Trend In Winter Precipitation Research Articles

Assessment of long-term historical trends in winter precipitation in Japan using large-ensemble climate simulations: Changes in the impact of southern coastal cyclones

Assessment of long-term historical trends in winter precipitation in Japan using large-ensemble climate simulations: Changes in the impact of southern coastal cyclones

The Importance of Accounting for the North Atlantic Oscillation When Applying Observational Constraints to European Climate Projections

AbstractVariability in the North Atlantic Oscillation (NAO) has contributed to the recent multidecadal trends observed in European climate, especially to trends in winter precipitation over Northern Europe. However, the current generation of coupled climate models struggle to reproduce the NAO's contribution to multidecadal trends, which has important implications for deriving constraints based on the comparison of observed and modeled trends. An observational constraint based on attribution results, both with and without the contribution of variability associated with the NAO, is applied to projections of Northern European precipitation and temperature, and observed NAO variability is shown to lead to a constraint that overestimates future forced changes. Only after removing the NAO variability is the observed climate change consistent with model simulations, and a tighter, unbiased observational constraint based on the forced signal (without the NAO) can be applied to future projections.

The Role of the North Atlantic Oscillation for Projections of Winter Mean Precipitation in Europe

AbstractClimate models generally project an increase in the winter North Atlantic Oscillation (NAO) index under a future high‐emissions scenario, alongside an increase in winter precipitation in northern Europe and a decrease in southern Europe. The extent to which future forced NAO trends are important for European winter precipitation trends and their uncertainty remains unclear. We show using the Multimodel Large Ensemble Archive that the NAO plays a small role in northern European mean winter precipitation projections for 2080–2099. Conversely, half of the model uncertainty in southern European mean winter precipitation projections is potentially reducible through improved understanding of the NAO projections. Extreme positive NAO winters increase in frequency in most models as a consequence of mean NAO changes. These extremes also have more severe future precipitation impacts, largely because of mean precipitation changes. This has implications for future resilience to extreme positive NAO winters, which frequently have severe societal impacts.

Observed and predicted precipitation variability across Pakistan with special focus on winter and pre-monsoon precipitation.

This study utilises ground, satellite and model data to investigate the observed and future precipitation changes in Pakistan. Pakistan Meteorological Department's (PMD) monthly precipitation data set along with the Tropical Rainfall Measuring Mission (TRMM) monthly dataset TRMM_3B43 (0.25° × 0.25° resolution) and European Centre for Medium-Range Weather Forecasts's (ECMWF) monthly reanalysis product ERA5 have been used to evaluate rainfall trends over the climatic zones of Pakistan through Mann-Kendall test, Sen's slope estimator and innovative trend analysis for the time period 1978-2018. Community Climate System Model (CCSM4) projections have been employed to explore the projected changes in precipitation until 2099. Furthermore, TRMM and CCSM4 projections have been correlated and validated using root mean square error (RMSE) and mean bias error (MBE). There is a good correlation between TRMM and PMD ground observation at all stations of the country for all seasons, with correlation coefficient values ranging from 0.89 (November) to 0.97 (July and August). However, ERA5 monthly precipitation tends to overestimate rainfall in the winter months. The study shows a decreasing trend in winter precipitation in all zones of the country with a significant decrease over western mountains, i.e. zone C of the country. During 2008-2018, a sharp decrease in winter precipitation is observed as compared to the baseline value of 1978-2007 in all climatic zones. Rainy days have also shown a decrease in winter and pre-monsoon seasons. There seems to be a shift in precipitation from winter towards pre-monsoon season as pre-monsoon precipitation in the last 11years increased in all zones except for zone C. Coherently, there is a decrease in an area affected by winter precipitation and an increase in area for pre-monsoon precipitation. Future precipitation estimates from the CCSM4 model for RCP 4.5 and RCP 8.5 overestimate precipitation in most parts of the country for the first 9 observed years (2010-2018) and predict a rise in precipitation by 2099 which is more pronounced in the northern and western Pakistan while a decrease is predicted for the plains of the country, which might have negative consequences for agriculture.

