Regional Climatic Features of the Arabian Peninsula

Biogeography and Conservation in the Arabian Peninsula: A Present Perspective

The Arabian Peninsula, with its rugged mountains, wadis, alluvial plains, sand dune deserts, and diverse coastlines, spans over 3 million km2. The Peninsula is situated at the crossroads of Africa and Asia and is a meeting point for diverse biogeographic realms, including the Palearctic, Afrotropical, and Indomalayan regions. This convergence of biogeographic zones has resulted in a remarkably diverse flora and fauna, which is adapted to the harsh and varied climates found throughout the Peninsula. Each of the countries of the Arabian Peninsula are biologically diverse and unique in their own right, but Yemen, Saudi Arabia, and Oman are the most diverse in terms of their landforms and biological diversity. The mountainous regions support a cooler and more moderate climate compared to the surrounding lowlands, thus forming unique ecosystems that function as refugia for plant and animal species, and have a high endemism of plant species. The desert ecosystems support a variety of lifeforms that are specially adapted to an extreme arid climate. Due to its long history of human habitation and subsistence agriculture, particularly in the mountainous areas, the Arabian Peninsula possesses unique crop varieties adapted to extreme arid climates, making them important genetic resources for the future in the face of climate change. The Arabian Peninsula, though rich and diverse in its biological diversity, has been greatly affected by human activities, especially in the last 50 years, including urbanization, habitat destruction, overgrazing, and climate change, which pose significant threats to the biodiversity of the region. This review presents the biogeography and background of conservation efforts made in the countries in the Arabian Peninsula and gives the progress made in botanical research and conservation practices throughout the Peninsula.

Augmented human thermal discomfort in urban centers of the Arabian Peninsula

Anthropogenic climate change has amplified human thermal discomfort in urban environments. Despite the considerable risks posed to public health, there is a lack of comprehensive research, evaluating the spatiotemporal changes in human thermal discomfort and its characteristics in hot-hyper arid regions, such as the Arabian Peninsula (AP). The current study analyzes spatiotemporal changes in human thermal discomfort categories and their characteristics in AP, using the newly developed high-resolution gridded ERA5-HEAT (Human thErmAl comforT) dataset for the period 1979-2022. In addition, the study assesses the interplay between the Universal Thermal Climate Index (UTCI) and El Niño-Southern Oscillation (ENSO) indices for the study period. The results reveal a significant increase in human thermal discomfort and its characteristics, with higher spatial variability in the AP region. The major urban centers in the southwestern, central, and southeastern parts of AP have experienced significant increases in human thermal discomfort (0.4-0.8 °C), with higher frequency and intensity of thermal stress during the study period. The temporal distribution demonstrates a linear increase in UTCI indices and their frequencies and intensities, particularly from 1998 onward, signifying a transition towards a hotter climate characterized by frequent, intense, and prolonged heat stress conditions. Moreover, the UTCI and ENSO indices exhibit a dipole pattern of correlation with a positive (negative) pattern in the southwestern (eastern parts) of AP. The study's findings suggest that policymakers and urban planners need to prioritize public health and well-being in AP's urban areas, especially for vulnerable groups, by implementing climate change adaptation and mitigation strategies, and carefully designing future cities to mitigate the effects of heat stress.

Accelerated Water Desorption of Oligomeric Poly(ethylene glycol) by Addition of Poly(propylene glycol) for Energy-Efficient Water Recovery Systems

Adsorbents are used to recover water vapor from the atmosphere in desiccant air conditioning (DAC) and atmospheric water harvesting (AWH) systems. Solid adsorbents have been conventionally used in these systems, though liquid adsorbents are considered to be more effective for energy-efficient fluidic thermosystems because of their low regeneration temperatures (45-70 °C). While most previous studies have focused on improving the adsorption performance, the desorption performance of adsorbents can also be a critical factor in improving the energy efficiency of these systems. Thus, this study aimed to improve the water desorption efficiency, focusing on the liquid adsorbents. We found that mixing hydrophobic molecules into a liquid adsorbent decreases the desorption temperature and increases the water-desorption efficiency. Oligomeric poly(ethylene glycol) (PEG), a common moisture-adsorbing liquid oligomer used in detergents and cosmetics, was selected as the liquid adsorbent. Oligomeric poly(propylene glycol) (PPG), which has a structure analogous to PEG and lower hygroscopicity, was selected as the hydrophobic molecule. Water adsorption and desorption experiments showed that the mixture of PPG with PEG promoted the desorption of water molecules beyond that of PEG, while thermogravimetric differential thermal analysis revealed a decrease in the water desorption temperature with increasing PPG content. The improved desorption efficiency was ascribed to the likely water adsorption equilibrium between PEG and PPG in the blend; water molecules are preferentially desorbed from PPG, which has weaker water-adsorbate interactions. The proposed concept is expected to be incorporated into various hygroscopic liquids to develop energy-efficient liquid adsorbents for DAC and AWH.

