Intensive Observation Period Research Articles

Importance of CCN activation for fog forecasting and its representation in the two‐moment microphysical scheme LIMA

AbstractThe work presented in this article studies the impact of cloud condensation nuclei (CCN) activation for fog forecasting and improves its parameterization in the LIMA (Liquid, Ice, Multiple Aerosols) two‐moment microphysical scheme, building upon the Local And Non‐local Fog EXperiment (LANFEX) field campaign observations, specifically the intensive observation period (IOP) 1 and the DEMISTIFY intercomparison. Large‐eddy simulations were performed with the Meso‐NH model, first using a prognostic supersaturation allowing us to compute the number of activated CCN at each time step, and then with the usual saturation adjustment hypothesis and a diagnostic maximum supersaturation. The prognostic supersaturation method provided very good results, similar to those from earlier simulations of this case using a bin scheme, and was thus used as a reference. In contrast, the diagnostic maximum supersaturation method strongly overestimated droplet numbers and produced a too‐thick fog. Thus, improvements to the maximum supersaturation diagnostic were proposed, by (1) revising the temperature tendency and (2) accounting for pre‐existing cloud droplets in the activation parameterization. These improvements resulted in a simulation in good agreement with observations and the reference simulation, and are promising for use in numerical weather prediction systems with a lower resolution and/or a longer time step.

Assessing the Convective Environment over Irrigated and Nonirrigated Land Use with Land–Atmosphere Coupling Metrics: Results from GRAINEX

Abstract Land-use land-cover change affects weather and climate. This paper quantifies land–atmosphere interactions over irrigated and nonirrigated land uses during the Great Plains Irrigation Experiment (GRAINEX). Three coupling metrics were used to quantify land–atmosphere interactions as they relate to convection. They include the convective triggering potential (CTP), the low-level humidity index (HIlow), and the lifting condensation level (LCL) deficit. These metrics were calculated from the rawinsonde data obtained from the Integrated Sounding Systems (ISSs) for Rogers Farm and York Airport along with soundings launched from the three Doppler on Wheels (DOW) sites. Each metric was categorized by intensive observation period (IOP), cloud cover, and time of day. Results show that with higher CTP, lower HIlow, and lower LCL deficit, conditions were more favorable for convective development over irrigated land use. When metrics were grouped and analyzed by IOP, compared to nonirrigated land use, HIlow was found to be lower for irrigated land use, suggesting favorable conditions for convective development. Furthermore, when metrics were grouped and analyzed by clear and nonclear days, CTP values were higher over irrigated cropland than nonirrigated land use. In addition, compared to nonirrigated land use, the LCL deficit during the peak growing season was lower over irrigated land use, suggesting a favorable condition for convection. It is found that with the transition from the early summer to the mid/peak summer and increased irrigation, the environment became more favorable for convective development over irrigated land use. Finally, it was found that regardless of background atmospheric conditions, irrigated land use provided a favorable environment for convective development.

Exploring the daytime boundary layer evolution based on Doppler spectrum width from multiple coplanar wind lidars during CROSSINN

Abstract. Over heterogeneous, mountainous terrain, the determination of spatial heterogeneity of any type of a turbulent layer has been known to pose substantial challenges in mountain meteorology. In addition to the combined effect in which buoyancy and shear contribute to the turbulence intensity of such layers, it is well known that mountains add an additional degree of complexity via non-local transport mechanisms, compared to flatter topography. It is therefore the aim of this study to determine the vertical depths of both daytime convectively and shear-driven boundary layers within a fairly wide and deep Alpine valley during summertime. Specifically, three Doppler lidars deployed during the CROSSINN (Cross-valley flow in the Inn Valley investigated by dual-Doppler lidar measurements) campaign within a single week in August 2019 are used to this end, as they were deployed along a transect nearly perpendicular to the along-valley axis. To achieve this, a bottom-up exceedance threshold method based on turbulent Doppler spectrum width sampled by the three lidars has been developed and validated against a more traditional bulk Richardson number approach applied to radiosonde profiles obtained above the valley floor. The method was found to adequately capture the depths of convective turbulent boundary layers at a 1 min temporal and 50 m spatial resolution across the valley, with the degree of ambiguity increasing once surface convection decayed and upvalley flows gained in intensity over the course of the afternoon and evening hours. Analysis of four intensive observation period (IOP) events elucidated three regimes of the daytime mountain boundary layer in this section of the Inn Valley. Each of the three regimes has been analysed as a function of surface sensible heat flux H, upper-level valley stability Γ, and upper-level subsidence wL estimated with the coplanar retrieval method. Finally, the positioning of the three Doppler lidars in a cross-valley configuration enabled one of the most highly spatially and temporally resolved observational convective boundary layer depth data sets during daytime and over complex terrain to date.

