multi-model weighted average prediction and the BMA values are further used to assess the climate variabilities in the near (2021–2050), middle (2046–2075) and far future (2071–2100) under four SSP-RCP scenarios. Results indicate that temperature is significantly underestimated by most CMIP6 models in TP especially IPSL-CM6A-LR and CanESM5 whereas precipitation is overestimated for CA and TP. Most CMIP6 models do not predict precipitation very well in SEA, the difference of annual total precipitation between the highest estimation from UKESM1-0-LL and the lowest estimation from CAMS-CSM1-0 is about 800 mm. Overall, BMA prediction is more reliable compared with individual models. In addition, Pan Third Pole region is projected to be warmer and wetter in the future and the trend is stronger under SSP5-8.5 scenario. The BMA predicted temperature uncertainty is larger for high latitude CA region whereas precipitation uncertainty is higher for low latitude SEA region. [ABSTRACT FROM AUTHOR]

The Colorado River is one of the most important rivers in the southwestern U.S., with ~ 90% of the total flow originating from the Upper Colorado River Basin (UCRB). The UCRB April–July streamflow is well-correlated to the UCRB spring precipitation. It is known that the UCRB precipitation is linked to an El Niño-like sea surface temperature (SST) pattern, but the causal effect of the tropical Pacific SST on the UCRB spring precipitation is still uncertain. Here, we apply a Granger causality approach to understand the causal effect of the tropical Pacific averaged SST in previous three seasons (winter, fall, and summer) on the UCRB averaged precipitation in spring in observations and two climate models. In observations, only the winter SST has Granger causal effect (with p-value ~ 0.05) on spring precipitation, while historical simulations of the two climate models overestimate the causal effect for winter and fall (with p-value < 0.01 and < 0.05, respectively) due to model biases. Moreover, future projections of the two climate models show divergent causal effects, especially for the scenario with high anthropogenic emissions. The divergent projections indicate that (1) there are large uncertainties in model projections of the causal effect of the tropical Pacific SST on UCRB spring precipitation and (2) it is uncertain whether climate models can reliably capture changes in such causality. These uncertainties may result in large uncertainties in seasonal forecasts of the UCRB hydroclimate under global climate change. [ABSTRACT FROM AUTHOR]

Six and 21 kyear BP represent the extreme states of climate since the last glacial maximum. The early Holocene, in contrast, was a time of transition, experiencing rapidly melting continental ice sheets, rising sea-level, and increasing summer insolation. Key features of the climate, illustrated by an NCAR CCM3 general circulation model experiment representing 11 kyr BP, include enhanced continentality and seasonality, and an enhanced northern monsoon. The principal circulation responses to the 11 kyr BP boundary conditions can be summarized as an intensification and northward shift of the mean meridional circulation and an intensification of the planetary wave structure of the Northern Hemisphere in northern summer, and a slight intensification of the mean meridional circulation coupled with a southward shift in the planetary wave structure in northern winter. These changes are manifest in the enhancement of the typical seasonal cycle of sea-level pressure in the Northern Hemisphere relative to that of the present day, and enhancement and equatorward shift of the Aleutian and Icelandic lows in northern winter. Over the period 15-8 kyr BP, within the current boreal forest zone, herbaceous tundra was replaced by shrub tundra, and subsequently by evergreen or deciduous forest, but there is uncertainty in the location, timing, and exact nature of these transitions. The specific location of the relatively small area of the Asian boreal forest-tundra transition can have an impact on regional climate, primarily in the net shortwave radiation component of the surface energy budget in spring, and in the cloudiness, net shortwave radiation, and turbulent heat fluxes in summer. These changes also have an impact on global climate. Our results suggest that the additional northern heating leads to a reduced equator-pole heat transport in the Northern Hemisphere which then influences heat and momentum transport in the Southern Hemisphere. [ABSTRACT FROM AUTHOR]

The analysis of seasonal and long-term changes of the Caspian Sea level examined from historical long time tide gauge data in order to consider the influence of climate factors on sea level changes in this lake system using spectral analysis method. The major peak at spectra corresponds to the annual cycle and semiannual oscillations peak is located at next vigorous. Effects of different global and regional factors on lake level changes are investigated by signal processing methods. Results show that annual cycle of Siberian High and Volga River discharge have the considerable effects on the Caspian Sea level changes in global and regional scales, respectively. Analyzing of seasonal cycle revealed that Volga river discharge is significant on sea level fluctuations by 1-month lag in northern and central sub-basins and 2 months delay for southern sub-basin. The results of long-term cycle show ascending trend of evaporation in Caspian central sub-basin, which it is the main driver of decreasing trend of the Caspian Sea level since 1990s. [ABSTRACT FROM AUTHOR]

Climate extremes can severely impact socio-economic development. Climate trends of three temperature and three precipitation climate indices were evaluated in observational data, 23 models from the 5th Coupled Model Intercomparison Projects (CMIP5), and 20 models from CMIP6. The climate indices were calculated over the whole of China, and individually over the basins of its three major rivers. The indices are the spatio-temporal evolution characteristics of annual mean temperature (Tas), minimum of daily minimum temperature (TNn), maximum of daily maximum temperature (TXx), number of tropical nights (TR), daily precipitation (Pre), very heavy precipitation days (R20mm), maximum consecutive 5-day precipitation (Rx5day) and consecutive dry days (CDD). From 1961 to 2018, most of China has warmed; Tas, TNn, TXx and TR over China has increased by 1.7 °C, 2.8 °C, 1.1 °C and 9 days, respectively. Changes of Tas, TNn and TXx over the Yellow River Basin, Yangtze River Basin and Pearl River Basin were generally similar in sign. The most significant increase of TR was seen over the Pearl River Basin. Historical Tas was well reproduced by both CMIP5 and CMIP6 over the study regions, but obvious uncertainties exist in the simulation of Pre. In general, CMIP6 models were improved from CMIP5 models. Climate projections were calculated for the 2021–2100 period. Future warming over China would be stronger with higher SSP scenarios; TNn over China would warm seven times more under the SSP5-8.5 scenario (5.6 °C) compared to the SSP1-2.6 scenario. Future wetting over China would be stronger with higher the SSP scenarios; Under the SSP5-8.5 scenario, Pre, R20mm, Rx5day would increase by 28%, 150%, and 38%, respectively. Projected changes of CDD different by region—decreasing over most of China and the Yellow River Basin, but increasing over the Yangtze and Pearl River Basins. The higher of the emission scenario, the less significant the reduction of CDD over the two basins. This suggests that the temporal distribution of precipitation over China will become more uneven in the future, especially under the higher SSP scenarios. [ABSTRACT FROM AUTHOR]

