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This work aims to better understand how small scale disturbances that are generated at the air-sea interface propagate into the surrounding atmosphere under realistic environmental conditions. To that end, a one-way coupled atmosphere-ocean model is presented, in which predictions of sea surface currents and sea surface temperatures from a microscale ocean model are used as constant boundary conditions in a larger atmospheric model. The coupled model consists of an ocean component implemented while using the open source CFD software OpenFOAM, an atmospheric component solved using the Weather Research and Forecast (WRF) model, and a Python-based utility foamToWRF, which is responsible for mapping field data between the ocean and atmospheric domains. The results are presented for two demonstration cases, which indicate that the proposed coupled model is able to capture the propagation of small scale sea surface disturbances in the atmosphere, although a more thorough study is required in order to properly validate the model.

In this study, a global atmospheric model, Specified Dynamics Whole Atmosphere Community Climate Model with thermosphere and ionosphere eXtension (SD-WACCM-X), and the residual circulation principle were used to study the global atmospheric circulation from the lower to upper atmosphere (~500 km) from 2002 to 2019. Our analysis shows that the atmospheric circulation is clearly influenced by solar activity, especially in the upper atmosphere, which is mainly characterized by an enhanced atmospheric circulation in years with high solar activity. The atmospheric circulation in the upper atmosphere also exhibits an ~11 year period, and its variation is highly correlated with the temporal variation in the F10.7 solar index during the same time series, with a maximum correlation coefficient of up to more than 0.9. In the middle and lower atmosphere, the impact of solar activity on the atmospheric circulation is not as obvious as in the upper atmosphere due to some atmospheric activities such as the Quasi-Biennial Oscillation (QBO), El Niño–Southern Oscillation (ENSO), sudden stratospheric warming (SSW), volcanic forcing, and so on. By comparing the atmospheric circulation in different latitudinal regions between years with high and low solar activity, we found the atmospheric circulation in mid- and high-latitude regions is more affected by solar activity than in low-latitude and equatorial regions. In addition, clear seasonal variation in atmospheric circulation was detected in the global atmosphere, excluding the regions near 10−4 hPa and the lower atmosphere, which is mainly characterized by a flow from the summer hemisphere to the winter hemisphere. In the middle and low atmosphere, the atmospheric circulation shows a quasi-biennial oscillatory variation in the low-latitude and equatorial regions. This work provides a referable study of global atmospheric circulation and demonstrates the impacts of solar activity on global atmospheric circulation.

This study analyzes the variability of the Choco jet (CJ) and Caribbean low-level jet (CLLJ) with consideration of the simultaneous Pacific interdecadal oscillation (PDO) and Atlantic multidecadal oscillation (AMO) low-frequency mean states and their effects on the atmospheric circulation and rainfall in northwestern South America and Central America for the 1900–2015 period, during the seasons with the highest intensities of the CJ (September–November (SON)) and the CLLJ (June–August). Variations in the sea surface temperature (SST) anomaly positioning in the eastern Pacific, tropical North Atlantic (TNA)/Caribbean Sea during different mean states restrict the anomalous circulation, and, consequently, the intensity of the CJ and CLLJ. During the warm AMO (WAMO)/cold PDO (CPDO), the SST gradient from the tropical Pacific into the TNA, accompanied by a cyclonic circulation near the east coast of the Americas, intensifies the west–east circulation in the region, strengthening the CJ and weakening the CLLJ during SON such that rainfall increases over Colombia, Central America and in adjacent oceans. During the cold AMO (CAMO)/warm PDO (WPDO) phase, a relative east/west SST gradient occurs in TNA, consistent with a cyclonic circulation in western TNA, establishing an anomalous southwest–northwestward circulation from the eastern Pacific into the Caribbean basin, forming a well-configured CJ, increasing precipitation over Central America and its adjacent oceans. For the CLLJ, during CAMO phases, the anticyclonic circulations extended over most of the TNA favor its intensification from 30° W to the Caribbean Sea. In contrast, during WAMO, the cyclonic circulation near the east coast of the United States restricts its intensification to the Caribbean Sea region. To the best of our knowledge, the results presented here are new and might be useful in atmospheric modeling and extreme event studies.

Solar eclipses are astronomic phenomena in which the Earth’s moon transits between the planet and the Sun, projecting a shadow onto the planet’s surface. As solar power installed capacity increases, detailed studies of this region-wide phenomenon’s effect in irradiance is of interest; however, the literature mainly reports its effects on localized scales. A measurement campaign spanning over 1400 km was pursued for the 2 July 2019 total solar eclipse in Chile, to register the event and establish a modeling framework to assess solar eclipse effects in irradiance over wide regional scales. This work describes the event and presents an estimation framework to decompose atmospheric and eclipse effects on irradiance. An analytical model was applied to study irradiance attenuation throughout the Chilean mainland territory, using satellite-derived and astronomical data as inputs compared to ground measurements in eight stations. Results showed good agreement between model and observations, with Mean Bias Errors of −0.008 to 0.98 W/m2 for Global Horizontal Irradiance and −0.004 to −4.664 W/m2 for Direct Normal Irradiance, with Normalized Root Mean Squared Errors of 0.7–5.8% and 1.4–12.2%, respectively. Energy losses due to obscuration corresponded between 20–40% for Global Horizontal Irradiance and 25–50% for Direct Normal Irradiance over Chilean territory.

Local air-sea interaction over the Mediterranean may amplify the effects of climate change. This study investigates the sensitivity of simulations of two different high impact weather events to changes in the specification of sea surface temperature (SST) using a regional atmospheric model. First we assess the impact of specifying SST from two reanalysis data sets with differing spatial resolution. The simulated tropical-like cyclone (TLC) is slightly stronger in the case of the lower resolution SST which is warmer over the formation region, most notably in the maximum rainfall which is ~7% higher. The differences in the two explosive cyclone simulations are negligible, most likely due to intensification occurring mainly over land. We then test the sensitivity of the storms to a range of SST anomalies. The TLC showed a clear trend of increasing storm intensity as SST rises. These results suggest that SST plays a direct role in determining the intensity of the storm. For the explosive cyclone there is no clear trend in dynamical intensity except for the highest warming anomalies. However, the rainfall increases with the magnitude of the SST anomaly. Our results suggest that extreme weather events over the Mediterranean will become more extreme if SST increases as the climate warms, assuming that upper air conditions do not change.

