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NASA NTRS2019

Cloud Influence on ERA5 and AMPS Surface Downwelling Longwave Radiation Biases in West Antarctica

The surface downwelling longwave radiation component (LW[down arrow]) is crucial for the determination of the surface energy budget and has significant implications for the resilience of ice surfaces in the polar regions. Accurate model evaluation of this radiation component requires knowledge about the phase, vertical distribution, and associated temperature of water in the atmosphere, all of which control the LW[down arrow] signal measured at the surface. In this study, we examine the LW[down arrow] model errors found in the Antarctic Mesoscale Prediction System (AMPS) operational forecast model and the ERA5 reanalysis model relative to observations from the AWARE campaign at McMurdo Station and the West Antarctic Ice Sheet (WAIS) Divide. The errors are calculated separately for observed clear-sky conditions, ice-cloud occurrences, and liquid-bearing cloud layer (LBCL) occurrences. The analysis results show a tendency in both models at each site to underestimate the LW[down arrow] during clear sky conditions, high error variability (standard deviations > 20 W/m[exp2]) during any type of cloud occurrence, and negative LW biases when LBCLs are observed (bias magnitudes > 15 W/m[exp2] in tenuous LBCL cases; > 43 W/m[exp2] in optically thick/opaque LBCLs instances). We suggest that a generally dry and liquid-deficient atmosphere responsible for the identified LW[down arrow] biases in both models is the result of excessive ice formation and growth, which could stem from model initial and lateral boundary conditions, microphysics scheme, aerosol representation, and/or limited vertical resolution.

Israel Silber↗

NASA NTRS2019

The RELAMPAGO Lightning Mapping Array: Preliminary Scientific Results and Application to GLM Calibration and Validation

During November 2018 through April 2019, an 11-station NASA lightning mapping array (LMA) was installed in the Cordoba region of Argentina, in support of GOES-16 Geostationary Lightning Mapper (GLM) calibration and validation, as well as the Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign. This region of Argentina is well known for frequent, intense thunderstorms and severe weather. The LMA was monitored remotely via the Internet throughout its deployment, but due to bandwidth limitations no real-time data were available. Custom GOES-16 imagery provided by NASA SPoRT assisted with monitoring of thunderstorm cases. Occasional site visits were done to obtain data disks, perform routine maintenance, and troubleshoot problems. During the deployment the network captured lightning in a variety of storm modes, including ordinary and severe multicells, supercells, and mesoscale convective systems. Many examples of normal-polarity thunderstorms, as well as a few examples of anomalously charged thunderstorms, were observed. Long (100+ km) horizontally stratified lightning flashes, as well as lightning in overshooting tops, also were frequently observed. Supporting research radar observations were available through January 2019, with operational radar coverage available after that time. Some cases featured supporting ABI meso scanning. This presentation will report on the LMA deployment in context with the RELAMPAGO field campaign, show results from some representative case studies, and will provide initial comparisons to GLM observations.

Lang, Timothy J.↗

NASA NTRS2020

A New Look at the Environmental Conditions Favorable to Secondary Ice Production

This study attempts a new identification of mechanisms of secondary ice production (SIP) based on the observation of small faceted ice crystals (hexagonal plates or columns) with typical sizes smaller than 100µm. Due to their young age, such small ice crystals can be used as tracers for identifying the conditions for SIP. Observations reported here were conducted in oceanic tropical mesoscale convective systems (MCSs) and midlatitude frontal clouds in the temperature range from 0 to −15◦C and heavily seeded by aged ice particles. It was found that in both MCSs and frontal clouds, SIP was observed right above the melting layer and extended to higher altitudes with colder temperatures. The roles of six possible mechanisms to generate the SIP particles are assessed using additional observations. In most observed SIP cases, small secondary ice particles spatially correlated with liquid-phase, vertical updrafts and aged rimed ice particles. However, in many cases, neither graupel nor liquid drops were observed in the SIP regions, and therefore, the conditions for an active Hallett–Mossop process were not met. In many cases, large concentrations of small pristine ice particles were observed right above the melting layer, starting at temperatures as warm as −0.5◦C. It is proposed that the initiation of SIP above the melting layer is stimulated by the recirculation of large liquid drops through the melting layer with convective turbulent updrafts. After re-entering a super cooled environment above the melting layer, they impact with aged ice, freeze, and shatter. The size of the splinters generated during SIP was estimated as 10µm or less. A principal conclusion of this work is that only the freezing drop-shattering mechanism could be clearly supported by the airborne in situ observations.

