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Forecasts of tropical cyclone (TC) tornadoes are less skillful than their non‐TC counterparts at all lead times. The development of a convection‐allowing regional ensemble, known as the Warn‐on‐Forecast System (WoFS), may help improve short‐fused TC tornado forecasts. As a first step, this study investigates the fidelity of convective‐scale kinematic and thermodynamic environments to a preliminary set of soundings from WoFS forecasts for comparison with radiosondes for selected 2020 landfalling TCs. Our study shows reasonable agreement between TC convective‐scale kinematic environments in WoFS versus observed soundings at all forecast lead times. Nonetheless, WoFS is biased toward weaker than observed TC‐relative radial winds, and stronger than observed near‐surface tangential winds with weaker winds aloft, during the forecast. Analysis of storm‐relative helicity (SRH) shows that WoFS underestimates extreme observed values. Convective‐scale thermodynamic environments are well simulated for both temperature and dewpoint at all lead times. However, WoFS is biased moister with steeper lapse rates compared to observations during the forecast. Both CAPE and, to a lesser extent, 0–3‐km CAPE distributions are narrower in WoFS than in radiosondes, with an underestimation of higher CAPE values. Together, these results suggest that WoFS may have utility for forecasting convective‐scale environments in landfalling TCs with lead times of several hours. Plain Language Summary: Landfalling tropical cyclones (known as tropical depressions, tropical storms, or hurricanes) often spawn tornadoes, which are more challenging to forecast than Great Plains tornadoes. The development of a weather forecast ensemble model, known as the Warn‐on‐Forecast system, may help improve tornado forecasts. This study compares vertical profiles of winds, temperature, moisture, and associated severe weather metrics from the Warn‐on‐Forecast with observed radiosonde data (i.e., balloon‐borne instruments) in landfalling tropical cyclones. Our analysis shows agreement between the observed and forecasted vertical structure of TC winds at all lead times including strong changes in near‐surface wind speed and direction. Nonetheless, forecasted tropical cyclone winds tend to be biased weaker than observed, which is associated with an underestimation of environmental favorability for tornadoes. Similarly, forecasted temperature and moisture are also reasonably represented compared to observations. However, Warn‐on‐Forecast tends to overestimate moisture and near‐surface temperature, with smaller‐than‐observed variability in thermodynamic environmental favorability. Together, these results suggest that the weather forecast model used here may be useful for improving forecasts of supercell environments in landfalling TCs. Key Points: Warn‐on‐Forecast tropical cyclone forecasts show reasonable agreement between observed and forecast convective‐scale kinematic environmentsForecast convective‐scale thermodynamic environments also show reasonable fidelity compared to observationsA case study shows stronger discrepancies than the full sample including weaker than observed winds, temperature inversions, and dry layers [ABSTRACT FROM AUTHOR]

Changes in tropical cyclones due to greenhouse‐gas forcing in the Shanghai area have been studied in a double‐nesting regional model experiment using the Met Office convection‐permitting model HadREM3‐RA1T at 4 km resolution and the regional model HadREM3‐GA7.05 at 12 km for the intermediate nest. Boundary conditions for the experiment have been constructed from HadGEM2‐ES, a General Circulation Model (GCM) from the 5th Coupled Model Intercomparison Project (CMIP5), directly using high‐frequency data for the atmosphere (6‐hourly) and the ocean (daily), for the historical period (1981–2000) and under the Representative Concentration Pathway 8.5 (2080–2099). These choices identify one of the warmest climate scenarios available from CMIP5. Given the direct use of GCM data for the baseline, large scale conditions relevant for tropical cyclones have been analyzed, demonstrating a realistic representation of environmental conditions off the coast of eastern China. GCM large scale changes show a reduction in wind shear in addition to the expected strong increase in sea‐surface temperature. Tropical cyclones from the 4 km historical simulation have a negative bias in intensity, not exceeding Category 4, and a wet bias in the rainfall associated with these cyclones. However, there is a clear improvement in cyclone intensity and rainfall at 4 km in comparison with the 12 km simulation. Climate change responses in the 4 km simulation include an extension of the tropical cyclone season, and strong increases in frequency of the most intense cyclones (approximately by a factor of 10) and associated rainfall. These are