Wintertime precipitation over the Australian Snowy Mountains: Observations from an Intensive Field Campaign 2018

Understanding the key dynamical and microphysical mechanisms driving precipitation in the Snowy Mountains region of southeast Australia, including the role of orography, can help improve precipitation forecasts, which is of great value for efficient water management. An intensive observation campaign was carried out during the 2018 austral winter, providing a comprehensive range of ground-based observations across the Snowy Mountains. We used data from three vertically pointing rain radars, cloud radar, a PARSIVEL disdrometer, and a network of 76 pluviometers. The observations reveal that all of the precipitation events were associated with cold front passages. About half accumulated during the frontal passage associated with deep, fully glaciated cloud tops; while the rest occurred in the post-frontal environment and was associated with clouds with supercooled liquid water (SLW) tops. About three quarters of the accumulated precipitation were observed under blocked conditions, likely associated with blocked stratiform orographic enhancement. Specifically, more than a third of the precipitation resulted from moist cloudless air being lifted over stagnant air, upwind from the barrier, creating SLW-top clouds. These SLW-clouds then produced stratiform precipitation mostly over the upwind slopes and mountain tops, with hydrometeors reaching the mountain tops mostly as rimed snow. Two precipitation events were studied in detail, which showed that during unblocked conditions, orographic convection invigoration and unblocked stratiform enhancement were the two main mechanisms driving the precipitation; with the latter being more prevalent after the frontal passage. During these events, ice particle growth was likely dominated by vapor deposition and aggregation during the frontal periods, while riming dominated during the post-frontal periods.

Multi-Scale Simulation of Wind Farm Performance during a Frontal Passage

Predicting the response of wind farms to changing flow conditions is necessary for optimal design and operation. In this work, simulation and analysis of a frontal passage through a utility scale wind farm is achieved for the first time using a seamless multi-scale modeling approach. A generalized actuator disk (GAD) wind turbine model is used to represent turbine–flow interaction, and results are compared to novel radar observations during the frontal passage. The Weather Research and Forecasting (WRF) model is employed with a nested grid setup that allows for coupling between multi-scale atmospheric conditions and turbine response. Starting with mesoscale forcing, the atmosphere is dynamically downscaled to the region of interest, where the interaction between turbulent flows and individual wind turbines is simulated with 10 m grid spacing. Several improvements are made to the GAD model to mimic realistic turbine operation, including a yawing capability and a power output calculation. Ultimately, the model is able to capture both the dynamics of the frontal passage and the turbine response; predictions show good agreement with observed background velocity, turbine wake structure, and power output after accounting for a phase shift in the mesoscale forcing. This study demonstrates the utility of the WRF-GAD model framework for simulating wind farm performance under complex atmospheric conditions.

Potential impacts of cold frontal passage on air quality over the Yangtze River Delta, China

Cold frontal passages usually promote quick removal of atmospheric pollutants over North China (e.g. the Beijing–Tianjin–Hebei region). However, in the Yangtze River Delta (YRD), cold fronts may bring air pollutants from the polluted North China Plain (NCP), thereby deteriorating the air quality in the YRD. In this study, a cold frontal passage and a subsequent stable weather event over YRD during 21–26 January 2015 was investigated with in situ observations and Weather Research and Forecasting – Community Multiscale Air Quality Modeling System simulations. Observations showed a burst of PM2.5 pollution and an obvious southward motion of PM2.5 peaks on the afternoon of 21 January, suggesting a strong inflow of highly polluted air masses to YRD by a cold frontal passage. Model simulations revealed an existing warm and polluted air mass over YRD ahead of the frontal zone, which climbed to the free troposphere along the frontal surface as the cold front passed, increasing the PM2.5 concentration at high altitudes. Strong north-westerly frontal airflow transported particles from the highly polluted NCP to the YRD. As the frontal zone moved downstream of YRD, high pressure took control over the YRD, which resulted in a synoptic subsidence that trapped PM2.5 in the boundary layer. After the cold frontal episode, a uniform pressure field took control over the YRD. Locally emitted PM2.5 started to accumulate under the weak winds and stable atmosphere. Tagging of PM2.5 by geophysical regions showed that the PM2.5 contribution from the YRD itself was 35 % and the contribution from the NCP was 29 % during the cold frontal passage. However, under the subsequent stable weather conditions, the PM2.5 contribution from the YRD increased to 61.5 % and the contribution from the NCP decreased to 14.5 %. The results of this study indicate that cold fronts are potential carriers of atmospheric pollutants when there are strong air pollutant sources in upstream areas, which may deteriorate air quality in downstream regions.

