Near-surface wind speed trends recorded at 67 land-based stations across Spain and Portugal for 1961–2011, also focusing on the 1979–2008 subperiod, were analyzed. Wind speed series were subjected to ...quality control, reconstruction, and homogenization using a novel procedure that incorporated the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5)-simulated series as reference. The resultant series show a slight downward trend for both 1961–2011 (−0.016 m s−1decade−1) and 1979–2008 (−0.010 m s−1decade−1). However, differences between seasons with declining values in winter and spring, and increasing trends in summer and autumn, were observed. Even though wind stilling affected 77.8% of the stations in winter and 66.7% in spring, only roughly 40% of the declining trends were statistically significant at thep< 0.10 level. On the contrary, increasing trends appeared in 51.9% of the stations in summer and 57.4% in autumn, with also around 40% of the positive trends statistically significant at thep< 0.10 level. In this article, the authors also investigated (i) the possible impact of three atmospheric indices on the observed trends and (ii) the role played by the urbanization growth in the observed decline. An accurate homogenization and assessment of the long-term trends of wind speed is crucial for many fields such as wind energy (e.g., power generation) and agriculture–hydrology (e.g., evaporative demand).
We evaluated the response of the Earth land biomes to drought by correlating a drought index with three global indicators of vegetation activity and growth: vegetation indices from satellite imagery, ...tree-ring growth series, and Aboveground Net Primary Production (ANPP) records. Arid and humid biomes are both affected by drought, and we suggest that the persistence of the water deficit (i.e., the drought time-scale) could be playing a key role in determining the sensitivity of land biomes to drought. We found that arid biomes respond to drought at short time-scales; that is, there is a rapid vegetation reaction as soon as water deficits below normal conditions occur. This may be due to the fact that plant species of arid regions have mechanisms allowing them to rapidly adapt to changing water availability. Humid biomes also respond to drought at short time-scales, but in this case the physiological mechanisms likely differ from those operating in arid biomes, as plants usually have a poor adaptability to water shortage. On the contrary, semiarid and subhumid biomes respond to drought at long time-scales, probably because plants are able to withstand water deficits, but they lack the rapid response of arid biomes to drought. These results are consistent among three vegetation parameters analyzed and across different land biomes, showing that the response of vegetation to drought depends on characteristic drought time-scales for each biome. Understanding the dominant time-scales at which drought most influences vegetation might help assessing the resistance and resilience of vegetation and improving our knowledge of vegetation vulnerability to climate change.
Accurate Computation of a Streamflow Drought Index Vicente-Serrano, Sergio M; López-Moreno, Juan I; Beguería, Santiago ...
Journal of hydrologic engineering,
02/2012, Volume:
17, Issue:
2
Journal Article
Peer reviewed
Open access
In this study, the authors investigated an approach to calculate the standardized streamflow index (SSI), which allows accurate spatial and temporal comparison of the hydrological conditions of a ...stream or set of streams. For this purpose, the capability of six three-parameter distributions (lognormal, Pearson Type III, log-logistic, general extreme value, generalized Pareto, and Weibull) and two different approaches to select the most suitable distribution the best monthly fit (BMF) and the minimum orthogonal distance (MD), were tested by using a monthly streamflow data set for the Ebro Basin (Spain). This large Mediterranean basin is characterized by high variability in the magnitude of streamflows and in seasonal regimes. The results show that the most commonly used probability distributions for flow frequency analysis provided good fits to the streamflow series. Thus, the visual inspection of the L-moment diagrams and the results of the Kolmogorov-Smirnov test did not enable the selection of a single optimum probability distribution. However, no single probability distribution for all the series was suitable for obtaining a robust standardized streamflow series because each of the distributions had one or more limitations. The BMF and MD approaches improved the results in the expected average, standard deviation, and the frequencies of extreme events of the SSI series in relation to the selection of a unique distribution for each station. The BMF and MD approaches involved using different probability distributions for each gauging station and month of the year to calculate the SSI. Both approaches are easy to apply and they provide very similar results in the quality of the obtained hydrological drought indexes. The proposed procedures are very flexible for analyses involving contrasting hydrological regimes and flow characteristics.
In this study we analyzed the influence of the El Niño‐Southern Oscillation (ENSO) phenomenon on drought severity at the global scale. A unique aspect of the analysis is that the ENSO influence was ...quantified using a multiscalar drought indicator, which allowed assessment of the role of the ENSO phases on drought types affecting various hydrological, agricultural and environmental systems. The study was based on ENSO composites corresponding to El Niño and La Niña phases, which were obtained from the winter El Niño 3.4 index for the period 1901–2006. Drought was identified in a multiscalar way using the Standardized Precipitation Evapotranspiration Index (SPEI) and the global SPEIbase data set. The study revealed the differing impacts of the El Niño and La Niña phases on drought severity, the time scales of droughts, and the period of the year when the ENSO phases explained drought variability worldwide. In large areas of America and eastern Europe the role of ENSO events were evident at the shortest time scales (1–3 months) at the beginning of events, but in areas of South Africa, Australia and Southeast Asia the effects were more obvious some months later, and at longer time scales. We also identified areas where severe drought conditions are associated with more than 70% of ENSO events. The persistence of the drought signal at longer time‐scales (e.g., 6‐ or 12‐months) is not directly determined by the atmospheric circulation response to the SST anomalies, since the SPEI anomalies will be caused by the cumulative dry conditions in some specific months. Knowledge of how these effects differ as a function of the El Niño and La Niña phases, and how they propagate throughout the drought time scales could aid in the prediction of the expected drought severity associated with the ENSO. Lags detected during the study may help forecasting of dry conditions in some regions up to one year before their occurrence.
