Meteorological Processes Research Articles

The development and validation of the Inhomogeneous Wind Scheme for Urban Street (IWSUS-v1)

Abstract. The layout of urban buildings shows significant heterogeneity, which leads to the significant spatial inhomogeneity of the wind field in and over the canopy of urban street canyons. However, most of the current urban canopy models do not fully consider the heterogeneity of the urban canopy. Large discrepancies thus exist between the wind speeds simulated by the current urban canopy models and those observed in the street canyon. In this study, a parameterization scheme for wind fields, Inhomogeneous Wind Scheme for Urban Street (IWSUS), is developed to better characterize the heterogeneity of the urban canopy. We use a computational fluid dynamics method to generate the IWSUS scheme and compare it with observations of the wind profile and turbulent flux in and over the street canyon for validation. In IWSUS, the wind speed vertical profiles at six representative positions located in a typical street canyon (i.e., the windward or leeward side of a long straight street or the inflow or outflow end) are parameterized separately. The wind profile by IWSUS thus can better describe the horizontal heterogeneity of the urban near-surface wind field, e.g., the dynamic drag effect of buildings in the lower atmospheric layer over the urbanized land use. The validation based on observations shows that the performance of simulation results by IWSUS is better than that by the exponential–logarithmic (exp-log) law widely used in the current urban schemes. We consider typical building arrangement and specific street orientations in IWSUS for wind field simulations, which can better match the distribution characteristics of street canyons around the observation point in the street canyon. The averaged wind profiles and turbulence energy fluxes in the model grids of urban areas by IWSUS are also nearer to the observations than those by the exp-log law. The normalized mean errors (NMEs) between the simulated and the observed vertical average wind speed are 49.0 % for IWSUS and 56.1 % for exp-log law in the range from the ground to 4 times the average height of the buildings and 70 % for IWSUS and 285.8 % for exp-log law in the street canyon (range from the ground to building top). This study proves that the accuracy of simulations of land surface processes and near-ground meteorological processes over the urban canopy can be improved by fully considering the heterogeneity of the urban canopy layout structures and the inhomogeneity of wind field distributions in and over the street canyon. IWSUS is expected to be coupled with mesoscale atmospheric models to improve the accuracy of the wind field, land surface energy budget, meteorological and atmospheric chemistry simulations.

Soaring migrants flexibly respond to sea-breeze in a migratory bottleneck: using first derivatives to identify behavioural adjustments over time

BackgroundMillions of birds travel every year between Europe and Africa detouring ecological barriers and funnelling through migratory corridors where they face variable weather conditions. Little is known regarding the response of migrating birds to mesoscale meteorological processes during flight. Specifically, sea-breeze has a daily cycle that may directly influence the flight of diurnal migrants.MethodsWe collected radar tracks of soaring migrants using modified weather radar in Latrun, central Israel, in 7 autumns between 2005 and 2016. We investigated how migrating soaring birds adjusted their flight speed and direction under the effects of daily sea-breeze circulation. We analysed the effects of wind on bird groundspeed, airspeed and the lateral component of the airspeed as a function of time of day using Generalized Additive Mixed Models. To identify when birds adjusted their response to the wind over time, we estimated first derivatives.ResultsUsing data collected during a total of 148 days, we characterised the diel dynamics of horizontal wind flow relative to the migration goal, finding a consistent rotational movement of the wind blowing towards the East (morning) and to the South-East (late afternoon), with highest crosswind speed around mid-day and increasing tailwinds towards late afternoon. Airspeed of radar detected birds decreased consistently with increasing tailwind and decreasing crosswinds from early afternoon, resulting in rather stable groundspeed of 16–17 m/s. In addition, birds fully compensated for lateral drift when crosswinds were at their maximum and slightly drifted with the wind when crosswinds decreased and tailwinds became more intense.ConclusionsUsing a simple and broadly applicable statistical method, we studied how wind influences bird flight through speed adjustments over time, providing new insights regarding the flexible behavioural responses of soaring birds to wind conditions. These adjustments allowed the birds to compensate for lateral drift under crosswind and reduced their airspeed under tailwind. Our work enhances our understanding of how migrating birds respond to changing wind conditions during their long-distance journeys through migratory corridors.