consistent with the results from the 12 km simulation. Plain Language Summary: Since global climate models do not have the spatial resolution to simulate tropical cyclones, higher resolution limited area models are commonly used to improve the representation of these phenomena. In this study, where changes in the Shanghai area have been estimated, this was done in two steps, using a regional model at 12 km resolution as the intermediate step to finally reach a 4 km resolution for the region around Shanghai with a model which can explicitly represent convection processes. This was done by using one of the warmest climate scenarios available from the climate projections run under realistic increases of greenhouse‐gas concentrations, to study climate change at the end of this century. The global climate model reproduces large scale conditions relevant for tropical cyclones which compare well with observations in the historical period and projects changes in the atmosphere and the ocean which are relevant for tropical cyclones. The downscaled model at 4 km reproduces the observation with some biases in intensity, not sufficient to reach Category 4, and in the cyclone precipitation, through marked improvements with respect to the 12 km model. The climate change response shows a strong increase in intense tropical cyclone frequency and rainfall, common to both models. Key Points: Double‐nesting experiment with a 4 km convective scale model driven by a high end Coupled Model Intercomparison Project general circulation model to study changes in tropical storms near ShanghaiImprovement at 4 km over the intermediate 12 km nest on rainfall and intensity of tropical storms, but not sufficient to reach category 4Future changes at 4 km show a marked increase in frequency of intense tropical cyclones and in rainfall, well matched by the 12 km model [ABSTRACT FROM AUTHOR]

A month‐long data assimilation experiment is carried out to assess the impact of CrIS and IASI Transformed Retrievals (TRs) on the accuracy of analyses and forecasts from a 3‐hr Weather Research and Forecasting cycling system implemented over the central North Pacific Ocean. Conventional observations and satellite MicroWave (MW) radiance data are assimilated along with TRs in comparative experiments. Both the NCEP Global Forecasting System and the European Centre for Medium‐Range Weather Forecasts analyses are used in the evaluation process. The results show that the assimilation of TRs alone, and in combination with MW radiance assimilation, have the greatest impact on the characterization of the moisture field in the middle atmospheric levels (800–300 hPa), and particularly in the lower portion (800–600 hPa). The latter improvement is likely due to a refinement in the vertical definition of the trade‐wind inversion. Plain Language Summary: A month‐long data assimilation experiment is carried out to assess the impact of hyper‐spectral sensor Transformed Retrievals (TRs) on the accuracy of analyses and forecasts from a 3‐hr Weather Research and Forecasting cycling system implemented over the central North Pacific Ocean. TRs are the result of a mathematical inversion process that compresses the informational content of the hyper‐spectral radiances into a limited number of uncorrelated parameters, and provides an ad hoc observation operator, for their assimilation within Numerical Weather Prediction models. Conventional observations and satellite MicroWave (MW) radiance data are assimilated along with TRs in comparative experiments. Both the NCEP Global Forecasting System and the European Centre for Medium‐Range Weather Forecasts analyses are used in the evaluation process. The results show that the assimilation of TRs, both alone, and in combination with MW radiance assimilation, have the greatest impact on the characterization of the moisture field in the middle atmospheric levels (800–300 hPa), and particularly in the lower portion (800–600 hPa). The latter improvement is likely due to a refinement in the vertical definition of the trade‐wind inversion. Key Points: Hyperspectral radiances are efficiently compressed into a limited number of uncorrelated parameters: the Transformed Retrievals (TRs)Assimilation of TRs is akin to assimilation of physical profilesThe assimilation of TRs results in a higher forecast accuracy in predicting the distribution of the water vapor [ABSTRACT FROM AUTHOR]