Diverse and severe weather conditions and rapid climate change rates in the Arctic emphasize the need for high-resolution climatic and environmental data that cannot be obtained from the scarce observational networks. This study presents a new detailed hydrometeorological dataset for the Russian Arctic region, obtained as a long-term hindcast with the nonhydrostatic atmospheric model COSMO-CLM for the 1980–2016 period. The modeling workflow, evaluation techniques, and preliminary analysis of the obtained dataset are discussed. The model domain included the Barents, Kara, and Laptev Seas with ≈12-km grid spacing. The optimal model setup was chosen based on preliminary simulations for several summer and winter periods with varied options, and included the usage of ERA-Interim reanalysis data as forcing data, the new model version 5.05 with so-called ICON-based physics, and a spectral nudging technique. The wind speed and temperature climatology in the new COSMO-CLM dataset closely agreed with the ERA-Interim reanalysis, but with detailed spatial patterns. The added value of the higher-resolution COSMO-CLM data with respect to the ERA-Interim was most pronounced for higher wind speeds during downslope windstorms with the influence of mountain ranges on the temperature patterns, including surface temperature inversions. The potential applications and plans of further product development are also discussed.

This work added semi-Lagrangian convected air particles to the Intermediate Complexity Atmospheric Research (ICAR) model. The ICAR model is a simplified atmospheric model using quasi-dynamical downscaling to gain performance over more traditional atmospheric models. The ICAR model uses Fortran coarrays to split the domain amongst images and handle the halo region communication of the image’s boundary regions. The newly implemented convected air particles use trilinear interpolation to compute initial properties from the Eulerian domain and calculate humidity and buoyancy forces as the model runs. This paper investigated the performance cost and scaling attributes of executing unsaturated and saturated air particles versus the original particle-less model. An in-depth analysis was done on the communication patterns and performance of the semi-Lagrangian air particles, as well as the performance cost of a variety of initial conditions such as wind speed and saturation mixing ratios. This study found that given a linear increase in the number of particles communicated, there is an initial decrease in performance, but that it then levels out, indicating that over the runtime of the model, there is an initial cost of particle communication, but that the computational benefits quickly offset it. The study provided insight into the number of processors required to amortize the additional computational cost of the air particles.

Geomagnetic storm is one of the most powerful factors affecting the state of the Earth&rsquo, s ionosphere. Revealing the significance of formation mechanisms for ionospheric storms is still an unresolved problem. The purpose of the study is to obtain a statistical pattern of the response in regional electron content to geomagnetic storms on a global scale to interpret the results using the upper atmosphere model (the Global Self-consistent Model of the Thermosphere, Ionosphere, and Protonosphere), to make the detailed comparison with the thermospheric storm concept, and to compare the obtained pattern with results from previous statistical studies. The regional electron content is calculated based on the global ionospheric maps data, which allows us to cover the midlatitude and high-latitude zones of both hemispheres, as well as the equatorial zone. Most of the obtained statistical pattern agrees with the thermospheric storm concept and with the previous statistical studies: ionospheric responses at ionospheric storm main phases including their seasonal dependences for the high- and midlatitudes and some features of ionospheric responses at recovery phases. However, some of the statistical patterns are inconsistent with the thermospheric storm concept or contradicts the previous statistical studies: negative midlatitude ionospheric responses at recovery phases in the local winter, the domination of the spring response in the equatorial zone, seasonal features of the positive after-effects, the interhemispheric asymmetry of ionospheric responses, and the prestorm enhancement. We obtained that the contribution of electric field to the interpretation of the zonal and diurnal averaged storm-time regional electron content (REC) disturbances is insignificant. The positive after-storm effects at different latitudes are caused by n(O) disturbances.

In atmospheric modeling, an accurate representation of land cover is required because such information impacts water and energy budgets and, consequently, the performance of models in simulating regional climate. This study analyzes the impact of the land cover data on an operational weather forecasting system using the Weather Research and Forecasting (WRF) model for central Mexico, with the aim of improving the quality of the operative forecast. Two experiments were conducted using different land cover datasets: a United States Geological Survey (USGS) map and an updated North American Land Change Monitoring System (NALCMS) map. The experiments were conducted as a daily 120 h forecast for each day of January, April, July, and September of 2012, and the near-surface temperature, wind speed, and hourly precipitation were analyzed. Both experiments were compared with observations from meteorological stations. The statistical analysis of this study showed that wind speed and near-surface temperature prediction may be further improved with the updated and more accurate NALCMS dataset, particularly in the forecast covering 48 to 72 h. The Root Mean Square Error (RMSE) of the average wind speed reached a maximum reduction of up to 1.2 m s&minus, 1, whereas for the near-surface temperature there was a reduction of up to 0.6 &deg, C. The RMSE of the average hourly precipitation was very similar between both experiments, however the location of precipitation was modified.

Coastal Arctic regions are characterized by severe mesoscale weather events that include extreme wind speeds, and the rugged shore conditions, islands, and mountain ranges contribute to mesoscale event formation. High-resolution atmospheric modeling is a suitable tool to reproduce and estimate some of these events, and so the regional non-hydrostatic climate atmospheric model COSMO-CLM (Consortium for Small-scale Modeling developed within the framework of the international science group CLM-Community) was used to reproduce mesoscale circulation in the Arctic coast zone under various surface conditions. Mid-term experiments were run over the Arctic domain, especially over the Kara Sea region, using the downscaling approach, with &asymp, 12 km and &asymp, 3 km horizontal grid sizes. The best model configuration was determined using standard verification methods, however, the model run verification process raised questions over its quality and aptness based on the high level of small-scale coastline diversity and associated relief properties. Modeling case studies for high wind speeds were used to study hydrodynamic mesoscale circulation reproduction, and we found that although the model could not describe the associated wind dynamic features at all scales using &asymp, 3 km resolution, it could simulate different scales of island wind shadow effects, tip jets, downslope winds, vortex chains, and so on, quite realistically. This initial success indicated that further research could reveal more about the detailed properties of mesoscale circulations and extreme winds by applying finer resolution modeling.