Elevated Mixed Layers during Great Lake Lake-Effect Events: An Investigation and Case Study from OWLeS

Abstract Data from rawinsondes launched during intensive observation periods (IOPs) of the Ontario Winter Lake-Effect Systems (OWLeS) field project reveal that elevated mixed layers (EMLs) in the lower troposphere were relatively common near Lake Ontario during OWLeS lake-effect events. Conservatively, EMLs exist in 193 of the 290 OWLeS IOP soundings. The distribution of EML base pressure derived from the OWLeS IOP soundings reveals two classes of EML, one that has a relatively low-elevation base (900–750 hPa) and one that has a relatively high-elevation base (750–500 hPa). It is hypothesized that the former class of EML, which is the focus of this research, is, at times, the result of mesoscale processes related to individual Great Lakes. WRF reanalysis fields from a case study during the OWLeS field project provide evidence of two means by which low-elevation base EMLs can originate from the lake-effect boundary layer convection and associated mesoscale circulations. First, such EMLs can form within the upper-level outflow branches of mesoscale solenoidal circulations. Evacuated Great Lakes–modified convective boundary layer air aloft then lies above ambient air of a greater static stability, forming EMLs. Second, such EMLs can form in the absence of a mesoscale solenoidal circulation when Great Lake–modified convective boundary layers overrun ambient air of a greater density. The reanalysis fields show that EMLs and layers of reduced static stability tied to Great Lakes–modified convective boundary layers can extend downwind for hundreds of kilometers from their areas of formation. Operational implications and avenues for future research are discussed.

Atmospheric and surface observations during the Saint John River Experiment on Cold Season Storms (SAJESS)

Abstract. The amount and the phase of cold-season precipitation accumulating in the upper Saint John River (SJR) basin are critical factors in determining spring runoff, ice jams, and flooding. To study the impact of winter and spring storms on the snowpack in the upper SJR basin, the Saint John River Experiment on Cold Season Storms (SAJESS) was conducted during winter–spring 2020–2021. Here, we provide an overview of the SAJESS study area, field campaign, and data collected. The upper SJR basin represents 41 % of the entire SJR watershed and encompasses parts of the US state of Maine and the Canadian provinces of Quebec and New Brunswick. In early December 2020, meteorological instruments were co-located with an Environment and Climate Change Canada station near Edmundston, New Brunswick. This included a separate weather station for measuring standard meteorological variables, an optical disdrometer, and a micro rain radar. This instrumentation was augmented during an intensive observation period that also included upper-air soundings, surface weather observations, a multi-angle snowflake camera, and macrophotography of solid hydrometeors throughout March and April 2021. During the study, the region experienced a lower-than-average snowpack that peaked at ∼ 65 cm, with a total of 287 mm of precipitation (liquid-equivalent) falling between December 2020 and April 2021, a 21 % lower amount of precipitation than the climatological normal. Observers were present for 13 storms during which they conducted 183 h of precipitation observations and took more than 4000 images of hydrometeors. The inclusion of local volunteers and schools provided an additional 1700 measurements of precipitation amounts across the area. The resulting datasets are publicly available from the Federated Research Data Repository at https://doi.org/10.20383/103.0591 (Thompson et al., 2023). We also include a synopsis of the data management plan and a brief assessment of the rewards and challenges of conducting the field campaign and utilizing community volunteers for citizen science.

