ALBERT

Description: The Saudi Arabia (SA) climate varies greatly, depending on the geography and the season. According to K ppen and Geiger, the climates of SA is “desert climate”. The analysis of the seasonal rainfall detects that spring and winter seasons have the highestrainfall incidence, respectively. Through the summer,small quantities of precipitation are observed, while autumn received more precipitation more than summer season considering the total annual rainfall. In all seasons, the SW area receives rainfall, with a maximum in spring, whereas in the summer season, the NE and NW areas receive very little quantities of precipitation. The Rub Al-Khali (the SE region) is almost totally dry. The maximum amount of annual rainfall does not always happen at the highest elevation. Therefore, the elevation is not the only factor in rainfall distribution.A great inter-annual change in the rainfall over the SA for the period (1978–2009) is observed. In addition, in the same period, a linear decreasing trend is found in the observed rainfall, whilst in the recent past (1994–2009) a statistically significant negative trend is observed. In the Southern part of the Arabian Peninsula (AP) and along the coast of the Red Sea, it is interesting to note that rainfall increased, whilst it decreased over most areas of SA during the 2000–2009 decade, compared to 1980–1989.Statistical and numerical models are used to predict rainfall over Saudi Arabia (SA). The statistical models based on stochastic models of ARIMA and numerical models based on Providing Regional Climates for Impact Studies of Hadley Centre (PRECIS). Climate and its qualitative character and quantified range of possible future changes are investigated. The annual total rainfall decreases in most regions of the SA and only increases in the south. The summertime precipitation will be the highest between other seasons over the southern, the southwestern provinces and Asir mountains, while the wintertime rainfall will remain the lowest.The climate in the SA is instructed by the El Niño Southern Oscillation (ENSO) and other circulations such as centers of high and low pressure, the North Atlantic Oscillation (NAO) and SOI. Strength and oscillation of subtropical jet stream play a big role in pulling hot, dry air masses of SA.

Description: Drought is a serious natural hazard with far-reaching impacts including soil damages, economic losses, and threatening the livelihood and health of local residents. The goal of the present work was to monitor the vegetation health across Lebanon in 2014 using remote sensing techniques. Landsat images datasets, with a spatial resolution of 30 m and from different platforms, were used to identify the VCI (Vegetation Condition Index) and TCI (Temperature Condition Index). The VCI was based on the Normalized Difference Vegetation Index (NDVI) datasets. The TCI used land surface temperature (LST) datasets. As a result, the VHI (Vegetation Health Index) was produced and classified into five categories: extreme, severe, moderate, mild, and no drought. The results show practically no extreme drought (~0.27 km2) in the vegetated area in Lebanon during 2014. Moderate to severe drought mainly occurred in the north of Lebanon (i.e., the Amioun region and the plain of Akkar). The Tyr region and the Bekaa valley experienced a low level of drought (mild drought). This approach allows decision makers to monitor, investigate and resolve drought conditions more effectively.

Description: Despite significant advances in watershed science and technology, water availability, water quality, and water related health problems remain a significant worldwide concern [1]. While the concept of watershed-scale management to address these concerns remains intact, most scientists recognize that application of natural science concepts and advanced technologies are not sufficient to adequately address watershed-scale water management issues. There is a significant need for a paradigm shift, i.e., namely increased public interaction and participation in watershed management and decision-making. The effective application of an integrated approach requires developing new scientific concepts on integration of natural and social sciences. In recent years, concepts, such as integrated watershed management and/or holistic approaches to water resource management, have been widely promoted (e.g., [2–6]). [...]