A new interpretative framework for below-cloud effects on stable water isotopes in vapour and rain

Raindrops interact with water vapour in ambient air while sedimenting from the cloud base to the ground. They constantly exchange water molecules with the environment and, in sub-saturated air, they evaporate partially or entirely. The latter of these below-cloud processes is important for predicting the resulting surface rainfall amount. It also influences the boundary layer profiles of temperature and moisture through evaporative latent cooling and humidity changes. However, despite its importance, it is very difficult to quantify this process from observations. Stable water isotopes provide such information, as they are influenced by both rain evaporation and equilibration (i.e. the exchange of isotopes between raindrops and ambient air). This study elucidates this option by introducing a novel interpretative framework for stable water isotope measurements performed simultaneously at high temporal resolution in both near-surface vapour and rain. We refer to this viewing device as the ΔδΔd-diagram, which shows the isotopic composition (δ2H, d-excess) of equilibrium vapour from precipitation samples relative to the ambient vapour. It is shown that this diagram facilitates the diagnosis of below-cloud processes and their effects on the isotopic composition of vapour and rain since equilibration and evaporation lead to different pathways in the two-dimensional phase space of the ΔδΔd-diagram, as investigated with a series of sensitivity experiments with an idealized below-cloud interaction model. The analysis of isotope measurements for a specific cold front in central Europe shows that below-cloud processes lead to distinct and temporally variable imprints on the isotope signal in surface rain. The influence of evaporation on this signal is particularly strong during periods with a weak precipitation rate. After the frontal passage, the near-surface atmospheric layer is characterized by higher relative humidity, which leads to weaker below-cloud evaporation. Additionally, a lower melting layer after the frontal passage reduces time for exchange between vapour and rain and leads to weaker equilibration. Measurements from four cold frontal events reveal a surprisingly similar slope of ΔdΔδ=-0.30 in the phase space, indicating a potentially characteristic signature of below-cloud processes for this type of rain event.

Cold fronts – a potential air quality threat over the Yangtze River Delta, China

Cold frontal passages usually promote quick removal of atmospheric pollutants over North China (e.g. the Beijing–Tianjin–Hebei region). However, in the Yangtze River Delta (YRD), cold fronts pose a potential threat to air quality. In this study, a cold frontal passage and a subsequent stable weather event over YRD during 21–26 January 2015 was investigated with in-situ observations and Weather Research and Forecasting–Community Multiscale Air Quality Modeling System simulations. Observations showed a burst of PM2.5 pollution and an obvious southward motion of PM2.5 peaks on the afternoon of 21 January, suggesting a strong inflow of highly polluted airmasses to YRD by a cold frontal passage. Model simulations revealed an existing warm and polluted airmass over YRD, which climbed to the free troposphere along the frontal surface as the cold front passed, increasing the PM2.5 concentration at high altitudes. Strong north-westerly flow behind the cold front transported particles from the highly polluted North China Plain (NCP) to YRD. As the cold front intruded into the downstream of YRD, high pressure took control over the YRD, which resulted in a synoptic subsidence that brought particles from the free troposphere (1.0–2.0 km) to the surface. After the cold front's passage, weakened winds and a stable atmosphere stayed over the YRD and led to the accumulation of locally emitted PM2.5. Tagging of PM2.5 by geophysical regions showed that the PM2.5 contribution from the YRD itself was 35 % and the contribution from the NCP was 29 % during the cold frontal passage. However, under the subsequent stable weather conditions, the PM2.5 contribution from the YRD increased to 61.5 % and the contribution from the NCP decreased to 14.5 %. The results of this study indicate that cold fronts are potential bringers of atmospheric pollutants when there are strong air pollutant sources in upstream areas, which may deteriorate air quality in downstream regions.

Mechanism of Urbanization Impact on a Summer Cold-Frontal Rainfall Process in the Greater Beijing Metropolitan Area

The WRF–Noah–urban canopy model (UCM) coupled modeling system is used to investigate the influence of urbanization on a typical frontal rainfall event that occurred in June 2008 over the greater Beijing metropolitan area (GBMA). The comparison between results of two experiments with and without the presence of urban areas suggests that more precipitation can be induced over and in the area downwind of Beijing because of the urbanization effects while less rainfall is found in the upwind region of central urban areas. The urbanization effects delay the onset of precipitation over Beijing but keep it sustained for a longer period with stronger rainfall intensity. The underlying urban surface not only retards the cold-frontal movement but also favors the development of a wet and unstable atmosphere. This explains why the precipitation can be sustained for a longer time with higher rainfall intensity over urban areas. From analyses of a density-current speed equation, it is found that the abrupt pressure jump during the frontal passage has a significant influence on the cold-frontal movement. A method derived from the surface pressure tendency equation is used to explore the mechanism of urban effects on the cold-frontal system. The cold advection is less intense in the experiment with urban land surface than in the experiment with urban areas replaced by cropland. Hence, the weaker-than-normal cold advection and subsequent smaller pressure jump during the frontal passage over the GBMA are the major mechanisms behind the urbanization effects, which lead to the retardation of the cold-frontal movement and late onset of precipitation over the GBMA.

