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

AbstractThe 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.</jats:p

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

Comparison of a simple logarithmic and equivalent neutral wind approaches for converting buoy-measured wind speed to the standard height: Special emphasis to North Indian Ocean

The difference between the transferred wind speed to 10-m height based on the equivalent neutral wind approach (Un) and the logarithmic approach (Ulog) is studied using in situ observations from the Indian, Pacific, and Atlantic Oceans, with special emphasis given to the North Indian Ocean. The study included Un - Ulog variations with pressure, relative humidity, wind speed, air temperature, and sea surface temperature (SST). Un - Ulog variation with respect to air temperature (Ta) reveals that Un - Ulog is out of phase with air temperature. Further analysis found that Un - Ulog is in phase with SST (Ts) - Ta and varies between -1.0 and 1.0 m/s over the North Indian Ocean, while for the rest of the Oceans, it is between -0.3 and 0.8 m/s. This higher magnitude of Un - Ulog over the North Indian Ocean is due to the higher range of Ts - Ta (-4 to 6 °C) in the North Indian Ocean. Associated physical processes suggested that the roughness length and friction velocity dependence on the air-sea temperature difference contributes to the Un - Ulog difference. The study is further extended to evaluate the behavior of Un - Ulog under cyclonic conditions (winds between 15 and 30 m/s), and it was found that the magnitude of Un - Ulog varies 0. 5-1. 5 m/s under the cyclonic wind conditions. The increasing difference with the wind speed is due to the increase in the momentum transfer coefficient with wind speed, which modifies the friction velocity significantly, resulting in Un higher than Ulog. Thus, under higher wind conditions, Un - Ulog can contribute up to half the retrieval error (5 of the wind speed magnitude) to the satellite validation exercise

Evaluating winter precipitation over the western Himalayas in a high-resolution Indian regional reanalysis using multi-source climate datasets

Considerable uncertainties are associated with precipitation characteristics over the western Himalayan region (WHR). These are due to typically small-scale but high intensity storms caused by the complex topography which are under-resolved by a sparse gauge network. Additionally, both satellite and gauge measurements of precipitation remain subject to systematic errors that typically result in underestimation over mountainous terrains. Reanalysis datasets provide a prospective alternative but are limited by their resolution, which has so far been too coarse to properly resolve orographic rainfall. In this study, we evaluate and cross-compare the Indian Monsoon Data Assimilation and Analysis (IMDAA), the first high-resolution (12 km) regional reanalysis over India, against various precipitation products during the winter season over the western Himalayas. We demonstrate the efficiency of IMDAA in representing the characteristics of winter precipitation at seasonal, diurnal and interannual scales, as well as heavy precipitation associated with western disturbances (WDs). IMDAA shows closer agreement to other reanalyses than to gauge-based and satellite products in error and bias analysis. Although depicting higher magnitudes, its fine resolution allows a much closer insight into localized spatial patterns and diurnal cycle, a key advantage over other datasets. Mean winter precipitation over WHR shows a significant decreasing trend in IMDAA, despite no significant trend in the frequency of WDs tracked in either IMDAA or ERA5. The study also exhibits the potential use of IMDAA for characterizing winter atmospheric dynamics, both for climatological studies and during WD activity such as localized valley wind patterns. Overall, these findings highlight the potential utility for IMDAA in carrying out various monitoring and climate change impact assessment studies over the fragile and vulnerable western Himalayan ecosystem

Enhanced Simulation of the Indian Summer Monsoon Rainfall Using Regional Climate Modeling and Continuous Data Assimilation

This study assesses a Continuous Data Assimilation (CDA) dynamical-downscaling algorithm for enhancing the simulation of the Indian summer monsoon (ISM) system. CDA is a mathematically rigorous technique that has been recently introduced to constrain the large-scale features of high-resolution atmospheric models with coarse spatial scale data. It is similar to spectral nudging but does not require any spectral decomposition for scales separation. This is expected to be particularly relevant for ISM, which involves various interactions between large-scale circulations and regional physical processes. Along with a control simulation, several downscaling simulations were conducted with the Weather Research and Forecasting (WRF) model using CDA, spectral (retaining different wavenumbers) and grid nudging for three ISM seasons: normal (2016), excess (2013), and drought (2009). The simulations are nested within the NCEP Final Analysis and the model outputs are evaluated against the observations. Compared to grid and spectral nudging, the simulations using CDA produce enhanced ISM features over the Indian subcontinent including the low-level jet, tropical easterly jet, easterly wind shear, and rainfall distributions for all investigated ISM seasons. The major ISM processes, in particular the monsoon inversion over the Arabian Sea, tropospheric temperature gradients and moist static energy over central India, and zonal wind shear over the monsoon region, are all better simulated with CDA. Spectral nudging outputs are found to be sensitive to the choice of the wavenumber, requiring careful tuning to provide robust simulations of the ISM system. In contrast, control and grid nudging generally fail to well reproduce some of the main ISM features

Overcoming the kinetic and deactivation limitations of Ni catalyst by alloying it with Zn for the dry reforming of methane

Stimulated by the capacity of Zn to improve the adoption of CO2 and CH4, we doped a Ni-supported ZrO2 catalyst with Zn to enhance its performance and stability in the dry reforming of methane. We prepared a set of catalysts with different Ni:Zn:Zr proportions and conducted extensive ex situ and in situ characterizations to prove that a Ni–Zn alloy was formed at 750 °C under reductive conditions. Combining a tailored morphology of the alloy nanoparticles, strong metal–support (ZnO–ZrO2) interactions, and additional oxygen vacancies created by Zn inclusion resulted in an enhanced catalyst with 15% higher initial activity and higher stability for over 100 h on stream than Zn-free catalyst. Our experimental and modeling results demonstrated that the catalyst with adjusted Ni:Zn:Zr proportion improves the adsorption and reaction rates of CH4 and CO2 while extending its lifetime through enhanced coke precursor gasification compared to its Zn-free counterpart