Change in Precipitation over the Tibetan Plateau Projected by Weighted CMIP6 Models

Precipitation over the Tibetan Plateau (TP) is important to local and downstream ecosystems. Based on a weighting method considering model skill and independence, changes in the TP precipitation for near-term (2021–40), mid-term (2041–60) and long-term (2081–2100) under shared socio-economic pathways (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSSP3-7.0, SSP5-8.5) are projected with 27 models from the latest Sixth Phase of the Couple Model Intercomparison Project. The annual mean precipitation is projected to increase by 7.4%–21.6% under five SSPs with a stronger change in the northern TP by the end of the 21st century relative to the present climatology. Changes in the TP precipitation at seasonal scales show a similar moistening trend to that of annual mean precipitation, except for the drying trend in winter precipitation along the southern edges of the TP.Weighting generally suggests a slightly stronger increase in TP precipitation with reduced model uncertainty compared to equally-weighted projections. The effect of weighting exhibits spatial and seasonal differences. Seasonally, weighting leads to a prevailing enhancement of increase in spring precipitation over the TP. Spatially, the influence of weighting is more remarkable over the northwestern TP regarding the annual, summer and autumn precipitation. Differences between weighted and original MMEs can give us more confidence in a stronger increase in precipitation over the TP, especially for the season of spring and the region of the northwestern TP, which requires additional attention in decision making.

The Mesoscale Response to Global Warming over the Pacific Northwest Evaluated Using a Regional Climate Model Ensemble

AbstractThis paper describes the downscaling of an ensemble of 12 general circulation models (GCMs) using the Weather Research and Forecasting (WRF) Model at 12-km grid spacing over the period 1970–2099, examining the mesoscale impacts of global warming as well as the uncertainties in its mesoscale expression. The RCP8.5 emissions scenario was used to drive both global and regional climate models. The regional climate modeling system reduced bias and improved realism for a historical period, in contrast to substantial errors for the GCM simulations driven by lack of resolution. The regional climate ensemble indicated several mesoscale responses to global warming that were not apparent in the global model simulations, such as enhanced continental interior warming during both winter and summer as well as increasing winter precipitation trends over the windward slopes of regional terrain, with declining trends to the lee of major barriers. During summer there is general drying, except to the east of the Cascades. The 1 April snowpack declines are large over the lower-to-middle slopes of regional terrain, with small snowpack increases over the lower elevations of the interior. Snow-albedo feedbacks are very different between GCM and RCM projections, with the GCMs producing large, unphysical areas of snowpack loss and enhanced warming. Daily average winds change little under global warming, but maximum easterly winds decline modestly, driven by a preferential sea level pressure decline over the continental interior. Although temperatures warm continuously over the domain after approximately 2010, with slight acceleration over time, occurrences of temperature extremes increase rapidly during the second half of the twenty-first century.Significance StatementThis paper provides a unique high-resolution view of projected climate change over the Pacific Northwest and does so using an ensemble of regional climate models, affording a look at the uncertainties in local impacts of global warming. The paper examines regional meteorological processes influenced by global warming and provides guidance for adaptation and preparation.

The inherent uncertainty of precipitation variability, trends, and extremes due to internal variability, with implications for Western US water resources

