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During the Deepwater Horizon (DWH) blowout, photooxidation of surface oil led to the formation of persistent photooxidized compounds, still found in shoreline sediments a decade later. Studies demonstrated that photooxidation modified both biodegradation rates of the surface oil and the effectiveness of aerial dispersant applications. Despite the significant consequences of this weathering pathway, the lack of measurements prevented photooxidation to be accounted for in the DWH oil budget calculations and in most predictive models. Here we develop a Lagrangian photooxidation module that estimates the dose of solar radiation individual oil droplets receive while moving in the ocean, quantifies the likelihood of photooxidative changes, and continues to track the transport of these persistent photooxidized compounds. We estimate and track the likelihood of photooxidation of Lagrangian oil droplets in the upper layers of the water column for the DWH case by coupling the net shortwave radiation from NOGAPS to the oil application of the Connectivity Modeling System (oil-CMS). The dose of solar radiation upon a droplet is computed with the intensity of the incoming irradiance at the ocean’s surface, the light attenuation coefficient, and the depth of the oil droplets. Considering a range of DWH empirical irradiance thresholds, we find that photooxidation can happen at short time scales of hours to days, in agreement with the new paradigm of oil photooxidation. Furthermore, the oxidized compounds are likely to form in a 110 km radius around the response site, suggesting that the oil reaching the coastline was already photooxidized. This new dynamic coupling provides a powerful tool to test oil weathering hypotheses, refine the oil budget during the DWH, and ultimately inform rapid response in future oil spills.

This study has examined both: (i) the global structure and seasonal variability of the eastward- and westward-travelling quasi 6-day waves (Q6DWs) observed in the geopotential height (GPH) NOGAPS-ALPHA hourly forecast data during the time interval of 14 months (January 2009–February 2010), and (ii) the climatology and interannual variability of the Q6DWs observed in the satellite MLS/Aura GPH data for an extended period of 10 years (January 2005–December 2014). Both data sets are analyzed by using the same approach. The detailed analysis revealed that the westward-travelling Q6DWs have been identified mainly at mid-high latitudes with zonal wave numbers 1 and 2. Two different types of eastward-travelling waves have been found: (i) waves at middle and high latitudes with zonal wave numbers 1 and 2, which are observed in the local winters, and (ii) waves observed over the equator with zonal wave number 1, which maximize mainly between June and September with a secondary enhancement between January–March belonging to the fast Kelvin waves. Some signatures of the solar cycle and SSW impact on the interannual variability as well as ∼2–3-year variability have been distinguished in the different ∼6-day waves. This study draws attention to both the rarely studied winter-time eastward-travelling PWs and the impact of the SSW events, particularly the major ones, on the short- and long-term variability of the PW populations.

We investigate the benefit of high altitude nudging in simulations of the structure and short-term variability of the upper mesosphere and lower thermosphere (UMLT) dynamical meteorology during boreal winter, specifically around the time of the January 2009 sudden stratospheric warming. We compare simulations using the Specified Dynamics, Whole Atmosphere Community Climate Model, extended version, nudged using atmospheric specifications generated by the Navy Operational Global Atmospheric Prediction System, Advanced Level Physics High Altitude. Two sets of simulations are carried out: one uses nudging over a vertical domain from 0-90 km; the other uses nudging over a vertical domain from 0-50 km. The dynamical behavior is diagnosed from ensemble mean and standard deviation of winds, temperature, and zonal accelerations due to resolved and parameterized waves. We show that the dynamical behavior of the UMLT is quite different in the two experiments, with prominent differences in the structure and variability of constituent transport. We compare the results of our numerical experiments to observations of carbon monoxide by the Atmospheric Chemistry Experiment – Fourier Transform Spectrometer to show that the high-altitude nudging is capable of reproducing with high fidelity the observed variability, and traveling planetary waves are a crucial component of the dynamics. The results of this study indicate that to capture the key physical processes that affect short-term variability (defined as the atmospheric behavior within about 10 days of a stratospheric warming) in the UMLT, specification of the atmospheric state in the stratosphere alone is not sufficient, and upper atmospheric specifications are needed.

