Precipitation Variability and Probabilities of Extreme Events in the Eastern Mediterranean Region (Latakia Governorate-Syria as a Case Study)

This study aimed at analysis of the general-index change for the mean annual and seasonal precipitation in six stations in Latakia Governorate (Syria). The data of precipitation were collected for 40 consecutive years (1970–2010) in order to figure out the extent of the changes and variability in precipitation rates and the impact of this change on changes in the potential density that might cause extremely high or low precipitation rates according to Gumbel distribution of the extreme precipitation rates. Results revealed a decrease of the annual precipitation rates in all stations, the reduction in precipitation ranged from 46 to 210 mm during the whole period of the study. Spring, however, recorded the highest and statistically significant reduction, which reached 46–210 mm, while winter precipitation increased by 21–82 mm. Spring also has witnessed a decrease of about 3–9% of the total annual precipitation as compared to winter precipitation which increased by 5–8% of the total. The potential density of extremely high winter precipitation rates increased in all stations as indicated from Gumbel distribution in winter, and a greater increase took place in the probabilities of occurrence of the extremely low spring precipitation rates. This shows significant probability of occurrence of drought during spring season. By contrast, probabilities of winter precipitation rates increased more, thus winter is relatively more humid than before and spring is relatively drier than before.

Potential influence of a planned landfill on a high karst plateau in Southwestern Montenegro to nearby karstic springs

The potential threat of a landfill projected on a high karst plateau in southwest Montenegro is investigated with respect to the subjacent nearby springs. The locality is called Duboki do. As the springs are used for drinking water supply this investigation is urgently needed. For the springs exist two hypotheses concerning their catchment area: I) from the high karst plateau, or II) from a topographically lower area. The stable H- and O-isotope ratios of water samples from the springs are compared with precipitation isotope data, to reveal the catchment area of the springs. The isotope results indicate that the catchment area of the springs is at higher altitude fitting to, and in good agreement with, winter precipitation from the high karst plateau of the planned land-fill locality.

Hydrometeor Classification of Winter Precipitation in Northern China Based on Multi-Platform Radar Observation System

Hydrometeor classification remains a challenge in winter precipitation cloud systems. To address this issue, 42 snowfall events were investigated based on a multi-platform radar observation system (i.e., X-band dual-polarization radar, Ka-band millimeter wave cloud radar, microwave radiometer, airborne equipment, etc.) in the mountainous region of northern China from 2016 to 2020. A fuzzy logic classification method is proposed to identify the particle phases, and the retrieval result was further verified with ground-based radar observation. Moreover, the hydrometeor characteristics were compared with the numerical simulations to clarify the reliability of the proposed hydrometeor classification approach. The results demonstrate that the X-/Ka- band radars are capable of identifying hydrometeor phases in winter precipitation in accordance with both ground observations and numerical simulations. Three particle categories, including snow, graupel and the mixture of snow and graupel are also detected in the winter precipitation cloud system, and there are three vertical layers identified from top to bottom, including the ice crystal layer, snow-graupel mixed layer and snowflake layer. Overall, this study has the potential for improving the understanding of microphysical processes such as freezing, deposition and aggregation of ice crystal particles in the winter precipitation cloud system.

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

This paper describes the downscaling of an ensemble of twelve GCMs using the 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 RCP 8.5 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. April 1 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 GCM’s 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 21st century.

The Strong Precipitation of the Dry Warm Front Cyclone in Syria and Its Prediction by Data Mining Modeling

The Eastern inland of Syria has a Mediterranean climate in the north and a tropical desert climate in the south, which results in a dry south and wet north climate feature, especially in winter. The circulation dynamics analysis of 16 winter strong precipitation events shows that the key system is the dry and warm front cyclone. In most cases (81–100% of the 16 cases), the moisture content in the northern part of the cyclone is higher than that in the southern part (influenced by the Mediterranean climate zone). The humidity in the middle layer is higher than that near the surface (uplifting of the dry warm front), and the thickness of the wet layer and the vertical ascending layer obviously expands upward (as shown by the satellite cloud top reflection). These characteristics lead to the moisture thermodynamic instability in the eastern part of the cyclone (dry and warm air at low level and wet and cold air at upper level). The cyclone flow transports momentum to the local humid layer of the Mediterranean climate belt and then causes unstable conditions and strong rainfall. Considering the limitations of the Syrian ground station network, the NCEP/CFSR global reanalysis data and MODIS aqua-3 cloud parameter data are used to build a multi-source factor index of winter precipitation from 2002 to 2016. A decision tree prediction model is then established and the factors index is constructed into tree shapes by the nodes and branches through calculating rules of information entropy. The suitable tree shape models are adjusted and selected by an automated training and testing process. The forecast model can classify rainfall with a forecast accuracy of more than 90% for strong rainfall over 30 mm.