Climate change simulation based on 30-member ensemble of Voeikov Main Geophysical Observatory RCM (resolution 25 km) for northern Eurasia is used to drive hydrological model CaMa-Flood. Using this modeling framework, we evaluate the uncertainties in the future projection of the peak river discharge and flood hazard by 2050-2059 relative to 1990-1999 under IPCC RCP8.5 scenario. Large ensemble size, along with reasonably high modeling resolution, allows one to efficiently sample natural climate variability and increase our ability to predict future changes in the hydrological extremes. It has been shown that the annual maximum river discharge can almost double by the mid-XXI century in the outlets of major Siberian rivers. In the western regions, there is a weak signal in the river discharge and flood hazard, hardly discernible above climate variability. Annual maximum flood area is projected to increase across Siberia mostly by 2-5% relative to the baseline period. A contribution of natural climate variability at different temporal scales to the uncertainty of ensemble prediction is discussed. The analysis shows that there expected considerable changes in the extreme river discharge probability at locations of the key hydropower facilities. This suggests that the extensive impact studies are required to develop recommendations for maintaining regional energy security. [ABSTRACT FROM AUTHOR]

Observing, modelling and understanding the climate-scale variability of the deep water formation (DWF) in the North-Western Mediterranean Sea remains today very challenging. In this study, we first characterize the interannual variability of this phenomenon by a thorough reanalysis of observations in order to establish reference time series. These quantitative indicators include 31 observed years for the yearly maximum mixed layer depth over the period 1980-2013 and a detailed multi-indicator description of the period 2007-2013. Then a 1980-2013 hindcast simulation is performed with a fully-coupled regional climate system model including the high-resolution representation of the regional atmosphere, ocean, land-surface and rivers. The simulation reproduces quantitatively well the mean behaviour and the large interannual variability of the DWF phenomenon. The model shows convection deeper than 1000 m in 2/3 of the modelled winters, a mean DWF rate equal to 0.35 Sv with maximum values of 1.7 (resp. 1.6) Sv in 2013 (resp. 2005). Using the model results, the winter-integrated buoyancy loss over the Gulf of Lions is identified as the primary driving factor of the DWF interannual variability and explains, alone, around 50 % of its variance. It is itself explained by the occurrence of few stormy days during winter. At daily scale, the Atlantic ridge weather regime is identified as favourable to strong buoyancy losses and therefore DWF, whereas the positive phase of the North Atlantic oscillation is unfavourable. The driving role of the vertical stratification in autumn, a measure of the water column inhibition to mixing, has also been analyzed. Combining both driving factors allows to explain more than 70 % of the interannual variance of the phenomenon and in particular the occurrence of the five strongest convective years of the model (1981, 1999, 2005, 2009, 2013). The model simulates qualitatively well the trends in the deep waters (warming, saltening, increase in the dense water volume, increase in the bottom water density) despite an underestimation of the salinity and density trends. These deep trends come from a heat and salt accumulation during the 1980s and the 1990s in the surface and intermediate layers of the Gulf of Lions before being transferred stepwise towards the deep layers when very convective years occur in 1999 and later. The salinity increase in the near Atlantic Ocean surface layers seems to be the external forcing that finally leads to these deep trends. In the future, our results may allow to better understand the behaviour of the DWF phenomenon in Mediterranean Sea simulations in hindcast, forecast, reanalysis or future climate change scenario modes. The robustness of the obtained results must be however confirmed in multi-model studies. [ABSTRACT FROM AUTHOR]

Tibetan Plateau is the headwater region of many major Asian rivers and very susceptive to climate change. Therefore, knowledge about climate and its spatiotemporal variability in this area is very important for ecological conservation, water resource management and social development. The aim of this study was to reconstruct and analyze the hydroclimate variation on eastern Tibetan Plateau (ETP) over many centuries and explore possible forcing factors on regional hydroclimate variability. We used 118 tree-ring chronologies from ETP to reconstruct the gridded May-July Standardized Precipitation Evapotranspiration Index for the ETP over the last millennium. The reconstruction was developed using an ensemble point-by-point reconstruction method, and a searching region method was used to locate the candidate tree-ring chronologies. The reconstructions have nicely captured the spatial and temporal features of the regional drought variation. The drought variations in south and north of 32.5°N are notably different, which may be related to the divergence influence of North Atlantic Oscillation on the climate systems in the south and north, as well as differences in local climate. Spectral analysis and series comparison suggest that the drought variation in the northeastern Tibetan Plateau has been possibly influenced by solar activity on centurial and longer time scale. [ABSTRACT FROM AUTHOR]

High-resolution weather data is crucial for assessing future climate change impacts on local environments, yet downscaling low-resolution Global Climate Models (GCMs) outputs and addressing associated uncertainty remain significant challenges. In this study, we propose a novel spatial weather generator using generative networks, specifically a numerical conditional deep convolutional generative adversarial network (cDCGAN), as a promising solution. The cDCGAN generates high-resolution weather data from low-resolution GCM outputs and was applied to four case areas in China under four Shared Socio-economic Pathway (SSP) scenarios. The results demonstrate the cDCGAN's accuracy, consistency, and stability, with low uncertainties. The model performs optimally in low-elevation plains and tropical regions. The cDCGAN offers advantages in uncertainty analysis over traditional downscaling methods, serving as a valuable tool for climate change analysis, response estimation, and environmental management decision-making within the spatial statistics domain. [ABSTRACT FROM AUTHOR]

The Indo-Gangetic Plain (IGP), the source of grains for around 40% Indian population, is known as the breadbasket of India. The Indian Summer Monsoon Rainfall (ISMR) plays a vital role in the agricultural activities in this region. The rapid urbanization, land use and land cover change have significantly impacted the region's agriculture, water resources, and socioeconomic facets. The present study has investigated the observed and regional modeling aspects of ISMR characteristics, associated extremes over the IGP, and future perspectives under the high-emission RCP8.5-scenario. Future projections suggest a 10–20% massive decrease during pre-monsoon (March–May) and earlier ISM season months (i.e., June and July). A significant 40–70% decline in mean monsoon rainfall during the June–July months in the near future (NF; 2041–2060) has been projected compared to the historical period (1986–2005). An abrupt increase of 80–170% in mean monsoon rainfall during the post-monsoon (October–December) in the far future (FF; 2080–2099) is also projected. The distribution of projected extreme rainfall events shows a decline in moderate or rather heavy events (5 or more) in NF and FF. Further, an increase in higher rainfall category events such as very heavy (5–10) and extremely heavy rainfall (5 or more) events in NF and FF under the warmer climate is found. However, the changes are less prominent during FF compared to the NF. The mean thresholds for extremely heavy rainfall may increase by 1.9–4.9% during NF and FF. Further, the evolution patterns of various quantities, such as tropospheric temperature gradient (TG), specific humidity, and mean sea level pressure, have been analyzed to understand the physical processes associated with rainfall extremes. The strengthening in TG and enhanced atmospheric moisture content in NF and FF support the intensification in projected rainfall extremes over IGP. [ABSTRACT FROM AUTHOR]