The main stages are considered of the process of Roshydromet forecast technologies modernization that started in the 1990s, especially those related to the use of supercomputers for operational numerical weather prediction (NWP) and to the development of supercomputer technologies for NWP with different lead times. Some outcomes of the modernization are presented.

Since October 2013 a convective-scale weather prediction model has been used operationally to provide short-term forecasts covering large parts of the Nordic region. The model is now operated by a bilateral cooperative effort [Meteorological Cooperation on Operational Numerical Weather Prediction (MetCoOp)] between the Norwegian Meteorological Institute and the Swedish Meteorological and Hydrological Institute. The core of the model is based on the convection-permitting Applications of Research to Operations at Mesoscale (AROME) model developed by Météo-France. In this paper the specific modifications and updates that have been made to suit advanced high-resolution weather forecasts over the Nordic regions are described. This includes modifications in the surface drag description, microphysics, snow assimilation, as well as an update of the ecosystem and surface parameter description. Novel observation types are introduced in the operational runs, including ground-based Global Navigation Satellite System (GNSS) observations and radar reflectivity data from the Norwegian and Swedish radar networks. After almost two years’ worth of experience with the AROME-MetCoOp model, the model’s sensitivities to the use of specific parameterization settings are characterized and the forecast skills demonstrating the benefit as compared with the global European Centre for Medium-Range Weather Forecasts’ Integrated Forecasting System (ECMWF-IFS) are evaluated. Furthermore, case studies are provided to demonstrate the ability of the model to capture extreme precipitation and wind events.

Forecast solar exposure fields produced by the Australian Bureau of Meteorology’s updated numerical weather prediction systems were validated against multiple sites for the 2012 calendar year. The updated systems are denoted as the Australian Community Climate and Earth-System Simulator (ACCESS) model and became operational in August 2010. The systems are based on the Met Office’s Unified Model and feature improved assimilation methods and radiation parameterizations that were expected to greatly improve forecasts of solar exposure several days in advance. In this study forecasts of global, direct, and diffuse exposure from the mesoscale model ACCESS-A were validated. Statistics were generated for all-sky and clear-sky conditions. Additionally, evaluation of the model’s forecast exposure through single-layer low clouds was conducted. Results show an improvement in global forecasts relative to the older operational model; however, forecasts of diffuse and direct exposure still suffer from large biases. These can be attributed to the choices of the asymmetry factor used in the two-stream approximation for incoming radiation, which determines scattering of the direct beam through clouds.

A global deterministic wave prediction system (GDWPS) is used to improve regional forecasts of waves off the Canadian coastline and help support the practice of safe marine activities in Canadian waters. The wave model has a grid spacing of ¼° with spectral resolution of 36 frequency bins and 36 directional bins. The wave model is driven with hourly 10-m winds generated by the operational global atmospheric prediction system. Ice conditions are updated every three hours using the ice concentration forecasts generated by the Global Ice–Ocean Prediction System. Wave forecasts are evaluated over two periods from 15 August to 31 October 2014 and from 15 December 2014 to 28 February 2015, as well as over select cases during the fall of 2012. The global system is shown to improve wave forecast skill over regions where forecasts were previously produced using limited-area models only. The usefulness of a global expansion is demonstrated for large swell events affecting the northeast Pacific. The first validation of a Canadian operational wave forecast system in the Arctic is presented. Improvements in the representation of forecast wave fields associated with tropical cyclones are also demonstrated. Finally, the GDWPS is shown to result in gains of at least 12 h of lead time.