Forecasting fire growth, plume rise and smoke impacts on air quality remains a challenging task. Wildland fires dynamically interact with the atmosphere, which can impact fire behavior, plume rises, and smoke dispersion. For understory fires, the fire propagation is driven by winds attenuated by the forest canopy. However, most numerical weather prediction models providing meteorological forcing for fire models are unable to resolve canopy winds. In this study, an improved canopy model parameterization was implemented within a coupled fire-atmosphere model (WRF-SFIRE) to simulate a prescribed burn within a forested plot. Simulations with and without a canopy wind model were generated to determine the sensitivity of fire growth, plume rise, and smoke dispersion to canopy effects on near-surface wind flow. Results presented here found strong linkages between the simulated fire rate of spread, heat release and smoke plume evolution. The standard WRF-SFIRE configuration, which uses a logarithmic interpolation to estimate sub-canopy winds, overestimated wind speeds (by a factor 2), fire growth rates and plume rise heights. WRF-SFIRE simulations that implemented a canopy model based on a non-dimensional wind profile, saw significant improvements in sub-canopy winds, fire growth rates and smoke dispersion when evaluated with observations.

Weather and climate extremes, such as heat waves (HWs), have become more frequent due to climate change, resulting in negative environmental and socioeconomic impacts in many regions of the world. The high vulnerability of South African society to the impacts of warm extreme temperatures makes the study of the effect of climate change on future HWs necessary across the country. We investigated the projected effect of climate change on future of South Africa with a focus on HWs using an ensemble of regional climate model downscalings obtained from the Conformal Cubic Atmospheric Model (CCAM) for the periods 2010&ndash, 2039, 2040&ndash, 2069, and 2070&ndash, 2099, with 1983&ndash, 2012 as the historical baseline. Simulations were performed under the Representative Concentration Pathway (RCP) 4.5 (moderate greenhouse gas (GHG) concentration) and 8.5 (high GHG concentration) greenhouse gas emission scenarios. We found that the 30-year period average maximum temperatures may rise by up to 6 &deg, C across much of the interior of South Africa by 2070&ndash, 2099 with respect to 1983&ndash, 2012, under a high GHG concentration. Simulated HW thresholds for all ensemble members were similar and spatially consistent with observed HW thresholds. Under a high GHG concentration, short lasting HWs (average of 3&ndash, 4 days) along the coastal areas are expected to increase in frequency in the future climate, however the coasts will continue to experience HWs of relatively shorter duration compared to the interior regions. HWs lasting for shorter duration are expected to be more frequent when compared to HWs of longer durations (over two weeks). The north-western part of South Africa is expected to have the most drastic increase in HWs occurrences across the country. Whilst the central interior is not projected to experience pronounced increases in HW frequency, HWs across this region are expected to last longer under future climate change. Consistent patterns of change are projected for HWs under moderate GHG concentrations, but the changes are smaller in amplitude. Increases in HW frequency and duration across South Africa may have significant impacts on human health, economic activities, and livelihoods in vulnerable communities.

The optimization of outdoor thermal comfort has become the keystone to guarantee the healthy and comfortable use of outdoor spaces. This study aims to optimize the outdoor thermal comfort through vegetation parameterization in a boulevard located in Guelma city, Algeria during summertime. However, two main parameters were investigated, species and tree layout, through a numerical simulation. We first collected microclimate data of a sunny summer day. Second, we used real microclimate data in different simulations using the Envi-met atmospheric model. The findings reveal that Ficus Nitida is the most significant species to intercept solar radiation and provide shade over the day in Souidani Boudjemaa Boulevard, with a maximum reduction of Ta = 0.3 °C and UTCI = 2.6 °C at 13:00 p.m. Tree layout is a determining parameter in the creation of shaded paths, based on the quality of the shadows cast by the trees, namely, their size. Thereby, planting the washingtonia palm trees along the center of the boulevard is the best option to maximize the shaded area within the boulevard, with maximum reduction of Ta = 1.8 °C and UTCI = 3.5 °C at 16:00 p.m.

Precise point positioning (PPP) with ambiguity resolution (AR) can improve positioning accuracy and reliability. The narrow-lane (NL) AR solution can reach centimeter-level accuracy but there is a certain initialization time. In contrast, extra-wide-lane (EWL) or wide-lane (WL) ambiguity can be fixed instantaneously. However, due to the limited correction accuracy of the empirical atmospheric model, the positioning accuracy is only a few decimeters. In order to further improve the real-time performance of PPP while ensuring accuracy, we developed a multi-system multi-frequency uncombined PPP single-epoch EWL/WL/NL AR method with regional atmosphere modelling. In the proposed method, the precise atmosphere, including zenith wet-troposphere delay (ZWD) and the slant ionosphere, is extracted through multi-frequency stepwise AR, which then is both interpolated and broadcast to users. By adding regional atmosphere constraints, users can achieve single-epoch PPP AR with centimeter-level accuracy. To verify the algorithm, four sets of reference networks with different inter-station distances are used for experiments. With atmosphere constraints, the accuracy of the single-epoch WL solution can be improved from the decimeter level to a few centimeters, with an improvement of more than 90%, and the epoch fix rate can also be improved to varying degrees, especially for the dual-frequency case. Due to the enlarged noise of the EWL combination, its accuracy is at the decimeter level, while the accuracy of the WL/NL solution can reach several centimeters. However, reliable NL ambiguity-fixing tightly relies on atmosphere constraints with sufficiently high accuracy. When the modelling of the atmosphere correction is not accurate enough, the NL AR performance is degraded, although this situation can be improved to a certain extent through the multi-GNSS combination. In contrast, in this case, the WL ambiguity can be successfully fixed and can support the precise positioning with an accuracy of several centimeters.

形態: カラー図版あり, Physical characteristics: Original contains color illustrations, Accepted: 2021-07-28, 資料番号: PA2210061000

In the event of an accidental or intentional hazardous material release in the atmosphere, researchers often run physics-based atmospheric transport and dispersion models to predict the extent and variation of the contaminant spread. These predictions are imperfect due to propagated uncertainty from atmospheric model physics (or parameterizations) and weather data initial conditions. Ensembles of simulations can be used to estimate uncertainty, but running large ensembles is often very time consuming and resource intensive, even using large supercomputers. In this paper, we present a machine-learning-based method which can be used to quickly emulate spatial deposition patterns from a multi-physics ensemble of dispersion simulations. We use a hybrid linear and logistic regression method that can predict deposition in more than 100,000 grid cells with as few as fifty training examples. Logistic regression provides probabilistic predictions of the presence or absence of hazardous materials, while linear regression predicts the quantity of hazardous materials. The coefficients of the linear regressions also open avenues of exploration regarding interpretability—the presented model can be used to find which physics schemes are most important over different spatial areas. A single regression prediction is on the order of 10,000 times faster than running a weather and dispersion simulation. However, considering the number of weather and dispersion simulations needed to train the regressions, the speed-up achieved when considering the whole ensemble is about 24 times. Ultimately, this work will allow atmospheric researchers to produce potential contamination scenarios with uncertainty estimates faster than previously possible, aiding public servants and first responders.

