Previous studies have indicated that approximately 20% of tropical cyclones (TCs) form under the influence of an upper-level disturbance globally. This study investigates tropical cyclogenesis (TCG) within a lower-tropospheric wave pouch (WP) in the presence of an upper-tropospheric cold low (CL) using idealized simulations in a resting environment. The β effect induces distinctly different wind and humidity asymmetries in the CL and WP owing to their differing vertical and horizontal structures. The CL exhibits a wetter western sector and a drier eastern sector, with stronger winds in the eastern sector. In contrast, the eastern sector of the WP, where a mesoscale vortex emerges, is slightly wetter than its western sector. This results in the strongest dry-air intrusion when the WP is positioned northeast of the CL and the weakest dry-air intrusion when the WP is located southwest of the CL. Additionally, when the WP is positioned northeast of the CL, the vortex developing from their vorticity superposition competes with the WP-induced vortex. The anticyclone southeast of the CL, induced by the Rossby energy dispersion, disrupts vorticity aggregation and hinders TCG. In contrast, when the WP is located southwest of the CL, the superposition of the WP and CL vorticity accelerates TCG. These combined mechanisms make the southwest quadrant of the CL the most favorable region for TCG, while the northeast quadrant being the least favorable. The sensitivity of TCG to the CL depth and the CL–WP separation distance are also investigated through further experiments.

Despite advancements in science and technology, flood prediction and preparedness remain challenging due to uncertainties in forecasting atmospheric and hydrologic processes, limited real-time data, and communication barriers. The Integrating Prediction of Precipitation and Hydrology for Early Actions (InPRHA) project, a 5-yr initiative under the WMO's World Weather Research Programme, is the first to bring together meteorology, hydrology, and social sciences within a steering committee to address these challenges. Building on knowledge from the High Impact Weather (HiWeather) project, InPRHA focuses on multihazard flood forecasting across the entire warning value chain from minutes to days, in a rapidly changing world. A key emphasis is understanding flood predictability and how uncertainties cascade through forecasting systems and are perceived, communicated, and acted upon by diverse stakeholders. This includes bridging research and operations, examining socioeconomic, cultural, and environmental challenges that influence risk perception and response. We propose key scientific questions across seven themes that address critical gaps in integrating predictions along the flood warning value chain. Addressing these gaps requires collaboration across disciplines and agencies. The project is structured into four work packages: DEFINE (identifying challenges), CONSTRUCT (gathering case studies), EXPERIMENT (scientific evaluations), and ENGAGE (community collaboration). Research will span rural, urban, and underdeveloped regions as well as countries with established warning systems, ensuring broad applicability. We invite scientists and practitioners from meteorology, hydrology, hydraulics, impacts, communication, human behavior, and economics to collaborate. By integrating disciplines and fostering transdisciplinary research, InPRHA aims to advance the science and practice of flood forecasting and early warnings to better protect vulnerable communities at risk. SIGNIFICANCE STATEMENT: InPHRA is a 5-yr project aimed at promoting international cooperation and advancing research to enhance flood hazard forecasting systems and warnings. By integrating precipitation and hydrologic predictions with social sciences, it seeks to improve early warning for communities in a rapidly changing world. InPRHA aims to reenvision the warning process by addressing flood multihazard interdependencies, local vulnerability, and climate change impacts on precipitation and hydrology forecasts. InPRHA calls on the broader research and operational community to collaborate on addressing key scientific questions and fostering transdisciplinary research across academia, research institutions, policymakers, and operational forecasting centers.