Aircraft Target Detection from Remote Sensing Images under Complex Meteorological Conditions

Taking all-day, all-weather airport security protection as the application demand, and aiming at the lack of complex meteorological conditions processing capability of current remote sensing image aircraft target detection algorithms, this paper takes the YOLOX algorithm as the basis, reduces model parameters by using depth separable convolution, improves feature extraction speed and detection efficiency, and at the same time, introduces different cavity convolution in its backbone network to increase the perceptual field and improve the model’s detection accuracy. Compared with the mainstream target detection algorithms, the proposed YOLOX-DD algorithm has the highest detection accuracy under complex meteorological conditions such as nighttime and dust, and can efficiently and reliably detect the aircraft in other complex meteorological conditions including fog, rain, and snow, with good anti-interference performance.

Assessing the Impact of Climate Change on Water Usage in Typical Industrial Enterprises

Climate change and water scarcity are significant global issues both currently and in the future. Investigating the changes in industrial water usage under this backdrop holds crucial guidance for enabling adaptive changes within industries. It offers methods and case support for assessing the impact of climate on the water usage processes of industrial enterprises as well. This study employed a physical model to examine the impact of climate factors on the primary water consumption processes of a selected case of a coal-fired power plant. Additionally, by utilizing the ScenarioMIP experimental outcomes from CMIP6 models, the future water consumption processes were predicted under four different SSPs-RCPs scenarios. A relevant LSTM neural network was constructed based on the primary water consumption calculation to establish connections between the power generation process, meteorological process, water consumption process, and water intake process. Findings from the study reveal that the annual average primary water consumption showed a decreasing trend in different SSPs-RCPs scenarios. Specifically, there were reductions of 1600, 5300, 9000, and 11,400 t/year in each respective scenario from SSP1–2.6 to SSP5–8.5. Conversely, the water intake exhibited a gradual increase, with increments of 2000, 5600, 9200, and 10,000 t/year, respectively. Moreover, the impact of climate change on evaporation showed an annual decrease of less than 0.056%, while the increase in water intake was below 0.044%. Under the SSPs-RCPs scenarios, both water intake and consumption exhibited a gradually increasing trend with fluctuations ranging from 1–2.6 to 5–8.5. However, the annual trends remained relatively stable. It is crucial to acknowledge that climate change has amplified the uncertainty surrounding water intake and consumption. Industrial enterprises should proactively ensure the stability of their production processes in response to climate change.

Updating and evaluating the NH3 gas-phase chemical mechanism of MOZART-4 in the WRF-Chem model

The accuracy of determining atmospheric chemical mechanisms is a key factor in air pollution prediction, pollution-cause analysis and the development of control schemes based on air quality model simulations. However, the reaction of NH3 and OH to generate NH2 and its subsequent reactions are often ignored in the MOZART-4 chemical mechanism. To solve this problem, the gas-phase chemical mechanism of NH3 was updated in this study. Response surface methodology (RSM), integrated gas-phase reaction rate (IRR) diagnosis and process analysis (PA) were used to quantify the influence of the updated NH3 chemical mechanism on the O3 simulated concentration, the nonlinear response relationship of O3 and its precursors, the chemical reaction rate of O3 generation and the meteorological transport process. The results show that the updated NH3 chemical mechanism can reduce the error between the simulated and observed O3 concentrations and better simulate the O3 concentration. Compared with the Base scenario (original chemical mechanism simulated), the first-order term of NH3 in the Updated scenario (updated NH3 chemical mechanism simulated) in RSM passed the significance test (p < 0.05), indicating that NH3 emissions have an influence on the O3 simulation, and the effects of the updated NH3 chemical mechanism on NOx-VOC-O3 in different cities are different. In addition, the analysis of chemical reaction rate changes showed that NH3 can affect the generation of O3 by affecting the NOx concentration and NOx circulation with radicals of OH and HO2 in the Updated scenario, and the change of pollutant concentration in the atmosphere leads to the change of meteorological transmission, eventually leading to the reduction of O3 concentration in Beijing. In conclusion, this study highlights the importance of atmospheric chemistry for air quality models to model atmospheric pollutants and should attract more research focus.

