A study of intense rainfall events in Madeira Island using numerical Models

Located in Atlantic Ocean, the Madeira Island is the largest island of the Madeira archipelago, with surface area about 737 km2, an approximately E–W elongated form and a maximum altitude of 1861m. This archipelago is a volcanic complex, with peculiar relief and climate as described by many researchers. In recent times, intense rainfall events in Madeira Island have occurred, resulting in several economical and social damages. Nowadays, the use of well defined dynamics and different physical processes in high resolution numerical models are becoming popular to predict the isolated heavily extreme rainfall episodes. These type of events that may be predicted by the high resolution numerical weather prediction models, basically depend on the design of the model, especially choice of the domain size, horizontal and vertical grid resolution, time step and usage of different physical processes. Therefore, this study aims at analyzing the main characteristics associated to the intense precipitation events in Madeira Island using numerical simulations. In this study we used the Weather Research Forecasting (WRF-ARW) model developed and distributed through the National Center for Atmospheric Research (NCAR), as well as the MESOscale Non-Hydrostatic model (MESO-NH) jointly developed by Météo-France and the Laboratoire d’Aérologie. Initial and boundary conditions are obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF) forecast models. The events were simulated using nested grids in a two-way interactive mode, in which the inner most domain, at a resolution of 1km, cover the Madeira island. Models configuration included state of art microphysical schemes for stratiform clouds and explicit precipitation. Convection schemes were activated in the coarser models. Several real cases of intense precipitation in Madeira Island were studied, in particular, the case observed on 02nd February 2010, when the Madeira Island was hit by a intense rainfall, responsible by some points of flooding and the disaster on February 20, 2010. The disaster caused more than 40 deaths, several missing and wounded people, as well as a vast range of material losses, including the destruction of houses, industries, roads, bridges and several thousands of vehicles. Initial analysis of these events suggests that the localized heavy rainfall is the product of the features of synoptic scale to local scale. Meteorologically, in the disaster case, there were several factors which contributed to this heavy rainfall event. This included the high latitude block over Greenland and the southward shift of the westerlies. In both cases is clearly possible verify the great influence of a local factor, showing that the application of numerical simulation is very efficient for meteorological studies. The results confirms the ability of high resolution non hydrostatic mesocale models in accurately simulated heavy precipitation events over isolated mountains and allows to quantify the effect of the orography on the precipitation. The results suggest some mechanisms of the generation of high precipitation over the Madeira as some relations between the large scale flow, the atmospheric hydro and thermal structure, the topography and the precipitation

Variabilidade da radiação solar à superfície em Portugal

A radiação solar modela o clima do nosso planeta e quaisquer alterações induz variações de temperatura, humidade, precipitação, etc. A radiação solar é também um factor que condiciona níveis económicos, sociais, ambientais e biológicos. Vários estudos indicam que, entre 1950 e meados da década de 80, se registou uma diminuição na radiação solar global que chega à superfície – fenómeno conhecido por “global dimming.”. Os estudos indicam que posteriormente se observou o efeito contrário – “brightening”. No presente estudo apresentam-se resultados da recolha das séries temporais da radiação solar à superfície medidas em Portugal, em sete estações meteorológicas (Lisboa, Porto, Coimbra, Faro, Évora, Penhas Douradas, Castelo Branco e Bragança), num período não inferior a três décadas (1960-1990). Estas séries são utilizadas para o estudo da variabilidade e o cálculo de tendências da radiação global

Resource tracking within and across continents in long-distance bird migrants

Migratory birds track seasonal resources across and between continents. We propose a general strategy of tracking the broad seasonal abundance of resources throughout the annual cycle in the longest-distance migrating land birds as an alternative to tracking a certain climatic niche or shorter-term resource surplus occurring, for example, during spring foliation. Whether and how this is possible for complex annual spatiotemporal schedules is not known. New tracking technology enables unprecedented spatial and temporal mapping of long-distance movement of birds. We show that three Palearctic-African species track vegetation greenness throughout their annual cycle, adjusting the timing and direction of migratory movements with seasonal changes in resource availability over Europe and Africa. Common cuckoos maximize the vegetation greenness, whereas red-backed shrikes and thrush nightingales track seasonal surplus in greenness. Our results demonstrate that the longest-distance migrants move between consecutive staging areas even within the wintering region in Africa to match seasonal variation in regional climate. End-of-century climate projections indicate that optimizing greenness would be possible but that vegetation surplus might be more difficult to track in the future

