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At least 91 records · Page 5

Assimilation of Satellite-Derived Soil Moisture for Improved Forecasts of the Great Plains Low-Level Jet

In the context of forecasting societally impactful Great Plains low-level jets (GPLLJs), the potential added value of satellite soil moisture (SM) data assimilation (DA) is high. GPLLJs are both sensitive to regional soil moisture gradients and frequent drivers of severe weather, including mesoscale convective systems. An untested hypothesis is that SM DA is more effective in forecasts of weakly synoptically forced, or uncoupled GPLLJs, than in forecasts of cyclone-induced coupled GPLLJs. Using the NASA Unified Weather Research and Forecasting (NU-WRF) Model, 75 GPLLJs are simulated at 9-km resolution both with and without NASA Soil Moisture Active Passive SM DA. Differences in modeled SM, surface sensible (SH) and latent heat (LH) fluxes, 2-m temperature (T2), 2-m humidity (Q2), PBL height (PBLH), and 850-hPa wind speed (W850) are quantified for individual jets and jet-type event subsets over the south-central Great Plains, as well as separately for each GPLLJ sector (entrance, core, and exit). At the GPLLJ core, DA-related changes of up to 5.4 kg m–2 in SM can result in T2, Q2, LH, SH, PBLH, and W850 differences of 0.68°C, 0.71 g kg –2 , 59.9 W m –2 , 52.4 W m –2 , 240 m, and 4 m s –1 , respectively. W850 differences focus along the jet axis and tend to increase from south to north. Further, jet-type differences are most evident at the GPLLJ exit where DA increases and decreases W850 in uncoupled and coupled GPLLJs, respectively. Data assimilation marginally reduces negative wind speed bias for all jets, but the correction is greater for uncoupled GPLLJs, as hypothesized.

54 ENVIRONMENTAL SCIENCES↗

Revisiting the Definition of Rapid Intensification of Tropical Cyclones by Clustering the Initial Intensity and Inner‐Core Size

Abstract Rapid intensification (RI) of tropical cyclones (TCs) provides a great challenge in operational forecasting and contributes significantly to the development of major TCs. RI is commonly defined as an increase in the maximum sustained surface wind speed of at least a certain threshold within 24 hr. The most widely used threshold is 30 kt (15.4 m/s), which was determined statistically. Here we propose a new definition for RI by objectively clustering TCs using the intensification rate, initial intensity, and radius of the maximum wind speed (RMW). A group of 770 samples is separated at a threshold of 45 kt (23.2 m/s). The threshold is 40 kt (20.6 m/s) for the western North Atlantic, where TC size measurements are more reliable. Monte Carlo experiments demonstrate that the proposed threshold is robust even considering the uncertainty in RMW of as high as 30 km. We show that, when a TC undergoes RI, its maximum wind speed is approximately 60 ± 15 kt (30.9 ± 7.7 m/s) and the RMW is 45 ± 20 km. The new threshold outperforms the conventional threshold of 30 kt/24 hr in describing the bimodal distribution of lifetime maximum intensity and explaining the annual count of Category 5 TCs. This new definition provides a more physically based threshold and describes a more reliable representation of extreme events. Although more comparisons are needed for operational application, it is likely to be desirable for case‐based process studies and could provide a more valuable metric for TC intensification classification and research.

Li, Yi↗

The Vertical Error Characteristics of GOES-derived Winds: Description and Impact on Numerical Weather Prediction

