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Atmospheric gravity waves are essential meso-small-scale oscillations that facilitate material exchange within the atmosphere. These waves can significantly affect the ozone layer in the Upper Troposphere and Lower Stratosphere (UTLS) on the Qinghai-Tibetan Plateau. However, the influence of gravity wave dynamic processes on upper stratospheric ozone has rarely been studied. This paper identifies the gravity waves on the Tibetan Plateau based on ECMWF Reanalysis 5 (ERA5) data, analyzes the response of the upper stratospheric ozone to the event, and simulates the dynamic propagation mechanism of gravity waves by the Weather Research and Forecasting (WRF) model. This analysis reveals that between 15:00 and 21:00 UTC on July 29, 2015, gravity waves propagated from the surface of Tibetan Plateau (450 hPa) up to the upper stratosphere (20 − 3 hPa) in an arc-shaped structure and tilted to the east with height. The gravity wave signals started to weaken at 21:00 UTC on the same day. Influenced by the easterly rapids, gravity waves partially broke near 3 hPa at 02:30 UTC on July 30, but gravity wave signals were still present, and gravity waves completely broke and released energy at 04:00 UTC. During this process, ozone in the 20–3 hPa region (upper stratosphere) on the Qinghai-Tibetan Plateau responds well to gravity waves, and the ozone mixing ratio began to drop in ozone concentration 30 min after the partial breakup (03:00 UTC). The ozone dropped drastically by about 0.014 ppmv from 04:00 to 05:00 UTC. The WRF simulation results agree well with ERA5 and accurately capture the intricate characteristics of gravity waves. Furthermore, the breakup of gravity waves caused a total drop in ozone of 0.024 ppmv. [ABSTRACT FROM AUTHOR]

Rotation in hurricane flows can significantly impact the dynamics and structure of the turbulent boundary layer. Despite this unique feature of hurricane boundary layers, the current planetary boundary layer (PBL) schemes in weather models are neither specifically designed nor comprehensively tested for intensifying hurricane flows. The objective of this paper is to bridge this knowledge gap by characterizing the role of vertical diffusion depth and magnitude in simulated hurricane intensity, size, and track. To this end, five major hurricane cases undergoing an intensification period are simulated using two widely used local and non-local PBL schemes in Weather Research and Forecasting (WRF) model. In total, eighty WRF simulations are conducted by varying the grid resolution, PBL scheme, eddy diffusivity depth and magnitude, and PBL height. By decreasing the existing vertical diffusion depth and magnitude, on average, ~ 38 and ~ 24% improvements in hurricane intensity forecasts were obtained compared to the default models. Hence, the results indicate that the current PBL schemes in WRF are overly diffusive for simulating major hurricanes since they do not account for turbulence suppression effects in rotating hurricane flows. The paper yields new insights into the role of vertical diffusion in simulated hurricane dynamics and provides some guidance to enhance the PBL schemes of NWPs for improved hurricane forecasts. [ABSTRACT FROM AUTHOR]

Understanding and evaluating the implications of photovoltaic solar panels (PVSPs) deployment on urban settings, as well as the pessimistic effects of densely populated areas on PVSPs efficiency, is becoming incredibly valuable. Thus, the deployment of low-efficiency, low-cost, and widely available PVSPs may diminish total solar reflectance, raising the risks of PVSPs-based urban heating, particularly during the summertime heatwaves. This study employs and assesses physical parameterizations that account for the impact of PVSPs on Sydney's urban environment in the context of the mesoscale model weather research and forecasting (WRF). To account for the impacts of PVSPs, the parameterization presented in this paper assumes that PVSP arrays are parallel, detachable from roofs, and consist of a single layer. Results showed that increasing PVSPs can raise peak summer ambient temperatures by up to 1.4 °C and surface temperatures by up to 2.3°C at city-scale. Temperature variability was found between the city's eastern and western parts due to the presence of PVSPs. In addition, local warming effects of PVSP were observed at urban district-scale as well. The large-scale deployment of PVSPs at local district-scale of the Sydney during a typical hot day caused air temperature to rise by 1.5 °C during the daytime and decrease by 2.7 °C at nighttime. The patterns of the city's ambient temperature distribution were found to be strongly dependent on synoptic meteorological conditions and advection flow strength. The maximum increases in sensible heat flux and latent heat flux were 245.5 Wm−2 and 11.5 Wm−2, respectively. Wind speed may be raised by up to 1.2 ms−2 due to regional low effect over city domain. As a result, large-scale deployment of PVSPs promotes advective flow between the city and its environs. Modification of the PVSPs in Sydney results in an increase in planetary boundary layer (PBL) heights of up to 537.9 m above the city and may lower pollutant concentrations at ground level. The advent of sea breeze in the city's eastern parts, which reduces the temperature of the coastal zone, along with inland westerly winds, which heat the city's western zones, lessened the intensity of the urban heat island (UHI) phenomenon induced by PVSPs warming. The findings of this study can be used to help policymakers make informed decisions about the use of PVSPs systems. PVSPs with a high solar reflectance in wavelengths that do not convert solar energy to electricity can be considered as an alternative solution to reduce local warming in urban environments. [ABSTRACT FROM AUTHOR]

The National Center for Atmospheric Research released a global atmosphere model named Community Atmosphere Model version 5.0 (CAM5), which aimed to provide a global climate simulation for meteorological research. Among them, the cloud microphysics scheme is extremely time-consuming, so developing efficient parallel algorithms faces large-scale and chronic simulation challenges. Due to the wide application of GPU in the fields of science and engineering and the NVIDIA's mature and stable CUDA platform, we ported the code to GPU to accelerate computing. In this paper, by analyzing the parallelism of CAM5 cloud microphysical schemes (CAM5 CMS) in different dimensions, corresponding GPU-based one-dimensional (1D) and two-dimensional (2D) parallel acceleration algorithms are proposed. Among them, the 2D parallel algorithm exploits finer-grained parallelism. In addition, we present a data transfer optimization method between the CPU and GPU to further improve the overall performance. Finally, GPU version of the CAM5 CMS (GPU-CMS) was implemented. The GPU-CMS can obtain a speedup of 141.69 × on a single NVIDIA A100 GPU with I/O transfer. In the case without I/O transfer, compared to the baseline performance on a single Intel Xeon E5-2680 CPU core, the 2D acceleration algorithm obtained a speedup of 48.75 × , 280.11 × , and 507.18 × on a single NVIDIA K20, P100, and A100 GPU, respectively. [ABSTRACT FROM AUTHOR]