In this study, the climatological precipitation increase from July to August over the western North Pacific (WNP) region was investigated through observations and simulations in the Coupled Model Intercomparison Project Phase 6 (CMIP6), atmospheric model simulations and historical experiments. Firstly, observational analysis showed that the precipitation increase is associated with a decrease in the local sea surface temperature (SST), indicating that the precipitation increase is not driven by the change in SST. In addition, the pattern of precipitation increase is similar to the vertical motion change at 500-hPa, suggesting that the precipitation increase is related to the circulation change. Moisture budget analysis further confirmed this relation. In addition to the observational analysis, the outputs from 26 CMIP6 models were further evaluated. Compared with atmospheric model simulations, air–sea coupled models largely improve the simulation of the climatological precipitation increase from July to August. Furthermore, model simulations confirmed that the bias in the precipitation increase is intimately associated with the circulation change bias. Thus, two factors are responsible for the bias of the precipitation increase from July to August in climate models: air–sea coupling processes and the performance in vertical motion change.

Scale-aware parameterizations of subgrid scale physics are essentials for multiscale atmospheric modeling. A single-ice (SI) microphysics scheme and Gaussian probability-density-function (Gauss-PDF) macrophysics scheme were implemented in the single-column Global-to-Regional Integrated forecast System model (SGRIST) and they were tested using the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) and the Atmospheric Radiation Measurement Southern Great Plains Experiment in 1997 (ARM97). Their performance was evaluated against observations and other reference schemes. The new schemes simulated reasonable precipitation with proper fluctuations and peaks, ice, and liquid water contents, especially in lower levels below 650 hPa during the wet period in the TWP-ICE. The root mean square error (RMSE) of the simulated cloud fraction was below 200 hPa was 0.10/0.08 in the wet/dry period, which showed an obvious improvement when compared to that, i.e., 0.11/0.11 of original scheme. Accumulated ice water content below the melting level decreased by 21.57% in the SI. The well-matched average liquid water content displayed between the new scheme and observations, which was two times larger than those with the referencing scheme. In the ARM97 simulations, the SI scheme produced considerable ice water content, especially when convection was active. Low-level cloud fraction and precipitation extremes were improved using the Gauss-PDF scheme, which displayed the RMSE of cloud fraction of 0.02, being only half of the original schemes. The study indicates that the SI and Gauss-PDF schemes are promising approaches to simplify the microphysics process and improve the low-level cloud modeling.

The Cassini mission made an unexpected discovery when it found evidence of linear dune fields on Titan&rsquo, s surface. The orientation of the dunes and their interaction with topography allow scientists to estimate the dominant wind direction on the surface of Titan. There is some consensus in the community that the dune-forming winds must be net westerly, however, there is an active debate about the dune-forming wind regime. This debate has been guided by several studies of Earth dune fields considered analogous to the Titan dunes including those in Namibia, the Sahara, the Serengeti, and China. Complicating this active debate about the surface wind regime is the fact that global circulation models (GCMs) have historically not been able to reproduce westerly surface winds in the tropics. Here we use the Titan Community Atmosphere Model (CAM) to quantify the impact of topography and an added torque on Titan&rsquo, s dune-forming winds. Dunes tend to form at higher elevations on Titan, and adding topography to the model alters the near-surface wind directions, making them more westerly and consistent with the dune orientations. The addition of topography and added torque create a wind regime that is consistent with linear dunes in areas of stabilized sediment.

The modular structure of the boundary layer and convection parameterizations in atmospheric models have long been affecting the numerical representation of subgrid-scale motions and their mutual interactions. A promising alternative, the eddy-diffusivity/mass-flux approach (EDMF), has the potential for unifying the existing formulations into a consistent scheme and improving some of the long-standing issues. This study documents a step towards developing such a unified approach by implementing a stochastic multi-plume EDMF scheme into the Community Atmosphere Model (Version 5.0). Its performance in single-column mode is evaluated against the control parameterization and large-eddy simulation (LES) for two benchmark cases: marine and continental shallow convection. Overall, the results for the two parameterizations agree well with each other and with LES in terms of mean profiles of moist conserved variables and their vertical fluxes, as well as the updraft properties. However, systematic differences between the two schemes, especially for transient continental convection, are also documented. Using EDMF helps improve some of the parameterized features of shallow convection. In particular, for the highest tested vertical resolution, the EDMF cloud base and top heights and the vertical fluxes of energy and water are remarkably close to LES.

The effects of coupling between the atmospheric model of the Consortium for Small-Scale Modelling-Climate Limited-area Modelling (CCLM) and the wind wave model (WAM) on the lower atmosphere within the North Sea area are studied. Due to the two-way coupling between the models, the influences of wind waves and the atmosphere on each other can be determined. This two-way coupling between these models is enabled through the introduction of wave-induced drag into CCLM and updated winds into WAM. As a result of wave-induced drag, different atmospheric parameters are either directly or indirectly influenced by the wave conditions. The largest differences between the coupled and reference model simulation are found during storm events as well as in areas of steep gradients in the mean sea level pressure, wind speed or temperature. In the two-way coupled simulation, the position and strength of these gradients vary, compared to the reference simulation, leading to differences that spread throughout the entire planetary boundary layer and outside the coupled model area, thereby influencing the atmosphere over land and ocean, although not coupled to the wave model. Ultimately, the results of both model simulations are assessed against in situ and satellite measurements, with a better general performance of the two-way coupled simulation with respect to the observations.