For this study, we present and evaluate an improved agent-based modeling framework, the Forecasting Laboratory for Exploring the Evacuation-system, version 2.0 (FLEE 2.0), designed to investigate relationships between hurricane forecast uncertainty and evacuation outcomes. Presented improvements include doubling its spatial resolution, using a quantitative approach to map real-world data onto the model's virtual world, and increasing the number of possible risk magnitudes for wind, surge, and rain risk. To assess model realism, we compare FLEE 2.0's simulated evacuations specifically its evacuation orders, evacuation rates, and traffic to available observational data collected during Hurricanes Irma, Dorian, and Ian. FLEE 2.0's evacuation response is encouraging, given that FLEE 2.0 responds reasonably and differently to all three different types of forecast scenarios. FLEE 2.0 well represents the spatial distribution of observed evacuation rates, and relative to a lower spatial resolution version of the model, FLEE 2.0 better captures sharp gradients in evacuation behaviors across the coastlines and metropolitan areas. Quantitatively evaluating FLEE 2.0's evacuation rates during Irma establishes model errors, uncertainties, and opportunities for improvement. In summary, this paper increases our confidence in FLEE 2.0, develops a framework for evaluating and improving these types of models, and sets the stage for additional analyses to quantify the impacts of forecast track, intensity, and other positional errors on evacuation.

Tropical Cyclone (TC) Oswald (2013) significantly impacted Australia with extensive rainfall and prolonged circulation over land, largely influenced by two mid‐latitude troughs. Unlike other documented studies, Oswald's interaction with the two troughs occurred in the mid‐troposphere, not the upper troposphere. Under the high vertical wind shear, the upper TC circulation was greatly weakened. However, in the middle levels between 400 and 600 hPa, high cyclonic potential vorticity (PV) air, was transported from the troughs to Oswald's mid‐layer circulation, replenishing its outer circulation. With the inner circulation, PV redistribution between the inner core and outer core was observed over the southeastern quadrant. This process enhanced mid‐to‐lower updrafts and boundary‐layer convergence, supporting the downshear reformation of mesovortices. Hence, despite sustained unfavorable strong shear and the absence of a warm ocean surface, the lower half of Oswald's circulation persisted and reorganized over land, significantly extending its impact after landfall.

Tropical cyclone numbers can vary from week to week within a hurricane season. Recent studies suggest that convectively coupled Kelvin waves can be partly responsible for such variability. However, the precise physical mechanisms responsible for that modulation remain uncertain partly due to the inability of previous studies to isolate the effects of Kelvin waves from other factors. This study uses an idealized modeling framework called an aquaplanet to uniquely isolate the effects of Kelvin waves on tropical cyclogenesis. The framework also captures the convective-scale dynamics of both tropical cyclones and Kelvin waves. Our results confirm fi rm an uptick in tropical cyclogenesis after the passage of a Kelvin wave twice as many tropical cyclones form 2 days after a Kelvin wave peak than at any other time lag from the peak. A detailed composite analysis shows anomalously weak ventilation during and after (or to the west of) the Kelvin wave peak. The weak ventilation stems primarily from anomalously moist conditions, with weaker vertical wind shear playing a secondary role. In contrast to previous studies, our results demonstrate that Kelvin waves modulate both kinematic and thermodynamic synoptic-scale conditions that are necessary for tropical cyclone formation. These results suggest that numerical models must capture the three-dimensional structure of Kelvin waves to produce accurate subseasonal predictions of tropical cyclone activity.

The emergence of exascale computing and artificial intelligence offer tremendous potential to significantly advance Earth system prediction capabilities. However, enormous challenges must be overcome to adapt models and prediction systems to use these new technologies effectively. A 2022 WMO report on exascale computing recommends "urgency in dedicating efforts and attention to disruptions associated with evolving computing technologies that will be increasingly difficult to overcome, threatening continued advancements in weather and climate prediction capabilities." Further, the explosive growth in data from observations, model and ensemble output, and postprocessing threatens to overwhelm the ability to deliver timely, accurate, and precise information needed for decision-making. Artificial intelligence (AI) offers untapped opportunities to alter how models are developed, observations are processed, and predictions are analyzed and extracted for decision-making. Given the extraordinarily high cost of computing, growing complexity of prediction systems, and increasingly unmanageable amount of data being produced and consumed, these challenges are rapidly becoming too large for any single institution or country to handle. This paper describes key technical and budgetary challenges, identifies gaps and ways to address them, and makes a number of recommendations.