We investigate the influence of bias correction of Global Climate Models (GCMs) prior to dynamical downscaling using regional climate models (RCMs), on the change in climate projected. We use 4 GCMs which are bias corrected against ERA-Interim re-analysis as a surrogate truth, and carry out bias corrected and non-bias corrected simulations over the CORDEX Australasia domain using the Weather Research and Forecasting model. Our results show that when considering the effect of bias correction on current and future climate separately, bias correction has a large influence on precipitation and temperature, especially for models which are known to have large biases. However, when considering the change in climate, i.e the Δ change (future minus current), we found that while differences between bias-corrected and non-corrected RCM simulations can be substantial (e.g. more than 1 ∘ C for temperatures) these differences are generally smaller than the models' inter-annual variability. Overall, averaged across all variables, bias corrected boundary conditions produce an overall reduction in the range, standard deviation and mean absolute deviation of the change in climate projected by the 4 models tested, over 61.5%, 62% and 58% of land area, with a larger reduction for precipitation as compared to temperature indices. In addition, we show that changes in the Δ change for DJF tasmax are broadly linked to precipitation changes and consequently soil moisture and surface sensible heat flux and changes in the Δ changefor JJA tasmin are linked to downward longwave heat flux. This study shows that bias correction of GCMs against re-analysis prior to dynamical downscaling can increase our confidence in projected future changes produced by downscaled ensembles. [ABSTRACT FROM AUTHOR]

Simulations with a very high resolution (~25 km) global climate model indicate that more severe Autumn storms will impact Europe in a warmer future climate. The observed increase is mainly attributed to storms with a tropical origin, especially in the later part of the twentyfirst century. As their genesis region expands, tropical cyclones become more intense and their chances of reaching Europe increase. This paper investigates the properties and evolution of such storms and clarifies the future changes. The studied tropical cyclones feature a typical evolution of tropical development, extratropical transition and a re-intensification. A reduction of the transit area between regions of tropical and extratropical cyclogenesis increases the probability of re-intensification. Many of the modelled storms exhibit hybrid properties in a considerable part of their life cycle during which they exhibit the hazards of both tropical and extratropical systems. In addition to tropical cyclones, other systems such as cold core extratropical storms mainly originating over the Gulf Stream region also increasingly impact Western Europe. Despite their different history, all of the studied storms have one striking similarity: they form a warm seclusion. The structure, intensity and frequency of storms in the present climate are compared to observations using the MERRA and IBTrACS datasets. Damaging winds associated with the occurrence of a sting jet are observed in a large fraction of the cyclones during their final stage. Baroclinic instability is of great importance for the (re-)intensification of the storms. Furthermore, so-called atmospheric rivers providing tropical air prove to be vital for the intensification through diabatic heating and will increase considerably in strength in the future, as will the associated flooding risks. [ABSTRACT FROM AUTHOR]

The distributions of forest, ice and snow in the Hengduan Mountains of China have undergone significant changes due to ongoing climatic warming. To better understand the spatiotemporal pattern of temperature changes in the Hengduan Mountains, we used tree-ring cores collected from multiple individuals of Larix speciosa Cheng et Law at five sites to develop a regional chronology and to establish the relationship between tree-ring radial growth and warm-season (May–September) mean temperature. The regional chronology accounts for 46.1% of the observed variance in the warm season and was used to reconstruct regional temperature levels back to 1420. Four cool intervals (1490–1570, 1590–1660, 1700–1790, and 1800–1880) indicate that the Western Hengduan Mountains experienced the Little Ice Age, and the changes were synchronous with cooling on the Tibetan Plateau and in the Northern Hemisphere, demonstrating a well-defined Little Ice Age signal in the South Asian monsoon region. Air–sea interactions and solar activity affected the variability of the warm-season mean temperature variations on interannual or interdecadal scales. Our temperature reconstruction improves the understanding of multi-centennial climate change in the Western Hengduan Mountains and has implications for advancing high-resolution paleoclimate science in the region. [ABSTRACT FROM AUTHOR]

Quantifying the extent of change in climatic and hydrological variables in the past and the future is essential for climate change-resilient development, especially in the climate change sensitive region of Nepal. This paper analyzed future climatic trends and extremes, historical hydrological extremes and their linkage with historical precipitation extremes, and discussed the impacts of climate change on various sectors in the less-studied Small and Medium-sized Eastern River Basins (SMERB) of Nepal. Applying an ensemble of five Coupled Model Intercomparison Project phase 6 (CMIP6) global climate models (GCMs), we evaluated 10 precipitation and 13 temperature extreme indices using Climpact2 for the historical (1979–2020), near-future (2021–2045), mid-future (2046–2070) and far-future (2071–2100) under two Shared Socioeconomic Pathway (SSP), SSP245 and SSP585. Hydrological extreme indices were assessed using Indicators of Hydrologic Alteration tool. Projected climate revealed significant increase (9–73%) in annual and seasonal rainfall except winter; frequent intense rainfall extremes but prolonged dry spells; significant increasing minimum and maximum temperature trends (0.4–5 °C); rise in extreme heat events; increasing minimum and maximum discharge extreme trends in most hydrological stations; as well as strong association between maximum 1 day precipitation (Rx1day) and 1 day max flow for all stations. Growing dry periods but intense rainfall in few wet days, coupled with warming pattern all-over SMERB with frequent extreme events indicate high risk for future climate-related disasters. The harsher climate will potentially have damaging implications, especially in climate-induced disasters, food security, and water and sanitation infrastructure. [ABSTRACT FROM AUTHOR]

Warming induced by increased greenhouse gas emissions is intensifying the global water cycle and increasing the water vapor content of the global atmosphere. However, there is a lack of scientific literature assessing how regional atmospheric moisture transport and recycling will change in a warming climate. This work analyzes the projections of atmospheric moisture transport and recycling over tropical South America by the end of the twenty-first century (2070–2100) under a climate change scenario (RCP8.5). We used the Dynamic Recycling Model to estimate atmospheric moisture contributions to the region considering input data from the European Centre for Medium-Range Weather Forecasts ERA5 reanalysis and 11 models included in the Fifth Phase of the Coupled Model Intercomparison Project. Projected increases of precipitable water in tropical South America are linked with increased evaporation from the oceans. However, those projections also indicate (1) reductions in the precipitation contributed by the main atmospheric moisture sources to the continental regions of tropical South America, (2) reductions of total precipitation, and (3) reductions of recycled precipitation over the region. The largest reductions of precipitation recycling are projected over the southern Amazon during the dry-to-wet transition season (about 31%) and the northern Amazon during its dry season (about 25%). This is particularly relevant since the southern Amazon has experienced the occurrence of longer dry seasons during the recent decades and has been highlighted as a hotspot of climate change. [ABSTRACT FROM AUTHOR]

