A Case of Pure Matrix Ureteral Stone: A rare type of urinary calculi that may be overlooked

Matrix stones are a rare form of urinary calculi with a low mineral content. We report a 63-year-old female patient who presented to the Sohar Hospital, Sohar, Oman, in 2018 with unexplained left flank pain and constipation. She had a history of chronic renal failure (CRF) and had previously undergone haemodialysis (HD). Non-contrast computed tomography (CT) did not show any renal or urinary stones. However, a left-sided ureteroscopy revealed a yellow-coloured stone that was soft in consistency occupying the proximal 5 cm section of the ureter. Many attempts at forceps extraction were required for complete clearance. A global quantitative composition analysis revealed the extracted stone to be composed entirely of protein-matrix material. Matrix stones require a high index of suspicion as they are sometimes radiolucent and cannot be visualised on CT scans. Risk factors include being female and a history of urinary tract infections, CRF and HD.Keywords: Urolithiasis; Ureteral Calculi; Diagnostic Imaging; Ureteroscopy; Case Report; Oman

Assessment of uncertainties in projected temperature and precipitation over the Arabian Peninsula using three categories of CMIP5 multimodel ensembles

Background: Projections of temperature and precipitation with low uncertainties are key parameters to climate change related studies. Purpose: The projected temperature and precipitation and their uncertainties over the Arabian Peninsula for the 21st century for three CMIP5 multimodel ensembles under RCP4.5 and RCP8.5 are examined in this paper. Methods: Analyzing the performance of 30 CMIP5 model individually, they are categorized into three groups for the present climate (1976–2005). By applying simple model averaging ensemble method, three multimodel ensemble means, namely: (i) all CMIP5 models ensemble (AME), (ii) selected CMIP5 models ensemble (SME), and (iii) best-performing CMIP5 models ensemble (BME) are developed. Results Over the Arabian Peninsula, a continuous rise in temperature is obtained in all three ensembles (i.e., AME, SME, and BME) in the 21st century. The BME shows enhanced changes in temperature at the end of 21st century as compared to AME and SME. Moreover, the BME shows a remarkable reduction in uncertainties for the projected temperature. The AME, SME, and BME show strong inter-annual variability for the projected precipitation over the peninsula. Compared to AME and SME, the BME revealed enhanced positive change in the annual mean precipitation by the end of 21st century. Conclusions: Regionally, southern/northwestern areas of the peninsula receive enhanced/reduced future precipitation as compared to the present climate. The diferences in the projected precipitation and temperature signals increase largely between the three ensembles towards the end of 21st century. Therefore, it is concluded that selecting the best-performing models may lead a better planning by the policy makers and stakeholder for the region

Strong Warming Rates in the Surface and Bottom Layers of a Boreal Lake: Results From Approximately Six Decades of Measurements (1964–2020)

High-latitude lakes are warming faster than the global average with deep implications for life on Earth. Using an approximately six-decade long in situ data set, we explored the changes in lake surface-water temperature (LST), lake deep-water temperature (LDT), lake depth-weighted mean water temperature (LDMT), and ice-free days in Lake Kallavesi, a boreal lake in central Finland, when the lake was stratified (June–August). Our results suggest that the LST is warming faster than the local air temperature (AT). As for the LST, fast warming was also observed in the LDT and LDMT, but at rates slower than those in the LST. The number of ice-free days also shows an upward trend, with a rate of about 7 days per decade during the study period. The corresponding local AT is the main driver of the LST, followed by the ice-free days and annual mean AT. Air temperature and ice-free days also mainly contribute to the changes in the LDMT. The LDT is affected more by the North Atlantic Oscillation signals in this freshwater lake. The AT in the prior months does not affect the LDT in Lake Kallavesi although the AT during the prior season, that is, spring, is the main driver of summer LDT. This highlights the local AT impact on the LDT at time scales longer than a month. The warming rates in the lake water are at a minimum in June because the lake is not yet strongly stratified in this month when compared to July and August. These findings improve our knowledge of long-term changes in the lake water temperature in a high-latitude lake, a region with severe environmental consequences due to fast changes in the AT and lake ice phenology