Simulation of Surface Ozone Pollution in the Central Gulf Coast Region Using WRF/Chem Model: Sensitivity to PBL and Land Surface Physics

The fully coupled WRF/Chem (Weather Research and Forecasting/Chemistry) model is used to simulate air quality in the Mississippi Gulf coastal region at a high resolution (4 km) for a moderately severe summer ozone episode between 18 CST 7 and 18 CST 10 June 2006. The model sensitivity is studied for meteorological and gaseous criteria pollutants (O3, NO2) using three Planetary Boundary Layer (PBL) and four land surface model (LSM) schemes and comparison of model results with monitoring station observations. Results indicated that a few combinations of PBL and LSMs could reasonably produce realistic meteorological fields and that the combination of Yonsei University (YSU) PBL and NOAH LSM provides best predictions for winds, temperature, humidity and mixed layer depth in the study region for the period of study. The diurnal range in ozone concentration is better estimated by the YSU PBL in association with either 5-layer or NOAH land surface model. The model seems to underestimate the ozone concentrations in the study domain because of underestimation of temperatures and overestimation of winds. The underestimation of NO2 by model suggests the necessity of examining the emission data in respect of its accurate representation at model resolution. Quantitative analysis for most monitoring stations indicates that the combination of YSU PBL with NOAH LSM provides the best results for various chemical species with minimum BIAS, RMSE, and high correlation values

Towards an end-to-end analysis and prediction system for weather, climate, and marine applications in the Red Sea

Author Posting. © American Meteorological Society, 2021. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 102(1), (2021): E99-E122, https://doi.org/10.1175/BAMS-D-19-0005.1.The Red Sea, home to the second-longest coral reef system in the world, is a vital resource for the Kingdom of Saudi Arabia. The Red Sea provides 90% of the Kingdom’s potable water by desalinization, supporting tourism, shipping, aquaculture, and fishing industries, which together contribute about 10%–20% of the country’s GDP. All these activities, and those elsewhere in the Red Sea region, critically depend on oceanic and atmospheric conditions. At a time of mega-development projects along the Red Sea coast, and global warming, authorities are working on optimizing the harnessing of environmental resources, including renewable energy and rainwater harvesting. All these require high-resolution weather and climate information. Toward this end, we have undertaken a multipronged research and development activity in which we are developing an integrated data-driven regional coupled modeling system. The telescopically nested components include 5-km- to 600-m-resolution atmospheric models to address weather and climate challenges, 4-km- to 50-m-resolution ocean models with regional and coastal configurations to simulate and predict the general and mesoscale circulation, 4-km- to 100-m-resolution ecosystem models to simulate the biogeochemistry, and 1-km- to 50-m-resolution wave models. In addition, a complementary probabilistic transport modeling system predicts dispersion of contaminant plumes, oil spill, and marine ecosystem connectivity. Advanced ensemble data assimilation capabilities have also been implemented for accurate forecasting. Resulting achievements include significant advancement in our understanding of the regional circulation and its connection to the global climate, development, and validation of long-term Red Sea regional atmospheric–oceanic–wave reanalyses and forecasting capacities. These products are being extensively used by academia, government, and industry in various weather and marine studies and operations, environmental policies, renewable energy applications, impact assessment, flood forecasting, and more.The development of the Red Sea modeling system is being supported by the Virtual Red Sea Initiative and the Competitive Research Grants (CRG) program from the Office of Sponsored Research at KAUST, Saudi Aramco Company through the Saudi ARAMCO Marine Environmental Center at KAUST, and by funds from KAEC, NEOM, and RSP through Beacon Development Company at KAUST

Effects of multi-observations uncertainty and models similarity on climate change projections

Abstract Climate change projections (CCPs) are based on the multimodel means of individual climate model simulations that are assumed to be independent. However, model similarity leads to projections biased toward the largest set of similar models and intermodel uncertainty underestimation. We assessed the influences of similarities in CMIP6 through CMIP3 CCPs. We ascertained model similarity from shared physics/dynamics and initial conditions by comparing simulated spatial temperature and precipitation with the corresponding observed patterns and accounting for intermodel spread relative to the observational uncertainty, which is also critical. After accounting for similarity, the information from 57 CMIP6, 47 CMIP5, and 24 CMIP3 models can be explained by just 11 independent models without significant differences in globally averaged climate change statistics. On average, independent models indicate a lower global-mean temperature rise of 0.25 °C (~0.5 °C–1 °C in some regions) relative to all models by the end of the 21st century under CMIP6’s highest emission scenario