Extreme weather events are more detrimental to human culture and ecosystems than typical weather patterns. A multimodel ensemble (MME) of the top-performing global climate models (GCMs) to simulate 11 precipitation extremes was selected using a hybrid method to project their changes in Pakistan. It also compared the benefits of using all GCMs compared to using only selected GCMs when projecting precipitation extremes for two future periods (2020–2059) and (2060–2099) for four shared socioeconomic pathways (SSPs), SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5. Results showed that EC-Earth3-Veg, MRI-ESM2-0 and NorESM2-MM performed best among GCMs in simulating historical and projecting future precipitation extremes. Compared to the MME of all GCMs, the uncertainty in future projections of all precipitation indices of the selected GCMs were significantly smaller. The MME median of the selected GCMs showed increased precipitation extremes over most of Pakistan. The greater increases were in RX1day by 6–12 mm, RX5day by 12–20 mm, Prcptot by 40–50 mm, R95ptot by greater than 30 mm, R99ptot by more than 9 mm, R4mm ≥ 4 mm by 0–4 days, R10mm by 2–6 days, R20mm by 1–3 days, and SDII by 1 mm/day, CWD by one day, CDD by 0–4 days in the northern high elevated areas for SSP5-8.5 in the late future. These results emphasize the greater influence of climate change on precipitation extremes in the northern, high-elevation areas, which provide the majority of the country's water. This emphasizes the necessity to adopt suitable climate change mitigation strategies for sustainable development, particularly in the country's northern regions. [ABSTRACT FROM AUTHOR]

It is essential to identify water sectors that will be significantly impacted by climate change and to develop strategies to enhance the resiliency of these sectors against climate change impacts. The Arabian Peninsula (AP) is an arid region facing increasingly more severe water-scarcity issues due to climate change impacts. We investigate abrupt changes in the AP's climate, and examined the spatial relationships between climatic changes, ENSO, and Indian Ocean Dipole (IOD). An analysis was conducted to examine how hydroclimatic changes impact the frequency of droughts in AP. The results show that AP is very sensitive to climate change impacts since 1990s. Regional climatic change hotspots in AP include an increase in geopotential height (GPH), surface temperature, potential evapotranspiration (PET), and a decrease in relative humidity, soil moisture, and rainfall between 1985 and 2020. The northern and northwestern areas of AP, specifically Hail, Al Qassim, Tabuk, and Al Jouf, experienced the most significant increases in GPH, warming, and PET. The meridional wind (zonal wind) speed has decreased (increased) between 1985 and 2020. Climate scenarios of CMIP6 of IPCC (Intergovernmental Panel of Climate Change) project future warmer and drier conditions over AP under significant warming and marginal increase in rainfall between 2020 and 2100. Furthermore, positive ENSO and IOD episodes are associated with negative rainfall and surface moisture anomalies, and positive surface temperature and PET anomalies over irrigated areas of AP. Climate warming in AP has also resulted in persistent drought conditions after 1998, which have significantly affected the agricultural sector of AP due to higher water demand for irrigated crops because of higher evaporation losses under climate warming. Therefore, representative estimations of regional water demand for irrigation in AP are essential in developing effective adaptation strategies against climate change impacts, such as introducing crop patterns of lower transpiration losses to achieve water saving and providing optimal irrigation water requirements for AP of arid climate. In conclusion, regions with limited water resources, such as the AP, will likely experience more significant water scarcity and drought. Therefore, identifying the water sectors most impacted by climate change and developing strategies to enhance their resiliency is essential. [ABSTRACT FROM AUTHOR]

The combined future impacts of climate change and industrial and agricultural practices in the Baltic Sea catchment on the Baltic Sea ecosystem were assessed. For this purpose 16 transient simulations for 1961-2099 using a coupled physical-biogeochemical model of the Baltic Sea were performed. Four climate scenarios were combined with four nutrient load scenarios ranging from a pessimistic business-as-usual to a more optimistic case following the Baltic Sea Action Plan (BSAP). Annual and seasonal mean changes of climate parameters and ecological quality indicators describing the environmental status of the Baltic Sea like bottom oxygen, nutrient and phytoplankton concentrations and Secchi depths were studied. Assuming present-day nutrient concentrations in the rivers, nutrient loads from land increase during the twenty first century in all investigated scenario simulations due to increased volume flows caused by increased net precipitation in the Baltic catchment area. In addition, remineralization rates increase due to increased water temperatures causing enhanced nutrient flows from the sediments. Cause-and-effect studies suggest that both processes may play an important role for the biogeochemistry of eutrophicated seas in future climate partly counteracting nutrient load reduction efforts like the BSAP. [ABSTRACT FROM AUTHOR]

Within the CIRCE project 'Climate change and Impact Research: the Mediterranean Environment', an ensemble of high resolution coupled atmosphere-ocean regional climate models (AORCMs) are used to simulate the Mediterranean climate for the period 1950-2050. For the first time, realistic net surface air-sea fluxes are obtained. The sea surface temperature (SST) variability is consistent with the atmospheric forcing above it and oceanic constraints. The surface fluxes respond to external forcing under a warming climate and show an equivalent trend in all models. This study focuses on the present day and on the evolution of the heat and water budget over the Mediterranean Sea under the SRES-A1B scenario. On the contrary to previous studies, the net total heat budget is negative over the present period in all AORCMs and satisfies the heat closure budget controlled by a net positive heat gain at the strait of Gibraltar in the present climate. Under climate change scenario, some models predict a warming of the Mediterranean Sea from the ocean surface (positive net heat flux) in addition to the positive flux at the strait of Gibraltar for the 2021-2050 period. The shortwave and latent flux are increasing and the longwave and sensible fluxes are decreasing compared to the 1961-1990 period due to a reduction of the cloud cover and an increase in greenhouse gases (GHGs) and SSTs over the 2021-2050 period. The AORCMs provide a good estimates of the water budget with a drying of the region during the twenty-first century. For the ensemble mean, he decrease in precipitation and runoff is about 10 and 15% respectively and the increase in evaporation is much weaker, about 2% compared to the 1961-1990 period which confirm results obtained in recent studies. Despite a clear consistency in the trends and results between the models, this study also underlines important differences in the model set-ups, methodology and choices of some physical parameters inducing some difference in the various air-sea fluxes. An evaluation of the uncertainty sources and possible improvement for future generation of AORCMs highlights the importance of the parameterisation of the ocean albedo, rivers and cloud cover. [ABSTRACT FROM AUTHOR]