Errors in the height assignment of some satellite-derived winds exist because the satellites sense radiation emitted from a finite layer of the atmosphere rather than a specific level. Potential problems in data assimilation may arise because the motion of a measured layer is often represented by a single-level value. In this research, cloud and water vapor motion winds that are derived from the Geostationary Operational Environmental Satellites (GOES winds) are compared to collocated rawinsonde observations (RAOBs). An important aspect of this work is that in addition to comparisons at each assigned height, the GOES winds are compared to the entire profile of the collocated RAOB data to determine the vertical error characteristics of the GOES winds. The impact of these results on numerical weather prediction is then investigated. The comparisons at individual vector height assignments indicate that the error of the GOES winds range from approx. 3 to 10 m/s and generally increase with height. However, if taken as a percentage of the total wind speed, accuracy is better at upper levels. As expected, comparisons with the entire profile of the collocated RAOBs indicate that clear-air water vapor winds represent deeper layers than do either infrared or water vapor cloud-tracked winds. This is because in cloud-free regions the signal from water vapor features may result from emittance over a thicker layer. To further investigate characteristics of the clear-air water vapor winds, they are stratified into two categories that are dependent on the depth of the layer represented by the vector. It is found that if the vertical gradient of moisture is smooth and uniform from near the height assignment upwards, the clear-air water vapor wind tends to represent a relatively deep layer. The information from the comparisons is then used in numerical model simulations of two separate events to determine the forecast impacts. Four simulations are performed for each case: 1) A control simulation that assimilates no satellite wind data, 2) assimilation of all GOES winds according to their assigned single level height, 3) assimilation of all GOES winds spread over multiple levels, and 4) assimilation of all GOES winds spread over multiple levels, but with variations in the vertical influence of clear-air water vapor winds based on the moisture profile in the model. In the first case, a strong mid-latitude cyclone is present and the use of the satellite data results in improved storm tracks during the initial approx. 36 h forecast period. This is because the satellite data improves the analysis of the environment into which the storm progresses. Statistics for mean wind vector and height differences show that, with the exception of the height field at later times in the first case, the use of GOES winds improves the simulation with time. The simulation results suggest that it is beneficial to spread the GOES wind information over multiple levels, particularly when the moisture profile is used to define the vertical influence.

Rao, P. Anil↗

Clusters of Regional Precipitation Seasonality Change in the Community Earth System Model, Version 2

Abstract The likely changes to precipitation seasonality with warming are both impactful and not well understood. This work aims to describe areas that experience similar changes to seasonal precipitation irrespective of the original underlying precipitation seasonality. We train a self-organizing map on the difference between the seasonal cycle of precipitation in the past and in a high-warming future climate as represented by the Community Earth System Model, version 2, to create regions with similar changes in precipitation seasonality. This method is applied separately over land and ocean surfaces because of the differing processes leading to precipitation over each. This method indicates that future changes in seasonal precipitation are most varied in the tropics because of a southward shift in the intertropical convergence zone. The seasonal shifts found over midlatitude oceans indicate a poleward shift in atmospheric river activity. We find a correspondence between certain land-based precipitation changes and Köppen climate classification. The seasonality of large-scale and convective precipitation is examined for each region. The relationship between the seasonal changes to precipitation and associated atmospheric processes is discussed. These processes include atmospheric rivers, the intertropical convergence zone, tropical cyclones, and monsoons.

54 ENVIRONMENTAL SCIENCES↗

Disentangling the long-term effects of disturbance on soil biogeochemistry in a wet tropical forest ecosystem

Climate change is increasing the intensity of severe tropical storms and cyclones (also referred to as hurricanes or typhoons), with major implications for tropical forest structure and function. These changes in disturbance regime are likely to play an important role in regulating ecosystem carbon (C) and nutrient dynamics in tropical and subtropical forests. Canopy opening and debris deposition resulting from severe storms have complex and interacting effects on ecosystem biogeochemistry. Disentangling these complex effects will be critical to better understand the long-term implications of climate change on ecosystem C and nutrient dynamics. In this paper, we used a well-replicated, long-term (10 years) canopy and debris manipulation experiment in a wet tropical forest to determine the separate and combined effects of canopy opening and debris deposition on soil C and nutrients throughout the soil profile (1 m). Debris deposition alone resulted in higher soil C and N concentrations, both at the surface (0–10 cm) and at depth (50–80 cm). Concentrations of NaOH-organic P also increased significantly in the debris deposition only treatment (20–90 cm depth), as did NaOH-total P (20–50 cm depth). Canopy opening, both with and without debris deposition, significantly increased NaOH-inorganic P concentrations from 70 to 90 cm depth. Soil iron concentrations were a strong predictor of both C and P patterns throughout the soil profile. Our results demonstrate that both surface- and subsoils have the potential to significantly increase C and nutrient storage a decade after the sudden deposition of disturbance-related organic debris. Our results also show that these effects may be partially offset by rapid decomposition and decreases in litterfall associated with canopy opening. Finally, the significant effects of debris deposition on soil C and nutrient concentrations at depth (>50 cm), suggest that deep soils are more dynamic than previously believed, and can serve as sinks of C and nutrients derived from disturbance-induced pulses of organic matter inputs.