Influence of environmental stresses on the durability of slag-based alkali-activated cement crusts for wind erosion control

Wind erosion is a significant environmental challenge in arid and semi-arid regions, and artificial crust creation on the soil surface has emerged as an effective approach to mitigate this phenomenon. Various methods of crust formation have been proposed to combat wind erosion in these regions. However, a comprehensive study assessing the durability of these crusts against environmental stresses has been lacking. Hence, the primary objective of the present study is to address this critical issue by evaluating the erodibility and surface strength of alkali-activated slag crusts in response to various environmental stressors. These stressors encompass ultraviolet radiation, heating and cooling cycles, wetting and drying cycles, and freezing and thawing cycles. Through wind tunnel tests, erosion rates were measured under different wind velocities and saltation bombardment conditions, while penetrometer tests were conducted to analyze surface strength. The results demonstrate that alkali-activated cementation produced robust crusts, exhibiting an impressive reduction of over 99.9 % in erosion rates compared to untreated samples. However, the introduction of environmental stresses led to a fivefold increase in erosion rates. Freeze and thaw cycles had the most detrimental effect on the alkali-activated cement crusts while heating and cooling cycles had a relatively minor impact. The wetting and drying cycles and UV radiation ranked second and third, respectively, in terms of their destructive effects on crust erodibility. Despite the observed effects, the crusts maintained their efficiency even when subjected to severe environmental stresses. Notably, the erosion rate of the treated crusts after enduring the most severe studied stress, that is five freeze and thaw cycles, was over 250 times lower than that of the untreated samples.

The COVID-19 Pandemic: Quantification of Temporal Variations in Air Pollutants Before, During and Post the Lockdown in Jeddah City, Saudi Arabia

The government of Saudi Arabia imposed a strict lockdown between March and July 2020 to stop the spread of the coronavirus disease (COVID-19), which has led to a sharp decline in economic activities. The daily temporal variations of PM₁₀, PM_2.5, carbon monoxide (CO), nitrogen dioxide (NO₂), and ozone (O₃) were used to investigate the changes in air quality in response to COVID-19 lockdown control measures from January to December 2020 in Jeddah, Saudi Arabia. Meteorological parameters (wind speed, direction, temperature, relative humidity) were also analyzed to understand the changes during the pandemic. As a result, significant reductions in the concentrations of NO₂ (- 44.5%), CO (- 41.5%), and PM_2.5, PM₁₀ (- 29.5%, each) were measured in the capital city of Jeddah during the quarantine compared to the pre-lockdown average. In contrast, the lockdown caused a significant increase in O₃ by 41%. The changes in air quality during the COVID-19 outbreak by comparing the average pollutant concentration before lockdown (January 1-March 21, 2020) and the following 12 weeks during the partial lockdown (March 22-July 28, 2020), reveal a very significant decrease in pollutants, and consequently a significant improvement in air quality. Observed differences are attributable to changes in point source emissions associated with changes in localized activities, possibly related to decreased economic and industrial activity in response to the lockdown. The results of the present study show during the study period indicated a positive response to lockdown during the COVID-19 pandemic. Furthermore, the results can be used to establish future control measures and strategies to improve air quality.

