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At least 469 records · Page 26

JPL Genesis and Rapid Intensification Processes (GRIP) Portal

Satellite observations can play a very important role in airborne field campaigns, since they provide a comprehensive description of the environment that is essential for the experiment design, flight planning, and post-experiment scientific data analysis. In the past, it has been difficult to fully utilize data from multiple NASA satellites due to the large data volume, the complexity of accessing NASA s data in near-real-time (NRT), as well as the lack of software tools to interact with multi-sensor information. The JPL GRIP Portal is a Web portal that serves a comprehensive set of NRT observation data sets from NASA and NOAA satellites describing the atmospheric and oceanic environments related to the genesis and intensification of the tropical storms in the North Atlantic Ocean. Together with the model forecast data from four major global atmospheric models, this portal provides a useful tool for the scientists and forecasters in planning and monitoring the NASA GRIP field campaign during the 2010 Atlantic Ocean hurricane season. This portal uses the Google Earth plug-in to visualize various types of data sets, such as 2D maps, wind vectors, streamlines, 3D data sets presented at series of vertical cross-sections or pointwise vertical profiles, and hurricane best tracks and forecast tracks. Additionally, it allows users to overlap multiple data sets, change the opacity of each image layer, generate animations on the fly with selected data sets, and compare the observation data with the model forecast using two independent calendars. The portal also provides the capability to identify the geographic location of any point of interest. In addition to supporting the airborne mission planning, the NRT data and portal will serve as a very rich source of information during the post-field campaign analysis stage of the airborne experiment. By including a diverse set of satellite observations and model forecasts, it provides a good spatial and temporal context for the high-resolution, but limited in space and time, airborne observations.

Knosp, Brian W.↗

Integration of Earth Remote Sensing into the NOAA/NWS Damage Assessment Toolkit

Following the occurrence of severe weather, NOAA/NWS meteorologists are tasked with performing a storm damage survey to assess the type and severity of the weather event, primarily focused with the confirmation and assessment of tornadoes. This labor‐intensive process requires meteorologists to venture into the affected area, acquire damage indicators through photos, eyewitness accounts, and other documentation, then aggregation of data in order to make a final determination of the tornado path length, width, maximum intensity, and other characteristics. Earth remote sensing from operational, polar‐orbiting satellites can support the damage assessment process by helping to identify portions of damage tracks that are difficult to access due to road limitations or time constraints by applying change detection techniques. In addition, higher resolution commercial imagery can corroborate ground‐based surveys by examining higher‐resolution commercial imagery. As part of an ongoing collaboration, NASA and NOAA are working to integrate near real‐time Earth remote sensing observations into the NOAA/NWS Damage Assessment Toolkit, a handheld application used by meteorologists in the survey process. The team has recently developed a more streamlined approach for delivering data via a web mapping service and menu interface, allowing for caching of imagery before field deployment. Near real‐time products have been developed using MODIS and VIIRS imagery and change detection for preliminary track identification, along with conduits for higher‐resolution Landsat, ASTER, and commercial imagery as they become available. In addition to tornado damage assessments, the team is also investigating the use of near real‐time imagery for identifying hail damage to vegetation, which also results in large swaths of damage, particularly in the central United States during the peak growing season months of June, July, and August. This presentation will present an overview of recent activities, challenges and successes, best practices, and opportunities for future work and collaboration.

Molthan, Andrew↗

Factors influencing recent trends in retail electricity prices in the United States

This study analyzes the primary drivers of recent state-level trends in U.S. retail electricity prices. We summarize pricing trends, explore descriptive relationships, and employ regression models to quantify the influence of various factors. Although the recent national rise in retail prices has largely tracked inflation, state-level trends vary widely. We identify a number of factors that explain trends in subsets of states. States with the greatest price increases typically exhibited shrinking customer loads—partially linked to growth in net metered behind-the-meter solar—and had renewables portfolio standards (RPS) in concert with relatively costly incremental renewable energy supplies. By contrast, recent utility-scale wind and solar deployment that occurred outside RPS programs (but that benefited from tax incentives) had no discernible impact on increased retail prices. Hurricanes, storms and wildfires also contributed to sizable price increases in some states, most notably in California, where wildfire risk mitigation and liability insurance were major cost drivers. Fluctuations in natural gas prices—particularly following the onset of the Ukraine-Russia war—further contributed to sharp price increases through 2022–2023 in many states, with moderation in 2024. The relative influence of these factors varies across states and over time, and relationships may change in the future. Nonetheless, the findings underscore the diverse set of price determinants and highlight the need for continued research to inform effective policy and ensure customer affordability.