Understanding and evaluating the implications of photovoltaic solar panels (PVSPs) deployment on urban settings, as well as the pessimistic effects of densely populated areas on PVSPs efficiency, is becoming incredibly valuable. Thus, the deployment of low-efficiency, low-cost, and widely available PVSPs may diminish total solar reflectance, raising the risks of PVSPs-based urban heating, particularly during the summertime heatwaves. This study employs and assesses physical parameterizations that account for the impact of PVSPs on Sydney's urban environment in the context of the mesoscale model weather research and forecasting (WRF). To account for the impacts of PVSPs, the parameterization presented in this paper assumes that PVSP arrays are parallel, detachable from roofs, and consist of a single layer. Results showed that increasing PVSPs can raise peak summer ambient temperatures by up to 1.4 °C and surface temperatures by up to 2.3°C at city-scale. Temperature variability was found between the city's eastern and western parts due to the presence of PVSPs. In addition, local warming effects of PVSP were observed at urban district-scale as well. The large-scale deployment of PVSPs at local district-scale of the Sydney during a typical hot day caused air temperature to rise by 1.5 °C during the daytime and decrease by 2.7 °C at nighttime. The patterns of the city's ambient temperature distribution were found to be strongly dependent on synoptic meteorological conditions and advection flow strength. The maximum increases in sensible heat flux and latent heat flux were 245.5 Wm−2 and 11.5 Wm−2, respectively. Wind speed may be raised by up to 1.2 ms−2 due to regional low effect over city domain. As a result, large-scale deployment of PVSPs promotes advective flow between the city and its environs. Modification of the PVSPs in Sydney results in an increase in planetary boundary layer (PBL) heights of up to 537.9 m above the city and may lower pollutant concentrations at ground level. The advent of sea breeze in the city's eastern parts, which reduces the temperature of the coastal zone, along with inland westerly winds, which heat the city's western zones, lessened the intensity of the urban heat island (UHI) phenomenon induced by PVSPs warming. The findings of this study can be used to help policymakers make informed decisions about the use of PVSPs systems. PVSPs with a high solar reflectance in wavelengths that do not convert solar energy to electricity can be considered as an alternative solution to reduce local warming in urban environments. [ABSTRACT FROM AUTHOR]

The ventilation corridor is an essential element in urban planning and design to improve the climate and environment. In this paper, four forms of two ventilation corridors were set up in the southeast of Wuhan City based on its urban planning outline to quantitatively study the influences of different ventilation corridor forms on the urban thermal environment in summer. The urban micro-meteorological environment was simulated using the next-generation mesoscale Weather Research and Forecast (WRF) model coupled with an urban canopy model (UCM). Critical time-dependent meteorological values were extracted and plotted, including temperature and wind difference fields, average temperature at 2-m height, average wind speed at 10-m height, and surface energy flux. By conducting a comparative analysis of the quantitative results, the ventilation corridors in construction land are arranged at intervals in the upwind position of the city in summer, which can slightly adjust the thermal environment of the central area of the city, and have an effective regulation on the temperature of the corridors and surrounding areas during the daytime. Especially at 15:00 pm when the temperature is at its highest during the day, the temperature can be reduced by 0.8 °C. Compared to other corridors, the wind speed in and around the corridor is the strongest 11 h a day. Due to the internal arrangement of construction land, this corridor form is more advantageous in the urban land utilization. After considering comprehensively, the ventilation corridor form with construction land arranged at intervals is the preferred corridor form in the southeast of Wuhan. The experimental results can provide quantitative reference for the layout of ventilation corridors in hot inland cities located in central China. [ABSTRACT FROM AUTHOR]

This paper reports analysis of eddy-covariance data collected during the WFIP2 field campaign in the complex-terrain of the US Pacific Northwest. A 31-day period representative of the region's dry season was used to address the following questions: (1) To what extent does the Constant-Flux Layer (CFL) assumption hold? (2) What is the spatial variability of turbulent and momentum fluxes over km scales? and (3) How skilful are the surface-layer parameterizations of mesoscale models? These questions are directly relevant to subgrid parameterization studies of mesoscale models. Results show that the efficacy of the CFL concept and the spatial variability of turbulent and momentum fluxes are dependent on: (i) the turbulent parameter being analysed, (ii) the measurement's location, (iii) the atmospheric stability regime (determined by the flow and vertical stratification), and (iv) the magnitude of the flux. Finally, the skill of the physics formulation of an often-used surface-layer parameterization scheme available in the Weather Research and Forecasting (WRF) model was also evaluated. Meteorological conditions associated with the highest and the lowest errors were identified. A metric to quantify (time-dependent) flow heterogeneity is proposed, which appears to be a good candidate to predict the skill of idealized surface-layer parameterization schemes in complex terrain. [ABSTRACT FROM AUTHOR]

Forecasting tropical cyclone track and intensity is a great challenge for the meteorological community, and safeguarding the life and property of people living near the coast is an important issue. One major reason for challenging forecasts is the lack of observations over the vast oceans. During tropical cyclone Mulan between 8 and 10 August 2022 over the northern part of the South China Sea, the meteorological authority and research institutes of Chinese mainland collaborated with the meteorological service in Hong Kong on conducting the first-ever ground-space-sky observing system experiment on tropical cyclone Mulan. The enhanced targeted observations collected during the experiment include Geostationary Interferometric Infrared Sounder, round-trip radiosondes, and aircraft-launched dropsondes. This paper describes the campaign, technical details of the meteorological models used, and impact of the additional targeted observation data on the tropical cyclone forecast. Ideally, similar enhanced observation campaigns could be conducted in the future, not only in the northern part of the South China Sea, but also in other ocean basins. [ABSTRACT FROM AUTHOR]