Assessment of uncertainties in projected temperature and precipitation over the Arabian Peninsula a comparison between different categories of CMIP3 models

Background: This paper examined the level of uncertainties in precipitation and temperature simulations by Coupled Model Intercomparison Project Phase 3 (CMIP3) over the Arabian Peninsula. Purpose: Different techniques are employed to assess the ranges of uncertainties in projected temperature and precipitation over the Arabian Peninsula. Methods: For the present climate (1970–1999), the 22 CMIP3 models are grouped into four out of which two main categories, i) all models ensemble and ii) best performing models ensemble, are used to assess the uncertainties in the future temperature and precipitation over the Arabian Peninsula. Results: The CMIP3 ensemble projections for the above two main categories revealed a continuous increase in temperature over the peninsula during the 21st century. For the period 2070–2099, the all (best performing) models ensemble revealed an increase in temperature by 2.32 ± 2.45 (3.85 ± 1.54), 3.49 ± 2.49 (4.91 ± 1.61), and 3.28 ± 1.47 (5.36 ± 1.47) C, relative to the present climate, under the B1, A1B, and A2 scenario, respectively, while the intermodel ranges are projected to be from -3.36 to 6.08 (0.84 to 5.96), -2.26 to 7.68 (1.94 to 7.29), and -1.79 to 7.40 (2.75 to 7.10) C, respectively. Meanwhile, for the same period, the annual precipitation is projected to increase by 5.16 ± 30 (3.2 ± 25), 10.48 ± 34 (1.82 ± 28), and 15.29 ± 43 (5.3 ± 32)%, relative to the present climate under the B1, A1B, and A2 scenario, while the intermodel ranges are projected to be from -94 to 265 (-71 to 175), -95 to 322 (-74 to 205), and -95 to 375 (-75 to 235)%, respectively, for all (best performing) models ensemble. Conclusion The uncertainty of projected temperature and precipitation is reduced in the best performing models ensemble compared to the all models. At annual scale, surplus (deficit) precipitation pattern is projected across southern and southwestern (northern and northwestern) parts of the peninsula. The above results indicate that a better choice of models from the CMIP3 database could reduce the uncertainty range associated with future projections over the Arabian Peninsula

Separating the Indian and Pacific Ocean Impacts on the Euro-Atlantic Response to ENSO and Its Transition from Early to Late Winter

AbstractThe present study focuses on the mechanism that controls the transition of the Euro-Atlantic circulation responses to El Niño–Southern Oscillation (ENSO) from early (December) to late winter (February) for the period 1981–2015. A positive phase of ENSO induces a precipitation dipole with increased precipitation in the western and reduced precipitation in the eastern tropical Indian Ocean; this occurs mainly during early winter (December) and less so in late winter (February). It is shown that these interbasin atmospheric teleconnections dominate the response in the Euro-Atlantic sector in early winter by modifying the subtropical South Asian jet (SAJET) and forcing a wavenumber-3 response that projects spatially onto the positive North Atlantic Oscillation (NAO) pattern. On the contrary, during late winter, the response in the Euro-Atlantic sector is dominated by the well-known ENSO wave train from the tropical Pacific region, involving extratropical anomalies that project spatially on the positive phase of the Pacific–North American (PNA) pattern and the negative phase of the NAO pattern. Numerical experiments with an atmospheric model (an AGCM) forced by an Indian Ocean heating dipole anomaly support the hypothesis that the Indian Ocean modulates the SAJET and enforces the Rossby wave propagation to the Euro-Atlantic region in early winter. These phenomena are also investigated using the ECMWF SEAS5 reforecast dataset. In SEAS5, the ENSO interbasin tropical teleconnections and the response of the Euro-Atlantic circulation anomalies and their change from early to late winter are realistically predicted, although the strength of the early winter signal originated from the Indian Ocean is underestimated