AbstractThe approximately century-long instrumental record of precipitation over land reflects a single sampling of internal variability. Thus, the spatiotemporal evolution of the observations is only one realization of `what could have occurred' given the same climate system and boundary conditions, but different initial conditions. While climate models can be used to produce initial-condition large ensembles that explicitly sample different sequences of internal variability, an analogous approach is not possible for the real world. Here, we explore the use of a statistical model for monthly precipitation to generate synthetic ensembles based on a single record. When tested within the context of the NCAR Community Earth System Model version 1 Large Ensemble (CESM1-LE), we find that the synthetic ensemble can closely reproduce the spatiotemporal statistics of variability and trends in winter precipitation over the extended contiguous United States, and that it is difficult to infer the climate change signal in a single record given the magnitude of the variability. We additionally create a synthetic ensemble based on the Global Precipitation Climatology Centre (GPCC) dataset, termed the GPCC-synth-LE; comparison of the GPCC-synth-LE with the CESM1-based ensembles reveals differences in the spatial structures and magnitudes of variability, highlighting the advantages of an observationally-based ensemble. We finally use the GPCC-synth-LE to analyze three water resource metrics in the Upper Colorado River Basin: frequency of dry, wet, and whiplash years. Thirty-one year ‘climatologies’ in the GPCC-synth-LE can differ by over 20% in these key water resource metrics due to sampling of internal variability, and individual ensemble members in the GPCC-synth-LE can exhibit large near-monotonic trends over the course of the last century due to sampling of variability alone.

Drivers of Twenty-First Century U.S. Winter Precipitation Trends in CMIP6 Models: A Storyline-Based Approach

AbstractClimate change during the twenty-first century has the potential to substantially alter geographic patterns of precipitation. However, regional precipitation changes can be very difficult to project, and in some regions, global climate models do not even agree on the sign of the precipitation trend. Since some of this uncertainty is due to internal variability rather than model bias, models cannot be used to narrow the possibilities to a single outcome, but they can usefully quantify the range of plausible outcomes and identify the combination of dynamical drivers that would be likely to produce each.This study uses a storylines approach—a type of regression-based analysis—to identify some of the key dynamical drivers that explain the variance in 21st century U.S. winter precipitation trends across CMIP6 models under the SSP3-7.0 emissions scenario. This analysis shows that the spread in precipitation trends is not primarily driven by differences in modeled climate sensitivity. Key drivers include global-mean surface temperature, but also tropical upper-troposphere temperature, the El Niño-Southern Oscillation (ENSO), the Pacific-North America (PNA) pattern, and the East Pacific (EP) dipole (a dipole pattern in geopotential heights over North America’s Pacific coast). Combinations of these drivers can reinforce or cancel to produce various high- or low-impact scenarios for winter precipitation trends in various regions of the United States. For example, the most extreme winter precipitation trends in the southwestern U.S. result from opposite trends in ENSO and EP, whereas the wettest winter precipitation trends in the midwestern U.S. result from a combination of strong global warming and a negative PNA trend.

Spatial Variability in Seasonal Snowpack Trends across the Rio Grande Headwaters (1984–2017)

AbstractThis study evaluated the spatial variability of trends in simulated snowpack properties across the Rio Grande headwaters of Colorado using the SnowModel snow evolution modeling system. SnowModel simulations were performed using a grid resolution of 100 m and 3-hourly time step over a 34-yr period (1984–2017). Atmospheric forcing was provided by phase 2 of the North American Land Data Assimilation System, and the simulations accounted for temporal changes in forest canopy from bark beetle and wildfire disturbances. Annual summary values of simulated snowpack properties [snow metrics; e.g., peak snow water equivalent (SWE), snowmelt rate and timing, and snow sublimation] were used to compute trends across the domain. Trends in simulated snow metrics varied depending on elevation, aspect, and land cover. Statistically significant trends did not occur evenly within the basin, and some areas were more sensitive than others. In addition, there were distinct trend differences between the different snow metrics. Upward trends in mean winter air temperature were 0.3°C decade−1, and downward trends in winter precipitation were −52 mm decade−1. Middle elevation zones, coincident with the greatest volumetric snow water storage, exhibited the greatest sensitivity to changes in peak SWE and snowmelt rate. Across the Rio Grande headwaters, snowmelt rates decreased by 20% decade−1, peak SWE decreased by 14% decade−1, and total snowmelt quantity decreased by 13% decade−1. These snow trends are in general agreement with widespread snow declines that have been reported for this region. This study further quantifies these snow declines and provides trend information for additional snow variables across a greater spatial coverage at finer spatial resolution.