Herein, we analyze the variations in the ionosphere for the period of two weeks before the M6.7 earthquake in India on January 3, 2016. The earthquake occurred after a series of magnetic substorms on December 31, 2015 and January 1, 2016. The relative total electron content (TEC) disturbances have been estimated using global TEC maps and calculated numerically using the 3D global first-principle Upper Atmosphere Model (UAM) for the whole period including the days before, during, and after the substorms. Numerical simulations were repeated with the seismogenic vertical electric currents switched on at the earthquake epicenter. The UAM calculations have reproduced the general behavior of the ionosphere after the main phase of the geomagnetic storm on January 1, 2016 in the form of negative TEC disturbances propagating from high latitudes, being especially strong in the Southern (summer condition) Hemisphere. It was shown that the local ionospheric effects of seismic origin can be identified in the background of the global geomagnetic disturbances. The seismo-ionospheric effects are visible in the nighttime regions with the additional negative TEC disturbances extending from the eastern side of the epicenter meridian to the western side, both in the observations and in the UAM simulations. It was found that the vertical electric field and corresponding westward component of the electromagnetic [E &times, B] drift played a decisive role in the formation of the ionospheric precursors of this earthquake.

This paper presents the wind resource assessment of the southernmost region of Thailand using atmospheric and computational fluid dynamics (CFD) wind flow modeling. The predicted wind data by the Weather Research and Forecasting (WRF) atmospheric modeling, assimilated to a virtual met mast, along with high-resolution topographic and roughness digital data, are then used as the main input for the CFD microscale wind flow modeling and high resolution wind resource mapping at elevations of 80 m, 100 m, 120 m, and 140 m agl. Numerical results are validated using measured wind data. Results show that the potential area where the wind speeds at 120 m agl are above 8.0 m/s is 86 km2, corresponding to a technical power potential in the order of 300 MW. The installation of wind power plants in the areas with the best wind resource could generate 690 GWh/year of electricity, thus avoiding greenhouse gas emissions of 1.2 million tonnes CO2eq/year to the atmosphere. On the other hand, developing power plants with International Electrotechnical Commission (IEC) Class IV wind turbines in areas of lower wind resource, but with easier access, could generate nearly 3000 GWh/yr of energy, with a CO2eq emissions avoidance of 5 million tonnes CO2eq on a yearly basis.

The climate of the Arabian Peninsula is characterized by significant spatial and temporal variations, due to its complex topography and the large-scale atmospheric circulation. Furthermore, the role of dust in the formation of regional climate is considered to be crucial. In this work, the regional climatology for the Arabian Peninsula has been studied by employing a high resolution state of the art atmospheric model that included sophisticated physical parameterization schemes and online treatment of natural aerosol particles. The simulations covered a 30-year period (1986&ndash, 2015) with a temporal resolution of 3 h and a spatial distance of 9 km. The main focus was given to the spatial and temporal variations of mean temperature and temperature extremes, wind speed and direction, and relative humidity. The results were evaluated using in situ measurements indicating a good agreement. An examination of possible climatic changes during the present climate was also performed through a comprehensive analysis of the trends of mean temperature and temperature extremes. The statistical significant trend values were overall positive and increased over the northwestern parts of the examined area. Similar spatial distributions were found for the daily minimum and maximum temperatures. Higher positive values emerged for the daily maxima.

Most weather and climate models simulate circulations by numerically approximating a complex system of partial differential equations that describe fluid flow. These models also typically use one of a few standard methods to parameterize the effects of smaller-scale circulations such as convective plumes. This paper discusses the continued development of a radically different modeling approach. Rather than solving partial differential equations, the author&rsquo, s Lagrangian models predict the motions of individual fluid parcels using ordinary differential equations. They also use a unique convective parameterization, in which the vertical positions of fluid parcels are rearranged to remove convective instability. Previously, a global atmospheric model and basin-scale ocean models were developed with this approach. In the present study, components of these models are combined to create a new global Lagrangian ocean model (GLOM), which will soon be coupled to a Lagrangian atmospheric model. The first simulations conducted with the GLOM examine the contribution of interior tracer mixing to ocean circulation, stratification, and water mass distributions, and they highlight several special model capabilities: (1) simulating ocean circulations without numerical diffusion of tracers, (2) modeling deep convective transports at low resolution, and (3) identifying the formation location of ocean water masses and water pathways.

The objective of this work is to analyze the wind and wave conditions along the coasts of the European seas. The emphasis is put on the mean and maximum values. The areas studied are characterized by intense maritime activities, including traffic, as well as various harbor and offshore operations. In the present study, 35 years of data (1983&ndash, 2017) coming from the European Centre for Medium-Range Weather Forecasts (ECMWF) were processed, corresponding to 40 different geographical locations. Thus, these 40 reference points are defined for some of the most relevant offshore locations in the coastal environments targeted. As regards the data considered in the analysis, two different sets were used. The first corresponds to the wave model, while the second to the atmospheric model, both operated by ECMWF. Finally, it can be concluded that the proposed work provides a global perspective related to the average and maximum wind and wave conditions and to a further extent on the climate dynamics along the coasts of the European seas.

The diurnal cycle of convection and precipitation is an important atmospheric feature. It also poses a great challenge to global numerical atmospheric modeling. Over continental East Asia, most global models cannot well capture the nocturnal and early morning peaks of summer rainfall. This problem may lead to dry biases and limit the modeling skills. This study investigates this problem using a global multiscale modeling framework (Super-Parameterized CAM5, SPCAM5). The nocturnal and early morning peaks, which are almost absent in CAM5 and a coarser-resolution SPCAM5, can be successfully captured by SPCAM5 with a moderate increase in the horizontal resolution. On the lee side of the Tibetan Plateau, SPCAM5 generates robust eastward propagating rainfall signals, which correspond to the moving convective systems, as revealed by the heating and drying profiles. Over the eastern plain of China, the early morning peaks become more evident, corresponding to a stratiform-type heating structure in the midlevel. A sensitivity experiment with altered grid-scale forcing also suggests the important preconditioning role of the vertical moisture advection in regulating the early morning peaks. These results highlight the added value of representing multiscale processes to the successful simulation of the diurnal cycle over continental East Asia.

The aim of this research is to present a weather-based forecasting system for apple fire blight (Erwinia amylovora) and downy mildew of grapevine (Plasmopara viticola) under Serbian agroecological conditions and test its efficacy. The weather-based forecasting system contains Numerical Weather Prediction (NWP) model outputs and a disease occurrence model. The weather forecast used is a product of the high-resolution forecast (HRES) atmospheric model by the European Centre for Medium-Range Weather Forecasts (ECMWF). For disease modelling, we selected a biometeorological system for messages on the occurrence of diseases in fruits and vines (BAHUS) because it contains both diseases with well-known and tested algorithms. Several comparisons were made: (1) forecasted variables for the fifth day are compared against measurements from the agrometeorological network at seven locations for three months (March, April, and May) in the period 2012&ndash, 2018 to determine forecast efficacy, (2) BAHUS runs driven with observed and forecast meteorology were compared to test the impact of forecasted meteorological data, and (3) BAHUS runs were compared with field disease observations to estimate system efficacy in plant disease forecasts. The BAHUS runs with forecasted and observed meteorology were in good agreement. The results obtained encourage further development, with the goal of fully utilizing this weather-based forecasting system.