Hydrometeorology: Review of Past, Present and Future Observation Methods

Hydrometeorology aims at measuring and understanding the physics, chemistry, energy and water fluxes of the atmosphere, and their coupling with the earth surface environmental parameters. Accurate hydrometeorological records and observations with different timelines are crucial to assess climate evolution and weather forecast. Historical records suggest that the first hydrometeorological observations date back to ca 3500 BC. Reviewing these observations in the light of our modern knowledge of the dynamic of atmospheres is critical as it can reduce the ambiguities associated to understanding major fluctuations or evolutions in the earth climate. Today, the ambiguities in hydrometeorological observations have significantly improved due to the advances in monitoring, modeling, and forecasting of processes related to the land-atmosphere coupling and forcing. Numerical models have been developed to forecast hydrometeorological phenomena in short-, medium- and long-term horizons, ranging from hourly to annual timescales. We provide herein a synthetic review of advances in hydrometeorological observations from their infancy to today. In particular, we discuss the role of hydrometeorological records, observations, and modeling in assessing the amplitude and time-scale for climate change and global warming

Climate Change and Weather Extremes in the Eastern Mediterranean and Middle East

Observation‐based and modeling studies have identified the Eastern Mediterranean and Middle East (EMME) region as a prominent climate change hotspot. While several initiatives have addressed the impacts of climate change in parts of the EMME, here we present an updated assessment, covering a wide range of timescales, phenomena and future pathways. Our assessment is based on a revised analysis of recent observations and projections and an extensive overview of the recent scientific literature on the causes and effects of regional climate change. Greenhouse gas emissions in the EMME are growing rapidly, surpassing those of the European Union, hence contributing significantly to climate change. Over the past half‐century and especially during recent decades, the EMME has warmed significantly faster than other inhabited regions. At the same time, changes in the hydrological cycle have become evident. The observed recent temperature increase of about 0.45°C per decade is projected to continue, although strong global greenhouse gas emission reductions could moderate this trend. In addition to projected changes in mean climate conditions, we call attention to extreme weather events with potentially disruptive societal impacts. These include the strongly increasing severity and duration of heatwaves, droughts and dust storms, as well as torrential rain events that can trigger flash floods. Our review is complemented by a discussion of atmospheric pollution and land‐use change in the region, including urbanization, desertification and forest fires. Finally, we identify sectors that may be critically affected and formulate adaptation and research recommendations toward greater resilience of the EMME region to climate change. The Eastern Mediterranean and Middle East is warming almost two times faster than the global average and other inhabited parts of the world Climate projections indicate a future warming, strongest in summers. Precipitation will likely decrease, particularly in the Mediterranean Virtually all socio‐economic sectors will be critically affected by the projected changes The Eastern Mediterranean and Middle East is warming almost two times faster than the global average and other inhabited parts of the world Climate projections indicate a future warming, strongest in summers. Precipitation will likely decrease, particularly in the Mediterranean Virtually all socio‐economic sectors will be critically affected by the projected change

Skill assessment of Saudi-KAU and C3S models in prediction of spring season rainfall over the Arabian Peninsula

A skillful prediction of precipitation has great value, particularly for regions that suffer from water stress. In this study, we assess the potential predictability and skill of the Copernicus Climate Change Service (C3S) and SaudiKAU models in their simulation of precipitation over the Arabian Peninsula during spring (March–May) for the period 1993–2016. For this purpose, data from individual models as well as the multi-model ensemble (MME) is used. The prediction data for MAM precipitation initialized at Feb (Lead 1), Jan (Lead 2), and Dec (Lead 3), were obtained from the 5 C3S and Saudi-KAU coupled global climate model. The potential predictability was computed by evaluating the signal to noise ratio and the theoretical limit of correlation skill, while the prediction skill was estimated from the temporal anomaly correlation co-efficient. The results show that the Saudi-KAU, CMCC, and UKMO models have slightly higher potential predictability of about 0.25, 0.35, and 0.25 respec­ tively, as compared to other models. It is also observed that individual models as well as their MME show a high (low) potential predictability over southwestern (northern) regions of the Peninsula. Moreover, the Saudi-KAU, CMCC, and MME show a reasonably good correlation skill (0.68, 0.59, and 0.57) while the SEAS model displays lower skill (0.14) for spring precipitation. All model simulations reveal a decrease in prediction skill for longer lead times. On the other hand, the individual models and their MME successfully reproduced the Pacific (i.e. ENSO) teleconnection patterns while displaying lower skill over the tropical Atlantic Ocean. The results indicate that the model biases have negative impacts on potential predictability and prediction skill over the Arabian Peninsula during the spring season