54 ENVIRONMENTAL SCIENCES↗

Prediction of Tropical Cyclone Genesis from Mesoscale Convective Systems using Machine Learning

Tropical cyclone (TC) genesis is a problem of great significance in climate and weather research. Although various environmental conditions necessary for TC genesis have been recognized for a long time, prediction of TC genesis remains a challenge due to complex and stochastic processes involved during TC genesis. Different from traditional statistical and dynamical modeling of TC genesis, in this research, a machine learning framework is developed to determine whether a mesoscale convective system (MCS) would evolve into a tropical cyclone. The machine learning models 1) are built upon a number of essential environmental predictors associated with MCS/TC, 2) predict whether MCSs can become TCs at different lead times, 3) provide information about the relative importance of each predictor, which can be conducive to discovering new aspects of TC genesis. The results indicate that the machine learning classifier, AdaBoost, is able to achieve a 97.2% F1-score accuracy in predicting TC genesis over the entire tropics at a 6-hour lead time using a comprehensive set of environmental predictors. A robust performance can still be attained when the lead time is extended to 12 hours, 24 hours, and 48 hours, and when this machine learning classifier is separately applied to the North Atlantic Ocean and the Western North Pacific Ocean. In contrast, the conventional approach based on genesis potential index can only have no more than 80% F1-score accuracy. Moreover, the machine learning classifier suggests that the low-level vorticity and genesis potential index are the most important predictors to TC genesis, which is consistent with previous discoveries.

54 ENVIRONMENTAL SCIENCES↗

Covariance analyses of satellite-derived mesoscale wind fields

Statistical structure functions have been computed independently for nine satellite-derived mesoscale wind fields that were obtained on two different days. Small cumulus clouds were tracked at 5 min intervals, but since these clouds occurred primarily in the warm sectors of midlatitude cyclones the results cannot be considered representative of the circulations within cyclones in general. The field structure varied considerably with time and was especially affected if mesoscale features were observed. The wind fields on the 2 days studied were highly anisotropic with large gradients in structure occurring approximately normal to the mean flow. Structure function calculations for the combined set of satellite winds were used to estimate random error present in the fields. It is concluded for these data that the random error in vector winds derived from cumulus cloud tracking using high-frequency satellite data is less than 1.75 m/s. Spatial correlation functions were also computed for the nine data sets. Normalized correlation functions were considerably different for u and v components and decreased rapidly as data point separation increased for both components. The correlation functions for transverse and longitudinal components decreased less rapidly as data point separation increased.

Maddox, R. A.↗

Scatterometer Observes Extratropical Transition of Pacific Typhoons

From September 15 to 25, 1996, NASA's scatterometer (NSCAT) monitored the evolution of twin typhoons, Violet and Tom, as they moved north from the western tropical Pacific, acquiring features of mid-latitude storms. The typhoons developed frontal structures, increased asymmetry, and dry air was introduced into their cores. Violet hit Japan, causing death and destruction (Figure 1), and Tom merged with a mid-latitude trough and evolved into a large extratropical storm with gale-force winds (Figure 2). We understand relatively little about the extratropical transition of tropical cyclones because of the complex thermodynamics involved [e.g., Sinclair, 1993], but we do know that the mid-latitude storms resulting from tropical cyclones usually generate strong winds and heavy precipitation. Since the transition usually occurs over the ocean, few measurements have been made. The transition is a fascinating science problem, but it also has important economic consequences. The transition occurs over the busiest trans-ocean shipping lanes, and when the resulting storms hit land, they usually devastate populated areas. NSCAT was successfully launched into a near-polar, sun-synchronous orbit on the Japanese Advanced Earth Observing Satellite (ADEOS) in August 1996 from Tanegashima Space Center in Japan. NSCAT's six antennas send microwave pulses at a frequency of 14 GHz to the Earth's surface and measure the backscatter. The antennas scan two 600-km bands of the ocean, which are separated by a 330-km data gap. From NSCAT observations, surface wind vectors can be derived at 25-km spatial resolution, covering 77% of the ice-free ocean in one day and 97% of the ocean in two days, under both clear and cloudy conditions.