Impacts of Dropsonde Observations on Forecasts of Atmospheric Rivers and Associated Precipitation in the NCEP GFS and ECMWF IFS Models

Abstract Atmospheric River Reconnaissance has held field campaigns during cool seasons since 2016. These campaigns have provided thousands of dropsonde data profiles, which are assimilated into multiple global operational numerical weather prediction models. Data denial experiments, conducted by running a parallel set of forecasts that exclude the dropsonde information, allow testing of the impact of the dropsonde data on model analyses and the subsequent forecasts. Here, we investigate the differences in skill between the control forecasts (with dropsonde data assimilated) and denial forecasts (without dropsonde data assimilated) in terms of both precipitation and integrated vapor transport (IVT) at multiple thresholds. The differences are considered in the times and locations where there is a reasonable expectation of influence of an intensive observation period (IOP). Results for 2019 and 2020 from both the European Centre for Medium-Range Weather Forecasts (ECMWF) model and the National Centers for Environmental Prediction (NCEP) global model show improvements with the added information from the dropsondes. In particular, significant improvements in the control forecast IVT generally occur in both models, especially at higher values. Significant improvements in the control forecast precipitation also generally occur in both models, but the improvements vary depending on the lead time and metrics used. Significance Statement Atmospheric River Reconnaissance is a program that uses targeted aircraft flights over the northeast Pacific to take measurements of meteorological fields. These data are then ingested into global weather models with the intent of improving the initial conditions and resulting forecasts along the U.S. West Coast. The impacts of these observations on two global numerical weather models were investigated to determine their influence on the forecasts. The integrated vapor transport, a measure of both wind and humidity, saw significant improvements in both models with the additional observations. Precipitation forecasts were also improved, but with differing results between the two models.

Cold Fog Amongst Complex Terrain

Abstract Cold fog forms via various thermodynamic, dynamic, and microphysical processes when the air temperature is less than 0°C. It occurs frequently during the cold season in the western United States yet is challenging to detect using standard observations and is very difficult to predict. The Cold Fog Amongst Complex Terrain (CFACT) project was conceived to investigate the life cycle of cold fog in mountain valleys. The overarching goals of the CFACT project are to 1) investigate the life cycle of cold-fog events over complex terrain with the latest observation technology, 2) improve microphysical parameterizations and visibility algorithms used in numerical weather prediction (NWP) models, and 3) develop data assimilation and analysis methods for current and next-generation (e.g., subkilometer scale) NWP models. The CFACT field campaign took place in Heber Valley, Utah, during January and February 2022, with support from NSF’s Lower Atmospheric Observing Facilities (managed by NCAR’s Earth Observing Laboratory), the University of Utah, and Ontario Technical University. A network of ground-based and aerial in situ instruments and remote sensing platforms were used to obtain comprehensive measurements of thermodynamic profiles, cloud microphysics, aerosol properties, and environmental dynamics. Nine intensive observation periods (IOPs) explored various mountainous weather and cold-fog conditions. Field observations, NWP forecasts, and large-eddy simulations provided unprecedented data sources to help understand the mechanisms associated with cold-fog weather and to identify and mitigate numerical model deficiencies in simulating winter weather over mountainous terrain. This article summarizes the CFACT field campaign, its observations, and challenges during the field campaign, including real-time fog prediction issues and future analysis.