Although solar activity may significantly impact the global environment and socioeconomic systems, the mechanisms for solar eruptions and the subsequent processes have not yet been fully understood. Thus, modern society supported by advanced information systems is at risk from severe space weather disturbances. Project for solar–terrestrial environment prediction (PSTEP) was launched to improve this situation through synergy between basic science research and operational forecast. The PSTEP is a nationwide research collaboration in Japan and was conducted from April 2015 to March 2020, supported by a Grant-in-Aid for Scientific Research on Innovative Areas from the Ministry of Education, Culture, Sports, Science and Technology of Japan. By this project, we sought to answer the fundamental questions concerning the solar–terrestrial environment and aimed to build a next-generation space weather forecast system to prepare for severe space weather disasters. The PSTEP consists of four research groups and proposal-based research units. It has made a significant progress in space weather research and operational forecasts, publishing over 500 refereed journal papers and organizing four international symposiums, various workshops and seminars, and summer school for graduate students at Rikubetsu in 2017. This paper is a summary report of the PSTEP and describes the major research achievements it produced. [ABSTRACT FROM AUTHOR]

Although solar activity may significantly impact the global environment and socioeconomic systems, the mechanisms for solar eruptions and the subsequent processes have not yet been fully understood. Thus, modern society supported by advanced information systems is at risk from severe space weather disturbances. Project for solar–terrestrial environment prediction (PSTEP) was launched to improve this situation through synergy between basic science research and operational forecast. The PSTEP is a nationwide research collaboration in Japan and was conducted from April 2015 to March 2020, supported by a Grant-in-Aid for Scientific Research on Innovative Areas from the Ministry of Education, Culture, Sports, Science and Technology of Japan. By this project, we sought to answer the fundamental questions concerning the solar–terrestrial environment and aimed to build a next-generation space weather forecast system to prepare for severe space weather disasters. The PSTEP consists of four research groups and proposal-based research units. It has made a significant progress in space weather research and operational forecasts, publishing over 500 refereed journal papers and organizing four international symposiums, various workshops and seminars, and summer school for graduate students at Rikubetsu in 2017. This paper is a summary report of the PSTEP and describes the major research achievements it produced. [ABSTRACT FROM AUTHOR]

Land cover change (LCC) significantly changed the local/regional temperature. This paper attempts to reveal the effects of cropland expansion in different ways on temperature change from the 1900s to 2010s in Heilongjiang Province. To reach this goal, we conducted four simulation research schemes with the coupled Weather Research and Forecast (WRF)-Noah model to investigate the warming/cooling effect of cropland expansion. The results show that cropland expansion exerted different effects with different land-use type conversions. In the last century, the areas with grassland-to-cropland and wetland-to-cropland transition show the warming effect, and the average surface temperature in Heilongjiang Province increased by 0.023 ℃ and 0.024 ℃, respectively. The areas with forest-to-cropland transition show the cooling effect, in which the average temperature decreased by 0.103 ℃. The variation of air temperature is mainly caused by the variation of surface reflectance and surface net radiation flux. The results provide evidence that cropland expansion changes to biophysical landscape characteristics, warming/cooling the land surface and thus enhancing/reducing the temperature, and lead to regional climate change eventually. [ABSTRACT FROM AUTHOR]

Water vapor plays a key role in weather, climate and environmental research on local and global scales. Knowledge about atmospheric water vapor and its spatiotemporal variability is essential for climate and weather research. Because of the advantage of a unique temporal and spatial resolution, satellite observations provide global or regional water vapor distributions. The advanced Medium Resolution Spectral Imager (MERSI) instrument—that is, MERSI-II—onboard the Fengyun-3D (FY-3D) meteorological satellite, has been one of the major satellite sensors routinely providing precipitable water vapor (PWV) products to the community using near-infrared (NIR) measurements since June 2018. In this paper, the major updates related to the production of the NIR PWV products of MERSI-II are discussed for the first time. In addition, the water vapor retrieval algorithm based on the MERSI-II NIR channels is introduced and derivations are made over clear land areas, clouds, and sun-glint areas over the ocean. Finally, the status and samples of the MERSI-II PWV products are presented. The accuracy of MERSI-II PWV products is validated using ground-based GPS measurements. The results show that the accuracies of the water vapor products based on the updated MERSI-II instrument are significantly improved compared with those of MERSI, because MERSI-II provides a better channel setting and new calibration method. The root-mean-square error and relative bias of MERSI-II PWV products are typically 1.8–5.5 mm and −3.0% to −14.3%, respectively, and thus comparable with those of other global remote sensing products of the same type. [ABSTRACT FROM AUTHOR]

In this paper, we evaluated a dynamical downscaling produced for Central South Chile (32°S–38°S) relative to climatic conditions between 1980 and 2005. Assessing the skill of dynamical downscaling relative to the present climate is key to determine the degree of confidence on regional climatic projections. We used the Weather Research and Forecasting model to simulate that period at ~ 9 km grid-cell size, forced by the bias-corrected Community Earth System Model. Results indicated that the dynamical downscaling adequately reproduced spatio-temporal features of the climate within the region. Temperature showed a positive bias at the annual scale while the opposite occurred for precipitation. The bias varied when the comparison was performed relative to a gridded product or instrumental records from weather stations. At the monthly scale, the model failed to capture long-term trends relative to the gridded dataset while reproducing spatial patterns, especially for temperature. We found a generally statistically significant spatial clustering of the monthly mean bias that can support implementation and application of dynamical downscaling and bias-correction methods that account for the distinct climatic features of the study area. In particular, the strip 34°S–35°S presented features that are coincident with previous findings suggesting this latitude to be a boundary between different climate regimes north and south. According to our results, we assert that this dynamical downscaling is comparable with other available databases and thus can be utilized in future studies as an additional and independent source of analysis, contributing to a balanced appraisal of climate scenarios for policymaking within the region. [ABSTRACT FROM AUTHOR]