Customer load↗

Dissemination of Earth Remote Sensing Data for Use in the NOAA/NWS Damage Assessment Toolkit

The National Weather Service has developed the Damage Assessment Toolkit (DAT), an application for smartphones and tablets that allows for the collection, geolocation, and aggregation of various damage indicators that are collected during storm surveys. The DAT supports the often labor‐intensive process where meteorologists venture into the storm‐affected area, allowing them to acquire geotagged photos of the observed damage while also assigning estimated EF‐scale categories based upon their observations. Once the data are collected, the DAT infrastructure aggregates the observations into a server that allows other meteorologists to perform quality control and other analysis steps before completing their survey and making the resulting data available to the public. In addition to in‐person observations, Earth remote sensing from operational, polar-orbiting satellites can support the damage assessment process by identifying portions of damage tracks that may be missed due to road limitations, access to private property, or time constraints. Products resulting from change detection techniques can identify damage to vegetation and the land surface, aiding in the survey process. In addition, higher resolution commercial imagery can corroborate ground‐based surveys by examining higher‐resolution commercial imagery. As part of an ongoing collaboration, NASA and NOAA are working to integrate near real‐time Earth remote sensing observations into the NOAA/NWS Damage Assessment Toolkit. This presentation will highlight recent developments in a streamlined approach for disseminating Earth remote sensing data via web mapping services and a new menu interface that has been integrated within the DAT. A review of current and future products will be provided, including products derived from MODIS and VIIRS for preliminary track identification, along with conduits for higher‐resolution Landsat, ASTER, and commercial imagery as they become available. In addition to tornado damage assessments, the team is also investigating the use of near real‐time imagery for identifying hail damage to vegetation, which also results in large swaths of damage, particularly in the central United States during the peak growing season months of June, July, and August. This presentation will present an overview of recent activities, challenges and successes, best practices, and opportunities for future work and collaboration

Molthan, Andrew↗

Recent Advancements in Lightning Jump Algorithm Work

In the past year, the primary objectives were to show the usefulness of total lightning as compared to traditional cloud-to-ground (CG) networks, test the lightning jump algorithm configurations in other regions of the country, increase the number of thunderstorms within our thunderstorm database, and to pinpoint environments that could prove difficult for any lightning jump configuration. A total of 561 thunderstorms have been examined in the past year (409 non-severe, 152 severe) from four regions of the country (North Alabama, Washington D.C., High Plains of CO/KS, and Oklahoma). Results continue to indicate that the 2 lightning jump algorithm configuration holds the most promise in terms of prospective operational lightning jump algorithms, with a probability of detection (POD) at 81%, a false alarm rate (FAR) of 45%, a critical success index (CSI) of 49% and a Heidke Skill Score (HSS) of 0.66. The second best performing algorithm configuration was the Threshold 4 algorithm, which had a POD of 72%, FAR of 51%, a CSI of 41% and an HSS of 0.58. Because a more complex algorithm configuration shows the most promise in terms of prospective operational lightning jump algorithms, accurate thunderstorm cell tracking work must be undertaken to track lightning trends on an individual thunderstorm basis over time. While these numbers for the 2 configuration are impressive, the algorithm does have its weaknesses. Specifically, low-topped and tropical cyclone thunderstorm environments are present issues for the 2 lightning jump algorithm, because of the suppressed vertical depth impact on overall flash counts (i.e., a relative dearth in lightning). For example, in a sample of 120 thunderstorms from northern Alabama that contained 72 missed events by the 2 algorithm 36% of the misses were associated with these two environments (17 storms).