Predictive Skill and Predictable Patterns of the U.S. Seasonal Precipitation in CFSv2 Reforecasts of 60 Years (1958–2017)

Abstract Analyzing a set of ensemble seasonal reforecasts for 1958–2017 using CFSv2, we evaluate the predictive skill of the U.S. seasonal mean precipitation and examine its sources of predictability. Our analysis is for each of the three periods of 1958–78, 1979–99, and 2000–17, corresponding to the positive phase of the Pacific decadal oscillation (PDO) during 1979–99 and negative ones before and after. The ensemble reforecasts at two-month lead reproduce the spatial distribution of winter precipitation trends throughout the 60 years and the continental-scale increase of summer precipitation since 2000. The predicted signal-to-noise (S/N) ratio also reveals greater predictability in the post-1979 period than during 1958–78. A maximized S/N ratio EOF analysis is applied to the ensemble seasonal precipitation predictions. In winter and spring, the most predictable patterns feature a north–south dipole throughout United States. The summer and fall patterns are dominated by the anomalies in central and southern United States, respectively. In verification with observations, the winter–spring patterns are more skillful. ENSO influences on these predictable patterns are most dominant in winter and spring, but other oceanic factors also play an active role during summer and fall. The multidecadal change of the U.S. precipitation predictability is attributable to the low-frequency modulation of the ENSO predictability and the influences of other major climate modes. PDO can be a dominant factor associated with enhanced prediction skill in 1979–99 and reduced skill in 1958–78. Since the 2000s, the forcing from the SST anomalies in the tropical North Atlantic with opposite sign to those in the tropical Pacific becomes a significant factor for the U.S. summer precipitation prediction.

Precipitation Variations under a Changing Climate from 1961–2015 in the Source Region of the Indus River

The source region of the Indus River (SRIR), which is located in the Hindukush, Karakoram and Himalayan (HKH) mountainous range and on the Third Pole (TP), is very sensitive to climate change, especially precipitation changes, because of its multifarious orography and fragile ecosystem. Climate changes in the SRIR also have important impacts on social and economic development, as well as on the ecosystems of the downstream irrigation areas in Pakistan. This paper investigates the changes in precipitation characteristics by dividing the daily precipitation rate into different classes, such as light (0–10 mm), moderate (10.1–25 mm) and heavy precipitation (>25 mm). Daily precipitation data from gauging and non-gauging stations from 1961–2015 are used. The results of the analysis of the annual precipitation and rainy day trends show significant (p < 0.05) increases and decreases, respectively, while light and heavy precipitation show significant decreasing and increasing trends, respectively. The analysis of the precipitation characteristics shows that light precipitation has the highest number of rainy days compared to moderate or heavy precipitation. The analysis of the seasonal precipitation trends shows that only 18 stations have significant increasing trends in winter precipitation, while 27 stations have significant increasing trends in summer precipitation. Both short and long droughts exhibit increasing trends, which indicates that the Indus Basin will suffer from water shortages for agriculture. The results of this study could help policymakers cope with floods and droughts and sustain eco-environmental resources in the study area.

Climate Variability and Change of Mediterranean-Type Climates

AbstractMediterranean-type climates are defined by temperate, wet winters, and hot or warm dry summers and exist at the western edges of five continents in locations determined by the geography of winter storm tracks and summer subtropical anticyclones. The climatology, variability, and long-term changes in winter precipitation in Mediterranean-type climates, and the mechanisms for model-projected near-term future change, are analyzed. Despite commonalities in terms of location in the context of planetary-scale dynamics, the causes of variability are distinct across the regions. Internal atmospheric variability is the dominant source of winter precipitation variability in all Mediterranean-type climate regions, but only in the Mediterranean is this clearly related to annular mode variability. Ocean forcing of variability is a notable influence only for California and Chile. As a consequence, potential predictability of winter precipitation variability in the regions is low. In all regions, the trend in winter precipitation since 1901 is similar to that which arises as a response to changes in external forcing in the models participating in phase 5 of the Coupled Model Intercomparison Project. All Mediterranean-type climate regions, except in North America, have dried and the models project further drying over coming decades. In the Northern Hemisphere, dynamical processes are responsible: development of a winter ridge over the Mediterranean that suppresses precipitation and of a trough west of the North American west coast that shifts the Pacific storm track equatorward. In the Southern Hemisphere, mixed dynamic–thermodynamic changes are important that place a minimum in vertically integrated water vapor change at the coast and enhance zonal dry advection into Mediterranean-type climate regions inland.