P-Type Processes and Predictability: The Winter Precipitation Type Research Multiscale Experiment (WINTRE-MIX)

Abstract During near-0°C surface conditions, diverse precipitation types (p-types) are possible, including rain, drizzle, freezing rain, freezing drizzle, ice pellets, wet snow, snow, and snow pellets. Near-0°C precipitation affects wide swaths of the United States and Canada, impacting aviation, road transportation, power generation and distribution, winter recreation, ecology, and hydrology. Fundamental challenges remain in observing, diagnosing, simulating, and forecasting near-0°C p-types, particularly during transitions and within complex terrain. Motivated by these challenges, the field phase of the Winter Precipitation Type Research Multiscale Experiment (WINTRE-MIX) was conducted from 1 February to 15 March 2022 to better understand how multiscale processes influence the variability and predictability of p-type and amount under near-0°C surface conditions. WINTRE-MIX took place near the U.S.–Canadian border, in northern New York and southern Quebec, a region with plentiful near-0°C precipitation influenced by terrain. During WINTRE-MIX, existing advanced mesonets in New York and Quebec were complemented by deployment of 1) surface instruments, 2) the National Research Council Convair-580 research aircraft with W- and X-band Doppler radars and in situ cloud and aerosol instrumentation, 3) two X-band dual-polarization Doppler radars and a C-band dual-polarization Doppler radar from the University of Illinois, and 4) teams collecting manual hydrometeor observations and radiosonde measurements. Eleven intensive observing periods (IOPs) were coordinated. Analysis of these WINTRE-MIX IOPs is illuminating how synoptic dynamics, mesoscale dynamics, and microscale processes combine to determine p-type and its predictability under near-0°C conditions. WINTRE-MIX research will contribute to improving nowcasts and forecasts of near-0°C precipitation through evaluation and refinement of observational diagnostics and numerical forecast models.

Wind Profiler for Understanding of Meiyu at Dongshan

Abstract: To understand the Meiyu Boundary layer evolutionand vertical structure of precipitating cloud systems over Dongshan, special observational campaigns have been conducted downstream of the Yangtze River during June and July in the years 2001 and 2002. We deployed a Lower Atmospheric Wind Profiler (LAWP) with Radio Acoustic Sounding System (RASS) at the Meteorological Observatory, Dongshan within a mesoscale network that consists of three X-band Doppler radars, three AWS, and Micro rain radar to observe the inner structure of precipitating cloud systems seen frequently in the observational area. The LAWP provides vertical profiles of three-dimensional wind, vertical structure of the precipitating cloud system, convective boundary layer (CBL), and temperature from the (RASS) lower atmosphere with a height resolution of 60 m to 200 m and a time resolution of about 1 to 60 minutes. LAWP had been operated in two modes: low mode and high mode up to 4 km and 11 km height during non-rainy and rain conditions, respectively. A study was carried out during an intensive observational period (IOP-2001 and IOP-2002) to understand the pre-convective environments in the boundary layer during pre-Meiyu and Meiyu convective days to find out whether there is any precursor before the convection triggering. Further in Meiyu precipitating cloud systems, the reflectivity vertical structure can be used to identify the range of precipitation processes from the young, dynamically vigorous cells to the mature, bright band resolved stratiform rain.

The Impact of Dropsonde Data on the Performance of the NCEP Global Forecast System during the 2020 Atmospheric Rivers Observing Campaign. Part II: Dynamic Variables and Humidity

Abstract The impact of assimilating dropsonde data from the 2020 Atmospheric River (AR) Reconnaissance (ARR) field campaign on operational numerical weather forecasts was assessed. Two experiments were executed for the period from 24 January to 18 March 2020 using the National Centers for Environmental Prediction (NCEP) Global Forecast System version 15 (GFSv15) with a four-dimensional hybrid ensemble–variational (4DEnVar) data assimilation system. The control run (CTRL) used all of the routinely assimilated data and included data from 628 ARR dropsondes, whereas the denial run (DENY) excluded the dropsonde data. Results from 17 intensive observing periods (IOPs) indicate a mixed impact for mean sea level pressure and geopotential height over the Pacific–North American (PNA) region in CTRL compared to DENY. The overall local impact over the U.S. West Coast and Gulf of Alaska for the 17 IOPs is neutral (−0.45%) for integrated vapor transport (IVT), but positive for wind and moisture profiles (0.5%–1.0%), with a spectrum of statistically significant positive and negative impacts for various IOPs. The positive dropsonde data impact on precipitation forecasts over U.S. West Coast domains appears driven, in part, by improved low-level moisture and wind fields at short-forecast lead times. Indeed, data gaps, especially for accurate and unbiased moisture profiles and wind fields, can be at least partially mitigated to improve U.S. West Coast precipitation forecasts.