The Influence of Synoptic-Scale Wind Patterns on Column-Integrated Nitrogen Dioxide, Ground-Level Ozone, and the Development of Sea-Breeze Circulations in the New York City Metropolitan Area

Abstract The continually changing atmospheric conditions over densely populated coastal urban regions make it challenging to produce models that accurately capture the complex interactions of anthropogenic and environmental emissions, chemical reactions, and unique meteorological processes, such as sea- and land-breeze circulations. The purpose of this study is to determine and identify the influence of synoptic-scale wind patterns on the development of local-scale sea-breeze circulations and air quality over the New York City (NYC), New York, metropolitan area. This study utilizes column-integrated nitrogen dioxide observations made during the Long Island Sound Tropospheric Ozone Study (LISTOS) field campaign, ground-level ozone observations, the HRRR numerical weather prediction model, and trajectory model simulations using the NOAA HYSPLIT model. A cluster analysis within the HYSPLIT modeling system was performed to determine that there were six unique synoptic-scale transport pathways for NYC. Stagnant conditions or weak transport out of the northwest resulted in the worst air quality for NYC. Weak synoptic-scale forcings associated with these conditions allowed for local-scale sea-breeze circulations to develop, resulting in air pollution being able to recirculate and mix with freshly emitted pollutants. Significance Statement The purpose of this work is to understand how synoptic-scale wind patterns influence air quality and sea-breeze circulations in the New York City, New York, metropolitan area. This work shows that clean air can be imported into the region from rural New England and over the Atlantic Ocean, whereas polluted air can be transported into the region from the northwest and southwest. This work also shows the importance of the strength in synoptic-scale forcings in the development of sea-breeze circulations. Weak synoptic-scale winds allow for strong sea-breeze circulations to develop over all coastlines in the New York City region, resulting in air pollutants recirculating and mixing with freshly emitted air pollution and contributing to poor air quality.

Using the U.S. Climate Reference Network to Identify Biases in Near- and Subsurface Meteorological Fields in the High-Resolution Rapid Refresh (HRRR) Weather Prediction Model

Abstract The ability of high-resolution mesoscale models to simulate near-surface and subsurface meteorological processes is critical for representing land–atmosphere feedback processes. The High-Resolution Rapid Refresh (HRRR) model is a 3-km numerical weather prediction model that has been used operationally since 2014. In this study, we evaluated the HRRR over the contiguous United States from 1 January 2021 to 31 December 2021. We compared the 1-, 3-, 6-, 12-, 18-, 24-, 30-, and 48-h forecasts against observations of air and surface temperature, shortwave radiation, and soil temperature and moisture from the 114 stations of the U.S. Climate Reference Network (USCRN) and evaluated the HRRR’s performance for different geographic regions and land cover types. We found that the HRRR well simulated air and surface temperatures, but underestimated soil temperatures when temperatures were subfreezing. The HRRR had the largest overestimates in shortwave radiation under cloudy skies, and there was a positive relationship between the shortwave radiation mean bias error (MBE) and air temperature MBE that was stronger in summer than winter. Additionally, the HRRR underestimated soil moisture when the values exceeded about 0.2 m3 m−3, but overestimated soil moisture when measurements were below this value. Consequently, the HRRR exhibited a positive soil moisture MBE over the drier areas of the western United States and a negative MBE over the eastern United States. Although caution is needed when applying conclusions regarding HRRR’s biases to locations with subgrid-scale land cover variations, general knowledge of HRRR’s biases will help guide improvements to land surface models used in high-resolution weather forecasting models. Significance Statement Weather forecasters rely upon output from many different models. However, the models’ ability to represent processes happening near the land surface over short time scales is critical for producing accurate weather forecasts. In this study, we evaluated the High-Resolution Rapid Refresh (HRRR) model using observations from the U.S. Climate Reference Network, which currently includes 114 reference climate observing stations in the contiguous United States. These stations provide highly accurate measurements of air temperature, precipitation, soil temperature, and soil moisture. Our findings helped illustrate conditions when the HRRR performs well, but also conditions in which the HRRR can be improved, which we expect will motivate ongoing improvements to the HRRR and other weather forecasting models.