The refined Cloud Imaging and Particle-Size (CIPS) cloud wind tracking algorithm is elaborated and the wind product is assessed against the Navy Operational Global Atmospheric Prediction System - Advanced Level Physics and High Altitude (NOGAPS-ALPHA) winds and the horizontal wind model (HWM14) climatological winds. Multiple searching frame sizes are adopted to generate the preliminary wind sets which are then merged and further edited based on the clustering of the similar wind directions (±20°). The mean values of the clusters within the sampling grids of 1.5 ° × 1.5 ° or 4.5 ° × 4.5 ° are taken as the final wind product. At the coincidences the CIPS and NOGAPS winds show a moderate degree of deterministic consistency. We have further shown that on the orbit-to-orbit basis when the NOGAPS modeled ice and CIPS measured ice correlate better, the wind agreement is also better. The difference in the two wind sets is most likely attributed to the NOGAPS temperature being deviated from the true temperature that will affect the geostrophic component of the winds and also to the fact that the CIPS winds are often ageostrophic and are cascaded into smaller scales. The CIPS zonal (westward) winds are decreased and then reversed in early June and late August whereas in the core of the season they are stronger. This overall variation pattern is shared by both NOGAPS and HWM14 zonal winds. Both NOGAPS and HWM14 zonal winds exhibit ~8–10 m/s difference between cases using all local times (LTs) and the CIPS LT range 13–23 h due to the dominant diurnal migrating tides, and this may partially interpret the weaker CIPS zonal winds. The meridional (equatorward) winds do not follow any established intra-seasonal variation pattern but rather the variability is susceptible to the sampling longitudes/latitudes.

This study presents the assessment and seasonal variation of wave energy along the southern coast of Java, Bali, and Nusa Tenggara Waters. For this purpose, the WAVEWATCH-III numerical model was used to simulate the Significant Wave Height in the study region over 25 years covering the time interval of 1991–2015. Wind field data input for the model was a combined dataset of Cross-Calibrated Multi-Platform, Navy Global Environmental Model, and Navy Operational Global Atmospheric Prediction System. In general, the simulation results showed that there was a good potential of wave energy along the southern coast of Java and Bali with the value of higher than 20 kW/m. Furthermore, it was found that there were 12 points which were considered to be the most promising high wave energy potential spots along the near-shore coastal waters of the Java and Bali southern coast. There was a noticeable seasonal variation of wave energy along the study area associated with tropical monsoon climates, which led to the highest value in the period of June to August for about 40 kW/m and the lowest value in the period of December to February for about 20 kW/m. All the selected points for wave energy exhibited dominant wave propagation between northward and northeastward. Moreover, there was an evident increasing trend of wave energy with the peak value appearing in 2005 for all stations.

Indonesia is passed by an atmospheric phenomenon, called the Madden-Julian Oscillation (MJO), which has an impact on the wave height in the Indonesian Seas. The significant wave height is simulated using WAVEWATCH-III (WW3) numerical model in Indonesian region (90 °E-150 °E, 20 °N-20 °S) forced by surface winds from Cross-Calibrated Multi-Platform (CCMP), Navy Global Environmental Model (NAVGEM), and Navy Operational Global Atmospheric Prediction System (NOGAPS). This simulation is concentrated on MJO phase 3, 4, and 5 which passed through Indonesia and its adjacent waters that occurred in particular time between 1990-2015. In this study, the impact of MJO was analyzed during every monsoon season. In addition, wind speed analysis was carried out to further enrich the analysis of the MJO impact. The simulation result shows that MJO exerts the highest impact during phase 5 and DJF, which contributes to the increase of wind speed (WS) and significant wave height (SWH) in Indonesian inner seas by 6 m/s and 30 cm, respectively, and in southern Lesser Sunda Island by 8 m/s and 1.2 m, respectively. MJO can also contribute to decreasing of the WS and SWH, when it occurred during DJF and MAM phase 3, and JJA phase 4. There is no noticabe change of WS and SWH during SON.

Numerical weather prediction systems generate very large amounts of output data. This chapter considers two different use cases for which cloud computing can be of use: • the routine dissemination of model output data in a timely fashion; • the provision of very large research data sets. This is done in the context of the data produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), an intergovernmental organization that is both a 24/7 operational service and a research institute.