Human Influence on Winter Precipitation Trends (1921–2015) over North America and Eurasia Revealed by Dynamical Adjustment

AbstractDetecting and attributing a human influence on observed rainfall trends is a major challenge due to the presence of large amplitude internal variability on all time scales and by limited temporal and spatial data coverage. Here we apply a “dynamical adjustment” methodology to a gridded archive of monthly precipitation to estimate an anthropogenic influence on long‐term (1920–2015) trends over North America and Eurasia during winter (November–March). This empirical approach aims to remove atmospheric circulation influences from precipitation variability and trends, thereby revealing the thermodynamically induced component as a residual. The geographical pattern and amplitude of this observed thermodynamic residual precipitation trend are in good agreement with anthropogenically forced trends obtained from ensembles of historical climate model simulations. Such consistency helps to reconcile observations and models and provides compelling evidence for a human influence on century‐scale precipitation trends over North America and Eurasia during the cold season.

On the Causes of Declining Colorado River Streamflows

AbstractThe Colorado River is the primary surface water resource in the rapidly growing U.S. Southwest. Over the period 1916–2014, the Upper Colorado River Basin naturalized streamflow declined by 16.5%, despite the fact that annual precipitation in the UCRB over that period increased slightly (+1.4%). In order to examine the causes of the runoff declines, we performed a set of experiments with the Variable Infiltration Capacity hydrology model. Our results show that the pervasive warming has reduced snowpacks and enhanced evapotranspiration over the last 100 years; over half (53%) of the long‐term decreasing runoff trend is associated with the general warming. Negative winter precipitation trends have occurred in the handful of highly productive subbasins that account for over half of the streamflow at Lee's Ferry. We also compared a midcentury drought with the (ongoing) post‐Millennium Drought and find that whereas the earlier drought was caused primarily by pervasive low‐precipitation anomalies across UCRB, higher temperatures have played a large role in the post‐Millennium Drought. The post‐Millennium Drought has also been exacerbated by negative precipitation anomalies in several of the most productive headwater basins. Finally, we evaluate the UCRB April–July runoff forecast for 2017, which decreased dramatically as the runoff season progressed. We find that while late winter and spring 2017 was anomalously warm, the proximate cause of most of the forecast reduction was anomalous late winter and early spring dryness in UCRB, which followed exceptionally large (positive) early winter precipitation anomalies.

Internal Variability and Regional Climate Trends in an Observational Large Ensemble

Recent observed climate trends result from a combination of external radiative forcing and internally generated variability. To better contextualize these trends and forecast future ones, it is necessary to properly model the spatiotemporal properties of the internal variability. Here, a statistical model is developed for terrestrial temperature and precipitation, and global sea level pressure, based upon monthly gridded observational datasets that span 1921–2014. The model is used to generate a synthetic ensemble, each member of which has a unique sequence of internal variability but with statistical properties similar to the observational record. This synthetic ensemble is combined with estimates of the externally forced response from climate models to produce an observational large ensemble (OBS-LE). The 1000 members of the OBS-LE display considerable diversity in their 50-yr regional climate trends, indicative of the importance of internal variability on multidecadal time scales. For example, unforced atmospheric circulation trends associated with the northern annular mode can induce winter temperature trends over Eurasia that are comparable in magnitude to the forced trend over the past 50 years. Similarly, the contribution of internal variability to winter precipitation trends is large across most of the globe, leading to substantial regional uncertainties in the amplitude and, in some cases, the sign of the 50-yr trend. The OBS-LE provides a real-world counterpart to initial-condition model ensembles. The approach could be expanded to using paleo-proxy data to simulate longer-term variability.