Evolution of summer surface ozone pollution patterns in China during 2015–2020

Surface ozone is one of the most severe air pollutants in China and is influenced by meteorological processes on multiple scales. By identifying the two dominant patterns of ozone pollution through Empirical Orthogonal Functions method, we show here that the widespread pollution processes in China may be closely related to high-pressure anomaly in North China and low-pressure anomaly in the western Pacific, respectively. The positive time period of the first pattern (PC1P) extracts the distribution characteristics of the most severe periods of ozone pollution in summer time. It is physically linked to the high-pressure anomaly in North China centered on the Huanghuai Region, which eventually induced the high-temperature anomaly and low-humidity anomaly that enhanced the photochemical reactions to elevate the ozone levels. The spatial and temporal evolution of ozone pollution during this meteorological process shows a uniform pollution characteristic in the northern region and a higher increase in ozone concentration in the Huanghuai Region. The positive time period of the second pattern (PC2P) is associated with the variation of the low-pressure anomaly in the western Pacific. It indicates uniformly high ozone pollution in the south, especially in the Yangtze River Delta, the middle reaches of the Yangtze River (MYR) and the Pearl River Delta. Our results highlight that summer ozone pollution in eastern China is closely related to weather patterns. In addition, it is noteworthy that in the positive time period, the annual growth trends of Huanghuai Region in the first pattern (PC1P) and MYR in the second pattern (PC2P) are significantly higher than the growth trends of the megacity clusters, which requires the attention of relevant policy-making authorities.

A Rolling Real-Time Correction Method for Minute Precipitation Forecast Based on Weather Radars

The quantitative precipitation estimation by weather radar plays an important role in observations and forecasts of meteorological processes. The National Minute Quantitative Precipitation Forecast system of China (MQPF), providing location-based refined short-term and imminent precipitation forecasting services, filled the gap in the official minute precipitation service products in China’s meteorological field. However, due to the technical limitations of radar itself and the complexity of the atmosphere, the corresponding relationship between radar echoes and surface precipitation is unstable. Based on radar and precipitation data from meteorological stations, a rolling real-time correction method is proposed to improve precipitation prediction accuracy through rolling correction of spatial and temporal structural errors in MQPF products. The results show the following: (1) Although this method may lead to a certain increase in the missing ratio, the significant improvement in the false alarm ratio after rolling correction has a positive guiding effect on short-term public meteorological services. (2) Regarding the time to complete rolling correction, the longest and shortest times appear in April and December, respectively. The mean running time to achieve correction of spatial and temporal error corrections ranges from 3.8 s to 6.4 s and 7.7 s to 11.5 s, respectively, which fully meets the real-time operational requirements of radar business.