Comparison of Rapid Diagnostic Test, Microscopy, and Polymerase Chain Reaction for the Detection of Plasmodium falciparum Malaria in a Low-Transmission Area, Jazan Region, Southwestern Saudi Arabia

This cross-sectional study aimed to assess the performances of a rapid diagnostic test (RDT)—the AllTest Malaria p.f./p.v., microscopy, and nested polymerase chain reaction (PCR) for diagnosing Plasmodium falciparum malaria in 400 febrile patients from a low-transmission region (Jazan) in southwestern Saudi Arabia. Diagnostic performance of all three methods was compared using microscopy and nested PCR as reference methods. Overall, 42 (10.5%), 48 (12.0%), and 57 (14.3%) samples were found positive by microscopy, RDT, and PCR, respectively. With PCR as reference method, the RDT showed higher sensitivity (79% vs. 71.9%), similar specificity (99.1% vs. 99.7%), and better NLR (0.20 vs. 0.27) and area under the curve (89.0% vs. 85.8%) than microscopy. The sensitivity of RDT and microscopy decreased as age increased, and false negatives were associated with low parasite density. In addition, the sensitivity of RDT and microscopy was higher in non-Saudi than in Saudi participants. Against microscopy, both RDT and PCR showed high sensitivity (83.3% vs. 97.6%), specificity (96.4% vs. 95.5%), and NPVs (98.0% vs. 99.7%), but reduced PPVs (72.9% vs. 71.9%), respectively. The results showed that the performance of the AllTest Malaria p.f./p.v RDT was better than that of microscopy in diagnosing P. falciparum malaria among febrile patients in the Jazan region when nested PCR was used as the reference. However, further studies are required to assess malaria diagnostic methods among asymptomatic individuals in the region.

Key Targets for Improving Algal Biofuel Production

A number of technological challenges need to be overcome if algae are to be utilized for commercial fuel production. Current economic assessment is largely based on laboratory scale up or commercial systems geared to the production of high value products, since no industrial scale plant exits that are dedicated to algal biofuel. For macroalgae (‘seaweeds’), the most promising processes are anaerobic digestion for biomethane production and fermentation for bioethanol, the latter with levels exceeding those from sugar cane. Currently, both processes could be enhanced by increasing the rate of degradation of the complex polysaccharide cell walls to generate fermentable sugars using specifically tailored hydrolytic enzymes. For microalgal biofuel production, open raceway ponds are more cost-effective than photobioreactors, with CO2 and harvesting/dewatering costs estimated to be ~50% and up to 15% of total costs, respectively. These costs need to be reduced by an order of magnitude if algal biodiesel is to compete with petroleum. Improved economics could be achieved by using a low-cost water supply supplemented with high glucose and nutrients from food grade industrial wastewater and using more efficient flocculation methods and CO2 from power plants. Solar radiation of not <3000 h·yr−1 favours production sites 30° north or south of the equator and should use marginal land with flat topography near oceans. Possible geographical sites are discussed. In terms of biomass conversion, advances in wet technologies such as hydrothermal liquefaction, anaerobic digestion, and transesterification for algal biodiesel are presented and how these can be integrated into a biorefinery are discussed.

Residual malaria in Jazan region, southwestern Saudi Arabia: the situation, challenges and climatic drivers of autochthonous malaria

Background

Saudi Arabia and Yemen are the only two countries in the Arabian Peninsula that are yet to achieve malaria elimination. Over the past two decades, the malaria control programme in Saudi Arabia has successfully reduced the annual number of malaria cases, with the lowest incidence rate across the country reported in 2014. This study aims to investigate the distribution of residual malaria in Jazan region and to identify potential climatic drivers of autochthonous malaria cases in the region.

Methods

A cross-sectional study was carried out from 1 April 2018 to 31 January 2019 in Jazan region, southwestern Saudi Arabia, which targeted febrile individuals attending hospitals and primary healthcare centres. Participants’ demographic data were collected, including age, gender, nationality, and residence. Moreover, association of climatic variables with the monthly autochthonous malaria cases reported during the period of 2010–2017 was retrospectively analysed.

Results

A total of 1124 febrile subjects were found to be positive for malaria during the study period. Among them, 94.3 and 5.7% were infected with Plasmodium falciparum and Plasmodium vivax, respectively. In general, subjects aged 18–30 years and those aged over 50 years had the highest (42.7%) and lowest (5.9%) percentages of malaria cases. Similarly, the percentage of malaria-positive cases was higher among males than females (86.2 vs 13.8%), among non-Saudi compared to Saudi subjects (70.6 vs 29.4%), and among patients residing in rural rather than in urban areas (89.8 vs 10.2%). A total of 407 autochthonous malaria cases were reported in Jazan region between 2010 and 2017. Results of zero-inflated negative binomial regression analysis showed that monthly average temperature and relative humidity were the significant climatic determinants of autochthonous malaria in the region.