We present the Adriatic atmosphere–ocean trends and variability simulated by the kilometer-scale Adriatic Sea and Coast (AdriSC) climate model during the 1987–2017 period. As the AdriSC model has been successfully validated over the entire basin against an extensive dataset of in situ measurements and remote sensing products, the reliability of the presented results at the regional (basin-wide) and local (sub-domains) scales is high. We found that trends and variability in the atmosphere reveal strong land-sea contrasts with (1) stronger temperature trends associated with lower, mostly seasonal, variability over the Adriatic Sea than over the land and (2) positive trends of wind speed and negative trends of relative humidity associated with high, mostly seasonal, variability over the sea and vice versa over the land. While, in the ocean, the analysis highlights several processes: (1) extensive warming by the atmosphere at the surface during summer, affecting both temperature and salinity, (2) shallowing of the advection of the saline Levantine Intermediate Water inflow into the Adriatic, (3) decrease of the Adriatic deep water outflow and therefore the Adriatic-Ionian thermohaline circulation, (4) warming of near-bottom waters, in particular in the middle and northern Adriatic, and (5) shrinking and weakening of the Southern Adriatic Gyre, in particular at its center. We thus demonstrate that kilometer-scale coupled atmosphere–ocean modelling is an indispensable tool for proper quantification of climate change in complex coastal basins, as it captures local characteristics not properly reproduced by present state-of-the-art regional climate models with an order of magnitude coarser resolutions. [ABSTRACT FROM AUTHOR]

Climate change is imminent and threatens the largest watershed in the world, the Amazon basin. As general circulation models may fail to represent cloud-scale phenomena, precipitation in a changing climate under global warming is still a factor of great uncertainty, especially in Tropical regions. In this study, we used long-term high-resolution simulations from a global cloud-resolving model under the scope of the Coupled Model Intercomparison Project (CMIP6) to verify the climate change impacts on the mesoscale convective systems (MCSs) over the Amazon basin. We generated a complete spatial, temporal, and statistical characterization of the MCSs for the past (1950–1960), present (2000–2010), and near-future (2040–2050). We found that MCSs are a critical mechanism for precipitation, especially in austral winter. The simulations are consistent with the observed precipitation and MCSs patterns over the Amazon basin, indicating that MCSs are less frequent compared to the past and are expected to continuously decline in the near-future. Most decreases are projected from September to December, while an increase between June to August, mainly in the southern portion of the Amazon basin. In addition, the investigation presented here shows the great potential of using a global cloud-resolving model under the CMIP6 scope to investigate mesoscale systems in a warming climate. [ABSTRACT FROM AUTHOR]

This study looks at the evolution of trends in the dynamic sea level (DSL) component of sea-level rise for the North Atlantic (18°–67° N), primarily over the twenty-first century but with some analysis extending to 2300. We use an 18-member climate model ensemble of projections under medium and high greenhouse gas scenarios. We find that the long-term trend pattern (1950–2099) tends to be indicated in the early twenty-first century: 14 (11) of the 18 models have pattern correlations between this period and 1993–2022 of > 0.5 under the medium (high) greenhouse gas scenario. Whether a particular 1993–2022 DSL trend indicates the long-term trend in our ensemble can be assessed from concurrent changes in the Atlantic Meridional Overturning Circulation (AMOC) at 30° N: those cases with larger AMOC weakening trends have high DSL-trend pattern correlations. This suggests that the observed AMOC (or a proxy for that) could indicate whether observed DSL trends are likely to be a constraint on projections, provided suitable AMOC trend indicators can be determined. More generally, North Atlantic DSL and the AMOC show a similar evolution of measures of their successive 30-year trends (with these being projection-onto-a-pattern and the ratio with the long-term trend, respectively), both in the ensemble mean and for individual models. Model-to-model differences in this evolution indicate that the changing DSL and AMOC trends are more interconnected than solely the common influence of external forcings associated with the climate-change scenario. Model simulations extending to 2300 indicate that the twenty-first century trend patterns do not generally persist into subsequent centuries, as has been shown in previous studies. [ABSTRACT FROM AUTHOR]

The present study uses observation-based gridded air temperature and precipitation datasets to investigate the spatiotemporal changes in meteorological drought from 1981 to 2020 in South Asia (SA). The drought characteristics i.e., duration, area, frequency, intensity, and severity are calculated using Run theory and the Standardized Precipitation Evapotranspiration Index (SPEI) on annual and seasonal timescales. SA is divided into four homogeneous subregions using the k-means clustering algorithm, while the trends were estimated using Sen's Slope estimator and modified Mann-Kendall (MMK) test. A state-of-the-art Bayesian Dynamic Linear (BDL) model was employed to assess the sub-regional drought variability and their possible links with large-scale atmospheric drivers such as the Indian Ocean Dipole (IOD), El Niño Southern Oscillation (ENSO), and the Pacific Decadal Oscillation (PDO). It is found that the SA winter season experienced a significant drying long-term trend, especially southwestern and northeastern parts of SA. Drought durations show dipolar patterns with longer drought duration in the southwestern compared to the northern parts of SA. Notably, arid and semi-arid regions have shown significant drying trends in terms of their area, frequency, and severity, implying that meteorological droughts are relatively more severe in those regions. Similarly, the relationship varies over time between drought variability and climate drivers. In particular, the IOD has an impact on drought episodes over southwest SA relative to the northern parts and is mostly affected by the Sea surface temperature (SST) variability. The study results contribute to a better understanding of the meteorological drought characteristics over SA, which is important for disaster risk managers and policymakers to mitigate drought impacts. [ABSTRACT FROM AUTHOR]

Precipitation is a main part of the regional hydrological cycle, and global warming affects the hydrological cycle because regional precipitation is impacted by mechanistic changes in the hydrological cycle under global warming. This study presents an exploration of the composition variation characteristics of precipitation time series under global climate change. Twelve CMIP6 models were used to forecast precipitation changes in the Yellow River Basin (YRB). Climatic Research Unit (CRU) data were applied in the analysis of historical precipitation. Trend analysis, precipitation bias correction, and Fourier functions were used to analyze the future precipitation change characteristics. Our results showed that the IPSL-CM6A-LR and EC-Earth3-CC models had excellent performances in simulating precipitation in the YRB. Most CMIP6 models showed that precipitation under the SSP5-8.5 scenario had a higher increasing trend and was higher than that under the SSP2-4.5 scenario. The multimodel ensemble means (MEM) of CMIP6 precipitation showed that the future trend and stochastic component of precipitation had a higher degree of contribution than the historical trend and stochastic component of precipitation. However, the future periodic component of precipitation had a lower degree of contribution than the historical component. Most models showed that the degree of contribution of the periodic component of precipitation in Period IV (2015–2057) was higher than that in Period V (2058–2100). Most models showed similar degrees of contribution in Period I (1901–1938), Period II (1939–1976), and Period III (1977–2014). However, the degree of contribution of the stochastic component in 2058–2100 was lower than that in 2015–2057. This study improves the understanding of future precipitation change characteristics and provides a reference for disaster prevention and mitigation in the YRB. [ABSTRACT FROM AUTHOR]