Temporal Change and Flow Velocity Estimation of Patseo Glacier, Western Himalaya, India

In the present study we estimate the velocity and thickness of the Patseo glacier, Himachal Pradesh, India. The average velocity of the glacier was estimated as similar to 5.47 m/year using co-registration of optically sensed images and correlation (COSI-Corr) method. The glacier thickness was found to vary between 12 and 278 m, with an average value 59 m. The total glacier ice volume was estimated as similar to 15.8 x 10(7) m(3), with equivalent water reservoir of similar to 14.5 x 10(7) m(3). Ground penetrating radar (GPR) surveys were conducted during 2004 and 2013 for validation of the estimated glacier thickness. The glacier thickness estimated using COSI-Corr method was found to be in agreement with GPR-retrieved glacier thickness (RMSE = 4.75 m; MAE = 3.74 m). The GPR profiles collected along the same geographic locations on the glacier during 2004 and 2013 showed a reduction in ice thickness of similar to 1.89 m, and thus resulting in an annual ice thickness decrease of similar to 0.21 m. The glacier area was estimated for 2004 and 2013 using LISS IV satellite data and found to be similar to 2.52 and similar to 2.30 sq. km respectively. This shows an annual reduction of similar to 0.024 sq. km in glacier area. The total annual loss in glacier ice volume was estimated as similar to 4.55 x 10(5) m(3). This loss in the glacier ice volume of the Patseo glacier is supported by the snow and meteorological observations collected at a nearby field observatory of Snow and Avalanche Study Establishment (SASE). The climate data collected at SASE meteorological observatory at Patseo (3800 m), between 1993-94 and 2014-15 showed an increasing trend in the mean annual temperature and a decreasing trend in winter precipitation.

Evaluation of precipitation trends from high-resolution satellite precipitation products over Mainland China

Many studies have reported the excellent ability of high-resolution satellite precipitation products (0.25° or finer) to capture the spatial distribution of precipitation. However, it is not known whether the precipitation trends derived from them are reliable. For the first time, we have evaluated the annual and seasonal precipitation trends from two typical sources of high-resolution satellite-gauge products, TRMM 3B43 and PERSIANN-CDR, using rain gauge observations over China, and they were also compared with those from gauge-only products (0.25° and 0.5° precipitation products, hereafter called CN25 and CN50). The evaluation focused mainly on the magnitude, significance, sign, and relative order of the precipitation trends, and was conducted at gridded and regional scales. The following results were obtained: (1) at the gridded scale, neither satellite-gauge products precisely measure the magnitude of precipitation trends but they do reproduce their sign and relative order; regarding capturing the significance of trends, they exhibit relatively acceptable performance only over regions with a sufficient amount of significant precipitation trends; (2) at the regional scale, both satellite-gauge products generally provide reliable precipitation trends, although they do not reproduce the magnitude of trends in winter precipitation; and (3) overall, CN50 and TRMM 3B43 outperform others in reproducing all four aspects of the precipitation trends. Compared with CN25, PERSIANN-CDR performs better in determining the magnitude of precipitation trends but marginally worse in reproducing their sign and relative order; moreover, both of them are at a level in capturing the significance of precipitation trends.