Conclusion

Malaria remains a public health problem in most governorates of Jazan region. The identification and monitoring of malaria transmission hotspots and predictors would enable control efforts to be intensified and focused on specific areas and therefore expedite the elimination of residual malaria from the whole region.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-021-03846-4.

Precipitation Climatology for the Arid Region of the Arabian Peninsula—Variability, Trends and Extremes

The Arabian Peninsula is a region characterized by diverse climatic conditions due to its location and geomorphological characteristics. Its precipitation patterns are characterized by very low annual amounts with great seasonal and spatial variability. Moreover, extreme events often lead to flooding and pose threat to human life and activities. Towards a better understanding of the spatiotemporal features of precipitation in the region, a thirty-year (1986-2015) climatic analysis has been prepared with the aid of the state-of-the-art numerical modeling system RAMS/ICLAMS. Its two-way interactive nesting capabilities, explicit cloud microphysical schemes with seven categories of hydrometeors and the ability to handle dust aerosols as predictive quantities are significant advantages over an area where dust is a dominant factor. An extended evaluation based on in situ measurements and satellite records revealed a good model behavior. The analysis was performed in three main components; the mean climatic characteristics, the rainfall trends and the extreme cases. The extremes are analyzed under the principles of the extreme value theory, focusing not only on the duration but also on the intensity of the events. The annual and monthly rainfall patterns are investigated and discussed. The spatial distribution of the precipitation trends revealed insignificant percentage differences in the examined period. Furthermore, it was demonstrated that the eastern part and the top half of the western Arabian Peninsula presented the lowest risk associated with extreme events. Apart from the pure scientific interest, the present study provides useful information for different sectors of society and economy, such as civil protection, constructions and reinsurance.

Regional Mapping of Groundwater Potential in Ar Rub Al Khali, Arabian Peninsula Using the Classification and Regression Trees Model

Mapping of groundwater potential in remote arid and semi-arid regions underneath sand sheets over a very regional scale is a challenge and requires an accurate classifier. The Classification and Regression Trees (CART) model is a robust machine learning classifier used in groundwater potential mapping over a very regional scale. Ten essential groundwater conditioning factors (GWCFs) were constructed using remote sensing data. The spatial relationship between these conditioning factors and the observed groundwater wells locations was optimized and identified by using the chi-square method. A total of 185 groundwater well locations were randomly divided into 129 (70%) for training the model and 56 (30%) for validation. The model was applied for groundwater potential mapping by using optimal parameters values for additive trees were 186, the value for the learning rate was 0.1, and the maximum size of the tree was five. The validation result demonstrated that the area under the curve (AUC) of the CART was 0.920, which represents a predictive accuracy of 92%. The resulting map demonstrated that the depressions of Mondafan, Khujaymah and Wajid Mutaridah depression and the southern gulf salt basin (SGSB) near Saudi Arabia, Oman and the United Arab Emirates (UAE) borders reserve fresh fossil groundwater as indicated from the observed lakes and recovered paleolakes. The proposed model and the new maps are effective at enhancing the mapping of groundwater potential over a very regional scale obtained using machine learning algorithms, which are used rarely in the literature and can be applied to the Sahara and the Kalahari Desert.

Predicting sun protection measures against skin diseases using machine learning approaches

BACKGROUND

The substantial growth rate of skin cancer has necessitated adequate protection from solar radiation. Consequently, analyzing sun protection practices is an imperative research area in dermatology and pharmacology.

AIMS

This paper aims to analyze public sun-protection manners in the Arabian Peninsula regions.

METHODS

A simple random survey was conducted to assess public sun protection manners. Artificial neural network (ANN) and support vector machine (SVM) were selected from several machine learning algorithms to create the models for predicting public sun protection measures based on the prediction accuracy. Model performances were evaluated based on several performance indicators depending on the confusion matrices and receiver operating characteristic curves.