Inter annual variability of surface solar radiation over Iberian Peninsula

In this study, the variability and trends of surface radiation over the Iberian Peninsula using ERA40 reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) are examined. Monthly means of surface incident and net shortwave radiation for 40 years are computed and analyzed. Deviations from the temporal mean for each month and for each year are computed and variations discussed. The relation between the interannual variability of solar radiation over Iberian Peninsula and the cloud cover is analyzed. The trends of surface radiation for each month during the past decades are computed and discussed

A Regional Climate Simulation Study Using WRF-ARW Model over Europe and Evaluation for Extreme Temperature Weather Events

In this study regional climate simulations of Europe over the 60-year period (1950–2010) made using a 25 km resolution WRF model with NCEP 2.5 degree analysis for initial/boundary conditions are presented for air temperature and extreme events of heat and cold waves. The E-OBS 25 km analysis data sets are used for model validation. Results suggest that WRF could simulate the temperature trends (mean, maximum, minimum, seasonal maximum, and minimum) over most parts of Europe except over Iberian Peninsula, Mediterranean, and coastal regions. Model could simulate the slight fall of temperatures from 1950 to 1970 as well as steady rise in temperatures from 1970 to 2010 over Europe. Simulations show occurrence of about 80% of the total heat waves in the period 1970–2010 with maximum number of heat/cold wave episodes over Eastern and Central Europe in good agreement with observations. Relatively poor correlations and high bias are found for heat/cold wave episodes over the complex topographic areas of Iberia and Mediterranean regions where land surface processes play important role in local climate. The poor simulation of temperatures over the above regions could be due to deficiencies in representation of topography and surface physics which need further sensitivity studies

Fabrication of praseodymium-doped ceria (PDC) films by slurry spin-coating technique and its structural, morphological and optical properties

The current study is on the fabrication of PDC films prepared by slurry spin-coating technique for photoluminescence activity. At lower spin rates (1000 rpm), thicker and uniform PDC films were obtained. The structural evolution of the sintered PDC films on a dense alumina substrate was studied using Grazing Incidence X-ray diffraction (GIXRD) and Raman Spectroscopy. Crystallite size, microstrain, and dislocation density values remain almost the same with the increase in the coating cycles. The A568/A463 ratio for 3, 5, and 10 coating cycles are 0.52, 0.49, and 0.61, respectively. Surface roughness studies of PDC films using a 3D Noncontact Profilometer. The mean surface roughness values are 12.55, 13.74, and 22.25 μm for the 3rd,5th, and 10th coating cycles, respectively. Microstructure observation by Field Emission Scanning Electron Microscope (FE-SEM). The average thickness of the films for the 3rd, 5th, and 10th coating cycles are 50.93, 41.64, and 109.95 μm, respectively. The PDC films obtained on a dense alumina substrate were porous. FE-SEM micrographs showed a particle aggregation of several irregular and smaller grains, indicating the sintering activity of PDC films. Optical properties were studied using ultraviolet-visible (UV–Vis) absorption spectra and photoluminescence spectra (PLS). The band gap values slightly increased with the increase in the coating cycles. A decrease in PL intensity with an increase in the coating cycle is related to higher oxygen vacancy concentration. PDC films fabricated by the slurry spin-coating technique can be successfully used for optoelectronic applications

Long‐Term Variability in the Arabian Peninsula Droughts Driven by the Atlantic Multidecadal Oscillation

Abstract Drought is a recurring hydroclimatic extreme over the Arabian Peninsula (AP). So far, no study has examined the changes in drought characteristics in recent decades, not to mention the background mechanisms for such changes. To this end, analyzing the Standardized Precipitation Evapotranspiration Index (SPEI) mainly from the European Reanalysis (ERA5) data sets, in addition to other observational/reanalysis data sets over the period of 1951–2020, we show that droughts over the AP have increased in frequency and severity over the last two decades. We show that this drought acceleration, which was not observed in the previous 40–50 years, is a combination of decadal variability and long‐term trends. Importantly, we demonstrate that the decadal SPEI variability is due to the Atlantic Multidecadal Oscillation (AMO). The unprecedented multiyear drought over the AP in recent decades is evidently associated with the current positive phase of the AMO. We also show that the recent warming of the AP is a more significant factor in the drought intensification than the concurrent weakening of local precipitation. Furthermore, we developed a machine learning model largely based on the observed AMO–SPEI relationship. This model predicts a reduced drought severity over the AP in the near future