Regional climate models (RCMs) are used to dynamically downscale global climate models (GCMs) to provide high-resolution projections of future climate change to better inform policy and decision making at the regional scale. However, biases from GCMs are transferred to RCMs and this can limit the usefulness of the regional climate projections. This paper investigates the influence of bias correcting 4 GCMs from the Coupled Model Intercomparison Project 3, for regional climate simulations over the CORDEX-Australasia domain using Weather Research and Forecasting. The GCM outputs are bias corrected against ERA-Interim reanalysis as a surrogate truth. Results show that over decadal time scales bias correction removes large systematic precipitation and temperature biases. However, bias correction also introduced biases where there were none, introduced biases of the opposite sign, or enhanced existing biases in other regions in some instances. The dynamical mechanisms driving the changes in the biases are explored. [ABSTRACT FROM AUTHOR]

In this paper we combine statistical modelling and climate models in order to develop a unified statistical framework for quantifying the Urban Heat Footprint (UHF) effect, thus quantifying the urban warming phenomenon. The UHF quantifies the urban warming at any location in the spatio-temporal domain due to different effects, such as anthropogenic effects and climatic effects. These effects can be controlled and configured by our modelling approach, thus allowing the evaluation of different scenarios of interest. We first provide a definition of UHF followed by definitions of the Anthropogenic Effects (AE) components. Then, based on those definitions, we define the fundamental quantity of UHF spatial-temporal stochastic (random) processes. Next, we propose several metrics for quantifying and summarising the UHF, which are statistical estimators. These provide insightful summaries of the population parameters of the UHF stochastic process, and can be easily calculated in practice. To illustrate how our framework can be used, we utilise a Weather Research and Forecasting (WRF) model, and provide detailed examples of various UHF metrics, based on real data of Singapore. [ABSTRACT FROM AUTHOR]

This paper presents an evaluation of the Weather Research and Forecasting (WRF) model in simulating wet and dry West African monsoon (WAM) rainfall seasons. Three model experiments with varying selected microphysics (MP), cumulus convection (CU), and planetary boundary layer (PBL) schemes based on previous study were performed. Each of the model combinations is used to run four WAM seasons that consist of two wet (2008 and 2010) and two dry years (2001 and 2011). To investigate the behavior of WAM in the context of wet and dry years, the four seasons were used to compute composites of wet and dry WAM seasons in terms of rainfall amount. The analyses majorly focus on the rainfall composites relative to rainfall from Global Precipitation Climatology Project (GPCP) and Tropical Rainfall Measurement Mission (TRMM) as well as temperature, moisture, and atmospheric circulation fields with respect to NCEP reanalyses. This study documents significant sensitivity in simulation of the West African monsoon to the choices of the MP, CU, and PBL schemes. The simulation with the combination of WRF single moment 5 (WSM5) MP, Yonsei University (YSU) PBL, and new Simplified Arakawa-Schubert CU (WSM5-YSU-nSAS) shows good spatial distribution pattern of rainfall and the dynamics associated with the monsoon. Quantitatively, the combination shows less agreement in distinguishing the selected WAM seasons compared with the Goddard MP, Mellor-Yamada-Janjic PBL, and Betts-Miller-Janjić CU (GD-MYJ-BMJ) and the WSM5, Mellor-Yamada-Nakanishi-Niino 2.5 level and new Tiedtke CU (WSM5-MYNN-nTDK). Also, the dynamical structures of the wet and dry WAM circulation composites are reasonably reproduced in GD-MYJ-BMJ and WSM5-YSU-nSAS. The GD-MYJ-BMJ was able to distinguish between wet and dry years and thus underscores its potential to reproduce climate change signals in future work. [ABSTRACT FROM AUTHOR]

Meteorological observations in Tibet are poor in quality with a severe amount of missing data; this is mostly caused by extreme climatological conditions and higher maintenance costs. This paper focuses on the imputation of missing data and the reconstruction of the regional temperature field. Due to insufficient observation stations and complicated topography, we employ the weather research and forecasting (WRF) model to produce the proper orthogonal decomposition (POD) basis for the study region. We then develop the gappy POD method for the imputation of missing data. Both methods are compared and tested for various missing data cases, and the results show that the gappy POD method dramatically outperforms the regularized EM algorithm when the amount of missing spatial data is not severe. Furthermore, between the two methods, only the gappy POD method is capable of reconstructing the temperature field at locations where the data are absent. The gappy POD method can also be generalized for data assimilation with the assumption that the data across all model grids have missing values. [ABSTRACT FROM AUTHOR]

Heatwaves are predicted to increase in frequency, duration, and severity in the future, including over Central Europe where populations are sensitive to extreme temperature. This paper studies six recent major heatwave events over Poland from 2006 through 2015 using regional-scale simulations (10-km grid spacing, hourly frequency) from the Weather Research and Forecast (WRF) model to define local-scale 2-m temperature patterns. For this purpose, a heatwave is defined as at least three consecutive days with maximum 2-m air temperature exceeding 30 °C. The WRF simulations were validated using maximum daily 2-m temperature observations from 12 meteorological stations in select Polish cities, which were selected to have even spatial coverage across the study area. Synoptic analysis of the six study events shows that the inflow of tropical air masses from the south is the primary driver of heatwave onset and maintenance, the highest temperatures (and most vulnerable areas) occur over arable land and artificial surfaces in central and western Poland, while coastal areas in the north, mountain areas in the south, and forested and mosaic areas of smaller fields and pastures of the northwest, northeast, and southeast are less affected by prolonged periods of elevated temperatures. In general, regional differences in 2-m temperature between the hottest and coolest areas is about 2-4 °C. Large urban areas like Warsaw, or the large complex of artificial areas in the conurbation of Silesian cities, are also generally warmer than surrounding areas by roughly 2-4 °C, and even up to 6 °C, especially during the night. Additionally, hot air from the south of Poland flows through a low-lying area between two mountain ranges (Sudetes and Carpathian Mountains)—the so-called Moravian Gate—hitting densely populated urban areas (Silesian cities) and Cracow. These patterns occur only during high-pressure synoptic conditions with low cloudiness and wind and without any active fronts or mesoscale convective disturbances. [ABSTRACT FROM AUTHOR]