Variation of Atmospheric Boundary Layer Height Over the Northern, Central, and Southern Parts of the Tibetan Plateau During Three Monsoon Seasons

AbstractThe atmospheric boundary layer (ABL) over the Tibetan Plateau (TP) is important to the study of the interactions between the underlying surface and the atmosphere. Radiosondes were released during three intensive ABL experimental periods (monsoon‐onset, monsoon, and post‐monsoon) in 2014 and 2019. Using these observational data, this study explored the features of the ABL height (ABLH) in the northern, central, and southern parts of the TP during the three periods and their possible association with the westerlies. Measurements showed that the ABLH over the northern part of the TP in the monsoon season was the highest (average 3 km above ground level [AGL]) among the three intensive observation periods. Meanwhile, the southern part of the TP had the highest ABLH (almost 3.5 km AGL) in post‐monsoon. Using ERA5, we discovered that the ABLH over the TP was not only affected by the surface sensible heat flux but also was influenced by the seasonal north‐south movement of the westerlies. The westerlies correspond to an upper‐level high potential vorticity (PV) center that is associated with the weak atmospheric stability below the westerlies and is conducive to the development of the ABL. When the westerlies are located above the southern TP in winter, they provide conditions that favor ABL increase. Westerlies are above the north TP in summer, and this provides favorable conditions for ABL increase in the northern TP. The role of westerlies in the ABLH explains why the northern and southern parts of the TP have different seasonal variation patterns.

Do Citizen Science Intense Observation Periods Increase Data Usability? A Deep Dive of the NASA GLOBE Clouds Data Set With Satellite Comparisons

AbstractThe Global Learning and Observations to Benefit the Environment (GLOBE) citizen science program has recently conducted a series of month‐long intensive observation periods (IOPs), asking the public to submit daily reports on cloud and sky conditions from all regions of Earth. This provides a wealth of crowdsourced observations from the ground, which complements other conventional scientific cloud data. In addition, the GLOBE reports are matched in space and time with geostationary and low Earth orbit satellites, which allows for a straightforward comparison of cloud properties, and minimizes the biases associated with mismatched sampling between participants and satellites. The matched GLOBE data set is used to calculate the mean observed cloud cover by atmospheric level both worldwide and by region. The overall magnitudes of cloud cover between the GLOBE participants and the matched satellites agree within 10%, which is notable given the distinctly different natures of the data sources. The mean vertical cloud profiles show GLOBE reporting more low‐level clouds and fewer high‐level clouds than satellites. The low cloud disagreement is likely related to satellites missing low clouds when high clouds block their view. Conversely, the high cloud disagreement is related primarily to cloud opacity, as satellites may miss some optically thin clouds. Monte Carlo testing shows the results to be robust, and the tripled amount of IOP data reduces uncertainty by half. These findings also highlight ways in which citizen science IOP data may be used to support scientific research while accounting for their unique properties.

Simulations of Mesoscale Flow Systems around Dugway Proving Ground Using the WRF Modeling System