Description: Soil water potential (Ψ) controls the dynamics of water in soils and can therefore affect greenhouse gas fluxes. We examined the relationship between soil moisture content (θ) at five different levels of water potential (Ψ = 0, −0.05, −0.1, −0.33 and −15 bar) and greenhouse gas (carbon dioxide, CO2; nitrous oxide, N2O and methane, CH4) fluxes. The study was conducted in 2011 in a silt loam soil at Freeman farm of Lincoln University. Soil samples were collected at two depths: 0–10 and 10–20 cm and their bulk densities were measured. Samples were later saturated then brought into a pressure plate for measurements of Ψ and θ. Soil air samples for greenhouse gas flux analyses were collected using static and vented chambers, 30 cm in height and 20 cm in diameter. Determination of CO2, CH4 and N2O concentrations from soil air samples were done using a Shimadzu Gas Chromatograph (GC-14). Results showed that there were significant correlations between greenhouse gas fluxes and θ held at various Ψ in the 0–10 cm depth of soil group. For instance, θ at Ψ = 0 positively correlated with measured CO2 (p = 0.0043, r = 0.49), N2O (p = 0.0020, r = 0.64) and negatively correlated with CH4 (p = 0.0125, r = −0.44) fluxes. Regression analysis showed that 24%, 41% and 19% of changes in CO2, N2O and CH4 fluxes, respectively, were due to θ at Ψ = 0 (p 〈 0.05). This study stresses the need to monitor soil water potential when monitoring greenhouse gas fluxes.

Description: Since the 90s, several studies were conducted to evaluate the predictability of the Sahelian rainy season and propose seasonal rainfall forecasts to help stakeholders to take the adequate decisions to adapt with the predicted situation. Unfortunately, two decades later, the forecasting skills remains low and forecasts have a limited value for decision making while the population is still suffering from rainfall interannual variability: this shows the limit of commonly used predictors and forecast approaches for this region. Thus, this paper developed and tested new predictors and new approaches to predict the upcoming seasonal rainfall amount over the Sirba watershed. Predictors selected through a linear correlation analysis were further processed using combined linear methods to identify those having high predictive power. Seasonal rainfall was forecasted using a set of linear and non-linear models. An average lag time up to eight months was obtained for all models. It is found that the combined linear methods performed better than non-linear, possibly because non-linear models require larger and better datasets for calibration. The R2, Nash and Hit rate score are respectively 0.53, 0.52, and 68% for the combined linear approach; and 0.46, 0.45, 61% for non-linear principal component analysis.

Description: Climate change impacts on nature and the environment have been widely discussed and studied. Traditionally, a company’s continuity management is based on risk analysis. There are also attempts to implement scenario-based methods in the risk management procedures of companies. For industrial decision makers, it is vital to acknowledge the impacts of climate change with regards to their adaptation strategies. However, a scenario-based approach is not always the most effective way to analyze these risks. This paper investigates the integration of scenario and risk-based methods for a company’s adaptation planning. It considers the uncertainties of the climate change scenarios and the recognized risks as well as suitable adaptation strategies. The paper presents the results of climate risk analysis prepared for two Finnish hydropower plants. The introduced method was first piloted in 2008 and then again in 2015. The update of the analysis pointed out that at the company level, the climate risks and other risks originating from governmental or political decisions form an intertwined wholeness where the origin of the risk is difficult to outline. It seems that, from the business point of view, the main adaptation strategies suggested by the integrated risk and scenarios approach are those that support buying “safety margins” in new investments and reducing decision time horizons. Both of these adaptation strategies provide an advantage in the circumstances where also political decisions and societal changes have a great effect on decision making.

Description: A detailed statistical analysis was performed at the Neuquén river basin using precipitation data for 1980–2007. The hydrological year begins in March with a maximum in June associated with rainfall and another relative maximum in October derived from snow-break. General features of the rainy season and the excess or deficits thereof are analyzed using standardized precipitation index (SPI) for a six-month period in the basin. The SPI has a significant cycle of 14.3 years; the most severe excess (SPI greater than 2) has a return period of 25 years, while the most severe droughts (SPI less than −2) have a return period of 10 years. The SPI corresponding to the rainy season (April–September) (SPI9) has no significant trend and is used to classify wet/dry years. In order to establish the previous circulation patterns associated with interannual SPI9 variability, the composite fields of wet and dry years are compared. There is a tendency for wet (dry) periods to take place during El Niño (La Niña) years, when there are positive anomalies of precipitable water over the basin, when the zonal flow over the Pacific Ocean is weakened (intensified) and/or when there are negative pressure anomalies in the southern part of the country and Antarctic sea. Some prediction schemes using multiple linear regressions were performed. One of the models derived using the forward stepwise method explained 42% of the SPI9 variance and retained two predictors related to circulation over the Pacific Ocean: one of them shows the relevance of the intensity of zonal flow in mid-latitudes, and the other is because of the influence of low pressure near the Neuquén River basin. The cross-validation used to prove model efficiency showed a correlation of 0.41 between observed and estimated SPI9; there was a probability of detection of wet (dry) years of 80% (65%) and a false alarm relation of 25% in both cases.