This paper investigates patterns of daily evolutions of CO in the lower atmosphere at a rural site over 2 years. The first part is devoted to observation analysis using a clustering procedure. However, direct application of the average-linkage method yielded undesirable results. In order to improve this procedure, data were previously processed using three smoothing procedures: the kernel smoothing method, the elliptical procedure, and the second-order cylindrical model. These procedures successfully revealed that clusters were based on daily concentration and range. However, the unequal distribution of frequencies in the clusters proved to be a noticeable disadvantage. Four alternative and simpler schemes for grouping observations were proposed in the second part of this paper. The first, comprising groups following fixed values of daily range and mean concentration, provided a sharp contrast between spring, with a marked daily cycle linked to the biological peak, and summer with a smooth daily cycle and low concentration when the biological minimum was reached. The second scheme is based on isopleth analysis and considers observation groups of similar frequencies following an increasing order of mean concentration and daily range. As a result, seasonal evolution was less marked. Straight lines were the borders for groups in the third scheme, which was similar and simpler than the second. The final scheme divided observations by means of equations of daily range as a quadratic function of daily concentration. The groups formed may be linked to seasons, with the group prevailing in summer presenting a noticeable daily range. [ABSTRACT FROM AUTHOR]

This paper presents the results of processing and analysis of acoustic waves in the surface layer of the atmosphere, registered at the Mikhnevo Geophysical Observatory, Institute of Geosphere Dynamics, Russian Academy of Sciences (IGD RAS). Using the autoregression model of digital series, the spectrum of acoustic oscillations was evaluated and the tidal waves in the envelopes of acoustic oscillations were distinguished. The tidal components with similar periods were separated using the method of extraction of harmonic components by using adaptive notch filters. The observed features of the spectrum of acoustic oscillations open up new opportunities for instrumental control over meteorological conditions and the establishment of general regularities controlling the regimes of energy-exchange processes in the Earth's atmosphere. [ABSTRACT FROM AUTHOR]

Extreme weather events have become more frequent and intense under global warming in recent years, which has attracted much attention of scholars at home and abroad. In this paper, we used data sets of daily precipitation recorded at 499 meteorological stations to analyze the temporal and spatial variations of precipitation extremes in China over the past 50 years (1960-2009). Through the comparison of detrended fluctuation analysis (DFA) and the percentile method, DFA was selected to define the thresholds of precipitation extremes in China. Temporal variations of extreme precipitation amount, frequency, and intensity were analyzed in four major regions: Northwest China, the Qinghai-Tibet region, North China, and South China. Spatial distributions were obtained by the Kriging interpolation method, and then, we examined the varying tendencies of extreme precipitation amount, frequency, and intensity by the Mann-Kendall test. The results show that increasing trends are dominant for all indices over China; extreme precipitation amount and frequency appear to have risen since 1970-1979, but there are some regional differences. The Qinghai-Tibet region and South China have an ascending trend, and Northwest China maintains balance while North China has a descending trend. The amount and intensity of precipitation extremes are decreasing from southeastern coastal areas to northwestern inlands, and the frequency of precipitation extremes is randomly distributed. However, they are all high in the Sichuan Basin, the middle and lower Yangtze River, and the southern part of South China. Trends of most stations are statistically insignificant, but the percentage of stations with a significant increased trend in the Qinghai-Tibet region is larger than that of other regions. [ABSTRACT FROM AUTHOR]

In this paper, the performance of the regional climate model (RegCM4) in simulating the interannual and interdecadal variation of Meiyu rainfall over lower and middle reaches of Yangtze River (LMRYR) in China is evaluated. The results show that the bias of the simulated Meiyu rainfall exhibits some uncertainties and obvious interdecadal variation similar with that of Meiyu rainfall itself. The rainfall bias and its interdecadal variation have little impact on the simulation of the interannual variation of the Meiyu rainfall. Not only the amplitude but also the phase of the interannual variation of the Meiyu rainfall can be reproduced by the RegCM4. However, the interdecadal variation of the rainfall bias has large impacts on the model's performance in simulating the interdecadal component of the Meiyu rainfall, leading to lower skill of RegCM4 in simulating the interdecadal variation of the Meiyu rainfall than that in simulating the interannual variation. In addition, the interannual signals of the temperature, humidity, and vorticity in the lower troposphere in the large-scale NCEP lateral boundary force are stronger than the interdecadal signals, and the model can respond well to these interannual signals. Therefore, the RegCM4 has better performance in simulating the interannual variation of water vapor budget than the interdecadal variation, which further favors the simulation of the Meiyu rainfall at interannual time scale. [ABSTRACT FROM AUTHOR]

This paper aims to introduce an approach for multi-hour forecasting (915 h ahead) of hourly global horizontal solar radiation time series and forecasting of a small-scale solar radiation database (30- and 1-s scales) for a period of 1 day (47,000 s ahead) using commonly and available measured meteorological solar radiation. Three methods are considered in this study. First, autoregressive-moving-average (ARMA) model is used to predict future values of the global solar radiation time series. However, because of the non-stationarity of solar radiation time series, a phase of detrending is needed to stationarize the irradiation data; a 6-degree polynomial model is found to be the most stationary one. Secondly, due to the nonlinearity presented in solar radiation time series, a nonlinear autoregressive (NAR) neural network model is used for prediction purposes. Taking into account the advantages of both models, the goodness of ARMA for linear problems and NAR for nonlinear problems, a hybrid method combining ARMA and NAR is introduced to produce better results. The validation process for the site of Ghardaia in Algaria shows that the hybrid model gives a normalized root mean square error (NRMSE) equals to 0.2034 compared to a NRMSE equal to 0.2634 for NAR model and 0.3241 for ARMA model. [ABSTRACT FROM AUTHOR]