Schultz, Christopher J.↗

Estuarine hurricane wind can intensify surge-dominated extreme water level in shallow and converging coastal systems

Based on the projected increase in hurricane landfall frequency on the middle to lower US east coast, we examined the crucial role of the estuarine wind field in exacerbating coastal flooding. A regionally refined atmospheric and two high-resolution hydrology and ocean models are integrated to provide plausible and physically consistent ensembles of hurricane events and the associated flooding inside the Delaware Bay and River, a US mid-Atlantic estuary. Model results show that the hurricane propagation direction, estuarine geometry, remote surge from the open ocean, and direct nearshore upwind stress could magnify the flood magnitude. More specifically, inland-bound tracks that make landfall before reaching the mid-Atlantic coast produce a more significant surge within Delaware Bay than the shore-parallel tracks, where the estuarine wind direction plays the primary role in surge amplification. Ultimately, this study emphasized the need for integrated models to capture the nonlinear dynamics and interactions in flood hazard modeling.

54 ENVIRONMENTAL SCIENCES↗

The detection of dust storms over land and water with satellite visible and infrared measurements

The position of a large area of dust was successfully located over the Sahara Desert and off the west coast of Africa with infrared measurements from the Temperature Humidity Infrared Radiometer (THIR) and visible information from the Image Dissector Camera System (IDCS) on Nimbus 4 between 20 and 25 April 1970. Over land, near midday, the dust areas were associated with lower equivalent blackbody temperatures (TBB's) than in the surrounding areas due to the mixing of the dust with the cooler air just above the surface. Near midnight dust areas appeared to be located where the TBB's were higher than the surrounding regions. The TBB contrast was insufficient for dust detection over the ocean, but the contrast in the visible was great enough to track the movement of the dust for several days off the African west coast. Measurements from the THIR 6.5-7.2 micron channel were useful for detecting the presence of cirrus clouds which could have caused a misinterpretation of the 10.5-12.5 micron TBB's.

Shenk, W. E.↗

A Southern California Perspective of the April, 1998 Trans-Pacific Asian Dust Event

The Jet Propulsion Laboratory (JPL) coherent CO2 backscatter lidar has been in almost continuous operation since 1984 and has now accumulated a significant time-series database tracking the long-term and seasonal variability of backscatter from the atmospheric column above the Pasadena, Calif. locale. A particularly noteworthy episode observed by the lidar in 1998 was a particularly extreme instance of incursion by Asian-sourced dust during the closing days of April. Such events are not uncommon during the northern spring, when strong cold fronts and convection over the Asian interior deserts loft crustal material into the mid-troposphere whence it can be transported across the Pacific Ocean, occasionally reaching the continental US. However, the abnormal strength of the initiating storm in this case generated an atypically dense cloud of material which resulted in dramatically reduced visibility along the length of the Western Seaboard. These dust events are now recognized as a potentially significant, non-negligible radiative forcing influence. The progress of the April 1998 dust cloud eastward across the Pacific Ocean was initially observed in satellite imagery and transmitted to the broader atmospheric research community via electronic communications. The use of Internet technology in this way was effective in facilitating a rapid response correlative measurement exercise by numerous atmospheric observation stations throughout the western US and its success has resulted in the subsequent establishment of an ad hoc communications environment, data exchange medium, and mechanism for providing early-warning alert of other significant atmospheric phenomena in the future.

Tratt, David M.↗

The Impact of Microphysical Schemes on Hurricane Intensity and Track

During the past decade, both research and operational numerical weather prediction models [e.g. the Weather Research and Forecasting Model (WRF)] have started using more complex microphysical schemes originally developed for high-resolution cloud resolving models (CRMs) with 1-2 km or less horizontal resolutions. WRF is a next-generation meso-scale forecast model and assimilation system. It incorporates a modern software framework, advanced dynamics, numerics and data assimilation techniques, a multiple moveable nesting capability, and improved physical packages. WRF can be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. The current WRF includes several different microphysics options. At NASA Goddard, four different cloud microphysics options have been implemented into WRF. The performance of these schemes is compared to those of the other microphysics schemes available in WRF for an Atlantic hurricane case (Katrina). In addition, a brief review of previous modeling studies on the impact of microphysics schemes and processes on the intensity and track of hurricanes is presented and compared against the current Katrina study. In general, all of the studies show that microphysics schemes do not have a major impact on track forecasts but do have more of an effect on the simulated intensity. Also, nearly all of the previous studies found that simulated hurricanes had the strongest deepening or intensification when using only warm rain physics. This is because all of the simulated precipitating hydrometeors are large raindrops that quickly fall out near the eye-wall region, which would hydrostatically produce the lowest pressure. In addition, these studies suggested that intensities become unrealistically strong when evaporative cooling from cloud droplets and melting from ice particles are removed as this results in much weaker downdrafts in the simulated storms. However, there are many differences between the different modeling studies, which are identified and discussed.