Providing storm surge risk information at multi-day lead times is critical for hurricane evacuation decisions, but predictability of storm surge inundation at these lead times is limited. This study develops a method to parameterize and adjust tropical cyclones derived from global atmospheric model data, for use in storm surge research and prediction. We implement the method to generate storm tide (surge + tide) ensemble forecasts for Hurricane Michael (2018) at five initialization times, using archived operational ECMWF ensemble forecasts and the dynamical storm surge model ADCIRC. The results elucidate the potential for extending hurricane storm surge prediction to several-day lead times, along with the challenges of predicting the details of storm surge inundation even 18 h before landfall. They also indicate that accurately predicting Hurricane Michael’s rapid intensification was not needed to predict the storm surge risk. In addition, the analysis illustrates how this approach can help identify situationally and physically realistic scenarios that pose greater storm surge risk. From a practical perspective, the study suggests potential approaches for improving real-time probabilistic storm surge prediction. The method can also be useful for other applications of atmospheric model data in storm surge research, forecasting, and risk analysis, across weather and climate time scales.

During a 6-day intensive observing period in January 2021, Atmospheric River Reconnaissance (AR Recon) aircraft sampled a series of atmospheric rivers (ARs) over the northeastern Pacific that caused heavy precipitation over coastal California and the Sierra Nevada. Using these observations, data denial experiments were conducted with a regional modeling and data assimilation system to explore the impacts of research flight frequency and spatial resolution of dropsondes on model analyses and forecasts. Results indicate that dropsondes significantly improve the representation of ARs in the model analyses and positively impact the forecast skill of ARs and quantitative precipitation forecasts (QPF), particularly for lead times . 1 day. Both reduced mission frequency and reduced dropsonde horizontal resolution degrade forecast skill. On the other hand, experiments that assimilated only G -IV data and experiments that assimilated both G -IV and C-130 data show better forecast skill than experiments that only assimilated C-130 data, suggesting that the additional information provided by G -IV data is necessary for improving forecast skill. Although this is a case study, the 6-day period studied encompassed multiple AR events that are representative of typical AR behavior. Therefore, the results indicate that future operational AR Recon missions incorporate daily mission or back-to-back flights, maintain current dropsonde spacing, support high-resolution data transfer capacity on the C -130s, and utilize G -IV aircraft in addition to C -130s.

© 2023 American Meteorological Society. This is an Author Accepted Manuscript distributed under the terms of the default AMS reuse license. For information regarding reuse and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses). Corresponding author: David Lavers, david.lavers@ecmwf.int

The Advanced Study Program (ASP) at the National Center for Atmospheric Research has supported the career development of postdoctoral fellows for over 60 years. This study of ASP alumni helps better understand their career paths and provides a window into the geoscience community. It examines career aspirations and job satisfaction, as well as experiences with mentoring and attitudes about diversity and inclusion in the workplace. While about half of ASP alumni today work in academia, job changes and pursuit of careers outside of academia are in-creasing. Former ASP participants are actively engaged in mentoring and are supportive of efforts in diversity, equity, and inclusion (DEI). Alumni who identify as women reported feeling less sup-ported by their employers in their career growth and in their service activities such as mentoring than alumni who identify as men. The study also found that women engage in a broader range of DEI activities and mentor more often out of altruistic reasons rather than as an expectation of their position. In addition to mastering research and teaching skills, future postdocs will need training in leadership, grant writing, DEI, and project management to succeed in today's geosci-ence workforce.