Liu, W. Timothy↗

A variational assimilation method for satellite and conventional data: Development of basic model for diagnosis of cyclone systems

A three-dimensional diagnostic model for the assimilation of satellite and conventional meteorological data is developed with the variational method of undetermined multipliers. Gridded fields of data from different type, quality, location, and measurement source are weighted according to measurement accuracy and merged using least squares criteria so that the two nonlinear horizontal momentum equations, the hydrostatic equation, and an integrated continuity equation are satisfied. The model is used to compare multivariate variational objective analyses with and without satellite data with initial analyses and the observations through criteria that were determined by the dynamical constraints, the observations, and pattern recognition. It is also shown that the diagnoses of local tendencies of the horizontal velocity components are in good comparison with the observed patterns and tendencies calculated with unadjusted data. In addition, it is found that the day-night difference in TOVS biases are statistically different (95% confidence) at most levels. Also developed is a hybrid nonlinear sigma vertical coordinate that eliminates hydrostatic truncation error in the middle and upper troposphere and reduces truncation error in the lower troposphere. Finally, it is found that the technique used to grid the initial data causes boundary effects to intrude into the interior of the analysis a distance equal to the average separation between observations.

Achtemeier, G. L.↗

Simulation of the Impact of New Ocean Surface Wind Measurements on H*Wind Analyses

The H*Wind analysis, a product of the Hurricane Research Division of NOAA's Atlantic Oceanographic and Meteorological Laboratory, brings together wind measurements from a variety of observation platforms into an objective analysis of the distribution of surface wind speeds in a tropical cyclone. This product is designed to improve understanding of the extent and strength of the wind field, and to improve the assessment of hurricane intensity. See http://www.aoml.noaa.gov/hrd/data sub/wind.html. The Hurricane Imaging Radiometer (HIRAD) is a new passive microwave remote sensor for hurricane observations that is currently under development by NASA Marshall Space Flight Center, NOAA Hurricane Research Division, the University of Central Florida and the University of Michigan. HIRAD is being designed to enhance the current real-time airborne ocean surface winds observation capabilities of NOAA and USAF Weather Squadron hurricane hunter aircraft using the operational airbome Stepped Frequency Microwave Radiometer (SFMR). Unlike SFMR, which measures wind speed and rain rate along the ground track directly beneath the aircraft, HIRAD will provide images of the surface wind and rain field over a wide swath (approximately 3 x the aircraft altitude, or approximately 2 km from space). The instrument is described in a separate paper presented at this conference. The present paper describes a set of Observing System Simulation Experiments (OSSEs) in which measurements from the new instrument as well as those from existing instruments (air, surface, and space-based) are simulated from the output of a numerical model from the University of Miami, and those results are used to construct H*Wind analyses. Evaluations will be presented on the relative impact of HIRAD and other instruments on H*Wind analyses, including the use of HIRAD from 2 aircraft altitudes and from a space-based platform.