The prescribed anthropogenic aerosol forcing recommended by Coupled Model Intercomparison Project Phase 6 (CMIP6) was implemented in an atmospheric model. With the reduced complexity of anthropogenic aerosol forcing, each component of anthropogenic aerosol effective radiative forcing (ERF) can be estimated by one or more calculation methods, especially for instantaneous radiative forcing (RF) from aerosol–radiation interactions (RFari) and aerosol–cloud interactions (RFaci). Simulation results show that the choice of calculation method might impact the magnitude and reliability of RFari. The RFaci—calculated by double radiation calls—is the definition-based Twomey effect, which previously was impossible to diagnose using the default model with physically based aerosol–cloud interactions. The RFari and RFaci determined from present-day simulations are very robust and can be used as offline simulation results. The robust RFari, RFaci, and corresponding radiative forcing efficiencies (i.e., the impact of environmental properties) are very useful for analyzing anthropogenic aerosol radiative effects. For instance, from 1975 to 2000, both RFari and RFaci showed a clear response to the spatial change of anthropogenic aerosol. The global average RF (RFari + RFaci) has enhanced (more negative) by ~6%, even with a slight decrease in the global average anthropogenic aerosol, and this can be explained by the spatial pattern of radiative forcing efficiency.

The Madden Julian Oscillation (MJO) is a large-scale convective and circulation system that propagates slowly eastward over the equatorial Indian and Western Pacific Oceans. Multiple, conflicting theories describe its growth and propagation, most involving equatorial Kelvin and/or Rossby waves. This study partitions MJO circulations into Kelvin and Rossby wave components for three sets of data: (1) a modeled linear response to an MJO-like heating, (2) a composite MJO based on atmospheric sounding data, and (3) a composite MJO based on data from a Lagrangian atmospheric model. The first dataset has a simple dynamical interpretation, the second provides a realistic view of MJO circulations, and the third occurs in a laboratory supporting controlled experiments. In all three of the datasets, the propagation of Kelvin waves is similar, suggesting that the dynamics of Kelvin wave circulations in the MJO can be captured by a system of equations linearized about a basic state of rest. In contrast, the Rossby wave component of the observed MJO&rsquo, s circulation differs substantially from that in our linear model, with Rossby gyres moving eastward along with the heating and migrating poleward relative to their linear counterparts. These results support the use of a system of equations linearized about a basic state of rest for the Kelvin wave component of MJO circulation, but they question its use for the Rossby wave component.

A new method is described for simulating the passive remote sensing image collection of ground targets that includes effects from atmospheric physics and dynamics at fine spatial and temporal scales. The innovation in this research is the process of combining a high-resolution weather model with image collection simulation to attempt to account for heterogeneous and high-resolution atmospheric effects on image products. The atmosphere was modeled on a 3D voxel grid by a Large-Eddy Simulation (LES) driven by forcing data constrained by local ground-based and air-based observations. The spatial scale of the atmospheric model (10–100 m) came closer than conventional weather forecast scales (10–100 km) to approaching the scale of typical commercial multispectral imagery (2 m). This approach was demonstrated through a ground truth experiment conducted at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. In this experiment, calibrated targets (colored spectral tarps) were placed on the ground, and the scene was imaged with WorldView-3 multispectral imagery at a resolution enabling the tarps to be visible in at least 9–12 image pixels. The image collection was simulated with Digital Imaging and Remote Sensing Image Generation (DIRSIG) software, using the 3D atmosphere from the LES model to generate a high-resolution cloud mask. The high-resolution atmospheric model-predicted cloud coverage was usually within 23% of the measured cloud cover. The simulated image products were comparable to the WorldView-3 satellite imagery in terms of the variations of cloud distributions and spectral properties of the ground targets in clear-sky regions, suggesting the potential utility of the proposed modeling framework in improving simulation capabilities, as well as testing and improving the operation of image collection processes.

In this paper on the analysis of the vertical distribution of different-diameter dust aerosols and the potential impacts on East Asia, the sensitivity simulation tests of dust aerosols during 2002&ndash, 03 were conducted by changing the underlying surface on the Qinghai-Tibet Plateau in the global atmospheric circulation model Community Atmosphere Model (CAM) 3.1. The results show that dust aerosol particles in East Asia are mainly distributed in the diameters of 0.64&ndash, 5.12 &mu, m. The high concentrations of dust aerosols are centered on the surface in the source areas and gradually raised during the eastward transport across East Asia, reaching a height of 4 km at 120&deg, E. The small dust particles with diameters less than 1.28 &mu, m are transported higher and farther driven by the midlatitude westerlies. The Qinghai-Tibet Plateau desertification leads to increasing concentrations of dust aerosols in all size bins and raisesthe transport height of dust aerosols in East Asia. The long-range transport in the East Asian troposphere is dominated by dust aerosols particles of diameters 0.64&ndash, 2.56 &mu, m, as well as a large contribution of dust aerosols with diameters larger than 1.28 &mu, m.

This paper demonstrates the role of meteorology and air transport in influencing the South African atmospheric CO2 distribution. CO2 data from December 2004 to December 2009 acquired by the Tropospheric Emission Spectrometer (TES) instrument onboard the Aura satellite were used to establish the CO2 vertical distribution at selected regions in South Africa. The Hybrid Single-Particle Lagrangian Integrated Trajectories (HYSPLIT) atmospheric model backward trajectories were used to determine the long-range air transport impacting on South African CO2 atmospheric distribution and to detect the source areas of air masses impacting on South Africa&rsquo, s atmosphere. The study found that long-range air transport can result in the accumulation or dilution of atmospheric CO2 at various sites in South Africa, depending on the source region and type of air flow. The long-range air transport from different source regions at the upper air level between the 700 and 500 hPa stable layers and the layer above 500 hPa strengthens the inhomogeneity in the vertical distribution of CO2, which is caused by the decoupling effect of the upper air stable layers. This long-range air transport also involves intercontinental air transport.