RESULTS

51% of the respondents have a low level, and 49% have a high level of sun protection practices. The results showed that the SVM performed considerably amended than the ANN for predicting the response. The relative importance of the predictors for the best predictive SVM model was also analyzed. The predictors are ranked as: the number of times having sunburnt >gender > use seat belt while driving/riding a vehicle >considers the UV index for personal sun exposure >income based on the expenses >sports/exercise activities >consciousness of the chance for having sunburnt on extended exposure to the sun >age > having any skin problem >nationality > skin type.

CONCLUSION

These identified significant predictors might be considered for developing an effective policy to increase public consciousness using proper protection from solar radiation's detrimental effect to rule out skin diseases.

Long-Term Assessment of Onshore and Offshore Wind Energy Potentials of Qatar

Exploitation of conventional energy resources has caused a deliberate increase in the emitted carbon in the atmosphere, which catalyzes global warming trends. This is a matter of concern, especially in Qatar, where fossil fuels (oil and gas) are largely relied upon for power production. The dependency on such resources could be gradually reduced by utilizing clean and renewable energy. Resource characterization is an important step to evaluate the potentiality of available renewable energy sources. Wind energy is one among them, which has not been assessed reliably so far in Qatar. We analyzed the wind energy potential along the onshore and offshore areas of Qatar using 40 years (1979–2018) of hourly wind data extracted from the ECMWF Reanalysis v5 (ERA5) database. Monthly, seasonal, annual, and decadal mean wind power densities have been derived. Reliability tests have been carried out at select onshore and offshore locations. Trends and inter-annual variability have been assessed. The study reveals that the available wind resources are generally moderate but consistent with no intense trends during the 40 year period. An inter-annual variability in wind power has been identified, which has secured links with the El Niño–Southern Oscillation (ENSO).

Impact of novel coronavirus disease (COVID-19) lockdown on ambient air quality of Saudi Arabia

The outbreak of COVID-19 has spread globally affecting human activities but with improvement in ambient air quality. The first case of the virus in the Kingdom of Saudi Arabia was on the 2nd of March 2020. The impact of COVID-19 lockdown on the ambient air quality of the Kingdom of Saudi Arabia for the first time using data from nine cities was determined in this study. Hourly air quality data, based on concentrations of carbon monoxide (CO), particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2) and ozone (O3), and meteorological conditions (atmospheric temperature, relative humidity, and wind speed) of the nine cities studied were obtained from Saudi Arabian General Authority of Meteorology and Environmental Protection (GAMEP), for the period between January 2019 to May 2020. Significant variation (p < 0.05) was recorded for the five atmospheric pollutants across the cities before and during the lockdown, with lower concentrations during the lockdown except for the concentration of O3 in Tabuk, Al Qasim, and Haql. This can be a result of NO and O3 reaction, causing the inability of effective O3 depletion. The percentage changes in concentrations of CO (33.60%) and SO2 (44.16%) were higher in Jeddah; PM10 (91.12%) in Riyadh, while NO2 (44.35%) and O3 (18.98%) were highest in Makkah. However, even though there was a decrease in pollutants concentrations during the lockdown, the concentrations for CO, PM10, SO2, NO2, and O3 were still above WHO 24 h and annual mean limit levels. The COVID-19 lockdown in the Kingdom of Saudi Arabia revealed the possibility of significant atmospheric pollutant reduction by controlling traffic, activities by industries, and environmentally friendly transportation programs such as green commuting programs.

Atmospheric Dynamics and Numerical Simulations of Six Frontal Dust Storms in the Middle East Region