Generation of type-specific synthetic design flood hydrographs

ABSTRACT Design flood hydrographs are essential for hydraulic engineering and flood risk assessment. Typically, they are derived from quantiles estimated from flood frequency analyses of flood peaks. This usually does not take into account that one and the same flood peak can occur with different volumes and various hydrograph shapes due to different meteorological and catchment-specific processes. In view of this issue, we generate design flood scenarios, i.e. type-specific design hydrographs are created for a flood quantile of a certain return period based on type-specific flood volumes and hydrograph shapes. Additionally, the probability of each flood type is derived. Different probability density functions are used as templates for generating different hydrograph shapes by varying their parameters. An ensemble of synthetic design flood hydrographs is obtained, which allows the consideration of best- and worst-case scenarios. A case study for 162 catchments in Germany demonstrates the applicability of the approach.

Lightning Development over the Distinct Climate Regions of Uttarakhand, India

Objectives: Lightning activity and its connections with meteorology and aerosol loading over Uttarakhand, with varying topography and climates, is studied using ISS Lightning Imaging Sensor (LIS) aboard international space station (ISS) data during the period 2018–2021. Methods: To understand the variation of lightning activity with meteorology and aerosol loading the correlation of lightning activity with different meteorological parameters such as surface temperature, convective available potential energy (CAPE), aerosol optical depth (AOD), and convective precipitation is studied. Findings: Very poor correlation is observed between lightning flash counts with the meteorological parameters. Annual variation of lightning activity over Uttarakhand shows maximum during the monsoon season (June–September) with a peak during the pre–monsoon season (March–May) month April. The high frequency of western disturbances defined as warm low-pressure systems associated with moisture originated over Mediterranean Sea travelling from west to east across the northern states are responsible for peak lightning activity during pre–monsoon month April and maximum lightning activity in the monsoon season is attributed to the monsoon convection. Novelty: The study made the spatio – temporal variation of lightning over Uttarakhand and also reveals the connection between lightning and different meteorological parameters in different climatic conditions of Uttarakhand which is first defining the importance of large-scale meteorological processes in the development of lightning in Uttarakhand. Keywords: Lightning; Meteorological Parameters; Aerosol optical depth and Convective Available Potential energy (CAPE)

Changes in tropospheric air quality related to the protection of stratospheric ozone in a changing climate

Ultraviolet (UV) radiation drives the net production of tropospheric ozone (O3) and a large fraction of particulate matter (PM) including sulfate, nitrate, and secondary organic aerosols. Ground-level O3 and PM are detrimental to human health, leading to several million premature deaths per year globally, and have adverse effects on plants and the yields of crops. The Montreal Protocol has prevented large increases in UV radiation that would have had major impacts on air quality. Future scenarios in which stratospheric O3 returns to 1980 values or even exceeds them (the so-called super-recovery) will tend to ameliorate urban ground-level O3 slightly but worsen it in rural areas. Furthermore, recovery of stratospheric O3 is expected to increase the amount of O3 transported into the troposphere by meteorological processes that are sensitive to climate change. UV radiation also generates hydroxyl radicals (OH) that control the amounts of many environmentally important chemicals in the atmosphere including some greenhouse gases, e.g., methane (CH4), and some short-lived ozone-depleting substances (ODSs). Recent modeling studies have shown that the increases in UV radiation associated with the depletion of stratospheric ozone over 1980–2020 have contributed a small increase (~ 3%) to the globally averaged concentrations of OH. Replacements for ODSs include chemicals that react with OH radicals, hence preventing the transport of these chemicals to the stratosphere. Some of these chemicals, e.g., hydrofluorocarbons that are currently being phased out, and hydrofluoroolefins now used increasingly, decompose into products whose fate in the environment warrants further investigation. One such product, trifluoroacetic acid (TFA), has no obvious pathway of degradation and might accumulate in some water bodies, but is unlikely to cause adverse effects out to 2100.Graphical abstract

Weather Types and Their Influence on PM10 and O3 Urban Concentrations in the Cergy-Pontoise Conurbation