Korolev, Alexei↗

NASA NTRS2018

Evaluation of a High-Resolution Numerical Weather Prediction Model’s Simulated Clouds Using Observations from CloudSat, GOES-13 and in Situ Aircraft

This study aimed to assess tropical cloud properties predicted by Environment and Climate Change Canada’s Global Environmental Multiscale (GEM)modelwhen run with the Milbrandt–Yau double-moment cloud microphysical scheme and one-way nesting that culminated at a (∼300 km)2 inner domain with 0.25 km horizontal grid spacing. The assessment utilized satellite and in situ data collected during the High Ice Water Content (HIWC) and High Altitude Ice Crystals (HAIC) projects for a mesoscale convective system on 16May 2015 over French Guiana.Data fromCloud- Sat’s cloud-profiling radar and GOES-13’s imager were compared to data either simulated directly by GEM or produced by operating on GEM’s cloud data with both the CFMIP (Cloud Feedback Model Intercomparison Project) Observation Simulator Package (COSP) instrument simulator and a three-dimensional Monte Carlo solar radiative transfer model. In situ observations were made from research aircraft – Canada’s National Research Council Convair-580 and the French SAFIRE Falcon-20 – whose flight paths were aligned with CloudSat’s ground-track. Spatial and temporal shifts of clouds simulated by GEM compared well to GOES-13 imagery. There are, however, differences between simulated and observed amounts of high and low cloud. While GEM did well at predicting ranges of ice-water content (IWC) near 11 km altitude (Falcon-20), it produces too much graupel and snow near 7 km (Convair-580). This produced large differences between CloudSat’s and COSP-generated radar reflectivities and two-way attenuations. On the other hand, CloudSat’s inferred values of IWC agree well with in situ samples at both altitudes. Generally, GEM’s visible reflectances exceeded GOES-13’s on account of having produced too much low-level liquid cloud. It is expected that GEM’s disproportioning of cloud hydrometeors will improve once it includes a better representation of secondary ice production.

Qu, Zhipeng↗

NASA NTRSDate not supplied

TPSAS-NF1676L-21193-DND

Researchers at NASA Langley Research Center have been developing an automated pattern recognition algorithm to identify overshooting convective cloud tops (OTs) in support of the GOES-R satellite program. This algorithm identify regions of overshooting at the individual 1-4 km geostationary satellite pixel scale using visible (during daytime only) and infrared channel imagery and numerical weather analysis data. The algorithm has been developed based upon analysis of 0.25-1 km spatial resolution Aqua MODIS imagery, using a database of over 2000 manually identified OT features throughout the world in storms with varying intensity and morphology. The OT database includes storms ranging from small, warm topped cells in Alaska and Mongolia, tornadic supercells over the U.S. Central Plains and Europe, large tropical mesoscale convective systems, and overshooting in the eyewalls and spiral bands of category 5 tropical cyclones. This database is available for use by the research community. The algorithm is designed to operate on data from any current and historical satellite imager, allowing for development of a highly accurate global OT detection climatology that extends back into the 1990's at up to a 15-30 min temporal resolution throughout the diurnal cycle. As members of the McIDAS Users Group, NASA LaRC has immediate access to the full global archive of geostationary imager data which would allows rapid development of OT climatologies and short-term databases. This type of capability has never been available within the weather and climate research community. Regional geostationary OT databases have been already developed over CONUS during SEAC4RS, for 18-years over the Eastern U.S., and for 5-10 years over Australia, Europe, Southeast Asia, and East Africa among many other regions. Some of these datasets are being used by climate researchers and private industry to examine UTLS-penetrating storm spatial distributions and their temporal variability, in addition to weather hazards associated with these storms at unprecedented spatial detail. This presentation will describe the OT pattern recognition algorithm and highlight recent product applications.