It is widely recognized that regions with complex heterogeneous topography and land-use properties produce a variety of diurnal mesoscale and microscale flows, which can be modified or even masked by significant large-scale synoptic forcing. These flows can be produced through both dynamic and thermal-forcing processes. Recent field programs such as the Terrain-induced Rotor Experiment (T-REX), Mountain Terrain Atmospheric Modeling and Observations Program (MATERHORN), and Perdigao have been used to observe and model flow behaviors under different topographical and large-scale meteorological conditions. Using the Advanced research version of the Weather Research and Forecast (WRF-ARW) model, we applied multi-nesting using an interactive one-way nesting approach to resolve to a sub-kilometer inner-grid spacing (0.452 km). Our interest was in the intensive observation period 6 (IOP6) of the Fall 2012 MATERHORN campaign conducted over Dugway Proving Ground (DPG) in Utah. An initial review of the IOP6 suggested that a range of diurnal flows were present, and that a relatively small subset of model setup configurations would be able to capture the general flows of this period. The review also led us to believe that this same subset would be able to capture differences due to variations in choice of model boundary-layer physics, land surface physics, land use/soil type specifications, and larger-scale meteorological conditions. A high model vertical resolution was used, with 90 vertical sigma levels applied. The IOP6 spanned the period of 2012 0800 UTC 14 October–0800 UTC 15 October. Based upon a lack of deep convection and moist microphysics throughout IOP6, we included comparison of planetary boundary layer (PBL) turbulence parameterization schemes even at the sub-kilometer grid spacing. We focused upon the gross model performance over our inner nest; therefore, a detailed comparison of the effects of model horizontal resolution are excluded. For surface parameters of wind and temperature, we compare mean absolute error and bias scores throughout the period at a number of surface meteorological observing sites. We found that despite attention given to the boundary layer turbulence physics, radiation physics and model vertical resolution, the results seemed to indicate more impact from the choices of thermal soil conductivity parameterization, land surface/soil texture category classification (and associated static property-parameter values), and large-scale forcing model. This finding lends support to what other researchers have found related to how these same forcings can exert a strong influence upon mesoscale flows around DPG. Our findings suggest that the two nights of IOP6 offer a pair of excellent consecutive nights to explore many of the forcing features important to local complex terrain flow. The flows of interest in this case included valley, anabatic/katabatic, and playa breeze systems. Subjective evidence was also found to support an influence provided by the modest synoptic northwesterly flow present within the lower troposphere (mainly on the night of 14 October). Follow-on research using the WRF-ARW capability to nest directly from mesoscale-to-LES can leverage IOP6 further. For example, to uncover more detailed and focused aspects of the dynamic and thermodynamic forcings contributing to the DPG diurnal flows.

The Impact of Dropsonde Data on the Performance of the NCEP Global Forecast System during the 2020 Atmospheric Rivers Observing Campaign. Part I: Precipitation

Abstract The impact of assimilating dropsonde data from the 2020 Atmospheric River (AR) Reconnaissance (ARR) field campaign on operational numerical precipitation forecasts was assessed. Two experiments were executed for the period from 24 January to 18 March 2020 using the NCEP Global Forecast System, version 15 (GFSv15), with a four-dimensional hybrid ensemble–variational (4DEnVar) data assimilation system. The control run (CTRL) used all the routinely assimilated data and included ARR dropsonde data, whereas the denial run (DENY) excluded the dropsonde data. There were 17 intensive observing periods (IOPs) totaling 46 Air Force C-130 and 16 NOAA G-IV missions to deploy dropsondes over targeted regions with potential for downstream high-impact weather associated with the ARs. Data from a total of 628 dropsondes were assimilated in the CTRL. The dropsonde data impact on precipitation forecasts over U.S. West Coast domains is largely positive, especially for day-5 lead time, and appears driven by different model variables on a case-by-case basis. These results suggest that data gaps associated with ARs can be addressed with targeted ARR field campaigns providing vital observations needed for improving U.S. West Coast precipitation forecasts.