Prediction of the potentially devastating impact of landfalling tropical cyclones (TCs) relies substantially on numerical prediction systems. Due to the limited predictability of TCs and the need to express forecast confidence and possible scenarios, it is vital to exploit the benefits of dynamic ensemble forecasts in operational TC forecasts and warnings. RSMCs, TCWCs, and other forecast centers value probabilistic guidance for TCs, but the International Workshop on Tropical Cyclones (IWTC-9) found that the “pull-through” of probabilistic information to operational warnings using those forecasts is slow. IWTC-9 recommendations led to the formation of the WMO/WWRP Tropical Cyclone-Probabilistic Forecast Products (TC-PFP) project, which is also endorsed as a WMO Seamless GDPFS Pilot Project. The main goal of TC-PFP is to coordinate across forecast centers to help identify best practice guidance for probabilistic TC forecasts. TC-PFP is being implemented in 3 phases: Phase 1 (TC formation and position); Phase 2 (TC intensity and structure); and Phase 3 (TC related rainfall and storm surge). This article provides a summary of Phase 1 and reviews the current state of the science of probabilistic forecasting of TC formation and position. There is considerable variability in the nature and interpretation of forecast products based on ensemble information, making it challenging to transfer knowledge of best practices across forecast centers. Communication among forecast centers regarding the effectiveness of different approaches would be helpful for conveying best practices. Close collaboration with experts experienced in communicating complex probabilistic TC information and sharing of best practices between centers would help to ensure effective decisions can be made based on TC forecasts. Finally, forecast centers need timely access to ensemble information that has consistent, user-friendly ensemble information. Greater consistency across forecast centers in data accessibility, probabilistic forecast products, and warnings and their communication to users will produce more reliable information and support improved outcomes.

The term jet stream generally refers to a narrow region of intense winds near the top of the midlatitude or subtropical troposphere. It is in the midlatitude jet stream where instabilities and waves may develop into synoptic-scale systems, which in turn makes accurately resolving the structure of the jet stream and associated features critical for atmospheric development, predictability, and impacts, such as extreme precipitation and winds. Using dropwindsonde observations collected during the Atmospheric River Reconnaissance (AR Recon) campaign from 2020 to 2022, this study assesses the North Pacific jet stream structure in the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). Results show that the IFS has a slow-wind bias on the lead times assessed, with the strongest winds (& GE;50 m & BULL;s(-1)) having a bias of up to -1.88 m & BULL;s(-1) on forecast day 4. Also, the IFS cannot resolve the sharp potential vorticity (PV) gradient across the jet stream and tropopause, and this PV gradient weakens with forecast lead time. Cases with larger wind biases are characterized by higher PV biases and PV biases tend to be larger for cases with a higher horizontal PV gradient. These results suggest that further model-based experiments are needed to identify and address these biases, which could ultimately yield increased forecast accuracy.

Abstract Tropical weather phenomena—including tropical cyclones (TCs) and equatorial waves—are influenced by planetary‐to‐convective‐scale processes; yet, existing data sets and tools can only capture a subset of those processes. This study introduces a convection‐permitting aquaplanet simulation that can be used as a laboratory to study TCs, equatorial waves, and their interactions. The simulation was produced with the Model for Prediction Across Scales‐Atmosphere (MPAS‐A) using a variable resolution mesh with convection‐permitting resolution (i.e., 3‐km cell spacing) between 10°S and 30°N. The underlying sea‐surface temperature is given by a zonally symmetric profile with a peak at 10°N, which allows for the formation of TCs. A comparison between the simulation and satellite, reanalysis, and airborne dropsonde data is presented to determine the realism of the simulated phenomena. The simulation captures a realistic TC intensity distribution, including major hurricanes, but their lifetime maximum intensities may be limited by the stronger vertical wind shear in the simulation compared to the observed tropical Pacific region. The simulation also captures convectively coupled equatorial waves, including Kelvin waves and easterly waves. Despite the idealization of the aquaplanet setup, the simulated three‐dimensional structure of both groups of waves is consistent with their observed structure as deduced from satellite and reanalysis data. Easterly waves, however, have peak rotation and meridional winds at a slightly higher altitude than in the reanalysis. Future studies may use this simulation to understand how convectively coupled equatorial waves influence the multi‐scale processes leading to tropical cyclogenesis.