Kristopher Bedka↗

NASA NTRS2018

Observing Fast Mesoscale Atmospheric Processes with a Geostationary Microwave Sounder

A geostationary microwave sounder, GeoSTAR, capable of providing continuous monitoring every 15 minutes of atmospheric temperature, water vapor, clouds, precipitation, and wind in the presence of clouds and precipitation, which will add tremendously to our ability to observe rapidly evolving dynamic atmospheric phenomena, such as hurricanes and severe storms, monsoonal moisture flow, and atmospheric rivers, has been developed at the Jet Propulsion Laboratory. GeoSTAR uses aperture synthesis to overcome the difficulty of attaining adequate spatial resolution from geostationary orbit. It is made possible with new technology that has now been developed and fully tested. Low-risk mission development can start as soon as funding becomes available. The sensor can be hosted on a commercial communications satellite, which could reduce the cost substantially. Plans have been developed at JPL for such a mission, called “GeoStorm”, focused on observing severe convective storms – tropical cyclones, mesoscale convective systems, and extratropical cyclones – with a goal of improving our understanding, modeling and prediction of these destructive phenomena. It can equally well be configured as an operational mission, where the goal is to collect data for immediate assimilation into regional forecast systems, provide “now-casting” as the storms unfold, and support post-disaster relief and recovery efforts. With key observables including vertical profiles of temperature, water vapor, wind and precipitation over a wide area, many focused applications are possible, particularly pertaining to aviation, transportation and marine operations, in both the civilian and defense domains.

Lambrigsten, Bjorn↗

NASA NTRS2019

POLARRIS: A POLArimetric Radar Retrieval and Instrument Simulator

This paper introduces a synthetic polarimetric radar simulator and retrieval package, POLArimetric Radar Retrieval and Instrument Simulator (POLARRIS), for evaluating cloud‐resolving models (CRMs). POLARRIS is composed of forward (POLARRIS‐f) and inverse (retrieval and diagnostic) components (iPOLARRIS) to generate not only polarimetric radar observables (Zh, Zdr, Kdp, ρhv) but also radar‐consistent geophysical parameters such as hydrometeor identification, vertical velocity, and rainfall rates retrieved from CRM data. To demonstrate its application and uncertainties, POLARRIS is applied to simulations of a mesoscale convective system over the Southern Great Plains on 23 May 2011, using the Weather Research and Forecasting model with both spectral bin microphysics (SBM) and the Goddard single‐moment bulk 4ICE microphysics. Statistical composites reveal a significant dependence of simulated polarimetric observables (Zdr, Kdp) on the assumptions of the particle axis ratio (oblateness) and orientation angle distributions. The simulated polarimetric variables differ considerably between the SBM and 4ICE microphysics in part due to the differences in their ice particle size distributions as revealed by comparisons with aircraft measurements. Regardless of these uncertainties, simulated hydrometeor identification distributions overestimate graupel and hail fractions, especially from the simulation with SBM. To minimize uncertainties in forward model, the particle shape and orientation angle distributions of frozen particles should be predicted in a microphysics scheme in addition to the size distributions and particle densities.

Toshi Matsui↗

NASA NTRSDate not supplied

Uncertainty Propagation in Pre-Flight Prediction of Unmanned Aerial Vehicle Separation Violation

Current forecasts on the future of aeronautics suggest an in- creasing number of unmanned aerial vehicles entering the low- altitude airspace in the next decades (FAA, 2018; Kopardekar et al., 2016). Small vehicles for package delivery as well as larger vehicles for urban air mobility will change the airspace drastically, increasing density of operations both in time, i.e. high number of take-off and landings per unit time, and in space, operating in dense urban environment. This scenario poses challenges to the current approach to air traffic control, and large efforts from academia, industry and regulatory bodies are dedicated to the development of new traffic management strategies that leverage higher computing and simulating capabilities available today. In this paper, we propose a simple look-ahead approach to predict potential minimum separation violations at the strategic level, that is before vehicles start flying, depending on the predefined 4D trajectories and uncertainty affecting the wind acting along those routes. The wind field is extracted from the NOAA North America Mesoscale Forecast System and interpolated using Gaussian process regression, while uncertainty affecting the expected cruise airspeed is propagated through error intervals. The approach allows the prediction of aircraft separation as a function of time, highlighting potential safety violations that would go undetected if uncertainty affecting the expected 4D trajectories is not considered. The paper will also discuss issues related to accuracy and scalability of the approach to multiple vehicle operations.