Gas phase hydrogen chloride (HCl) was measured at Pasadena and San Joaquin Valley (SJV) ground sites in California during May and June 2010 as part of the CalNex study. Observed mixing ratios were on average 0.83 ppbv at Pasadena, ranging from below detection limit (0.055 ppbv) to 5.95 ppbv, and were on average 0.084 ppbv at SJV with a maximum value of 0.776 ppbv. At both sites, HCl levels were highest during midday and shared similar diurnal variations with HNO3. Coupled phase partitioning behavior was found between HCl/Cl− and HNO3/NO3− using thermodynamic modeling and observations. Regional modeling of Cl− and HCl using Community Multiscale Air Quality captures some of the observed relationships but underestimates measurements by a factor of 5 or more. Chloride in the 2.5–10 μm size range in Pasadena was sometimes higher than sea salt abundances, based on co‐measured Na+, implying that sources other than sea salt are important. The acid‐displacement of HCl/Cl− by HNO3/NO3− (phase partitioning of semi‐volatile acids) observed at the SJV site can only be explained by aqueous phase reaction despite low RH conditions and suggests the temperature dependence of HCl phase partitioning behavior was strongly impacted by the activity coefficient changes under relevant aerosol conditions (e.g., high ionic strength). Despite the influence from activity coefficients, the gas‐particle system was found to be well constrained by other stronger buffers and charge balance so that HCl and Cl− concentrations were reproduced well by thermodynamic models. Plain Language Summary: Despite the known importance of gas‐particle partitioning in chlorine activation chemistry, the sources and atmospheric fate of hydrogen chloride (HCl) and particulate Cl− require further study. HCl concentrations and the corresponding phase partitioning mechanisms with Cl− in PM2.5 were studied through field measurements and modeling as part of the CalNex field campaign. The measurements confirmed that gas phase HCl was the dominant component of atmospheric chlorine and suggested that even though the current modeling can explain the diurnal variation of HCl, the mixing ratios were severely underestimated. Temperature dependence of Cl− replacement reaction by HNO3 was observed at one site. This study suggests further model development and field observations of HCl, as well as more reliable understanding of HCl phase partitioning behavior are needed to better predict the atmospheric fate of HCl and Cl−. Key Points: Hydrogen chloride (HCl) was measured at two CalNex sites. At both, the diurnal variation of HCl was similar and HCl was correlated with HNO3 on a given dayThe Community Multiscale Air Quality model captures HCl diurnal variation but underestimates the atmospheric chlorine concentrations by at least a factor of 5The aqueous phase exchange reaction drove coupled partitioning behavior between HCl/Cl− and HNO3/NO3− at one site despite low humidity [ABSTRACT FROM AUTHOR]

The Long Island Sound (LIS) Tropospheric Ozone Study was a multi‐agency collaborative field campaign conducted during the summer of 2018 to improve the understanding of ozone chemistry and transport from New York City to areas downstream, especially the LIS and adjacent Connecticut coastline. Measurements made during this campaign were leveraged to test and evaluate the coupled WRF‐CMAQ model at 12 km, 4 and 1.33 km horizontal grid spacing. Special attention was placed on the model's representation of sea breeze circulations, low level jets, and boundary layer evolution. The evaluation suggests using higher resolutions resulted in improved surface meteorology statistics throughout the whole summer, with temperature biases seeing the biggest statistical improvements when using 1.33‐km grid spacing, going from −0.12 to 0.08 K. Additionally, 4‐km grid spacing provided the biggest advantage when simulating ozone over the region of interest, with biases being reduced from 2.40 to 0.57 to 0.37 ppbV with increased resolution. Case studies of two high ozone concentration events (July 10 and August 6) revealed that sound breezes and low‐level jets had a critical role in transporting pollutant‐rich, shallow marine air masses from the LIS inland over the Connecticut coast. Modifications were made to the representation of sea surface temperatures, which subsequently improved the simulation of surface ozone predictions. Plain Language Summary: Surface‐level ozone pollution across the country is closely monitored by the U.S. Environmental Protection Agency due to the threat it can pose to public health and safety. Ozone is not emitted naturally; instead it forms when other pollutants are emitted and exposed to sunlight. Ozone pollution can be especially harmful near large urban areas like New York City where high emissions of pollutants and local meteorology interact to produce ozone within the city and transport it downwind across the Long Island Sound into Connecticut. In this study, we used a weather and chemistry model to explore how surface winds over the LIS impact high ozone along the Connecticut and Long Island coastlines. Our work highlighted the importance of accurately modeling meteorological conditions so that we can adequately represent high ozone events in models. We also found that ozone over Connecticut is especially sensitive to where and when local wind features like sound breezes and low‐level jets form and dissipate. Continued work in these areas of study can help policy makers develop strategies that control all the factors that cause ozone pollution in this area. Key Points: High‐res WRF‐CMAQ model simulations showed improvements to surface meteorology and ozone over the NYC‐Connecticut‐Long Island Sound regionSound breezes along the CT and Long Island coasts were found to be instrumental to the modeled transport of ozone and its precursorsIncorporating diurnal variations to sea surface temperatures improved the representation of transport and surface ozone mixing ratios [ABSTRACT FROM AUTHOR]