MM5 v3.6.1 and WRF v3.5.1 model comparison of standard and surface energy variables in the development of the planetary boundary layer

Air quality forecasting requires atmospheric weather models to generate accurate meteorological conditions, one of which is the development of the planetary boundary layer (PBL). An important contributor to the development of the PBL is the land–air exchange captured in the energy budget as well as turbulence parameters. Standard and surface energy variables were modeled using the fifth-generation Penn State/National Center for Atmospheric Research mesoscale model (MM5), version 3.6.1, and the Weather Research and Forecasting (WRF) model, version 3.5.1, and compared to measurements for a southeastern Texas coastal region. The study period was 28 August–1 September 2006. It also included a frontal passage. The results of the study are ambiguous. Although WRF does not perform as well as MM5 in predicting PBL heights, it better simulates energy budget and most of the general variables. Both models overestimate incoming solar radiation, which implies a surplus of energy that could be redistributed in either the partitioning of the surface energy variables or in some other aspect of the meteorological modeling not examined here. The MM5 model consistently had much drier conditions than the WRF model, which could lead to more energy available to other parts of the meteorological system. On the clearest day of the study period, MM5 had increased latent heat flux, which could lead to higher evaporation rates and lower moisture in the model. However, this latent heat disparity between the two models is not visible during any other part of the study. The observed frontal passage affected the performance of most of the variables, including the radiation, flux, and turbulence variables, at times creating dramatic differences in the r2 values.

MM5 v3.6.1 and WRF v3.2.1 model comparison of standard and surface energy variables in the development of the planetary boundary layer

Air quality forecasting requires atmospheric weather models to generate accurate meteorological conditions, one of which is the development of the planetary boundary layer (PBL). An important contributor to the development of the PBL is the land-air exchange captured in the energy budget as well as turbulence parameters. Standard and surface energy variables were modeled using the fifth-generation Penn State/National Center for Atmospheric Research mesoscale model (MM5), version 3.6.1, and the Weather Research and Forecasting (WRF) model, version 3.2.1, and compared to measurements for a southeastern Texas coastal region. The study period was 28 August–1 September 2006. It also included a frontal passage. The results of the study are ambiguous. Although WRF does not perform as well as MM5 in predicting PBL heights, it better simulates most of the general and energy budget variables. Both models overestimate incoming solar radiation, which implies a surplus of energy that could be redistributed in either the partitioning of the surface energy variables or in some other aspect of the meteorological modeling not examined here. The MM5 model consistently had much drier conditions than the WRF model, which could lead to more energy available to other parts of the meteorological system. On the clearest day of the study period MM5 had increased latent heat flux, which could lead to higher evaporation rates and lower moisture in the model. However, this latent heat disparity between the two models is not visible during any other part of the study. The observed frontal passage affected the performance of most of the variables, including the radiation, flux, and turbulence variables, at times creating dramatic differences in the r2 values.

Impact of Cloud-Nucleating Aerosols in Cloud-Resolving Model Simulations of Warm-Rain Precipitation in the East China Sea

Cloud-nucleating aerosols emitted from mainland China have the potential to influence cloud and precipitation systems that propagate through the region of the East China Sea. Both simulations from the Spectral Radiation-Transport Model for Aerosol Species (SPRINTARS) and observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) reveal plumes of pollution that are transported into the East China Sea via frontal passage or other offshore flow. Under such conditions, satellite-derived precipitation estimates from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR) frequently produce discrepancies in rainfall estimates that are hypothesized to be a result of aerosol modification of cloud and raindrop size distributions. Cloud-resolving model simulations were used to explore the impact of aerosol loading on three identified frontal-passage events in which the TMI and PR precipitation estimates displayed large discrepancies. Each of these events was characterized by convective and stratiform elements in association with a frontal passage. Area-averaged time series for each event reveal similar monotonic cloud and rain microphysical responses to aerosol loading. The ratio in the vertical distribution of cloud water to rainwater increased. Cloud droplet concentration increased and the mean diameters decreased, thereby reducing droplet autoconversion and collision–coalescence growth. As a result, raindrop concentration decreased, while the drop mean diameter increased; furthermore, average rainwater path magnitude and area fraction both decreased. The average precipitation rate fields reveal a complex modification of the timing and spatial coverage of rainfall. This suggests that the warm-rain microphysical response to aerosols, in addition to the precipitation life cycle, microphysical feedbacks, and evaporative effects, play an important role in determining surface rainfall.