Evolution of two cirque glaciers in Lombardy and their relation to climatic factors (1962–2016)

ABSTRACTIn order to assess the climate–glacier relationship in the Southern European Alps, two small glaciers in Lombardy, Suretta Sud and Lupo, have been chosen for investigation. GPS profiling in 2016 allowed the determination of elevation changes since 2007 and thus the determination of the glacier mass balance using the geodetic method. Older maps have been digitized to reconstruct mass changes back to 1962. The two glaciers react synchronously and show overall mass losses, but the narrower observation pattern at Suretta Sud reveals positive mass changes from 1970 to 1982. Long-term meteorological series of precipitation and air temperature of representative stations have been analysed, they show highly significant warming trends of 0.32–0.40°C per decade during summer, but no significant trend in winter precipitation. Since 2009/2010, annual mass balance measurements applying the glaciological method were undertaken by the Servizio Glaciologico Lombardo. These annual observations reveal that, despite the decadal mass loss observed by geodetic observations, years with positive mass changes still occur. These years showed below average winter precipitation and below average summer temperatures, indicating that glacier behaviour is influenced by both parameters. Ice thicknesses observed by echo radio sounding allow to calculate glacier volume and the bedrock topography. Maximum ice thicknesses are around 40 m and the cirques are not overdeepened by glacial erosion. Using very simple extrapolations of observed rates of downwasting results in theoretical life expectancies of these glacierets of 50–70 yr.

Hydro-climatological changes in the Colorado River Basin over a century

ABSTRACTThis study evaluates changes in streamflow, temperature and precipitation over a time span of 105 years (1906–2010) in the Colorado River Basin (CRB). Monthly precipitation and temperature data for 29 climate divisions, and streamflow data for 29 naturalized gauges were analyzed. Two variations of the Mann-Kendall test, considering lag-1 auto correlation and long-term persistence, and the Pettitt test were employed to assess trends and shifts, respectively. Results indicated that streamflow increased during the winter–spring months and decreased during the summer– autumn period. Decreasing trends in winter precipitation were identified over snow-dominated regions in the upper basin. Significant increases in temperature were detected over several months. Major shifts were noticed in 1964, 1968 and in the late 1920s. Increasing temperature while decreasing streamflow and precipitation were noticed after major shifts in the 1930s, and these shifts coincided with coupled phases of El Niño Southern Oscillation and Pacific Decadal Oscillation.EDITOR A. Castellarin; ASSOCIATE EDITOR R. Hirsch

Potential links between the North Atlantic Oscillation and decreasing precipitation and runoff on a Mediterranean area

In the Mediterranean region, the reduction in precipitation and warmer temperatures is generating a desertification process, with dramatic consequences for both agriculture and the sustainability of water resources. On the island of Sardinia (Italy), the decrease in runoff impacts the management of water resources, resulting in water supply restrictions even for domestic consumption. In the 10 Sardinian basins with a longer database (at least 40 complete years of data, including data from the past 10years), runoff decreased drastically over the 1975–2010 period, with mean yearly runoff reduced by more than 40% compared to the previous 1922–1974 period. Trends in yearly runoff are negative, with Mann-Kendall τ values ranging from −0.39 to −0.2. Decreasing winter precipitation over the 1975–2010 period everywhere on Sardinia island has led to these decreases in runoff, as most yearly runoff in the Sardinian basins (70% on average) is produced by winter precipitation due to the seasonality typical of the Mediterranean climate regime. The trend in winter precipitation is not homogenous; the negative trend is higher (around −0.25) on the west Sardinian coast, becoming lower across the island toward the east coast (around −0.14). Winter precipitation is highly correlated with the North Atlantic Oscillation (NAO), a weather phenomenon in the North Atlantic Ocean that controls the direction and strength of westerly winds and storm tracks into Europe. High negative correlations (up to −0.45) between winter NAO index and winter precipitation are estimated along the west coast. Meanwhile, these correlations decrease east across the island toward the high mountain in the center of Sardinia, reaching the lowest values along the east coast (about −0.25). The generally decreasing correlation between winter NAO index and winter precipitation in the longitudinal direction (from the North Atlantic dipole to the east) here accelerates due to local-scale orographic effects that overlap the large-scale NAO impact on the winter precipitation regime, thus softening the precipitation reduction due to the NAO. Such local topographic effects that may attenuate large-scale climate change effects must be considered in water resource planning and management alongside such climate change effects related to large-scale circulations, such as NAO.