Abstract Daily atmospheric concentrations of the pollutants PM10 and O3 vary according to weather types. This study aims to identify the weather patterns associated with PM10 and O3 pollution episodes from 2009 to 2020. Episodes characterized by exceedance of World Health Organization standards were identified, and their duration and persistence were studied. The results show that air pollution days are associated with three atmospheric patterns for PM10 and four for O3. The dominant weather pattern corresponds to an anticyclonic situation in central and Eastern Europe with a ridge of high pressure over France at the surface and 500-hPa geopotential height. For PM10, the persistent high-concentration sequences were found to be associated with a thermal inversion constraining the vertical dispersion of pollutants. For O3, the four weather types responsible for ozone pollution all have a higher occurrence in summer. The highest percentage (46% of days) is associated with the presence of a ground-level barometric marsh (an area of the atmosphere between two weather systems where the pressure varies slightly but is slightly low) and a ridge at 500 hPa (weather type T1). Similarly, thermal inversions and thermal winds cause pollution to persist beyond 8 consecutive days. Significance Statement Air quality is not only influenced by ground-level emissions, but also by complex meteorological processes that can contribute to pollutant accumulations. The importance of this research is that the prediction of these processes helps to prevent the development of extreme concentrations near the surface. The results of this study provide a better understanding of how characteristic weather patterns in the Cergy-Pontoise conurbation impact PM10 and O3 pollutant levels. These impacts are expressed by the intensity and frequency of pollution episodes.

Hydro-Meteorological Characteristics of the 1973 Catastrophic Flood in the Mahi Basin, India

The September 1973 flood in the Mahi Basin was one of the most catastrophic and widespread in the 20th century. However, the hydro-meteorological characteristics of the 1973 flood were not studied. Therefore, an attempt has been made to analyze the meteorological and hydrological processes that led to the 1973 flood. Accordingly, daily rainfall data, river discharge, and cross-section data were obtained for the analysis. The 1973 flood was associated with very heavy rainfall resulting from two successive low-pressure systems (LPS) from 26 to 31 August 1973 and 2 to 5 September 1973. The rainfall variability in the Mahi Basin was 24% (annual) and 25% (monsoon) in 1973. The analysis showed that out of 69 rainfall stations, 13 stations received 100% rainfall in the monsoon season in 1973. Under the influence of the second LPS (7 and 9 September 1973), 21 rain gauge stations recorded very heavy rainfall (124.5–244.4 mm) on 8 September. As a result, the maximum discharge of the Mahi River (40,663 m3/s) was observed at Wanakbori on 9 September. The flood hydrograph denoted two flood peaks of 28,125 m3/s and 33,097 m3/s magnitudes resulting from LPS at Kadana. A newly constructed bridge (in 1972) on the Mahi River at the Kailashpuri village washed out due to a large discharge of 21,553 m3/s magnitude on 7 September 1973. The hydro-meteorological analysis of the 1973 flood specified the significance of the LPS in a flash flood disaster in the Mahi Basin. This study will benefit hydrologists and civil engineers creating design floods for the construction of the hydraulic structures in the Mahi Basin, and will help to avoid any future catastrophic floods.

Sensitivity of WRF/Chem simulated PM2.5 to initial/boundary conditions and planetary boundary layer parameterization schemes over the Indo-Gangetic Plain.

The ability of a chemical transport model to simulate accurate meteorological and chemical processes depends upon the physical parametrizations and quality of meteorological input data such as initial/boundary conditions. In this study, weather research and forecasting model coupled with chemistry (WRF-Chem) is used to test the sensitivity of PM2.5 predictions to planetary boundary layer (PBL) parameterization schemes (YSU, MYJ, MYNN, ACM2, and Boulac) and meteorological initial/boundary conditions (FNL, ERA-Interim, GDAS, and NCMRWF) over Indo-Gangetic Plain (Delhi, Punjab, Haryana, Uttar Pradesh, and Rajasthan) during the winter period (December 2017 to January 2018). The aim is to select the model configuration for simulating PM2.5 which shows the lowest errors and best agreement with the observed data. The best results were achieved with initial/boundary conditions from ERA and GDAS datasets and local PBL parameterization (MYJ and MYNN). It was also found that PM2.5 concentrations are relatively less sensitive to changes in initial/boundary conditions but in contrast show a stronger sensitivity to changes in the PBL scheme. Moreover, the sensitivity of the simulated PM2.5 to the choice of PBL scheme is more during the polluted hours of the day (evening to early morning), while that to the choice of the meteorological input data is more uniform and subdued over the day. This work indicates the optimal model setup in terms of choice of initial/boundary conditions datasets and PBL parameterization schemes for future air quality simulations. It also highlights the importance of the choice of PBL scheme over the choice of meteorological data set to the simulated PM2.5 by a chemical transport model.