Miller, Timothy↗

A High-Resolution Merged Wind Dataset for DYNAMO: Progress and Future Plans

In order to support research on optimal data assimilation methods for the Cyclone Global Navigation Satellite System (CYGNSS), launching in 2016, work has been ongoing to produce a high‐resolution merged wind dataset for the Dynamics of the Madden Julian Oscillation (DYNAMO) field campaign, which took place during late 2011/early 2012. The winds are produced by assimilating DYNAMO observations into the Weather Research and Forecasting (WRF) three‐dimensional variational (3DVAR) system. Data sources from the DYNAMO campaign include the upper‐air sounding network, radial velocities from the radar network, vector winds from the Advanced Scatterometer (ASCAT) and Oceansat‐2 Scatterometer (OSCAT) satellite instruments, the NOAA High Resolution Doppler Lidar (HRDL), and several others. In order the prep them for 3DVAR, significant additional quality control work is being done for the currently available TOGA and SMART‐R radar datasets, including automatically dealiasing radial velocities and correcting for intermittent TOGA antenna azimuth angle errors. The assimilated winds are being made available as model output fields from WRF on two separate grids with different horizontal resolutions ‐ a 3‐km grid focusing on the main DYNAMO quadrilateral (i.e., Gan Island, the R/V Revelle, the R/V Mirai, and Diego Garcia), and a 1‐km grid focusing on the Revelle. The wind dataset is focused on three separate approximately 2‐week periods during the Madden Julian Oscillation (MJO) onsets that occurred in October, November, and December 2011. Work is ongoing to convert the 10‐m surface winds from these model fields to simulated CYGNSS observations using the CYGNSS End‐To‐End Simulator (E2ES), and these simulated satellite observations are being compared to radar observations of DYNAMO precipitation systems to document the anticipated ability of CYGNSS to provide information on the relationships between surface winds and oceanic precipitation at the mesoscale level. This research will improve our understanding of the future utility of CYGNSS for documenting key MJO processes.

Lang, Timothy J.↗

Weather Avoidance Guidelines for NASA Global Hawk High-Altitude Unmanned Aircraft Systems (UAS)

The current Global Hawk flight rules would probably not have been effective in the single event of greatest concern (the Emily encounter). The cloud top had not reached 50,000 ft until minutes before the encounter. The TOT and lightning data would not have been available until near the overflight time since this was a rapidly growing cell. This case would have required a last‐minute diversion when lightning became frequent. Avoiding such a cell probably requires continual monitoring of the forward camera and storm scope, whether or not cloud tops have been exceeding specific limits. However, the current overflight rules as strictly interpreted would have prohibited significant fractions of the successful Global Hawk overpasses of Karl and Matthew that proved not to be hazardous. Many other high altitude aircraft (ER‐2 and Global Hawk) flights in NASA tropical cyclone field programs have successfully overflown deep convective clouds without incident.The convective cell that caused serious concern about the safety of the ER‐2 in Emily was especially strong for a tropical cyclone environment, probably as strong or stronger than any that was overflown by the ER‐2 in 20 previous flights over tropical cyclones. Specifically, what made that cell a safety concern was the magnitude of the vertical velocity of the updraft, at least 20 m/s (4000 ft/minute) at the time the ER‐2 overflew it. Such a strong updraft can generate strong gravity waves at and above the tropopause, posing a potential danger to aircraft far above the maximum altitude of the updraft itself or its associated cloud top. Indeed, the ER‐2 was probably at least 9000 ft above that cloud top. Cloud‐top height, by itself, is not an especially good indicator of the intensity of convection and the likelihood of turbulence. Nor is overflying high cloud tops (i.e. > 50,000 ft) of particular concern unless there is other evidence of very strong convective updrafts beneath those tops in the path of the aircraft. center dot Lightning, especially lightning with a high flash rate, is well correlated with convective intensity. Lightning with a minimal flash rate (say 1‐3 flashes per minute) is indicative of updraft speeds of about 10 m/s in the mixed phase region where charge is being separated, generally at altitudes about 20‐25 kft in a hurricane. That is still stronger than typical updrafts (more like 5 m/s). An unresolved issue is whether there is a high and instantaneous correlation between vertical velocity in the middle troposphere (necessary for lightning generation) and near cloud top (more direct concern for overflights).

Cecil, Daniel J.↗

Numerical investigation of vortex tubes with extended vortex chambers

Ranque–Hilsch vortex tubes are often utilized to produce cooling when a compressed air source is readily available. In comparison with traditional cooling technologies, vortex-tube devices are much simpler, since they do not have moving parts. However, their thermal efficiencies are also lower, so they are used primarily for industrial spot cooling. Several options to modify and improve vortex tube performance exist. While a lot of previous research efforts addressed optimization of the inlet and outlet components, the main tube variations have not been thoroughly explored beyond simple tapered tubes. In this paper we numerically investigate augmenting vortex tubes with cyclonic-type extensions of the vortex chambers. The computational fluid dynamics software STAR-CCM+ was utilized to simulate a typical counter-flow vortex tube operating with air. The numerical approach was validated via comparison to experimental studies available in the literature. A reasonably efficient high-capacity vortex tube design was parametrically analyzed. This setup and its several modifications were numerically modeled under selected external conditions. The configuration with an intermediate-size vortex chamber extension demonstrated the highest performance among the studied setups. This variant of the vortex tube was also predicted to perform better than the original system by about 15% in a range of cold-flow fractions.