This study aims to couple a deterministic atmospheric dispersion solver based on Gaussian model with a nonintrusive stochastic model to quantify the propagation of multiple uncertainties. The nonintrusive model is based on probabilistic collocation framework. The advantage of nonintrusive nature is to retain the existing deterministic plume dispersion model without missing the accuracy in extracting the statistics of stochastic solution. The developed model is applied to analyze the SO emission released from coal firing unit in the second stage of the National Thermal Power Corporation (NTPC) in Dadri, India using 'urban' conditions. The entire application is split into two cases, depending on the source of uncertainty. In case 1, the uncertainties in stack gas exit conditions are used to construct the stochastic space while in case 2, meteorological conditions are considered as the sources of uncertainty. Both cases develop 2D uncertain random space in which the uncertainty propagation is quantified in terms of plume rise and pollutant concentration distribution under slightly unstable atmospheric stability conditions. Starting with deterministic Gaussian plume model demonstration and its application, development of stochastic collocation model, convergence study, error analysis, and uncertainty quantification are presented in this paper. [ABSTRACT FROM AUTHOR]

Drought is a serious problem in southwestern China, where drought risk exceeds the national average. Climate change is likely to exacerbate the problem, thereby endangering China's food security. In this paper, we used the analytic hierarchy process and meteorological, geographic, soil, and remote-sensing data to develop a drought risk assessment model based on the drought hazard, environmental vulnerability, sensitivity and exposure of the values at risk, and capacity to prevent or mitigate the problem. Using the model, we assessed the drought risk (defined using a comprehensive drought risk index, R) and its spatial distribution in southwestern China and revealed complex zonality. The eastern part of the study area had an extremely high risk, and risk was generally greater in the north than in the south, and increased from southwest to northeast. The comprehensive risk ( R) was lowest in Yunnan province. It was highest in Sichuan Province and Chongqing Municipality. The contribution of the risk factors to R was highest for the capacity for prevention and mitigation, followed by the drought hazard, sensitivity and exposure, and environmental vulnerability. [ABSTRACT FROM AUTHOR]

The effects of surface flux parameterizations on tropical cyclone (TC) intensity and structure are investigated using the Advanced Research Weather Research and Forecasting (WRF-ARW) modeling system with high-resolution simulations of Typhoon Morakot (2009). Numerical experiments are designed to simulate Typhoon Morakot (2009) with different formulations of surface exchange coefficients for enthalpy ( C) and momentum ( C) transfers, including those from recent observational studies based on in situ aircraft data collected in Atlantic hurricanes. The results show that the simulated intensity and structure are sensitive to C and C, but the simulated track is not. Consistent with previous studies, the simulated storm intensity is found to be more sensitive to the ratio of C/ C than to C or C alone. The pressure-wind relationship is also found to be influenced by the exchange coefficients, consistent with recent numerical studies. This paper emphasizes the importance of C and C on TC structure simulations. The results suggest that C and C have a large impact on surface wind and flux distributions, boundary layer heights, the warm core, and precipitation. Compared to available observations, the experiment with observed C and C generally simulated better intensity and structure than the other experiments, especially over the ocean. The reasons for the structural differences among the experiments with different C and C setups are discussed in the context of TC dynamics and thermodynamics. [ABSTRACT FROM AUTHOR]

Numerical weather modelling has gained considerable attention in the field of hydrology especially in un-gauged catchments and in conjunction with distributed models. As a consequence, the accuracy with which these models represent precipitation, sub-grid-scale processes and exceptional events has become of considerable concern to the hydrological community. This paper presents sensitivity analyses for the Weather Research Forecast (WRF) model with respect to the choice of physical parameterization schemes (both cumulus parameterisation (CPSs) and microphysics parameterization schemes (MPSs)) used to represent the '1999 York Flood' event, which occurred over North Yorkshire, UK, 1-14 March 1999. The study assessed four CPSs (Kain-Fritsch (KF2), Betts-Miller-Janjic (BMJ), Grell-Devenyi ensemble (GD) and the old Kain-Fritsch (KF1)) and four MPSs (Kessler, Lin et al., WRF single-moment 3-class (WSM3) and WRF single-moment 5-class (WSM5)] with respect to their influence on modelled rainfall. The study suggests that the BMJ scheme may be a better cumulus parameterization choice for the study region, giving a consistently better performance than other three CPSs, though there are suggestions of underestimation. The WSM3 was identified as the best MPSs and a combined WSM3/BMJ model setup produced realistic estimates of precipitation quantities for this exceptional flood event. This study analysed spatial variability in WRF performance through categorical indices, including POD, FBI, FAR and CSI during York Flood 1999 under various model settings. Moreover, the WRF model was good at predicting high-intensity rare events over the Yorkshire region, suggesting it has potential for operational use. [ABSTRACT FROM AUTHOR]

Precipitation time series were analysed using the Mann-Kendall (MK) test and wavelet analysis based on the mean seasonal and annual precipitation from 29 meteorological stations in Jilin Province for the period 1958-2011. Both the temporal and spatial distribution characteristics of the seasonal and annual precipitation trends and periodicities in different regions in Jilin Province were studied for the first time in this paper. New findings from the intensive calculations and appropriate analysis of data in longer period are as follows: (i) The annual precipitation of Jilin Province has experienced four states: a decrease (1958-1980), increase (1980-1987), decrease (1987-2003) and increase (2003-2011). (ii) The annual precipitation and seasonal precipitation increased from the northwest and northeast of the study area toward the south. (iii) Almost 90 % of the stations showed negative trends in annual precipitation variations. (iv) The trends in spring and winter are mainly increasing, whereas the trends in summer and autumn are mainly decreasing. (v) Jilin Province can be divided into four parts based on the periodicities of annual precipitation sequences: 5-6, 10-20 and 25-30 years in the northwest; 4-8 and 16-25 years in the centre; 7-8 and 13-17 years in the south and 5-10 and 12-17 years in the southeast. [ABSTRACT FROM AUTHOR]