An Evaluation of the Dynamics of Some Meteorological and Hydrological Processes along the Lower Danube

The objective of the present work was to perform a 30-year analysis of some significant meteorological and hydrological processes along the Lower Danube. This was motivated by the fact that, due to the effects of climate change, the global configuration of the environmental matrix has suffered visible transformations in many places. Another important factor considered is related to the constant development noticed in the last few decades of European inland navigation, in general, and in the Lower Danube sector, in particular. From this perspective, the processes analysed were the wind speed at a 10 m height, the air temperature at a 2 m height, precipitation, and river discharge. The 30-year period of 1991–2020 was considered for analysis. The ERA5 reanalysis data were processed and analysed in the case of the first three processes, while for the river discharge, the data provided by the European Flood Awareness System were used. The emphasis was placed on the evolution of the extreme values and on the identification of the geographical locations with a higher probability of occurrence. The average values and the seasonal variations of the four processes were also considered. The results indicated that the maximum wind speed and air temperature values along the Lower Danube did not suffer significant changes in the last few decades. However, the values of the minimum air temperatures increased with an average value of about 0.8 °C per decade, and the same tendency was noticed also for the average temperatures. Regarding the precipitation, the trend indicated a tendency to decrease by about 0.5 mm per decade, while for the river discharge, a clear increase of more than 1200 m3/s corresponded to each ten-year period. Finally, it can be concluded that the present analysis provided a global and more comprehensive perspective of the recent environmental dynamics along the Lower Danube, delivering useful information for inland navigation, as well as for other human activities.

Column crossing and lateral transport in numerical weather models

AbstractTransport in numerical weather models is typically restricted to advection by the resolved wind field, and representation of other flow processes relies on forcing or coupling to other models. A discussion of non‐advective transport in numerical weather models is presented and illustrated using two examples. These are the sea breeze and surface water flow. Simple models of these phenomena are represented in an adapted version of the Met Office Unified Model (UM) by means of modifying the existing cold‐pool scheme in the UM. This approach of incorporating different transport processes in one framework could facilitate a better representation of the Earth system, by increasing interaction between meteorological, surface and subsurface processes.

Characteristics of Dust Storms Generated by Trapped Waves in the Lee of Mountains

Abstract In situ observations and output from a numerical model are utilized to examine three dust outbreaks that occurred in the northwestern Sonoran Desert. Via analysis of these events, it is shown that trapped waves generated in the lee of an upwind mountain range produced high surface wind speeds along the desert floor and the observed dust storms. Based on analysis of observational and model output, general characteristics of dust outbreaks generated by trapped waves are suggested, including dust-layer depths and concentrations that are dependent upon wave phase and height above the surface, emission and transport associated with the presence of a low-level jet, and wave-generated high wind speeds and thus emission that occurs far downwind of the wave source. Trapped lee waves are ubiquitous in Earth’s atmosphere and thus it is likely that the meteorological aspects of the dust storms examined here are also relevant to understanding dust in other regions. These dust outbreaks occurred near the Salton Sea, an endorheic inland body of water that is rapidly drying due to changes in water-use management. As such, these findings are also relevant in terms of understanding how future changes in size of the Salton Sea will impact dust storms and air quality there. Significance Statement Dust storms are ubiquitous in Earth’s atmosphere, yet the physical processes underlying dust emission and subsequent transport are not always understood, in part due to the wide variety of meteorological processes that can generate high winds and dust. Here we use in situ measurements and numerical modeling to demonstrate that vertically trapped atmospheric waves generated by air flowing over a mountain are one such mechanism that can produce dust storms. We suggest several features of these dust outbreaks that are specific to their production by trapped waves. As the study area is a region undergoing rapid environmental change, these results are relevant in terms of predicting future dust there.