Dynamical downscaling remains a powerful tool for studying regional climate processes, and the genesis of high‐resolution historical and future climate data. This technique is particularly important over areas of complex terrain, such as the western United States (WUS), where global models are especially limited in representing regional climate. After identifying a suite of WRF options that best simulate snow and precipitation for an average water year (2010) over the WUS, we evaluate the performance of the dynamically downscaled European Centre for Medium‐range Weather Forecasting's fifth Reanalysis (ERA5) from 1980 to 2020 on 45‐km, 9‐km, and two 3‐km grids. We find that by decreasing the horizontal grid spacing within WRF, improvements to Sierra Nevada and Northern Rocky Mountain snow, Santa Ana and Diablo winds, and coastal meteorology occur. For landfalling atmospheric rivers (ARs), the downscaled reanalysis simulates greater upstream integrated vapor transport (IVT) than ERA5. However, WRF skillfully simulates the positioning of the IVT and the timing and magnitude of AR precipitation. This potential IVT bias, in conjunction with increasing resolution, leads to a wet precipitation bias across the Sierra Nevada in the 3‐km experiment. This conclusion is supported by streamflow analysis, although we note that the bias in the 3‐km experiment can also be explained by in situ undercatch issues. Meanwhile, the 9‐km experiment is more biased than the 3‐km experiment across the Northern Rocky Mountains compared to in situ measured SWE and precipitation, indicating a geographic sensitivity to biases. Plain Language Summary: Atmospheric reanalyses are often used to evaluate the performance of global climate models (GCMs). Reanalyses have a model component, but they also incorporate observations in post‐processing to orient the final product about reality. The horizontal resolution of reanalyses is too low to resolve small landscape features that control localized meteorology and climate. Thus, scientists are in need of an even higher resolution modeling framework. It is therefore necessary to embed a regional climate model (RCM), a tool that uses physics to simulate weather in higher resolution, within the reanalysis to generate kilometer‐scale weather and climate information. This process is called dynamical downscaling. Using this process, we show that, in spite of increased resolution, selecting the wrong RCM configurations can lead to poor RCM performance compared to observations, and we identify a superior set of RCM options for simulating weather and climate across the western United States. Following our tests, we find that the RCM adequately reproduces the historical weather and climate (1980–2020), and RCM accuracy improves with increasing model resolution. In creating this product, we now have a benchmark by which to evaluate the fidelity of dynamically downscaled GCMs, as we seek to extend this modeling framework to future climate. Key Points: A tractable method for dynamically downscaling the historical record across the western United States is presentedThorough testing of regional climate model (RCM) options is imperative before dynamically downscaling over climate time scalesHigher‐resolutions in RCMs should generally add value when considering a diverse array of simulated atmospheric phenomena [ABSTRACT FROM AUTHOR]

Providing skilful predictions of high‐impact weather up to 2 weeks ahead is on the agenda of international weather centers. Evaluating the capabilities of current numerical systems in predicting past events can bring extremely valuable contributions to the assessment of the information content available today with operational models. In the framework of the activities for the fiftieth anniversary of the extreme precipitation event that occurred in Italy in November 1966, this paper investigates its predictability using state‐of‐the‐art global and regional ensemble simulations. The first goal is to assess if and how many days in advance, this event can be predicted by current European Centre for Medium‐Range Weather Forecasts (ECMWF) global ensembles. A second goal is to evaluate the potential added value of running nested higher‐resolution and convection‐permitting ensembles. It is shown that ECMWF ensembles are able to provide valuable