The ambient air temperature (T) is an important environmental parameter which can be estimated from satellite observations of the land surface temperature (LST) using a linear regression model. This paper attempts to answer the question of whether the series of a single pixel or a spatially averaged series over several pixels should be used for modelling T from remotely sensed LST data. Sensitivity of LST-T relationship to the moderate resolution imaging spectroradiometer (MODIS) window size, which determines the number of pixels contributed in the correlations, over a number of test sites in New Zealand was analysed. LST series of a single pixel over a period of 10 years gave a correlation coefficient $r\geqslant $ 0.80 with T measurements. Bootstrapping by random resampling from seasonal subsets of both time-series was applied to determine seasonal and inter-annual variability of LST-T relationship. A fast Fourier filtering was applied for noise reduction and detection of dominant spectra in LST series. Spatially averaged time-series from larger windows, which included more pixels, showed slightly higher agreement with T measurements. We considered the effects of wind speed (WS) and wind direction (WD) on the LST-T relationship. Highest correlation between T and LST time-series was achieved using a 25 × 25 window at 2 ≤ WS < 8 ms. No significant effect due to WD was found in the results. MODIS-Terra nighttime (∼10:30 PM) observations showed the highestwhile MODIS-Aqua nighttime (∼1:30 AM) observations showed the lowest agreement with T measurements. These results indicate that the best approach for modelling T based on LST observations from MODIS in the long-term is to use a spatially averaged LST series over a window of 5 × 5 to 25 × 25 pixels, with a consideration of WS effects and observation times. [ABSTRACT FROM AUTHOR]

The principal aim of this paper is to assess the influence of meteorological conditions on the variability of sulfur dioxide and PM10 particulate matter concentration of pollutants during winter with consideration of an excess of admissible standards. The basis for the analysis were hourly concentrations of PM10 and sulfur dioxide as well as the basic meteorological elements automatically recorded at five stations located in the Tricity agglomeration, and operating within the weather station network belonging to the Agency of Regional Air Quality Monitoring in the Gdańsk Metropolitan Area (ARMAAG). The analysis covers the calendar winters (December-February) in the years 2004/2005 through 2009/2010. The variability of the concentrations of both pollutants under certain weather conditions, i.e. air temperature and relative humidity, atmospheric pressure, as well as wind speed and direction, were evaluated by means of cluster analysis using k-means belonging to a group of non-hierarchical cluster analysis method. The composite effect of meteorological conditions on the variability of sulfur dioxide and PM10 concentrations in isolated clusters were determined by multiple linear regression, using a stepwise procedure, at the significance level α = 0.05 and α = 0.01. The effect of individual weather elements on the pattern of concentration levels was determined using partial regression coefficients. Clusters grouping the highest concentrations of pollutants were characterised, in most cases, by the lowest air temperature and a lower wind speed, and often a higher pressure, and sometimes slightly lower relative air humidity, i.e. the conditions of anticyclonic weather. Weather conditions had a statistically significant effect on the concentrations of both pollutants in all clusters; however, air temperature and wind speed had the crucial role. Thermal conditions were the decisive factor in the winter season 2005/2006 with the most frequent, overnormative daily particulate matter concentration, yet the inversion layers both lower and upper, occurring almost every day in January 2006 also had a significant influence. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate characteristics of meteorological and agricultural droughts and their trends in Iran, as well as several subregions with different climate conditions from 1980 to 2013. The Standardized Precipitation Index (SPI) and Standardized Soil Moisture Index (SSI) are used as the primary indicators of meteorological and agricultural droughts, respectively. This study assesses historical droughts using the Multivariate Standardized Drought Index (MSDI), which provides a composite model of meteorological-agricultural drought. Furthermore, this study discusses the behavior of MSDI relative to the other indices (SPI and SSI) over different climatic conditions ranging from humid, semiarid, and hyperarid regions. The Mann-Kendall trend test shows that the northern, northwestern, and central parts of Iran have experienced significant drying trends at a 95 % confidence level. However, no statistically significant drying trend was observed in the eastern part of Iran. The most severe drought across the country occurred between 1998 and 2001, with approximately 80 % of the country experiencing an exceptional drought (<2 % probability of occurrence). This event coincided with a prolonged cold phase El Niño-Southern Oscillation (La Niña) that led to persistently cold sea surface temperatures in the eastern Pacific and warm sea surface temperatures in the Indian and western Pacific. [ABSTRACT FROM AUTHOR]

This paper examines the connection between the probability of precipitation and forecast amounts from Weather Research and Forecasting (WRF) model runs over Central and West Africa. A one season period (June-September 2010) was used to investigate the quantitative precipitation forecast-probability relationship. The predictive capability of this relationship was then tested on an independent sample of data (June-September 2011); 2010 and 2011 were wet and dry years, respectively. The results show that rainfall is less likely to occur in those areas where the model indicates no precipitation than it is elsewhere in the domain. Rainfall is more likely to occur in those regions where precipitation is predicted, especially where the predicted precipitation amounts are largest. The probabilities of rainfall forecasts based on this relationship are found to possess skill as measured by relative operating characteristic curves, reliability diagrams, and Brier skill scores. Skillful forecasts from the technique exist throughout 24-h periods for which WRF output was available. The results suggest that this forecasting tool might assist forecasters throughout the season in a wide variety of weather events and not only in areas of difficult-to-forecast convective systems. [ABSTRACT FROM AUTHOR]