This study investigates the effects of surface fluxes on ventilation pathways and the development of Hurricane Michael (2018), and is a real-case comparison to previous idealized modeling studies that investigate ventilation. Two modeling experiments are conducted by altering surface exchange coefficients to achieve a strong and weak experiment. Ventilation pathways are evaluated to understand how the vortex responds to dry-air infiltration. Pathways for dry-air infiltration are split into downdraft and radial ventilation. Results show that downdraft ventilation at low levels is maximized left of shear, exists between the surface and a height of 3 km, and is associated with rainband activity. Trajectories from downdraft ventilation demonstrate slower thermodynamic recovery for the weaker experiment. The slower recovery contributes to the initial intensity bifurcation between experiments. Radial ventilation has two pathways. At low levels, it is coupled with downdraft ventilation. Aloft, between heights of 5 and 10 km, it is maximized upshear and associated with storm-relative flow. This pathway is similar for each experiment initially, suggesting that the initial bifurcation of intensity is not a consequence of radial ventilation aloft. Trajectories from radial ventilation during a later time period show the destructive impact of lower- θ e air in the near environment on convection upshear and right of shear for the weaker experiment. This study demonstrates how ventilation pathways at low levels and aloft are affected by surface fluxes, and how ventilation pathways operate, at different times, to affect tropical cyclone development.

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 obser-vations (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 drop -sondes 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 assimi-lating 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.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).Corresponding author: Anna Wilson, amw061@ucsd.edu

The Sierras de Córdoba (SDC) mountain range in Argentina is a hotspot of deep moist convection initiation (CI). Radar climatology indicates that 44% of daytime CI events that occur near the SDC in spring and summer seasons and that are not associated with the passage of a cold front or an outflow boundary involve a northerly LLJ, and these events tend to preferentially occur over the southeast quadrant of the main ridge of the SDC. To investigate the physical mechanisms acting to cause CI, idealized convection-permitting numerical simulations with a horizontal grid spacing of 1 km were conducted using CM1. The sounding used for initializing the model featured a strong northerly LLJ, with synoptic conditions resembling those in a previously postulated conceptual model of CI over the region, making it a canonical case study. Differential heating of the mountain caused by solar insolation in conjunction with the low-level northerly flow sets up a convergence line on the eastern slopes of the SDC. The southern portion of this line experiences significant reduction in convective inhibition, and CI occurs over the SDC southeast quadrant. Thesimulated storm soon acquires supercellular characteristics, as observed. Additional simulations with varying LLJ strength also show CI over the southeast quadrant. A simulation without background flow generated convergence over the ridgeline, with widespread CI across the entire ridgeline. A simulation with mid- and upper-tropospheric westerlies removed indicates that CI is minimally influenced by gravity waves. We conclude that the low-level jet is sufficient to focus convection initiation over the southeast quadrant of the ridge.

Scale-dependent processes within the tropical cyclone (TC) eyewall and their contributions to intensification are examined in an idealized simulation of a TC translating in uniform environmental flow. The TC circulation is partitioned into axisymmetric, low-wavenumber (m = 1-3), and high-wavenumber (m > 3) categories, and scale-dependent contributions to the intensification process are quantified through the azimuthal-mean relative (vertical) vorticity and tangential momentum budgets. To further account for the interdependent relationship between the axisymmetric vortex structure and eyewall asymmetries, the analyses are subdivided into three periods-early, middle, and late-that represent the approximate quartiles of the full intensification period prior to the TC attaining its maximum intensity. The asymmetries become concentrated among lower azimuthal wavenumbers during the intensification process and are persistently distributed among a broader range of azimuthal scales at higher altitudes. The scale-dependent budgets demonstrate that the axisymmetric and asymmetric processes generally oppose each other during TC intensification. The axisymmetric processes are mostly characterized by a radial spinup dipole pattern, with a tangential momentum spinup tendency concentrated along the radius of maximum tangential winds (RMW) and a spindown tendency concentrated radially inward of the RMW. The asymmetric processes are mostly characterized by an opposing spindown dipole pattern that is slightly weaker in magnitude. The most salient exception occurs from high-wavenumber processes contributing to a relatively modest, net spinup along the RMW between similar to 2- and 4-km altitude. Given that the maximum tangential winds persistently reside below 2-km altitude, eyewall asymmetries are primarily found to impede TC intensification. Significance StatementThe convection fueling a tropical cyclone progressively organizes into a compact region called the eyewall where the strongest winds and rainfall occur. As the tropical cyclone intensifies, convection in the circular eyewall becomes more uniform, and the eyewall takes the appearance of a ring. We call this ring shape the "symmetric" part of the eyewall. As convection in the eyewall evolves and interacts, the eyewall becomes deformed and develops wiggles. We call these wiggly shapes the "asymmetric" parts of the eyewall. We demonstrate that the symmetric part of the eyewall helps intensification. The asymmetric parts of the eyewall mostly hurt intensification except during the earlier stages. Our results indicate that a symmetric eyewall shape is preferable for tropical cyclone intensification.