Tao, Wei-Kuo↗

Tracking Aerosol Convection Interactions Experiment (TRACER) Field Campaign Report

Convective clouds serve a critical role in the Earth’s energy and water cycles through their transport of heat, moisture, momentum, and chemical species through the troposphere driving the global circulation (e.g., Hartmann et al. 1984, Del Genio et al. 2012, Su et al. 2014). On more local scales, convective clouds impact the atmospheric heating profile through diabatic heating effects, removal of water from the atmospheric column through precipitation, and conditioning of the local environment impacting further development of clouds (e.g., Sullivan and Voigt 2021). These critical roles underscore the importance of realistic representation of convective processes across scales of models from large-eddy simulation (LES), to convection-permitting models (CPM; e.g., Kendon et al. 2020, Marinescu et al. 2021), to numerical weather prediction (NWP) models used for operational weather forecasting, to Earth system models used to predict climate sensitivity (Sanderson et al. 2011, Sherwood et al. 2014, Tomassini et al. 2014, Zhao et al. 2016, Cronin et al. 2017). A key component of improving model representation of convective clouds is better quantification and parameterization of updraft microphysics and dynamics, including their interactions with the surrounding environment and storm organization (Bony et al. 2015, Hagos and Houze 2016, Donner et al. 2016, Morrison et al. 2020). Aerosol is an important environmental factor that could affect convective clouds and precipitation since cloud droplet and ice formation processes are initiated by it. Andrae et al. (2004) hypothesized that aerosols associated with increased biomass burning particles acting as cloud condensation nuclei (CCN) result in smaller and more monodisperse cloud droplets leading to suppression of warm rain formation, ultimately leading to more cloud water being lofted above the freezing level based on observations in the Amazon region. The subsequent increase in latent heat release increases the buoyancy of rising convective parcels invigorating the deep convection. This work was followed by a description of the theoretical basis for this “cold-phase invigoration” by Rosenfeld et al. (2008), who argued that it could have a significant effect for deep convective clouds with warm cloud-bases. Several modeling studies (e.g., Khain et al. 2005, 2009, van den Heever et al. 2006, Fan et al. 2007, 2009, 2012, Lee et al. 2008, Storer et al. 2010, Lebo et al. 2012, Storer and van den Heever 2013, Chen et al. 2020, Dagan et al. 2022) have investigated these aerosol-convection interactions and the environmental factors that influence their relative importance and magnitude. More recently, several studies have indicated that “warm-phase invigoration”, the enhancement of convection through condensational heating, also appears to play a role in enhancing both shallow cumuli (Seiki and Nakajima 2014, Saleeby et al 2015) and deeper tropical convection (Lebo and Seinfeld 2011, Khain et al. 2012, Sheffield et al 2015, Fan et al. 2018, Igel and van den Heever 2021), as well as Houston thunderstorms (Fan et al. 2007, 2020). However, still other studies have provided additional evidence of systematic biases in simulated convective outflow ice size distribution properties, which are consistent with a lack of poorly understood secondary ice production within convective updrafts (e.g., Fridlind et al. 2017). To help address these critical gaps in our understanding of cloud processes, aerosol processes and aerosol-cloud interactions, the Tracking Aerosol Convection Interactions Experiment was designed building upon efforts by the Aerosol, Cloud, Precipitation and Climate (ACPC) Initiative (http://acpcintiative.org/), a joint effort of the International Geosphere-Biosphere Programme (IGBP) and the World Climate Research Program (WCRP) that focused on resolving uncertainties in the interactions between aerosol and clouds towards better understanding the role that these interactions play in the climate system. The TRACER campaign was motivated by recommendations from a number of pilot studies undertaken by ACPC (van den Heever et al. 2017, Fridlind et al. 2019, Hu et al. 2019, Fan et al. 2020, Marinescu et al. 2021, Hernandez-Deckers et al. 2022) that pointed towards the southeastern Texas region as a locale where aerosol-convection interactions could be studied owing to the copious occurrence of isolated convection during the summer months accompanied by diverse and significant sources of aerosols from both anthropogenic and natural sources. The TRACER campaign began on 01 October 2021 and extended through 30 September 2022 with an intensive operational period (IOP) during June-September 2022. Three main sites (Table 1) were managed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility.