Shifting Precipitation Patterns Drive Growth Variability and Drought Resilience of European Atlas Cedar Plantations

Tree plantations have been proposed as suitable carbon sinks to mitigate climate change. Drought may reduce their carbon uptake, increasing their vulnerability to stress and affecting their growth recovery and resilience. We investigated the recent growth rates and responses to the climate and drought in eight Atlas cedar (Cedrus atlantica) plantations located along a wide climate gradient from wetter sites in south-eastern France and north Spain to dry sites in south-eastern Spain. The cedar growth increased in response to the elevated precipitation from the prior winter to the current summer, but the influence of winter precipitation on growth gained importance in the driest sites. The growth responsiveness to climate and drought peaked in those dry sites, but the growth resilience did not show a similar gradient. The Atlas cedar growth was driven by the total precipitation during the hydrological year and this association strengthened from the 1980s onwards, a pattern related to the winter North Atlantic Oscillation (NAO). High winter NAO indices and drier conditions were associated with lower growth. At the individual level, growth resilience was related to tree age, while growth recovery and year-to-year growth variability covaried. Plantations’ resilience to drought depends on both climate and tree-level features.

Wintertime precipitation climate of Central Southwest Asia: Diagnostics and forecasting

<p>Central Southwest Asia (CSWA; 20°–47°N, 40°–85°E) is a water-scarce and a societally vulnerable region, prone to significant variations in precipitation during the winter months of November–April. Wintertime precipitation variations have a direct impact on CSWA's water resources, agricultural productivity, energy use, and human society. Because of the close relationship between climate and human well-being, an improved understanding of winter season precipitation and its variability over CSWA is of critical importance. However, due to multiple regional challenges (e.g. socio-political instability, extreme topographical heterogeneity, poor coverage of in situ stations, and others) analysis of precipitation in this region has been limited. In an attempt to bridge the existing knowledge gap, this thesis aims to advance our understanding of CSWA's wintertime precipitation climate through three separate, but inter-related studies on 1) evaluation of multi-source gridded precipitation dataset, 2) investigation of spatial and temporal patterns of precipitation and its links with large-scale modes of climate variability, 3) development of a statistical forecast model. Additionally, precipitation evaluation is also relevant to the overlapping and important region of the Indian subcontinent; a detailed seasonal analysis for which is also presented. First, the performance of several commonly used gridded precipitation products from multiple sources: gauge-based, satellite-derived, and reanalysis is analysed for all four seasons over the Indian Subcontinent. Results show that the degree of uncertainty in all precipitation estimates varies by region (e.g. topographic relief) and the type of precipitation (e.g. convective, orographic). At the seasonal scale, satellite-products perform better, while reanalyses generally overestimate precipitation. Greater discrepancies occur in areas with low gauge densities, owing to which a complete understanding of the accuracy and limitations of precipitation estimates is hampered for the northwestern region of the Indian subcontinent. In an extension study, ten multi-source precipitation products are evaluated against an ensemble of four gauge-only datasets. This analysis is carried out for CSWA, which also includes the northwestern region of the Indian subcontinent. Spatial and temporal analysis of results shows that GPCC is a suitable observational dataset for studying long-term wintertime precipitation variations over CSWA. The satellite-derived TRMM 3B42-V7 is a potentially reliable alternative to gauge measurements, while the performance of MERRA reanalysis is satisfactory. Further, the spatial-temporal patterns of wintertime precipitation variability over CSWA are explored. Three leading patterns are identified by empirical orthogonal function (EOF) analysis, and the associated time series are related to global SST and other large-scale atmospheric circulation fields. The leading patterns of winter precipitation are significantly linked with the El Niño–Southern Oscillation (ENSO); East Atlantic–Western Russia (EA-WR); Siberian High; North Pacific Oscillation (NPO); Scandinavian pattern; and the long-term warming of the Indian Ocean SST. The inter-decadal change of relationship between the first-mode of winter precipitation and ENSO is also investigated, which shows that CSWA precipitation variability was closely related to the extratropical EA-WR (tropical ENSO) teleconnection before (after) the 1980's. Finally, the level and origin of seasonal forecast skill of wintertime precipitation anomalies over CSWA are examined using the statistical method of canonical correlation analysis (CCA). The preceding months’ (September–October) SST is used as predictors, and CCA experiments are performed for two sets of time periods, 1950/51–2014/15 and 1980/81–2014/15. For both prediction periods, the potential source of predictability originates largely from SST variations related to ENSO and the Pacific Decadal Oscillation (PDO). A higher (lower) correlation skill of 0.71 (0.38) is obtained between observations and cross-validated precipitation forecasts for the period 1980/81–2014/15 (1950/51–2014/15); which shows that ENSO played a dominant role in creating skillful predictions for CSWA wintertime precipitation in recent years.</p>