Key Points
The first global analysis of the ENSO impact on multi‐scalar droughts
Timing of the impacts varied as a function of the time scale
Negative anomalies was much higher for El Niño events than for La Niña events
The temporal concentration of snowfalls has direct implications on the management of water resources as well as on the economic activity of mountain areas, conditioning, for example, the seasonal ...performance of ski resorts. This work uses the daily concentration index (CI) for analysing the frequency concentration of snowfalls in the Iberian Peninsula Mountain ranges. First, we provide a spatiotemporal analysis of the CI patterns and trends for the 1980–2014 period. Subsequently, we determine the atmospheric circulation patterns that control the CI variability. In addition, we determine the geographical and low‐frequency climate modes that control the CI for this mid‐latitude area. In addition, we have estimated the partial dependence relationship between the CI and several geographical factors by fitting a multiple linear regression. The results from these analyses show that elevation as well as the distance from the Atlantic are the main geographical pattern that controls the CI in the Iberian Peninsula Mountain ranges. These geographical factors also reflect the role of the main atmospheric circulation patterns in the Iberian Peninsula in controlling the spatial dynamics of the CI. The Cantabrian, Iberian, and northern slopes of the Pyrenees show the lowest CI due to their exposition to northern and Atlantic circulation weather types. On the contrary, the highest CI values are found in the southern and eastern slopes of the Pyrenees, eastern slopes of Sierra Nevada, and southern slopes of the Central system. Trend analysis shows a slight increase of CI in the Central system and in the western Sierra Nevada. However, eastern Sierra Nevada, Cantabrian, Central, and Iberian show a downward CI trend. CI is principally driven by the East‐Atlantic/Western Russia pattern and the North Atlantic Oscillation (NAO) in the Cantabrian, Iberian, and northern slopes of the Central range. The CI values in the Pyrenees show a different relationship with the Western Mediterranean Oscillation (WeMO) depending on whether it is the southern or the northern slope. In addition, the positive phase of the NAO oscillation controls the higher values of CI for the whole Pyrenees, especially in the mid‐south part. Finally, in Sierra Nevada the CI dynamics are controlled mostly by the WeMO.
The concentration index (CI) aids in understanding implications on water resources management and economic activity, such as ski resort performance. Lower CI values, associated with more regular snowfalls, are found in the Cantabrian, Iberian, and northern slopes of the Pyrenees.
In a warmer climate, significant variations in the snow regime are expected. Thus, it is crucial to better understand present‐day snow cover regime, its duration and thickness, in order to anticipate ...future changes. This work presents the first characterization of snow patterns in the Catalan Pyrenees based on 11 snow stations located in high elevation areas (>2,000 m). Here, we examine spatio‐temporal evolution of the daily snow depth and new snow height (HN) since the earliest 2000s to 2020. In addition, we analyse the different synoptic patterns that cause HN events in the study area as well as the low frequency climate modes on the different stages of the snow season. Our results show evidence that the measured snow amount differs considerably between the western and the eastern Catalan Pyrenees independently of the considered elevation. While the eastern part has an average seasonal cumulative HN of 278 cm, the western sector gets almost twice (433 cm). Nonetheless, the onset of the snow melting does not show substantial differences, being primarily ruled by the elevation in both areas. The longest snow records (Núria, 1971 m) point to an increase of HN from 1985 to 2020, a trend which is also observed in most stations from 2000 to 2020. Nevertheless, some stations of the N western fringe record negative trends associated with the low frequency variability of the Western Mediterranean Oscillation (WeMO). Results also indicate that the NW Atlantic low‐pressure systems are the circulation weather types that provide more abundant HN in the majority of snow stations. The Atlantic advections are more frequent in autumn and winter, while the Mediterranean advections provide more intense and recurrent HN in spring. The atmospheric circulation is basically ruled by the East Atlantic/West Russia and the WeMO teleconnection patterns.
This work presents the first characterization of snow patterns in high elevation areas (>2,000 m) of the Catalan (SE) Pyrenees. We analyse the different synoptic patterns that cause new snow height events as well as the impact of the modes of low frequency climate. The longest snow records point to an increase of new snow height (from 1985 to 2020). Nevertheless, some stations of the N western fringe record negative trends associated with the frequency variability of the circulation weather types.