information up to 3 days before the event. Within this forecast range, convection‐permitting simulations can provide more accurate estimations of precipitation maxima. However, the results indicate also a strong underestimation of rainfall amounts with both global and regional models even at short forecast range. To partially explain this shortcoming, we discuss how the scarcity of observations available in 1966 for the analysis process limits the quality of the ensemble initial conditions and we adopt a method to obtain more reliable ensemble forecasts. The paper concludes with a comparison with previous similar works; results indicate a gain in predictability of up to 12 hr with respect to numerical revisitations performed to mark the fortieth anniversary of the event. Key Points: Current state‐of‐the‐art global ensembles are able to provide valuable information up to 3 days before the Arno River flooding event (Italy, November 1966)Convection‐permitting ensembles provide more accurate estimations of precipitation maximaAdvances in numerical modeling occurred in the last 10 years, determine a gain in predictability of up to 12 hr with respect to similar works [ABSTRACT FROM AUTHOR]

Abstract: Tropical cyclone (TC) 05A (TC05A, November 2011) over the Indian Ocean originated near the equator and brought huge damages to Sri Lanka and India. The genesis and propagation of TC05A involves interactions with the Madden–Julian Oscillation (MJO), interannual (IA) variations, and other synoptic (SY) systems. To investigate the impacts of the SY, MJO, and IA forcings across the lateral boundaries on TC05A, regional simulation with the Weather Research and Forecast model through the partial lateral forcing approach is conducted. The control experiment reproduces realistic genesis and movement of TC05A and associated heavy rainfall, as well as the mean states and MJO. Both the SY and IA forcings make a moderate contribution to the initiation of cyclonic vorticity and rainfall enhancement in the central Indian Ocean and moderate modification of the TC05A track. However, it is the MJO forcing that fundamentally reproduces a coherent moist, low‐level convergence, and a cyclonic environment that is favorable for the development of TC05A. The greatest impact of northern boundary intraseasonal (IS) forcing on the genesis location and path of TC05A is further identified, suggesting the importance of the interaction between the MJO and northeast winter monsoon. In contrast, the southern boundary IS forcing is unimportant and the western and eastern boundary IS forcings play a moderate role in slowing down TC05A and modifying its track, intensity, and rainfall. This study demonstrates that the partial lateral forcing method is an effective tool to identify the key factors controlling the extreme events through regional climate modeling. [ABSTRACT FROM AUTHOR]

The Arctic is influenced by air pollution transported from lower latitudes, and increasingly by local sources such as shipping and resource extraction. Local Arctic emissions could increase significantly in the future due to industrialization in a warming Arctic and further influence Arctic climate. We use the regional model Weather Research and Forecasting, including chemistry, to investigate current (2012) and future (2050) sources of Arctic aerosol and ozone pollution and their radiative impacts, focusing on spring and summer emissions from midlatitude anthropogenic sources, biomass burning, Arctic shipping, and Arctic gas flaring. Results show that remote anthropogenic and biomass burning emissions are likely to remain the main source of Arctic pollution burdens and of black carbon (BC) deposition over snow, and the main contributors to direct aerosol and ozone radiative effects in the Arctic. However, local Arctic flaring emissions are already a major source of BC in northwestern Russia, with a direct radiative effect of ∼25 mW/m2, and Arctic shipping is a strong current source of aerosols and ozone during summer in the Nordic Seas. We find that the direct effect of ozone and aerosols from summertime Arctic shipping is respectively negative (due to frequent temperature inversions) and positive (because of the high surface albedo) in our simulations, two new results. With the development of diversion shipping through the Arctic Ocean in summer 2050, Arctic shipping emissions could become the main source of surface aerosol and ozone pollution at the surface, with strong associated indirect effects of −0.8 W/m2, while flaring would remain an important BC source. Key Points: Arctic shipping and gas flaring significantly contribute to present‐day and future surface Arctic pollutionOzone from shipping cools the atmosphere due to the near‐surface temperature inversions in the ArcticFuture Arctic diversion shipping causes significant negative summertime aerosol indirect effects (‐0.8 W/m2) [ABSTRACT FROM AUTHOR]