54 ENVIRONMENTAL SCIENCES↗

The Influence of Shallow Cloud Populations on Transitions to Deep Convection in the Amazon

Abstract In this study, a pair of convection-permitting (2-km grid spacing), month-long, wet-season Weather Research and Forecasting (WRF) Model simulations with and without the eddy-diffusivity mass-flux (EDMF) scheme are performed for a portion of the Green Ocean Amazon (GoAmazon) 2014/15 field campaign period. EDMF produces an ensemble of subgrid-scale convective plumes that evolve in response to the boundary layer meteorological conditions and can develop into shallow clouds. The objective of this study is to determine how different treatments of shallow cumulus clouds (i.e., with and without EDMF) impact the total cloud population and precipitation across the Amazonian rain forest, with emphasis on impacts on the likelihood of shallow-to-deep convection transitions. Results indicate that the large-scale synoptic conditions in the EDMF and control simulations are nearly identical; however, on the local scale their rainfall patterns diverge drastically and the biases decrease in EDMF. The EDMF scheme significantly increases the frequency of shallow clouds, but the frequencies of deep clouds are similar between the simulations. Deep convective clouds are tracked using a cloud-tracking algorithm to examine the impact of shallow cumulus on the surrounding ambient environment where deep convective clouds initiate. Results suggest that a rapid increase of low-level cloudiness acts to cool and moisten the low to midtroposphere during the day, favoring the transition to deep convection.

54 ENVIRONMENTAL SCIENCES↗

Overview of the Fourth Convection and Moisture Experiment (CAMEX-4)

The Convection And Moisture Experiment (CAMEX) is a series of field research investigations sponsored by the Earth Science Enterprise of the National Aeronautics and Space Administration (NASA). The fourth field campaign in the CAMEX series (CAMEX-4) was recently conducted during 16 August - 24 September 2001 using the Jacksonville Naval Air Station in Florida as the main base of operations. CAMEX-4 focused on the study of tropical cyclone (hurricane) development, tracking, intensification, and landfalling impacts using NASA-funded aircraft and surface remote sensing instrumentation. The results of this study will be used to address key issues pertinent to a larger NASA ESE study of the global water cycle as well as to provide synergistic contributions to the research goals of the Hurricane Research Division (HRD) of the National Oceanic and Atmospheric Administration (NOAA) and the Hurricanes At Landfall Initiative of the United States Weather Research Program. All CAMEX-4 aircraft missions were planned and jointly conducted with NOAA aircraft to insure comprehensive sampling. An overview of preliminary observations of Tropical Storms Chantal and Gabrielle as well as Hurricanes Erin and Humberto will be presented.

Hood, Robbie↗

The High Altitude MMIC Sounding Radiometer on the GLOBAL HAWK: From Technology Development to Science Discovery

This paper presents results from the High Altitude MMIC Sounding Radiometer (HAMSR) during three recent field campaigns on the Global Hawk Unmanned Ariel Vehicles (UAV), focusing on the enabling technology that led to unprecedented observations of significant weather phenomenon, such as thermodynamic evolution of the tropical cyclone core during rapid intensification and the high resolution three dimensional mapping of several atmospheric river events. HAMSR is a 25 channel cross-track scanning microwave sounder with channels near the 60 and 118 GHz oxygen lines and the 183 GHz water vapor line. HAMSR was originally designed and built at the Jet Propulsion Laboratory as a technology demonstrator in 1998. Subsequent to this, HAMSR participated in three NASA hurricane field campaigns, CAMEX-4, TCSP and NAMMA. Beginning in 2008, HAMSR was extensively upgraded to deploy on the NASA Global Hawk (GH) platform and serve as an asset to the NASA sub-orbital program. HAMSR has participated on the Global Hawk during the 2010 Genesis and Rapid Intensification (GRIP) campaign, the 2011 Winter Storms and Atmospheric Rivers (WISPAR) campaign and is currently participating in the NASA Ventures Hurricane and Severe Storm Sentinel (HS3) campaign (2011-2015).