Description: The Abdus Salam International Center for Theoretical Physics (ICTP) version 4.4 Regional Climate Model (RegCM4) is used to investigate the rainfall response to cooler/warmer sea surface temperature anomaly (SSTA) forcing in the Indian and Atlantic Oceans. The effect of SSTA forcing in a specific ocean basin is identified by ensemble, averaging 10 individual simulations in which a constant or linearly zonally varying SSTA is prescribed in individual basins while specifying the 1971–2000 monthly varying climatological sea surface temperature (SST) across the remaining model domain. The nonlinear rainfall response to SSTA amplitude also is investigated by separately specifying +1K, +2K, and +4K SSTA forcing in the Atlantic and Indian Oceans. The simulation results show that warm SSTs over the entire Indian Ocean produce drier conditions across the larger Blue Nile catchment, whereas warming ≥ +2K generates large positive rainfall anomalies exceeding 10 mm·day−1 over drought prone regions of Northeastern Ethiopia. However, the June–September rainy season tends to be wetter (drier) when the SST warming (cooling) is limited to either the Northern or Southern Indian Ocean. Wet rainy seasons generally are characterized by deepening of the monsoon trough, east of 40°E, intensification of the Mascarene high, strengthening of the Somali low level jet and the tropical easterly jet, enhanced zonal and meridional vertically integrated moisture fluxes, and steeply vertically decreasing moist static energy. The opposite conditions hold for dry monsoon seasons.

Description: A new dynamical downscaling methodology to analyze the impact of global climate change on the local climate of cities worldwide is presented. The urban boundary layer climate model UrbClim is coupled to 11 global climate models contained in the Coupled Model Intercomparison Project 5 archive, conducting 20-year simulations for present (1986–2005) and future (2081–2100) climate conditions, considering the Representative Concentration Pathway 8.5 climate scenario. The evolution of the urban heat island of eight different cities, located on three continents, is quantified and assessed, with an unprecedented horizontal resolution of a few hundred meters. For all cities, urban and rural air temperatures are found to increase strongly, up to 7 °C. However, the urban heat island intensity in most cases increases only slightly, often even below the range of uncertainty. A potential explanation, focusing on the role of increased incoming longwave radiation, is put forth. Finally, an alternative method for generating urban climate projections is proposed, combining the ensemble temperature change statistics and the results of the present-day urban climate.

Description: Large parts of the northern hemisphere are covered by snow and seasonal frost. Climate warming is affecting spatiotemporal variations of snow and frost, hence influencing snowmelt infiltration, aquifer recharge and river runoff patterns. Measurement difficulties have hampered progress in properly assessing how variations in snow and frost impact snowmelt infiltration. This has led to contradicting findings. Some studies indicate that groundwater recharge response is scale dependent. It is thus important to measure snow and soil frost properties with temporal and spatial scales appropriate to improve infiltration process knowledge. The main aim with this paper is therefore to review ground based methods to measure snow properties (depth, density, water equivalent, wetness, and layering) and soil frost properties (depth, water and ice content, permeability, and distance to groundwater) and to make recommendations for process studies aiming to improve knowledge regarding infiltration in regions with seasonal frost. Ground-based radar (GBR) comes in many different combinations and can, depending on design, be used to assess both spatial and temporal variations in snow and frost so combinations of GBR and tracer techniques can be recommended and new promising methods (auocostics and self potential) are evolving, but the study design must be adapted to the scales, the aims and the resources of the study.