08 HYDROGEN↗

Relating Lightning Flash Size and Energy to Tropical Cyclone Structure and Intensity Change

The number and location of lightning flashes within tropical cyclones (TCs) has proven to be a useful predictor of TC intensity change. Generally, a large number of lightning flashes located within the radius of maximum wind indicates a convective structure favorable for intensification. However, weakening TCs can also exhibit numerous lightning flashes, and rapid intensification can occur in the absence of inner-core lightning. It is thus difficult to interpret what the presence or absence of inner-core lightning might mean for a TC’s future evolution. The Geostationary Lightning Mapper (GLM) offers a new capability to observe not only the number and location of lightning flashes, but also the size and optical energy of those flashes. This presentation describes the application of these new metrics to further understand the relationship between lightning and TC structural and intensity evolution. Evidence is presented that flash size and optical energy reveal more about the convective and kinematic structures relevant to intensity change than an analysis of lightning flash count and location alone. We hypothesize that large, energetic lightning flashes are generated when the TC secondary circulation is strongest, an environment which favors increased generation of ice particles in the eyewall updraft and larger charge separation through outward advection of ice in the upper-level outflow. Conversely, smaller, lower-energy lightning flashes tend to occur in more localized turbulent updrafts, which can be forced by a variety of processes – some of which act to weaken the storm. These hypotheses are supported by numerical simulations of TC convection.

Patrick Duran↗

Production of Medically Important Radionuclides 52 Mn and 90 Nb

Over the final reporting period of this project, we at MGH finalized our effort on Project 2: Production and Characterization of 90 Nb which, as per our previous report led us to an interesting application of mass spectrometry in radiometal chemistry. Overall, our research has developed parameters and procedures for delivering high 90 Nb for preclinical and translational applications by initializing the cyclotron targetry and separation chemistry for delivering 90 Nb in a chemical form suitable for subsequent development of 90 Nb-based PET radiotracers, and most recently we have published on the mass spectrometry applications described in the present report. We have been working with MSKCC (PI Jason Lewis) on the 90 Nb methodology and have had input from UAB (PI Suzy Lapi). An in-person meeting was held during the upcoming funding period with 2 PIs who are co-organizing the Radiochemistry Symposium (Lapi and Vasdev) and Program Director Dr. Ethan Balkin, during the ACS National Meeting in March 2018, and 2 PIs (Lewis and Vasdev) co presented in at the World Federation of Nuclear Medicine and Biology at a symposium sponsored by the Australian Nuclear Sciences and Technology Organisation, where they are both collaborating, in Melbourne, Australia in April 2018. Future projects and collaborations are under discussion with the Lapi lab to focus on new applications of 76 Br chemistry, and a new collaboration has already resulted with the Lewis lab on 18 F radiochemistry that employ iodonium ylide based precursors developed in the Vasdev lab, for clinical production of [ 18 F]MFBG. It is noteworthy that the PI has now relocated to the University of Toronto and has 2 cyclotrons (IBA Cyclone and Scanditronix MC-17) that will also be used to explore new 11 C-radiochemistry including [ 11 C]CO.

07 ISOTOPE AND RADIATION SOURCES↗

Investigating Lightning Behavior in Rapidly Intensifying Atlantic Tropical Cyclones