This study performed several sensitivity experiments to investigate the impact of atmosphere&ndash, wave coupling on the simulated wind and waves over the East China Sea (ECS) with a focus on typhoon events. These experiments include stand-alone regional atmosphere model (CCLM) simulations, stand-alone spectral wave model (WAM) simulations driven by the regional atmospheric model CCLM or ERA5 reanalysis, and two-way (CCLM-WAM) coupled simulations. We assessed the simulated wind speed and significant wave height against in situ observations and remote sensing data and focused on typhoon events in 2010. We analyzed the differences between the experiments in capturing the surface pressure, wind speed, and roughness length. Both ERA5 reanalysis data and our regional model simulations demonstrate high quality in capturing wind and wave conditions over the ECS. The results show that downscaled simulations tend to be closer to in situ observations than ERA5 reanalysis data in capturing wind variability and probability distribution, dominant wind and wave directions, strong typhoon intensity and related extreme significant wave height. In comparison with satellite observations, the CCLM-WAM simulation outperforms the CCLM in reducing wind bias. The coupled and uncoupled simulations are very similar in terms of other wind and wave statistics. Though there is much improvement in capturing typhoon intensity to ERA5, regional downscaled simulations still underestimate the wind intensity of tropical cyclones.

Simulations of a Regional Climate Model (RCM) driven by identical lateral boundary conditions but initialized at different times exhibit the phenomenon of so-called internal model variability (or in short, Internal Variability&mdash, IV), which is defined as the inter-member spread between members in an ensemble of simulations. Our study investigates the effects of air-sea coupling on IV of the regional atmospheric model COSMO-CLM (CCLM) of the new regional coupled system model GCOAST-AHOI (Geesthacht Coupled cOAstal model SysTem: Atmosphere, Hydrology, Ocean and Sea Ice). We specifically address physical processes parameterized in CCLM, which may cause a large IV during an extreme event, and where this IV is affected by the air-sea coupling. Two six-member ensemble simulations were conducted with GCOAST-AHOI and the stand-alone CCLM (CCLM_ctr) for a period of 1 September&ndash, 31 December 2013 over Europe. IV is expressed by spreads within the two sets of ensembles. Analyses focus on specific events during this period, especially on the storm Christian occurring from 27 to 29 October 2013 in northern Europe. Results show that simulations of CCLM_ctr vary largely amongst ensemble members during the storm. By analyzing two members of CCLM_ctr with opposite behaviors, we found that the large uncertainty in CCLM_ctr is caused by a combination of two factors (1) uncertainty in parameterization of cloud-radiation interaction in the atmospheric model. and (2) lack of an active two-way air-sea interaction. When CCLM is two-way coupled with the ocean model, the ensemble means of GCOAST-AHOI and CCLM_ctr are relatively similar, but the spread is reduced remarkably in GCOAST-AHOI, not only over the ocean where the coupling is done but also over land due to the land-sea interactions.

An atmosphere&ndash, ocean coupled model is proposed as an optimal numerical prediction method for the offshore wind resource. Meteorological prediction models are mainly used for wind speed prediction, with active studies using atmospheric models. Seawater mixing occurring at sea due to solar radiation and wind intensity can significantly change the sea surface temperature (SST), an important variable for predicting wind resources and energy production, considering its wind effect, within a short time. This study used the weather research forecasting and ocean mixed layer (WRF-OML) model, an atmosphere&ndash, ocean coupled model, to reflect time-dependent SST and sea surface fluxes. Results are compared with those of the WRF model, another atmospheric model, and verified through comparison with observation data of a meteorological mast (met-mast) at sea. At a height of 94 m, the wind speed predicted had a bias and root mean square error of 1.09 m/s and 2.88 m/s for the WRF model, and &minus, 0.07 m/s and 2.45 m/s for the WRF-OML model, respectively. Thus, the WRF-OML model has a higher reliability. In comparing to the met-mast observation data, the annual energy production (AEP) estimation based on the predicted wind speed showed an overestimation of 15.3% and underestimation of 5.9% from the WRF and WRF-OML models, respectively.

A diagnostic method is presented for analysing the large-scale behaviour of the Met Office Unified Model, which is a comprehensive atmospheric model used for weather and climate prediction. Outside the boundary layer, on scales larger than the radius of deformation, semi-geostrophic theory will give an accurate approximation to the model evolution. In particular, the ageostrophic circulation required to maintain geostrophic and hydrostatic balance against prescribed forcing and a rate of change of the geostrophic pressure can be calculated. In the tropics, the balance condition degenerates to the weak temperature gradient approximation. Within the boundary layer, the semi-geotriptic approximation has to be used because friction and rotation are equally important. Assuming the calculated pressure tendency and ageotriptic circulation match the observed model behaviour, the influence of the large-scale state and the nature of the forcing on the model response can be deduced in a straightforward way. The capabilities of the diagnostic are illustrated by comparing predictions of the ageotriptic circulation from the theory and the model. It is then used to show that the effects of latent heat release can be included by modifying the static stability, and to show the effect of an idealised tropical heat source on the subtropical jet. Finally, the response of the ageotriptic flow to boundary layer heating in the tropics is demonstrated. These illustrations show that the model behaviour on large scales conforms with theoretical expectations, so that the results of the diagnostic can be used to aid the development of further improvements to the model, in particular investigating systematic errors and understanding the large-scale atmospheric response to forcing.

An idealized study with two land surface models (LSMs): TERRA-Multi Layer (TERRA-ML) and Community Land Model (CLM) alternatively coupled to the same atmospheric model COSMO (Consortium for Small-Scale Modeling), reveals differences in the response of the LSMs to initial soil moisture. The bulk parameterization of evapotranspiration pathways, which depends on the integrated soil moisture of active layers rather than on each discrete layer, results in a weaker response of the surface energy flux partitioning to changes in soil moisture for TERRA-ML, as compared to CLM. The difference in the resulting surface energy flux partitioning also significantly affects the model response in terms of the state of the atmospheric boundary layer. For vegetated land surfaces, both models behave quite differently for drier regimes. However, deeper reaching root fractions in CLM align both model responses with each other. In general, differences in the parameterization of the available root zone soil moisture, evapotranspiration pathways, and the soil-vegetation structure in the two LSMs are mainly responsible for the diverging tendencies of the simulated land atmosphere coupling responses.