NASA sub-orbital program↗

SAIL Storm Boards 2022-2023

“Storm Boards” are simple installations comprised of a horizontal white plastic board that is placed in situ on the surface of the snowpack with a 1 m vertical marker pole for identifying the board center and approximate new snow height. Storm boards allow newly fallen snow to accumulate on them while staying separated from moisture and energy exchange with the snowpack, thus creating a discrete sample of newly fallen snow depth & SWE (snow water equivalent) that can be measured to calculate the net moisture input of individual or multiple storm events to the seasonal snowpack. Samples are measured with a 2” diameter plastic tube that allows the observer to non destructively take a snow core of the newly deposited snow; this core is weighed with a small hand scale - then the mass of the sample is converted to SWE. Depth of the snow sample is obtained with a snow depth probe or from graduated marks on the plastic tube. 3 or more replicate samples are taken for each board measurement and averaged. Total snow height (HS) of the snowpack is measured with a snow depth probe for each site & timepoint to track snowpack accumulation/ablation.

54 ENVIRONMENTAL SCIENCES↗

The Illumination of Thunderclouds by Lightning: 1. The Extent and Altitude of Optical Lightning Sources

Abstract Optical space‐based lightning sensors including NOAA's Geostationary Lightning Mapper (GLM) detect lightning though its transient illumination of the surrounding clouds. What space‐based optical lightning sensors measure is influenced by the physical attributes of the light source, the location of the source within the cloud scene, and the spatial variations in cloud composition. We focus on the lightning channels that serve as optical sources for GLM groups and flashes in this first part of our thundercloud illumination study. We match Lightning Mapping Array (LMA) sources with GLM groups and flashes during two thunderstorms to examine channel segments that are active during optical emission. We find that in each storm, the LMA sources matched with GLM groups are small (median: 3 km) compared to GLM pixels (nominal: 8 km), and preferentially come from high altitudes in the cloud (>8–10 km). The detection advantage for high‐altitude sources permits GLM to resolve faint optical pulses near the cloud top that might be missed from lower altitudes. However, the most energetic groups can be detected from all altitudes, and the largest groups largely originate at low altitudes. The relationship between group energy and illuminated area depends on flash development within the cloud medium, and flash development into different cloud regions can be identified by tracking GLM metrics of cloud illumination over time.

58 GEOSCIENCES↗

Uncertainty in Synthetic Tropical Cyclone Hazard and Risk Estimates: Insights from RAFT, CHAZ, MIT, STORM, and CLIMADA

We synthesize five complementary tropical cyclone (TC) hazard frameworks—RAFT (physics-based machine learning), CHAZ and MIT (statistical–dynamical), STORM (fully statistical), and CLIMADA (observation-driven resampling)—to characterize uncertainty in wind-related TC metrics relevant to energy applications. All datasets and the IBTrACS observational record are harmonized to a common 6-hourly, 2.5° grid. We compare basin-wide and coastal properties using consistent definitions for TC frequency, mean and maximum intensity, 24-hour intensification, and 6-hour translation speed, and quantify agreement with Pearson r, RMSE, and Kling–Gupta efficiency (KGE) alongside resampling-based confidence intervals. CLIMADA is included for basin context but excluded from coastal skill scoring because it resamples historical IBTrACS; if supplied with projected future tracks from an external hazard model, CLIMADA can be used to simulate future TC scenarios. Results show robust, cross-model signals: (i) a corridor of activity from the tropical Atlantic through the Caribbean into the Bahamas and western subtropical Atlantic; (ii) a meridional dipole in 24-hour intensification (low-latitude strengthening, subtropical weakening); and (iii) a transition from slower tropical motion to faster midlatitude translation. Coastal winds (mean and maximum) consistently cluster from the eastern Gulf into the Bahamas–western Atlantic transition. The largest structural spread occurs in the amplitude and footprint of lifetime maximum intensity and, secondarily, in translation speed; intensification exhibits similar central behavior across frameworks with variability in extremes. Translation speed shows the most uniform coastal agreement. These findings provide a decision envelope for wind-focused risk screening and clarify where uncertainty should be carried forward; wind-only results represent a lower bound on total hazard, motivating integration of surge and rainfall modules and a companion, asset-level damage analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Airborne Radar Observations of Hurricane Georges during Landfall over the Dominican Republic