Effects of meteorological forcing uncertainty on high-resolution snow modeling and streamflow prediction in a mountainous karst watershed

In the mountainous Western U.S., a considerable portion of water supply originates as snowmelt passing through karst watersheds. Accurately simulating streamflow in snow-dominated, karst basins is important for water resources management. However, this has been challenging due to high spatiotemporal variability of meteorological and hydrogeological processes in these watersheds and scarcity of climate stations. To overcome these challenges, a physically based snow model is used to simulate snow processes at 100 m resolution, and the calculated snowmelt and potential evapotranspiration rates are fed into a deep learning model to simulate streamflow. The snow model was driven by meteorological variables from a regional scale Weather Research and Forecasting (WRF) model or from the North American Land Data Assimilation System (NLDAS-2). The two datasets were used both at the original resolution and downscaled to 100 m resolution based on orographic adjustments, leading to four sets of forcings. Snow model simulation results from the four sets of forcings showed large differences in simulated snow water equivalent (SWE) and snowmelt rate and timing. However, the differences were damped in simulated streamflow, as the deep learning model is partially immune to input bias and picked up different streamflow responses to snowmelt and rainfall when trained using snow model results. While the meteorological datasets considered yielded close streamflow simulation accuracy, averaging simulated streamflow from the four sets of forcings consistently achieved better performance, suggesting the value of including multiple meteorological datasets for modeling streamflow in mountainous watersheds.

Assimilating GNSS PWV and radiosonde meteorological profiles to improve the PWV and rainfall forecasting performance from the Weather Research and Forecasting (WRF) model over the South China

Precipitable Water Vapor (PWV) and rainfall play important roles in the meteorological processes. In this study, we have investigated the impact of assimilation of Global Navigation Satellite System (GNSS) PWV and radiosonde profiles on the performance of Weather Research and Forecasting (WRF) model in forecasting PWV and rainfall over the South China region for April 01, 2020 to May 31, 2020. PWV observations derived from 213 GNSS stations and meteorological profiles recorded by 23 radiosonde stations are assimilated into WRF model. Five different WRF schemes are adopted: WRF scheme 0: no data assimilation (DA); WRF scheme 1: assimilation of PWV from 76 GNSS stations; WRF scheme 2: assimilation of PWV from 213 GNSS stations; WRF scheme 3: assimilation of meteorological profiles from 23 radiosonde stations; WRF scheme 4: assimilation of both PWV from 213 GNSS stations and meteorological profiles from 23 radiosonde stations. PWV observations derived from 170 independent GNSS (have not been used in assimilation) and rainfall data recorded by 648 surface meteorological stations are used to evaluate WRF forecasting performance in PWV and rainfall, respectively. The results indicate that all DA schemes improve the WRF forecasting performance for both PWV and rainfall. For the first 6 h after data assimilation, WRF schemes 1 to 4 improve the PWV forecasting accuracy by 11.6%, 14.5%, 2.9%, and 14.8%, respectively. For the accumulated rainfall within the first 6 h after data assimilation, WRF scheme 2 and WRF scheme 4 have a similar performance and outperform other DA schemes while the WRF scheme 4 is the best one among all five schemes. WRF scheme 4 improves the rainfall forecast probability of detection and equitable threat score by 0.085 and 0.057, respectively.