Transitional Climate Zone (TCZ) over East Asia, characterized by semi-arid climate, is ecologically fragile environment with limited water resources, making atmospheric moisture supply being the key influential factor. This study investigates the moisture sources of summer (JJA) rainfall in the TCZ over East Asia and associated impact during 1979–2010 with the Lagrangian particle dispersion model. Seven moisture source regions and associated contribution are quantified: Eurasia continent to northwest of the TCZ (EC, 32.14%), central-eastern China (CEC, 16.62%), western Pacific Ocean (WPO, 8.58%), South China Sea and Indonesia (SCSI, 2.99%), Bay of Bengal (BOB, 1.4%), Arabian Sea (AS, 0.71%) and local evaporation (TCZ, 32.58%). The direct moisture contribution from ocean (13.67%) is much less than those from the continent (81.34%), due to the great loss en-route. In particular, the local evaporation not only contributes the most moisture among 7 selected source regions, but also exerts the greatest influence in summer precipitation variability in TCZ. Furthermore, the moisture related to summer rainfall over TCZ conveyed by westerlies and monsoon are discriminated according to the dominant system of moisture source regions. It is found that moisture contributions from summer monsoon system (30.3%) and the mid-latitude westerlies (32.14%) dominant areas are quite close. However, further analysis shows that summer monsoon system takes more responsibility for inter-annual fluctuation of summer precipitation in TCZ from the perspective of moisture supply, followed by local evaporation and mid-latitude westerlies. [ABSTRACT FROM AUTHOR]

Despite the emerging influence of anthropogenic climate change on the global water cycle, at regional scales the combination of observational uncertainty, large internal variability, and modeling uncertainty undermine robust statements regarding the human influence on precipitation. Here, we use output from global climate models in a perfect-data sense to develop a framework for conducting regional detection and attribution (D&A) for precipitation, starting with the contiguous United States (CONUS) where observational uncertainty is lower than in other regions. Our unified approach can simultaneously detect systematic trends in mean and extreme precipitation, attribute trends to anthropogenic forcings, compute the effects of forcings as a function of time, and map the effects of individual forcings. Model output is used to conduct a set of tests that yield a parsimonious representation for characterizing seasonal precipitation over the CONUS for the historical record (1900 to present day), which ensures our D&A is insensitive to structural uncertainty. Our framework is developed using synthetic data in a Pearl-causal perspective wherein causality can be identified using intervention-based simulations. While the hypothesis-based framework and accompanying generalized D&A formula we develop should be widely applicable, we include a strong caution that the hypothesis-guided simplification of the formula for the historical climatic record of CONUS as described in this paper will likely fail to hold in other geographic regions and under future warming. [ABSTRACT FROM AUTHOR]

Understanding the spatial–temporal changes in glacier mass balance and associated drivers on the Tibetan Plateau (TP) is important for predicting future water supplies and glacier-related hazards. However, the comparative study of changes in glacier mass balance in different regions of the same glacierized massif on the TP remains scarce. Combining the reconstructed detailed mass balance time-series from 1970 to 2015 for Ningchan No.1 Glacier in the eastern Qilian Mountains and Qiyi Glacier in the western Qilian Mountains using the energy and mass balance model in this work with the published mass balance data from different glaciers, we find that interannual changes in glacier mass balance are broadly similar in different regions of the Qilian Mountains. These interannual changes are primarily driven by variations in ablation-season (June–September) air temperature (Ta), which impact albedo and melt by changing snowfall and incoming longwave radiation (Lin). We link such interannual mass balance variability to the combination of changes in atmospheric circulation over Europe and changes in sea surface temperature (SST) in the Northwest Pacific during the ablation season which can cause the changes in Ta across the Qilian Mountains. In addition, we find a trend of increasingly negative glacier mass balance across the Qilian Mountains from 1970–1994 compared to 1995–2015. This interdecadal trend is driven by higher ablation-season Ta through increasing Lin and through increasing precipitation falling as rain. Lastly, higher glacier mass loss in the east than in the west Qilian Mountains from 1970–1994 and 1995–2015 was mainly caused by lower glacier area-altitude distribution, as well as a reduction in ablation-season precipitation in the eastern Qilian Mountains. [ABSTRACT FROM AUTHOR]

High-resolution rainfall information is of great value, particularly over southeastern South America (SESA) where the observed and projected climate changes pose a substantial threat to socio-economic activities and the hydrological sector. Consequently, this work focuses on the construction of an unprecedented multi-model ensemble of statistically downscaled (ESD) global climate models (GCMs) for daily precipitation. Different statistical techniques were employed - including analogs, stochastic versions of regression-based models involving neural networks and generalised linear models and linear regressions conditioned by weather types - and a variety of CMIP5 and CMIP6 models. In general, most of the models added value in the representation of the main features of daily precipitation, especially in the spatial and intra-annual variability of extremes. The statistical models were sensible to the driving GCMs, although the ESD family choice also introduced differences among the simulations. The ESD projections depicted increases in mean precipitation associated with a rising frequency of extreme events - mostly during the warm season - following the observed trends over SESA. Change rates were consistent among downscaled models up to mid-21st century, when model spread started to emerge. Furthermore, these projections were compared to the available CORDEX-CORE RCM simulations, evidencing a consistent agreement between statistical and dynamical downscaling procedures in terms of the sign of the changes, presenting the main differences in their intensity. Overall, this study evidences the potential of statistical downscaling in a changing climate and contributes to its undergoing development over SESA. [ABSTRACT FROM AUTHOR]

Extreme precipitation events are expected to increase in magnitude in response to global warming, but the magnitude of the forced response may vary considerably across distances of ~ 100 km or less. To examine the spatial variability of extreme precipitation and its sensitivity to global warming with high statistical certainty, we use a large (16,980 years), initial-condition ensemble of dynamically downscaled global climate model simulations. Under approximately 2 °C of global warming above a recent baseline period, we find large variability in the change (0 to > 60%) of the magnitude of very rare events (from 10 to 1000-year return period values of annual maxima of daily precipitation) across the western United States. Western (and predominantly windward) slopes of coastal ranges, the Cascades, and the Sierra Nevada typically show smaller increases in extreme precipitation than eastern slopes and bordering valleys and plateaus, but this pattern is less evident in the continental interior. Using the generalized extreme value shape parameter to characterize the tail of the precipitation distribution (light to heavy tail), we find that heavy tails dominate across the study region, but light tails are common on the western slopes of mountain ranges. The majority of the region shows a tendency toward heavier tails under warming, though some regions, such as plateaus of eastern Oregon and Washington, and the crest of the Sierra Nevada, show a lightening of tails. Spatially, changes in long return-period precipitation amounts appear to partially result from changes in the shape of the tail of the distribution. [ABSTRACT FROM AUTHOR]