Abstract
In this study, the authors provide a global assessment of the performance of different drought indices for monitoring drought impacts on several hydrological, agricultural, and ecological ...response variables. For this purpose, they compare the performance of several drought indices the standardized precipitation index (SPI); four versions of the Palmer drought severity index (PDSI); and the standardized precipitation evapotranspiration index (SPEI) to predict changes in streamflow, soil moisture, forest growth, and crop yield. The authors found a superior capability of the SPEI and the SPI drought indices, which are calculated on different time scales than the Palmer indices to capture the drought impacts on the aforementioned hydrological, agricultural, and ecological variables. They detected small differences in the comparative performance of the SPI and the SPEI indices, but the SPEI was the drought index that best captured the responses of the assessed variables to drought in summer, the season in which more drought-related impacts are recorded and in which drought monitoring is critical. Hence, the SPEI shows improved capability to identify drought impacts as compared with the SPI. In conclusion, it seems reasonable to recommend the use of the SPEI if the responses of the variables of interest to drought are not known a priori.
Snow patterns in ice-free areas of Greenland play important roles in ecosystems. Within a changing climate, a comprehensive understanding of the snow responses to climate change is of interest to ...anticipate forthcoming dynamics in these areas. In this study, we analyze the future snowpack evolution of a polar maritime Arctic location, Qeqertarsuaq (Disko Island, Central-Western Greenland). A physically-based snow model (FSM2) is validated and forced with CMIP6 projections for SSP2–4.5 and SSP5–8.5 greenhouse gasses emission scenarios, using two models: CanESM5 and MIROC6. The future snowpack evolution is assessed through four key seasonal (October to May) snow climate indicators: snow depth, snow days, snowfall fraction and ablation rate. Comparison against the observed air temperature for the reference climate period demonstrates superior accuracies for MIROC6 SSP2.4–5, with anomalies at 19 %, compared to CanESM5 SSP5.8–5 (25 %) and CanESM5 SSP2.4–5 (78 %). In terms of precipitation, CanESM5 SSP2.4–5 and SSP2.4–5 exhibit smaller anomalies against the observed data (5 %) in contrast to MIROC6 SSP2.4–5 (15 %) and MIROC6 SSP2.8–5 (17 %). Results demonstrate distinct snowpack responses to climate change depending on the model and emission scenario. For CanESM5, seasonal snow depth anomalies with respect to the reference period range from – 38 % (SSP2–4.5, 2040–2050 period) to – 74 % (SSP5–8.5, 2090–2100 period). MIROC6 projects lower snowpack reductions, with a decrease ranging from – 38 % (SSP2–4.5, 2040–2050 period) to – 57 % (SSP5–8.5, 2090–2100 period). Similar reductions are anticipated for snowfall and snow days. Changes in the snowpack evolution are primarily driven by positive trends in downwelling longwave radiation and air temperature. The projected increase in precipitation by the mid to late 21st century will lead to more frequent rain-on-snow events, intensifying snowpack melting. These findings help enhance the comprehension of future snow dynamics in the ice-free zones of Greenland, as well as the associated hydrological and ecological changes.
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•CMIP6 projections anticipate significant reductions in snowpack.•MIROC6 projected winter snowfall increases for SSPS4–8.5 scenario.•Snow reductions are driven by temperature and downwelling longwave radiation.•Snow cover depletion has a key impact on hydrological and ecological system.
ABSTRACT
In this study we analysed the spatial distribution of the long‐term average and interannual variability of the number of snow days (NSD) and the number of precipitation days (NPD) in winter ...(DJFM) in the Spanish Pyrenees, using data from 38 meteorological stations for the period 1981–2010. The interannual variability of the NSD and the NPD in winter was related to the frequency of weather types over the Iberian Peninsula. Data from six stations were also used to analyse a longer time period (1961–2013) to confirm the consistency of the results obtained during the main study period (1981–2010).
The results indicated that the NPD is only influenced by the distance to sea whereas the NSD is determined by elevation and distance to the sea. A high frequency of west (W), northwest (NW) and cyclonic (C) weather systems led to a high NPD in winter across the entire study area, whereas the frequency of north (N) weather types was only correlated with the NPD at the most westerly stations. For the NSD there was a gradient from the Western Pyrenees to eastern areas, mainly explained by the frequency of N weather types in the former area, and high frequencies of NW and W weather types associated with the latter. For most stations there was no significant trend found in the NPD or the NSD for the 1981–2010 period. However, a slight decrease was found for stations strongly correlated with NW weather types, and a slight increase was found for stations strongly correlated with the C weather type, which was related to a decreasing (increasing) frequency of NW (C) weather types during the same period. Analysis of the 1961–2013 and 1971–2000 time slices using a smaller subset of stations revealed a similar relationship between weather types and the NSD. This indicates that the 1981–2010 period is sufficiently representative to describe the relationship of the NSD and the NPD to weather type frequency. However, the study period chosen can markedly influence the trends observed, as the results showed a statistically significant decrease in the NSD for the 1971–2000 period, but no significant trends for the 1961–2013 and 1980–2010 periods.
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