The Aullene fire devastated more than 3000 ha of Mediterranean maquis and pine forest in July 2009. The simulation of combustion processes, as well as atmospheric dynamics represents a challenge for such scenarios because of the various involved scales, from the scale of the individual flames to the larger regional scale. A coupled approach between the Meso-NH (Meso-scale Non-Hydrostatic) atmospheric model running in LES (Large Eddy Simulation) mode and the ForeFire fire spread model is proposed for predicting fine- to large-scale effects of this extreme wildfire, showing that such simulation is possible in a reasonable time using current supercomputers. The coupling involves the surface wind to drive the fire, while heat from combustion and water vapor fluxes are injected into the atmosphere at each atmospheric time step. To be representative of the phenomenon, a sub-meter resolution was used for the simulation of the fire front, while atmospheric simulations were performed with nested grids from 2400-m to 50-m resolution. Simulations were run with or without feedback from the fire to the atmospheric model, or without coupling from the atmosphere to the fire. In the two-way mode, the burnt area was reproduced with a good degree of realism at the local scale, where an acceleration in the valley wind and over sloping terrain pushed the fire line to locations in accordance with fire passing point observations. At the regional scale, the simulated fire plume compares well with the satellite image. The study explores the strong fire-atmosphere interactions leading to intense convective updrafts extending above the boundary layer, significant downdrafts behind the fire line in the upper plume, and horizontal wind speeds feeding strong inflow into the base of the convective updrafts. The fire-induced dynamics is induced by strong near-surface sensible heat fluxes reaching maximum values of 240 kW m &minus, 2 . The dynamical production of turbulent kinetic energy in the plume fire is larger in magnitude than the buoyancy contribution, partly due to the sheared initial environment, which promotes larger shear generation and to the shear induced by the updraft itself. The turbulence associated with the fire front is characterized by a quasi-isotropic behavior. The most active part of the Aullene fire lasted 10 h, while 9 h of computation time were required for the 24 million grid points on 900 computer cores.

Satellite data suggest that summertime aerosol optical depth (AOD) over the southeastern USA depends on the air/land surface temperature, but the magnitude of the radiative effects caused by this dependence remains unclear. To quantify these radiative effects, we utilized several remote sensing datasets and ECMWF reanalysis data for the years 2005–2011. In addition, the global aerosol–climate model ECHAM-HAMMOZ was used to identify the possible processes affecting aerosol loads and their dependence on temperature over the studied region. The satellite-based observations suggest that changes in the total summertime AOD in the southeastern USA are mainly governed by changes in anthropogenic emissions. In addition, summertime AOD exhibits a dependence on southerly wind speed and land surface temperature (LST). Transport of sea salt and Saharan dust is the likely reason for the wind speed dependence, whereas the temperature-dependent component is linked to temperature-induced changes in the emissions of biogenic volatile organic compounds (BVOCs) over forested regions. The remote sensing datasets indicate that the biogenic contribution increases AOD with increasing temperature by approximately (7 ± 6) × 10−3 K−1 over the southeastern USA. In the model simulations, the increase in summertime AOD due to temperature-enhanced BVOC emissions is of a similar magnitude, i.e., (4 ± 1) × 10−3 K−1. The largest source of BVOC emissions in this region is broadleaf trees, thus if the observed temperature dependence of AOD is caused by biogenic emissions the dependence should be the largest in the vicinity of forests. Consequently, the analysis of the remote sensing data shows that over mixed forests the biogenic contribution increases AOD by approximately (27 ± 13) × 10−3 K−1, which is over four times higher than the value for over the whole domain, while over other land cover types in the study region (woody savannas and cropland/natural mosaic) there is no clear temperature dependence. The corresponding clear-sky direct radiative effect (DRE) of the observation-based biogenic AOD is −0.33 ± 0.29 W/m2/K for the whole domain and −1.3 ± 0.7 W/m2/K over mixed forests only. The model estimate of the regional clear-sky DRE for biogenic aerosols is similar to the observational estimate for the whole domain: −0.29 ± 0.09 W/m2/K. Furthermore, the model simulations showed that biogenic emissions have a significant effective radiative forcing (ERF) in this region: −1.0 ± 0.5 W/m2/K.

This study analyzed the noise equivalent sigma zero (NESZ) and ocean wind sensitivity for Chinese C-band Gaofen-3 (GF-3) quad-polarization synthetic aperture radar (SAR) measurements to facilitate further operational wind extraction from GF-3 data. Data from the GF-3 quad-polarization SAR and collocated winds from both NOAA/NCEP Global Forecast System (GFS) atmospheric model and National Data Buoy Center (NDBC) buoys were used in the analysis. For NESZ, the co-polarization was slightly higher compared to the cross-polarization. Regarding co-polarization and cross-polarization, NESZ was close to RadarSAT-2 and Sentinel-1 A. Wind sensitivity was analyzed by evaluating the dependence on winds in terms of normalized radar cross-sections (NRCS) and polarization combinations. The closest geophysical model function (GMF) and the polarization ratio (PR) model to GF-3 data were determined by comparing data and the model results. The dependence of co-polarized NRCS on wind speed and azimuth angle was consistent with the proposed GMF models. The combination of CMOD5 and CMOD5.N was considered to be the closest GMF in co-polarization. The cross-polarized NRCS exhibited a strong linear relationship with moderate wind speeds higher than 4 m·s−1, but a weak correlation with the azimuth angle. The proposed model was considered as the closest GMF in cross-polarization. For polarization combinations, PR and polarization difference (PD) were considered. PR increased only with the incidence angle, whereas PD increased with wind speed and varied with azimuth angle. There were three very close PR models and each can be considered as the closest. Preliminary results indicate that GF-3 quad-polarization data are valid and have the ability to extract winds in each polarization.

In this work we present preliminary results regarding a proof-of-concept project which aims to provide tools for mapping the amount of solar radiation reaching surfaces of objects, accounting for obstructions between objects themselves. The implementation uses the NASA World Wind development platform (NASA WW) to model the different physical phenomena that participate in the process, from the calculation of the Sun’s position relative to the area that is being considered, to the interaction between atmosphere and solid obstructions, e.g., terrain or buildings. A more complete understanding of the distribution of energy from the Sun illuminating elements on the Earth’s surface adds value to applications ranging from planning the renewable energy potential of an area to ecological analyses.