How the value of higher-resolution climate variables dynamically downscaled can affect the hydrological impact assessment has been a long standing issue. This study investigates the potential benefit of high-resolution climate data locally tailored over South Korea in terms of the reduction of uncertainties in hydrological projections. For this purpose, a large ensemble consisting of three Global Climate Model (GCM) projections and their dynamical downscaling products in different resolutions (i.e., 20 and 5 km), and four bias correction (BC) methods is fed into a semi-distributed hydrological model (HM) customized over Korean river basins. The in-depth comparison among the 45-members hydrological simulations proves the benefit in using high-resolution Regional Climate Model (RCM) for the runoff projections. While this study acknowledges the necessity of BC to remove the systematic bias in climate simulations, it is found that the high-resolution dynamical downscaling can significantly narrow the spread brought with different BC methods, thus reducing the uncertainty in the projected hydrological change. The projected runoff changes for both the mean of wet season and the high flows indicate that there will be an intensified runoff, especially for the extremes, over South Korea under the warming. Altogether, this study provides a valuable exploration of uncertainty reduction in hydrological projections from the perspective of resolution effect of dynamical downscaling, which is meaningful for hydroclimate studies and climate change impact assessment. [ABSTRACT FROM AUTHOR]

Precipitation changes over the Tibetan Plateau (TP), "Asian Water Tower", greatly affect water resources of the surrounding countries. A dipole pattern in summer precipitation trend over the TP is observed for 1961–2013, increasing over the north TP (NTP) and decreasing over the south TP (STP). Since the TP is one of the most vulnerable regions to climate change in the world, it is of great importance to investigate the role of anthropogenic forcing in the TP precipitation changes. Moisture budget analysis based on reanalysis reveals that the precipitation trends over NTP and STP are dominated by thermodynamic and dynamic terms of vertical moisture advection, respectively. Southward shift in the summer subtropical Asian westerly jet (AWJ) over the west of TP and northward shift in AWJ over the east of TP collaboratively result in the increase and decrease in dynamic component over NTP and STP, respectively. Here, we successfully detect the anthropogenic contribution to the NTP summer precipitation trends using the attribution experiments from the CLIVAR Climate of the 20th Century Plus Project (C20C+). The drying trends over STP are mainly controlled by internal variability, and the anthropogenic forcing is favorable for the drying trends. The impacts of anthropogenic forcing are twofold. First, human activity induced warming increases the specific humidity over TP, increasing the thermodynamic component of moisture budget. Second, the warming trend caused by anthropogenic forcing is unevenly distributed over the Eurasian continent, leading to the southward (northward) shift of AWJ over the west (east) of TP, favoring more precipitation over the NTP but less precipitation over the STP. This study provides evidence of the importance of anthropogenic forcing on the water cycle changes over the TP. [ABSTRACT FROM AUTHOR]

Recent climate change in the Arctic has been rapid and dramatic, leading to numerous physical and societal consequences. Many studies have investigated these ongoing and projected future changes across a range of climatic variables, but surprisingly little attention has been paid to wind speed, despite its known importance for sea ice motion, ocean wave heights, and coastal erosion. Here we analyzed future trends in Arctic surface wind speed and its relationship with sea ice cover among CMIP5 global climate models. There is a strong anticorrelation between climatological sea ice concentration and wind speed in the early 21st-century reference climate, and the vast majority of models simulate widespread future strengthening of surface winds over the Arctic Ocean (annual multi-model mean trend of up to 0.8 m s−1 or 13%). Nearly all models produce an inverse relationship between projected changes in sea ice cover and wind speed, such that grid cells with virtually total ice loss almost always experience stronger winds. Consistent with the largest regional ice losses during autumn and winter, the greatest increases in future wind speeds are expected during these two seasons, with localized strengthening up to 23%. As in other studies, stronger surface winds cannot be attributed to tighter pressure gradients but rather to some combination of weakened atmospheric stability and reduced surface roughness as the surface warms and melts. The intermodel spread of wind speed changes, as expressed by the two most contrasting model results, appears to stem from differences in the treatment of surface roughness. [ABSTRACT FROM AUTHOR]

Extreme climate events can cause large risks to ecosystems and human society in a short period. Investigating the changing trends of such events is essential for regional climate risk management. However, there is limited information on the regional assessment of the history and future trends of extreme climate events in Xinjiang, China. This study investigated the historical changes and projected trends of extreme climate events in Xinjiang based on observational data and Coupled Model Intercomparison Project phase 6 (CMIP6) model simulations. The results showed that the bias correction effectively reduced the bias of the CMIP6 model to the extreme climate indices simulation. During the period 1961–2014, the extreme indices representing warmth showed robust growth, while the extreme indices representing cold showed a robust decline. The intensity and frequency indices of extreme precipitation continued to increase, while consecutive dry days (CDDs) shortened and consecutive wet days (CWDs) lengthened. The changing trend of the extreme temperature indices had strong spatial consistency, while the changing trend of the extreme precipitation indices had obvious spatial heterogeneity. Based on the CMIP6 model simulations, the extreme climate indices in the twenty-first century were projected to continue the changing trend of the historical period (1961–2014). Compared with north Xinjiang (NXJ) and south Xinjiang (SXJ), the cold spell duration index (CSDI), cold nights (TN10p), cold days (TX10p), and extreme precipitation events in the Tianshan Mountains (TSM) were projected to experience stronger changes in the twenty-first century. The response of extreme temperature and extreme precipitation indices to global warming was approximately linear. Compared with SSP585, most extreme climate indices under the SSP245 scenario changed slightly in response to global warming. The superposition of the increase (decrease) in extreme warm (cold) events and the increase in extreme precipitation events will exacerbate the threat of extreme climate events to the agricultural and ecological security of the Xinjiang oasis, especially in the TSM. Given the limited water vapor sources and precipitation and the high rate of evapotranspiration, it is projected that the current situation of water shortages in Xinjiang will not be fundamentally changed. [ABSTRACT FROM AUTHOR]

Under global warming, according to results obtained from offline drought indices driven by projections of general circulation models (GCMs), future droughts in China will worsen but the results are not consistent. We analyzed changes in droughts covering the entire hydrologic cycle using outputs of GCMs of the 6th Coupled Model Intercomparison Project (CMIP6) for SSP2-4.5 and SSP5-8.5 climate scenarios, and compared the results with that of popular, offline drought indices [the self-calibrating Palmer Drought Severity Index (scPDSI), Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Precipitation Actual Evapotranspiration Index (SPAEI)]. Among meteorological, agricultural, and hydrological drought indices tested under both SSP scenarios, the results obtained from SPAEI and scPDSI agree better with univariate drought indices than SPEI. scPDSI generally agrees well with agricultural droughts (Standardized Soil Moisture Index with the surface soil moisture content; SSIS). Future droughts estimated using soil moisture analysis are more widespread than that from precipitation and runoff analysis in humid regions of South China by the end of the twenty-first century. In arid northwestern China and Inner Mongolia, drought areas and severity based on scPDSI and SSIS forced with the SSP scenarios show obvious decreasing trends, in contrast to increasing trends projected in South China. Trends projected using SPEI contradict those projected by other drought indices in non-humid regions. Therefore, selecting appropriate drought indices is crucial in project representative future droughts and provides meaningful information needed to achieve effective regional drought mitigation strategies under climate warming impact. [ABSTRACT FROM AUTHOR]