Societal vulnerability to tropical cyclone (TC) hazards continues to grow among expanding coastal communities. Additionally, climate projections indicate that TCs will likely attain higher intensities, produce greater amounts of rainfall, and contribute to enhanced storm-surge inundation amid a warmer climate. Despite accumulating confidence among the climate projections for TCs, a vital element to the compounding nature of TC hazards remains highly uncertain: how might the frequency of TCs change amid a warmer climate? We posit that the frequency of TCs is inextricably connected to variability among the multi-scale processes that constitute tropical cyclogenesis. Therefore, TC frequency projections should be substantiated with multi-scale assessments that account for convective processes, the evolution of mesoscale precursor disturbances, and large-scale environmental forcing. As a first step towards understanding variability among cyclogenesis events in the context of the Earth’s warming climate system, we present intercomparisons between simulations of cyclogenesis by varying the horizontal grid spacing in an idealized, aquaplanet modeling framework using the Model for Prediction Across Scales-Atmosphere (MPAS-A). Four simulations are constructed—three with quasi-uniform horizontal grid spacings of 60 km, 30 km, and 15 km, and a high-resolution simulation with 3-km horizontal grid spacing in the tropics that smoothly transitions to 15-km grid spacing in the extratropics. Tropical precursor disturbances to cyclogenesis are identified and objectively tracked with the TRACK algorithm. Probability density functions are created for each 6-h time step along the disturbance trajectories to characterize and compare the composite environmental conditions accompanying cyclogenesis as a function of the model grid spacing. Intercomparisons between simulations are further investigated with phase diagrams that depict the composite area- and volume-averaged evolution of thermodynamic and dynamic processes throughout cyclogenesis. Furthermore, shear-relative composite-mean analyses are created to assess structural differences between precursor disturbances to cyclogenesis in the simulations. Collectively, the analyses provide an extensible framework and systematic method to assess multi-scale variability during the cyclogenesis process. We will discuss the implications of our findings in the context of the Earth’s warming climate system and proffer a path towards elucidating TC frequency projections through process-oriented diagnostics that characterize the multi-scale variability inherent to tropical cyclogenesis.

Atmospheric River Reconnaissance (AR Recon) is a targeted campaign that complements other sources of observational data, forming part of a diverse observing system. AR Recon 2021 operated for ten weeks from January 13 to March 22, with 29.5 Intensive Observation Periods (IOPs), 45 flights and 1142 successful dropsondes deployed in the northeast Pacific. With the availability of two WC-130J aircraft operated by the 53rd Weather Reconnaissance Squadron (53 WRS), Air Force Reserve Command (AFRC) and one National Oceanic and Atmospheric Administration (NOAA) Aircraft Operations Center (AOC) G-IVSP aircraft, six sequences were accomplished, in which the same synoptic system was sampled over several days. The principal aim was to gather observations to improve forecasts of landfalling atmospheric rivers on the U.S. West Coast. Sampling of other meteorological phenomena forecast to have downstream impacts over the U.S. was also considered. Alongside forecast improvement, observations were also gathered to address important scientific research questions, as part of a Research and Operations Partnership. Targeted dropsonde observations were focused on essential atmospheric structures, primarily atmospheric rivers. Adjoint and ensemble sensitivities, mainly focusing on predictions of U.S. West Coast precipitation, provided complementary information on locations where additional observations may help to reduce the forecast uncertainty. Additionally, Airborne Radio Occultation (ARO) and tail radar were active during some flights, 30 drifting buoys were distributed, and 111 radiosondes were launched from four locations in California. Dropsonde, radiosonde and buoy data were available for assimilation in real-time into operational forecast models. Future work is planned to examine the impact of AR Recon 2021 data on model forecasts.