This study analyzes six frontal dust storms in the Middle East during the cold period (October–March), aiming to examine the atmospheric circulation patterns and force dynamics that triggered the fronts and the associated (pre- or post-frontal) dust storms. Cold troughs mostly located over Turkey, Syria and north Iraq played a major role in the front propagation at the surface, while cyclonic conditions and strong winds facilitated the dust storms. The presence of an upper-atmosphere (300 hPa) sub-tropical jet stream traversing from Egypt to Iran constitutes also a dynamic force accompanying the frontal dust storms. Moderate-Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) observations are used to monitor the spatial and vertical extent of the dust storms, while model (Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), Copernicus Atmospheric Monitoring Service (CAMS), Regional Climate Model-4 (RegCM4)) simulations are also analyzed. The WRF-Chem outputs were in better agreement with the MODIS observations compared to those of CAMS and RegCM4. The fronts were identified by WRF-Chem simulations via gradients in the potential temperature and sudden changes of wind direction in vertical cross-sections. Overall, the uncertainties in the simulations and the remarkable differences between the model outputs indicate that modelling of dust storms in the Middle East is really challenging due to the complex terrain, incorrect representation of the dust sources and soil/surface characteristics, and uncertainties in simulating the wind speed/direction and meteorological dynamics. Given the potential threat by dust storms, more attention should be directed to the dust model development in this region.

A remote sensing study of spatiotemporal variations in drought conditions in northern Asir, Saudi Arabia

Changes in vegetation land cover are influenced by, and therefore an indicator of, climatic conditions. The aim of this study is to investigate the relationship between vegetation cover changes and drought events in a small-scale area. Six Landsat images during 1987-2019 were used to extract information about the vegetation land cover changes using the normalized difference vegetation index (NDVI) and the fractional vegetation cover (FVC) in Balqarn Governorate in the northern mountains of Asir, Saudi Arabia. Two climatic parameters, temperature and precipitation, were used as time series for the same period and were decomposed to investigate the seasonal and trend changes for each parameter. The two parameters were also used to calculate the standardized precipitation evapotranspiration index (SPEI) to conduct an in-depth analysis of the drought events influencing vegetation cover. The results showed that the state of the vegetation coverage of the study area remained at a medium level with an average NDVI value, but the FVC values showed evidence of dynamic variability associated with drought and moisture events. The SPEI showed that the study area has been undergoing a long-duration drought event since 2004, ranging from light to severe drought, which was consistent with the time series decomposition results. This investigation has revealed that drought drives changes in vegetation cover and is expressed on small geographic scales as changes in the vegetation cover structure. The framework described here is simple and can be used to evaluate and manage drought risks.

Sun Awareness and Sun Protection Practices

Background

The incidence of skin cancer has increased over the past few years, owing to excessive exposure to ultraviolet (UV) radiation. Over the past decade, protection against solar radiation has been highly encouraged in numerous public health education campaigns. The adopted sun protection practices include avoiding exposure to the sun, using protective clothing, and applying sunscreen. The aim of this paper was to analyze the awareness and attitudes towards sun protection practices in some regions of the Arabian Peninsula.

Objective

The main objective of this study is to estimate the level of sun protection practices and determine the factors that have a significant impact on the level of adoption of sun protection practices by residents in the Arabian Peninsula.

Methods

A 35-question self-reporting online questionnaire to evaluate the sun protection measures adopted by the residents was distributed in the Kingdom of Saudi Arabia and Kingdom of Bahrain. The survey was conducted from January 2018 to May 2019, and a total 830 responses were collected for analysis. The data were analyzed using the statistical software SPSS. The chi-squared test and Spearman's correlation were performed to determine the association of the sun protection level with factors concerning the socio-demographic characteristics, sun sensitivity, health-conscious lifestyle, adopted sun protection measures, and general awareness about the UV index, skin cancer, and vitamin D. Logistic regression classification was applied in developing the empirical model to predict the sun protection level of the residents.

Results

Based on the analysis, only 34% of the total 830 respondents use sunscreen and most of the sunscreen users are female. The three most popular sun protection practices are: 1) avoiding exposure to the sun during peak hours, 2) using protective clothing, and 3) using sunglasses. The results indicate that 22% of respondents use a low level of sun protection, 53% use a medium level of protection, while 25% of respondents use a high level of sun protection. Many of the respondents understand that exposure to the sun can cause skin cancer and skin aging, while 54% of the respondents still believe that a suntan can be healthy if sunburn is avoided. Thirty percent of the participants of this study are aware of the UV index, and only 20% of all respondents know the correct meaning of the UV index. The overall predictive accuracy of the constructed logistic regression model is 67%. Based on the results of the logistic regression model, the five most significant factors of the sun protection level are: 1) perception that the sun can cause skin aging, or not, 2) age, 3) awareness of the dangerous effects of sun exposure, 4) income with respect to expenses, and 5) taking the UV index into consideration during exposure to the sun.