On 22 September 1998 hurricane Georges made landfall on the Dominican Republic (DR). Georges cost the DR at least 500 lives, made more than 155,000 people homeless and caused extensive damage to the country's main industries, tourism and agriculture. There was considerable wind damage, with wind gusts up to 58 m/s in Santa Domingo on the south coast, but most of the damage and deaths resulted from mudslides and the flooding of rivers. While this may have been the worst natural disaster to strike the DR, the sustained rapid storm movement saved the island from worse damage. Georges had previously affected several islands in the Lesser Antilles and Puerto Rico, but it had retained much of its circulation strength. Forty raingauge stations across the DR measured rainfall totals from Georges between 0.7 and 41 cm, the latter at the capital Santo Domingo, located on the south coast. At Herrera the maximum 1 h rainfall rate was 72 mm/h. It is suspected that much higher rain rates occurred in DR's mountainous interior. Before landfall the eye was clearly evident in satellite imagery. When the eye moved over southeastern DR, it filled rapidly, and the cloud top height decreased in all storm sectors except in the southern inflow sector, where a long-lived MCS, with a diameter larger than that of the eyewall, slowly became enwrapped in the hurricane circulation. The eye closure was most rapid between 16-18 UTC, when the eyewall circulation felt the mountainous terrain of the Cordillera Central, which rises up to 3,093 m. The estimated central pressure increased from 962 hPa at 15 UTC to 986 hPa at 03Z on 23 Sept, and the maximum sustained surface wind speed decreased from 54 to 36 in s-1 during the same period. The island of Hispaniola has a cross-track width of about 250 km, much wider than the diameter of the eyewall anvil (about 100 km before landfall). So the event can truly be considered to be a landfalling case, even though Georges recovered after crossing Hispaniola, albeit never to the same strength. This talk will summarize satellite and ground observations of Georges, as it passed the DR, and it will focus on EDOP data. In particular, we will try to estimate the rainfall rate over the mountainous terrain of the DR. And we will use detailed sounding data to explain the presence and characteristics of the massive MCS to the south, as well as the upper-level updrafts apparent over this MCS and over the mountains of the DR.

Geerts, B.↗

Connecting Large‐Scale Meteorological Patterns to Extratropical Cyclones in CMIP6 Climate Models Using Self‐Organizing Maps

Abstract Extratropical cyclones (ETCs) are responsible for the majority of cool‐season extreme events in the northeastern United States (NEUS), often leading to high‐impact weather conditions that can have wide‐ranging socioeconomic impacts. Evaluating the ability of climate models to adequately simulate ETC dynamics is essential for improving model performance and increasing confidence in future projections used by stakeholders and policymakers. ETCs are traditionally studied using techniques such as case studies and synoptic typing, however, these approaches can be time‐consuming, require subjective analysis, and do not necessarily identify the coincident large‐scale meteorological patterns (LSMPs). Here, we apply self‐organizing maps (SOMs) as an automated machine‐learning approach to characterize the LSMPs and associated frequency and intensity of discrete ETC events over NEUS. The dominant patterns of geopotential height variability are identified through SOM analysis of five reanalysis products during the last four decades. ETC events are tracked using TempestExtremes and are integrated with SOMs to classify the accumulated cyclone activity (ACA) associated with each pattern. We then evaluate the skill of CMIP6 historical experiments in simulating the LSMPs and ETC events identified in the SOM. Our results identify a robust bias toward more zonal patterns, with models struggling to reproduce the more amplified patterns typically associated with the highest cyclone activity. While model resolution has some impact on simulation credibility, model configuration appears to be more important in LSMP representation. The vast majority of CMIP6 models produce too few ETCs, although model errors are distributed around historical reanalyses when ACA is normalized by storm frequency.

54 ENVIRONMENTAL SCIENCES↗