Extant climate observations suggest the dry season over large parts of the Amazon Basin has become longer and drier over recent decades. However, such possible intensification of the Amazon dry season and its underlying causes are still a matter of debate. Here we used oxygen isotope ratios in tree rings (δ18OTR) from six floodplain trees from the western Amazon to assess changes in past climate. Our analysis shows that δ18OTR of these trees is negatively related to inter-annual variability of precipitation during the dry season over large parts of the Amazon Basin, consistent with a Rayleigh rainout model. Furthermore δ18OTR increases by approximately 2‰ over the last four decades (~ 1970–2014) providing evidence of an Amazon drying trend independent from satellite and in situ rainfall observations. Using a Rayleigh rainout framework, we estimate basin-wide dry season rainfall to have decreased by up to 30%. The δ18OTR record further suggests such drying trend may not be unprecedented over the past 80 years. Analysis of δ18OTR with sea surface temperatures indicates a strong role of a warming Tropical North Atlantic Ocean in driving this long-term increase in δ18OTR and decrease in dry season rainfall. [ABSTRACT FROM AUTHOR]

The cross-shelf exchange between the Yellow and East China Seas (YECS) with the Kuroshio is important for vorticity, freshwater, and effluence balances of the regional and global oceans, the responses of which to future climate changes are estimated based on Max-Planck coupled model simulations under one historical (20C, 1970–2005) and two representative concentration pathway scenarios of global warming (RCP4.5 and RCP8.5) from 2006 to 2099. The results of the 20C simulation have shown prominent cross-shelf transports in the YECS, with annual mean outflow (OVT) and inflow (IVT) volume transports across the 100 m isobath of 3.97 Sv and 2.86 Sv (1 Sv = 106 m3 s−1), respectively. These annual mean OVTs (and their equivalent IVTs) are projected to increase by 0.42 Sv and 0.48 Sv from 2006 to 2099, at rates of 11.0% and 12.8% from the 2006–2016 means, under the RCP4.5 and RCP8.5 scenarios, respectively. The maximum rates of increase are found in winter to be at 13.2% and 19.9%, respectively. Analyses suggest that the winter monsoon has a long-term southwesterly change, forcing coastal currents to flow into the Yellow Sea along the China coasts to compensate for the increase of the southeastward surface Ekman transport. Due to increases of the Tsushima Strait and upper-layer Kuroshio transports, both the OVT and IVT across the 200 m isobath have onshore changes, resulting in net onshore transport increments of 0.30 Sv and 0.57 Sv under the RCP4.5 and RCP8.5 scenarios, respectively. The enhanced cross-shelf exchanges under future warming scenarios in the YECS suggest their potential importance in carbon transportation and storage. [ABSTRACT FROM AUTHOR]

Ice sheet processes are often simplified in global climate models as changes in ice sheets have been assumed to occur over long time scales compared to ocean and atmospheric changes. However, numerous observations show an increasing rate of mass loss from the Greenland Ice Sheet and call for comprehensive process-based models to explore its role in climate change. Here, we present a new model system, EC-Earth-PISM, that includes an interactive Greenland Ice Sheet. The model is based on the EC-Earth v2.3 global climate model in which ice sheet surface processes are introduced. This model interacts with the Parallel Ice Sheet Model (PISM) without anomaly or flux corrections. Under pre-industrial climate conditions, the modeled climate and ice sheet are stable while keeping a realistic interannual variability. In model simulations forced into a warmer climate of four times the pre-industrial CO2 concentration, the total surface mass balance decreases and the ice sheet loses mass at a rate of about 500 Gt/year. In the climate warming experiments, the resulting freshwater flux from the Greenland Ice Sheet increases 55% more in the experiments with the interactive ice sheet and the climate response is significantly different: the Arctic near-surface air temperature is lower, substantially more winter sea ice covers the northern hemisphere, and the ocean circulation is weaker. Our results indicate that the melt-albedo feedback plays a key role for the response of the ice sheet and its influence on the changing climate in the Arctic. This emphasizes the importance of including interactive ice sheets in climate change projections. [ABSTRACT FROM AUTHOR]

Future changes in river discharge driven by climate change are expected to affect various water-resource sectors. In this study, we investigated the influence of climate change on streamflow in a heavy snowfall area of mountainous central Japan using hydrological model simulations driven by climate projections obtained from the d4PDF database. We projected an increase in snowmelt discharge during winter and a decrease in spring, along with a general decrease in water resources and an increase in the frequency of annual maximum daily discharge during winter because of increasing future snowmelt. Self-organizing maps (SOMs) were then applied using atmospheric data to study the linkage between streamflow and weather regime patterns (WPs) in future and present climate scenarios. The SOM analysis suggested that the impacts of climate change on streamflow varied by WP. The increase in future winter discharge was due to the strengthening of impacts of certain WPs, causing snowmelt. However, the decrease during spring could be due to changes in the predominant discharge-related WPs resulting from a decreasing snowpack. The obtained results can be useful information for considering adaptation strategies for sustainable management of water resources in heavy snowfall areas that must meet both economic and environmental demands. [ABSTRACT FROM AUTHOR]

Growing evidence indicates that the atmospheric and oceanic circulation experiences a systematic poleward shift in a warming climate. However, the complexity of the climate system, including the coupling between the ocean and the atmosphere, natural climate variability and land-sea distribution, tends to obfuscate the causal mechanism underlying the circulation shift. Here, using an idealised coupled aqua-planet model, we explore the mechanism of the shifting circulation, by isolating the contributing factors from the direct CO 2 forcing, the indirect ocean surface warming, and the wind-stress feedback from the ocean dynamics. We find that, in contrast to the direct CO 2 forcing, ocean surface warming, in particular an enhanced subtropical ocean warming, plays an important role in driving the circulation shift. This enhanced subtropical ocean warming emerges from the background Ekman convergence of surface anomalous heat in the absence of the ocean dynamical change. It expands the tropical warm water zone, causes a poleward shift of the mid-latitude temperature gradient, hence forces a corresponding shift in the atmospheric circulation and the associated wind pattern. The shift in wind, in turn drives a shift in the ocean circulation. Our simulations, despite being idealised, capture the main features of the observed climate changes, for example, the enhanced subtropical ocean warming, poleward shift of the patterns of near-surface wind, sea level pressure, storm tracks, precipitation and large-scale ocean circulation, implying that increase in greenhouse gas concentrations not only raises the temperature, but can also systematically shift the climate zones poleward. [ABSTRACT FROM AUTHOR]