Conclusion

Most of the respondents are aware about sun protection. However, the sun protection level of the residents is still inadequate. An efficient strategy of increasing the awareness of the effective use of sun protection systems must be established based on the significant factors to prevent skin cancer.

Cryptosporidium and Cryptosporidiosis: The Perspective from the Gulf Countries

The present review discusses the burden of cryptosporidiosis in the Gulf Cooperation Council (GCC), which is underreported and underestimated. It emphasizes that the Cryptosporidium parasite is infecting inhabitants and expatriates in the Gulf countries. Children under 5 years are a vulnerable group that is particularly affected by this parasitic disease and can act as carriers, who contribute to the epidemiology of the disease most probably via recreational swimming pools. Various risk factors for cryptosporidiosis in the GCC countries are present, including expatriates, predisposing populations to the infection. Water contamination, imported food, animal contact, and air transmission are also discussed in detail, to address their significant role as a source of infection and, thus, their impact on disease epidemiology in the Gulf countries' populations.

The Role of Sea Surface Temperature Forcing in the Life-Cycle of Mediterranean Cyclones

Air–sea interface processes are highly associated with the evolution and intensity of marine-developed storms. Specifically, in the Mediterranean Sea, the air–ocean temperature deviations have a profound role during the several stages of Mediterranean cyclonic events. Subsequently, this enhances the need for better knowledge and representation of the sea surface temperature (SST). In this work, an analysis of the impact and uncertainty of the SST from different well-known datasets on the life-cycle of Mediterranean cyclones is attempted. Daily SST from the Real Time Global SST (RTG_SST) and hourly SST fields from the Operational SST and Sea Ice Ocean Analysis (OSTIA) and the NEMO ocean circulation model are implemented in the RAMS/ICLAMS-WAM coupled modeling system. For the needs of the study, the Mediterranean cyclones Trixi, Numa, and Zorbas were selected. Numerical experiments covered all stages of their life-cycles (five to seven days). Model results have been analyzed in terms of storm tracks and intensities, cyclonic structural characteristics, and derived heat fluxes. Remote sensing data from the Integrated Multi-satellitE Retrievals (IMERG) for Global Precipitation Measurements (GPM), Blended Sea Winds, and JASON altimetry missions were employed for a qualitative and quantitative comparison of modeled results in precipitation, maximum surface wind speed, and wave height. Spatiotemporal deviations in the SST forcing rather than significant differences in the maximum/minimum SST values, seem to mainly contribute to the differences between the model results. Considerable deviations emerged in the resulting heat fluxes, while the most important differences were found in precipitation exhibiting spatial and intensity variations reaching 100 mm. The employment of widely used products is shown to result in different outcomes and this point should be taken into consideration in forecasting and early warning systems.

UV Index Forecasting under the Influence of Desert Dust: Evaluation against Surface and Satellite-Retrieved Data

Human exposure to healthy doses of UV radiation is required for vitamin D synthesis, but exposure to excessive UV irradiance leads to several harmful impacts ranging from premature wrinkles to dangerous skin cancer. However, for countries located in the global dust belt, accurate estimation of the UV irradiance is challenging due to a strong impact of desert dust on incoming solar radiation. In this work, a UV Index forecasting capability is presented, specifically developed for dust-rich environments, that combines the use of ground-based measurements of broadband irradiances UVA (320–400 nm) and UVB (280–315 nm), NASA OMI Aura satellite-retrieved data and the meteorology-chemistry mesoscale model WRF-Chem. The forecasting ability of the model is evaluated for clear sky days as well as during the influence of dust storms in Doha, Qatar. The contribution of UV radiation to the total incoming global horizontal irradiance (GHI) ranges between 5% and 7% for UVA and 0.1% and 0.22% for UVB. The UVI forecasting performance of the model is quite encouraging with an absolute average error of less than 6% and a correlation coefficient of 0.93. In agreement with observations, the model predicts that the UV Index at local noontime can drop from 10–11 on clear sky days to approximately 6–7 during typical dusty conditions in the Arabian Peninsula—an effect similar to the presence of extensive cloud cover.