Climate Change and Weather Extremes in the Eastern Mediterranean and Middle East

Observation-based and modeling studies have identified the Eastern Mediterranean and Middle East (EMME) region as a prominent climate change hotspot. While several initiatives have addressed the impacts of climate change in parts of the EMME, here we present an updated assessment, covering a wide range of timescales, phenomena and future pathways. Our assessment is based on a revised analysis of recent observations and projections and an extensive overview of the recent scientific literature on the causes and effects of regional climate change. Greenhouse gas emissions in the EMME are growing rapidly, surpassing those of the European Union, hence contributing significantly to climate change. Over the past half-century and especially during recent decades, the EMME has warmed significantly faster than other inhabited regions. At the same time, changes in the hydrological cycle have become evident. The observed recent temperature increase of about 0.45 degrees C per decade is projected to continue, although strong global greenhouse gas emission reductions could moderate this trend. In addition to projected changes in mean climate conditions, we call attention to extreme weather events with potentially disruptive societal impacts. These include the strongly increasing severity and duration of heatwaves, droughts and dust storms, as well as torrential rain events that can trigger flash floods. Our review is complemented by a discussion of atmospheric pollution and land-use change in the region, including urbanization, desertification and forest fires. Finally, we identify sectors that may be critically affected and formulate adaptation and research recommendations toward greater resilience of the EMME region to climate change.Peer reviewe

Classification of aerosols over Saudi Arabia from 2004–2016

Knowledge of aerosol size and composition is very important for investigating the radiative forcing impacts of aerosols, distinguishing aerosol sources, and identifying harmful particulate types in air quality monitoring. The ability to identify aerosol type synoptically would greatly contribute to the knowledge of aerosol type distribution at both regional and global scales, especially where there are no data on chemical composition. In this study, aerosol classification techniques were based on aerosol optical properties from remotely-observed data from the Ozone Monitoring Instrument (OMI) and Aerosol Robotic Network (AERONET) over Saudi Arabia for the period 2004–2016 and validated using data from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). For this purpose, the OMI-based Aerosol Absorption Optical Depth (AAOD) and Ultra-Violet Aerosol Index (UVAI), and AERONET-based AAOD, Ångström Exponent (AE), Absorption Ångström Exponent (AAE), Fine Mode Fraction (FMF), and Single Scattering Albedo (SSA) were obtained. Spatial analysis of the satellite-based OMI-AAOD showed the dominance of absorbing aerosols over the study area, but with high seasonal variability. The study found significant underestimation by OMI AAOD suggesting that the OMAERUV product may need improvement over bright desert surfaces such as the study area. Aerosols were classified into (i) Dust, (ii) Black Carbon (BC), and (iii) Mixed (BC and Dust) based on the relationships technique, between the aerosol absorption properties (AAE, SSA, and UVAI) and size parameters (AE and FMF). Additionally, the AE vs. UVAI and FMF vs. UVAI relationships misclassified the aerosol types over the study area, and the FMF vs. AE, FMF vs. AAE and FMF vs. SSA relationships were found to be robust. As expected, the dust aerosol type was dominant both annually and seasonally due to frequent dust storm events. Also, fine particulates such as BC and Mixed (BC and Dust) were observed, likely due to industrial activities (cement, petrochemical, fertilizer), water desalination plants, and electric energy generation. This is the first study to classify aerosol types over Saudi Arabia using several different aerosol property relationships, as well as over more than one site, and using data over a much longer time-period than previous studies. This enables classification and recognition of specific aerosol types over the Arabian Peninsula and similar desert regions