In this paper we describe the results of a research campaign dedicated to the studies of aerosol optical properties in different regions of both the open Baltic Sea and its coastal areas. During the campaign we carried out simultaneous measurements of aerosol optical depth at 4 stations with the use of the hand-held Microtops II sun photometers. The studies were complemented with aerosol data provided by the MODIS. In order to obtain the full picture of aerosol situation over the study area, we added to our analyses the air mass back-trajectories at various altitudes as well as wind fields. Such complex information facilitated proper conclusions regarding aerosol optical depth and Ångström exponent for the four locations and discussion of the changes of aerosol properties with distance and with changes of meteorological factors. We also show that the Microtops II sun photometers are reliable instruments for field campaigns. They are easy to operate and provide good quality results. [ABSTRACT FROM AUTHOR]

Impacts of El Niño Modoki (ENM), La Niña Modoki (LNM), canonical El Niño (CEN) and canonical La Niña (CLN) on tropical cyclones (TCs) that made landfall over mainland China during 1951-2011 are analysed using best-track data from China, the USA and Japan. Relative to cold phase years (LNM and CLN), landfalling TCs in warm years (ENM and CEN) have a farther east genesis location, as well as longer track lengths and durations, both in total and before landfall. ENM demonstrates the highest landfall frequency, most northerly mean landfall position, and shortest after-landfall sustainability (track length and duration), which indicate a more frequent and extensive coverage of mainland China by TCs, but with shorter after-landfall influence. CEN has low landfall frequency and the most southerly mean landfall location. LNM has the most westerly genesis location, being significantly farther west than the 1951-2011 average and leading to short mean track lengths and durations both in total or before landfall, all of which are significantly shorter than the 1951-2011 average. Variations in the low-level wind anomaly, vertical wind shear, mid-level relative humidity, steering flow, the monsoon trough and the western Pacific subtropical high (WPSH) can to some extent account for the features of frequency, location, track length and duration of landfalling TCs. Since ENSO Modoki is expected to become more frequent in the near future, the results for ENSO Modoki presented in this paper are of particular significance. [ABSTRACT FROM AUTHOR]

The paper discusses a methodology able to estimate both the discrete and continuous spectra without any assumption on the shape of spectral densities. The approach to estimate the spectral density is based on a robust smoothing of the periodogram. Bandwidth, a quantity similar to the width of spectral windows traditionally used in spectral analysis, is estimated locally in contrast to intuitively chosen global window lengths. Detection and estimation of frequencies forming discrete spectra are also addressed. The procedure is applied to Central England temperature (CEt), North Atlantic Oscillation (NAO) index and Oxygen Isotope of North Greenland Ice Core Project (δ18O of NGRIP) data. Annual and half annual cycles were detected in CEt data, whilst 118.2- and 41.7-ky cycles were found in δ18O of NGRIP. This latter periodicity is almost as intense as the dominant longer cycle. Several local peaks of spectral densities were recognised in each time series that mostly cover earlier results. However, a few previous findings at low frequencies have not been reinforced by the present method. Identification of modest local peaks or discrete amplitudes at low frequencies is an extremely challenging task as climatic data generally have spectral densities rising to low frequencies. [ABSTRACT FROM AUTHOR]

The article focuses on the research on ocean circulation in a warming climate. Accordingly, findings show that the Last Glacial Maximum (LGM) had stronger winds which fit to the common observation that it is windier in the winter than in the summer because there is greater thermal contrast within the atmosphere in the winter hemisphere. Moreover, the paper cited several observations that predict that oceans' circulation will weaken in response to global warming, but the warming at the end of the last ice age suggests a different outcome. However, by studying these observations, it is clear that large circulation changes took place and it seems unlikely that circulation changes of this magnitude could have happened without substantial changes in the wind forcing.

Nowadays, due to the expansion of people's living ranges and the impact of human life on the natural environment, climate changes fiercely than before. In order to observe the changing climate environment accurately, multi-modal sensors are used to collect the various data around us, and we could analyze and predict the weather based on these collected data. One of the applications is 3D visualization simulation, and the 3D visualization simulation of cloud data has always been the research hotspot in the field of computer graphics and meteorology. Currently, it is a key challenge to resolve the problems of 3D cloud simulation, such as reducing complexity of modeling and computation and improving the real-time performance. Technically, a method for data modeling and optimizing based on Weather Research and Forecasting (WRF) is proposed in this paper, aiming to solve the problems of the existing 3D cloud simulation and realize 3D virtual simulation of real-world cloud data. According to the characteristics (e.g., color, size, shape) of the cloud, the spherical particle system is designed to model, and the initial color, size, shape, and other attributes are given to these spherical particles to realize the modeling of WRF cloud data. From the perspective of new particles' generation, the level of detail (LOD) technique, based on the relationship between the quantity of new generated spherical particles and the distance of the viewpoint, is used to change the quantity of new particles generated in real time according to the distance of the simulated scene distance. Finally, illumination model is introduced to render and simulate the modeling particles. Experimental simulation results verify the effectiveness of this method in improving the modeling and rendering speed of cloud data as well as the fidelity of the 3D virtualization model. [ABSTRACT FROM AUTHOR]

The article discusses various aspects that affect glaciation. It is said that several theories have been proposed towards proper understanding on glaciation such as the proposal of Joseph Adhémar that glaciation occurs when winters are anomalously long, which happen when they coincide with the point of Earth's orbit that is farthest from the sun. However, it is suggested that despite the wide acceptance of the variations in Earth's orbit that affect glaciation, there is still a need for a better and more detailed understanding of this process. The paper also presented a strong evidence from James Hays, John Imbrie and Nicholas Shackleton in support to the orbital hypothesis of glaciation.

The article provides several concepts regarding the study of Satrurn's biggest moon, Titan. It was found that there is a hydrological cycle in the moon. It was claimed that the rivers on Titan's surface were probably not caused by methane drizzle because the rainfall is too weak. The paper will be of interest to terrestrial meteorologists.