The variability of volatile organic compounds during a persistent fog-haze episode

A persistent fog-haze process associated with high pollution occurred in the northern suburbs of Nanjing from November to December 2013. Based on the comprehensive chemical and microphysical observations during the intense observation period, the composition characteristics, and variation rules of volatile organic compounds (VOCs) in the atmosphere under four weather conditions (slight haze, haze, fog, and dense fog) were compared and analyzed, the influencing factors for VOCs during extremely dense fog were discussed in more detail. The average concentrations of VOCs displayed as alkanes > aromatics > alkenes > alkynes, and their concentrations were ranked as dense fog > fog > haze > slight haze, the main factor contributing to the difference in concentrations of VOCs under different weather conditions is the boundary layer characteristics and photochemical reaction rate. Microphysical parameters such as liquid water content (LWC) were negatively correlated with VOCs concentration in dense fog (LWC>0.008 g m−3). Also, the concentration of VOCs showed an oscillating decrease in extremely dense fog (LWC>0.12 g m−3), and the total VOCs removal rate was close to 30%, which may be attributed to an indirect/direct removal effect, in which the enhanced collision and deposition of fog droplets promote the redistribution of VOCs gas-aqueous/particle partitioning, and remove them from the atmosphere by fog water.

Swabian MOSES 2021: An interdisciplinary field campaign for investigating convective storms and their event chains

The Neckar Valley and the Swabian Jura in southwest Germany comprise a hotspot for severe convective storms, causing tens of millions of euros in damage each year. Possible reasons for the high frequency of thunderstorms and the associated event chain across compartments were investigated in detail during the hydro-meteorological field campaign Swabian MOSES carried out between May and September 2021. Researchers from various disciplines established more than 25 temporary ground-based stations equipped with state-of-the-art in situ and remote sensing observation systems, such as lidars, dual-polarization X- and C-band Doppler weather radars, radiosondes including stratospheric balloons, an aerosol cloud chamber, masts to measure vertical fluxes, autosamplers for water probes in rivers, and networks of disdrometers, soil moisture, and hail sensors. These fixed-site observations were supplemented by mobile observation systems, such as a research aircraft with scanning Doppler lidar, a cosmic ray neutron sensing rover, and a storm chasing team launching swarmsondes in the vicinity of hailstorms. Seven Intensive Observation Periods (IOPs) were conducted on a total of 21 operating days. An exceptionally high number of convective events, including both unorganized and organized thunderstorms such as multicells or supercells, occurred during the study period. This paper gives an overview of the Swabian MOSES (Modular Observation Solutions for Earth Systems) field campaign, briefly describes the observation strategy, and presents observational highlights for two IOPs.

Snowband Characteristics Associated With Lake‐Effect Misovortices During the OWLeS Project

AbstractVortices of diameters 100 m to 10 km have been observed during lake‐effect snowstorms. Lines of misovortices (diameters = 40–4,000 m) have recently been documented forming over Lake Ontario during long lake‐axis‐parallel (LLAP)‐type lake‐effect storms. Using National Weather Service Weather Surveillance Radar—1988 Doppler (WSR‐88D) and Doppler on Wheels radar data from the Ontario Winter Lake‐effect Systems (OWLeS) project, lines of misovortices (also referred to as “misovortex lines” in this study) were investigated for intensive observation period (IOP)7 (7 January 2014) and IOP9 (9 January 2014). Results revealed that the misovortex lines formed on the southern or northern side of the west‐to‐east‐oriented LLAP band, whichever was closest to a low‐level boundary nearest the corresponding south or north shoreline (northern part in IOP7, southern part in IOP9). Examination of these two IOPs in the context of a total of 23 OWLeS IOPs, 11 of which had predominantly LLAP band morphology, showed that, in 4 of the 11 LLAP IOPs, horizontal shear zones/reflectivity bands formed in preferred regions over Lake Ontario and nearby land areas where low‐level boundaries (e.g., land breeze fronts) have been noted to develop near shoreline irregularities. Horizontal shear zones were predominant in approximately half of the OWLeS LLAP IOPs and were associated with storms having a well‐organized, solid banded reflectivity structure. Misovortices occurred when horizontal shear zones were prevalent, supporting the idea that horizontal shearing instability was important to their formation.