Lightning is a useful tool in forecasting and understanding the behavior of tropical cyclones (TCs). The Geostationary Lightning Mapper (GLM) aboard the GOES-16 geostationary satellite measures a multitude of lightning parameters, such as flash extent density (FED), average flash area (AFA) and optical energy for most of North America, South America, and the Pacific Ocean. GLM has brought about an era of spaceborne measurements to track storms many miles off the coasts and has allowed for the study of lightning throughout a TCs entire lifespan. FED has been found to be indicative of strength and intensification in TCs, but optical energy is a relatively new parameter that has not been studied intensively. This presentation analyzes the relationship between rapid intensification (RI) and GLM optical energy, AFA, and FED in Hurricanes Florence (2018) and Laura (2020). Using a 24-hour time interval in which each storm underwent RI, optical energy was analyzed from the innermost 100 kilometers of the eye and then was averaged for each minute to determine if there was a relationship between optical energy, AFA, FED, and intensification. Optical energy, FED, and AFA spiked just before RI began and then fell as the storms intensified more rapidly. These parameters increased again as intensification slowed slightly, while the optical energy peaks much lower in Hurricane Laura and much higher in Hurricane Florence. While these results show a pattern in lightning in these two TCs, further investigation of parameters like updraft strength and charge separation from microwave imagery during these secondary peaks in which optical energy behaves differently than the first peak may provide further insight as to the behavior of these TCs during RI.

Kiahna Mollette↗

Changes in Lightning Flash Size and Energy during the Intensification of Hurricanes Florence (2018) and Laura (2020)

Lightning is a useful tool in forecasting and understanding the behavior of tropical cyclones (TCs). The Geostationary Lightning Mapper (GLM) aboard the GOES-16 geostationary satellite measures a multitude of lightning parameters, such as flash extent density (FED), average flash area (AFA) and optical energy for most of North America, South America, and the Pacific Ocean. GLM has brought about an era of spaceborne measurements to track storms many miles off the coasts and has allowed for the study of lightning throughout a TCs entire lifespan. FED has been found to be indicative of strength and intensification in TCs, but optical energy is a relatively new parameter that has not been studied intensively. This presentation analyzes the relationship between rapid intensification (RI) and GLM optical energy, AFA, and FED in Hurricanes Florence (2018) and Laura (2020). Using a 24-hour time interval in which each storm underwent RI, optical energy was analyzed from the innermost 100 kilometers of the eye and then was averaged for each minute to determine if there was a relationship between optical energy, AFA, FED, and intensification. Optical energy, FED, and AFA spiked just before RI began and then fell as the storms intensified more rapidly. These parameters increased again as intensification slowed slightly, while the optical energy peaks much lower in Hurricane Laura and much higher in Hurricane Florence. While these results show a pattern in lightning in these two TCs, further investigation of parameters like updraft strength and charge separation from microwave imagery during these secondary peaks in which optical energy behaves differently than the first peak may provide further insight as to the behavior of these TCs during RI.

Kiahna Mollette↗

Episodes of Cross-Polar Transport in the Arctic Troposphere During July 2008 as Seen from Models, Satellite, and Aircraft Observations

During the POLARCAT summer campaign in 2008, two episodes (2 5 July and 7 10 July 2008) occurred where low-pressure systems traveled from Siberia across the Arctic Ocean towards the North Pole. The two cyclones had extensive smoke plumes from Siberian forest fires and anthropogenic sources in East Asia embedded in their associated air masses, creating an excellent opportunity to use satellite and aircraft observations to validate the performance of atmospheric transport models in the Arctic, which is a challenging model domain due to numerical and other complications. Here we compare transport simulations of carbon monoxide (CO) from the Lagrangian transport model FLEXPART and the Eulerian chemical transport model TOMCAT with retrievals of total column CO from the IASI passive infrared sensor onboard the MetOp-A satellite. The main aspect of the comparison is how realistic horizontal and vertical structures are represented in the model simulations. Analysis of CALIPSO lidar curtains and in situ aircraft measurements provide further independent reference points to assess how reliable the model simulations are and what the main limitations are. The horizontal structure of mid-latitude pollution plumes agrees well between the IASI total column CO and the model simulations. However, finer-scale structures are too quickly diffused in the Eulerian model. Applying the IASI averaging kernels to the model data is essential for a meaningful comparison. Using aircraft data as a reference suggests that the satellite data are biased high, while TOMCAT is biased low. FLEXPART fits the aircraft data rather well, but due to added background concentrations the simulation is not independent from observations. The multi-data, multi-model approach allows separating the influences of meteorological fields, model realisation, and grid type on the plume structure. In addition to the very good agreement between simulated and observed total column CO fields, the results also highlight the difficulty to identify a data set that most realistically represents the actual pollution state of the Arctic atmosphere.

Sodemann, H.↗