Going Mobile to Address Emerging Climate Equity Needs in the Heterogeneous Urban Environment

Abstract The Brookhaven National Laboratory Center for Multiscale Applied Sensing (CMAS) aims to address environmental equity needs in the context of a changing climate. As a first step toward this goal, the center developed a one-of-a-kind observatory tailored to the study of highly heterogeneous urban environments. This article describes the features of the mobile observatory that enable its rapid deployment either on or off the power grid, as well as its instrument payload. Beyond its unique design, the observatory optimizes data collection within the obstacle-laden urban environment using a new smart sampling paradigm. This setup facilitated the collection of previously poorly documented environmental properties, including wind profiles throughout the atmospheric column. The mobile observatory captured unique observations during its first few intensive observation periods. Vertical air motion and infrared temperature measurements collected along the faces of the supertall One Vanderbilt skyscraper in Manhattan, NY, reveal how solar and anthropogenic heating affect wind flow and thus the venting of heat, pollution, and contaminants in urban street canyons. Also, air temperature measurements collected during travel along a 150-km transect between Upton and Manhattan, NY, offer a high-resolution view of the urban heat island and reveal that temperature disparities also exist within the city across different neighborhoods. Ultimately, the datasets collected by CMAS are poised to help guide equitable urban planning by highlighting existing disparities and characterizing the impact of urban features on the urban microclimate with the goal of improving human comfort.

Evaluation of a forest parameterization to improve boundary layer flow simulations over complex terrain. A case study using WRF-LES V4.0.1

Abstract. We evaluate the influence of a forest parametrization on the simulation of the boundary layer flow over moderate complex terrain in the context of the Perdigão 2017 field campaign. The numerical simulations are performed using the Weather Research and Forecasting model in large eddy simulation mode (WRF-LES). The short-term, high-resolution (40 m horizontal grid spacing) and long-term (200 m horizontal grid spacing) WRF-LES are evaluated for an integration time of 12 h and 1.5 months, respectively, with and without forest parameterization. The short-term simulations focus on low-level jet events over the valley, while the long-term simulations cover the whole intensive observation period (IOP) of the field campaign. The results are validated using lidar and meteorological tower observations. The mean diurnal cycle during the IOP shows a significant improvement of the along-valley wind speed and the wind direction when using the forest parametrization. However, the drag imposed by the parametrization results in an underestimation of the cross-valley wind speed, which can be attributed to a poor representation of the land surface characteristics. The evaluation of the high-resolution WRF-LES shows a positive influence of the forest parametrization on the simulated winds in the first 500 m above the surface.

Impacts of dropsonde and satellite observations on the forecasts of two atmospheric-river-related heavy rainfall events

This study focuses on two intensive observing periods (IOPs) that cause heavy rainfall over California during the atmospheric river (AR) Reconnaissance Program in 2019. The impacts of dropsonde and satellite observations on the forecasts of the two AR-related heavy rainfall are investigated through both forecast sensitivity to observations (FSO) and observing system experiments (OSEs). In the first case (IOP3), satellite and dropsonde data coverage were relatively independent, whereas in the second case (IOP5), the satellite coverage was more extensive and substantially overlapped with dropsonde coverage. The FSO experiments indicate that the dropsondes improve the atmospheric forecast by a greater contribution per observation than that of an individual satellite instrument. In the OSEs, the heavy rainfall forecast presents a higher improvement when assimilating both dropsondes and satellite radiances. In IOP3, the dropsonde data slightly amplify the improvement achieved from the satellite data in terms of structure and location of the AR and attendant precipitation. In IOP5, the improvement from dropsonde data is more evident in the forecast of heavy precipitation. The influence of the dropsonde data in each case is broadly consistent with the relative coverage of dropsonde and satellite data. The best forecast performance acquired from the assimilation of both dropsonde and satellite data indicates the complementarity between the two data sources. Based on circulation analyses and further experiments assimilating satellite radiances from temperature channels and humidity channels separately, the improved rainfall forecasts are found to be related to the improvements in the three-dimensional circulation structure impacted by temperature characteristics.