Trajectory Prediction↗

NASA NTRS2020

Object-Based Comparison of Data-Driven and Physics-Driven Satellite Estimates of Extreme Rainfall

The Global Precipitation Measurement (GPM) constellation of spaceborne sensors provides a variety of direct and indirect measurements of precipitation processes. Such observations can be employed to derive spatially and temporally consistent gridded precipitation estimates either via data-driven retrieval algorithms or by assimilation into physically based numerical weather models. We compare the data-driven Integrated Multisatellite Retrievals for GPM (IMERG) and the assimilation-enabled NASA-Unified Weather Research and Forecasting (NU-WRF) model against Stage IV reference precipitation for four major extreme rainfall events in the southeastern United States using an object-based analysis framework that decomposes gridded precipitation fields into storm objects. As an alternative to conventional ‘‘grid-by-grid analysis,’’ the object-based approach provides a promising way to diagnose spatial properties of storms, trace them through space and time, and connect their accuracy to storm types and input data sources. The evolution of two tropical cyclones are generally captured by IMERG and NU-WRF, while the less organized spatial patterns of two mesoscale convective systems pose challenges for both. NU-WRF rain rates are generally more accurate, while IMERG better captures storm location and shape. Both show higher skill in detecting large, intense storms compared to smaller, weaker storms. IMERG’s accuracy depends on the input microwave and infrared data sources; NU-WRF does not appear to exhibit this dependence. Findings highlight that an object-oriented view can provide deeper insights into satellite precipitation performance and that the satellite precipitation community should further explore the potential for ‘‘hybrid’’ data-driven and physics-driven estimates in order to make optimal usage of satellite observations.

extreme events↗

NASA NTRSDate not supplied

Characteristics and Origins of Frontal Convection During IMPACTS on 25 January 2020

This presentation will discuss the characteristics of frontal convection and its estimation from the ER-2 multifrequency nadir reflectivity and Doppler velocity from a warm-occlusion frontal system that traversed across the Northeast U.S. on 25 January 2020. This system that occurred during the IMPACTS field deployment, brought widespread clouds and precipitation to the Northeast. The system brought primarily rain in most areas of more intense rainfall associated with embedded convection near the frontal band and some freezing rain and/or snowfall in the northern regions or higher terrain due to the pre-existing low-level cold air. The NASA ER-2 instrumented with multifrequency radar and the NASA P-3 with in situ microphysics measurements both collected data from this system. The focus of this presentation is on the estimation of vertical velocity in convective and non-convective regions using the ER-2 nadir Doppler measurements. Vertical velocities are inherently difficult to estimate in frontal systems at mesoscale and below other than from direct in situ measurement because of their small magnitudes and errors in the measurements. Estimates from nadir Doppler measurements such as from the ER-2 are challenging because of both Doppler velocity uncertainties and the need to estimate particle fallspeed since the Doppler measurement is the vertical velocity plus the hydrometeor fallspeed. In the presentation, the vertical velocity estimation, its associated errors, and a possible mitigation scheme are described. The characteristics of the convective and stratiform regions on 25 January 2020 are discussed. The vertical velocity estimated from the nadir Doppler measurements are compared with P-3 in situ measurements. Estimation of vertical velocity is one of the goals for upcoming spaceborne missions such as EarthCare and ACCP.

Gerald M. Heymsfield↗

NASA NTRS2020

Geostar – a ‘Shovel Ready’ Geostationary Microwave Sounder

A geostationary microwave sounder, capable of providing temperature, water vapor, clouds, precipitation, and wind in the presence of clouds, convection and precipitation, will add tremendously to our ability to observe dynamic atmospheric phenomena, such as hurricanes and severe storms, monsoonal moisture flow, atmospheric rivers, etc. Such a sensor is now feasible, enabled by technology that has been developed under NASA’s Instrument Incubator Program at the Jet Propulsion Laboratory. The Geostationary Synthetic Thinned Aperture Radiometer (GeoSTAR) is essentially an “AMSU in GEO”, i.e. it has similar capabilities as AMSU would have if it were operating on a geostationary satellite, but with similar spatial resolution. GEO orbits are almost 50 times higher than the LEO orbits that current AMSUs operate from, and the corresponding scaling of aperture size required to maintain spatial resolution has stymied the development of such a sensor for many decades. The aperture synthesis approach implemented with GeoSTAR finally overcomes that obstacle, and the large number of microwave receivers and associated electronics required is made possible with new technology that has now been developed. A low-cost mission operating as a hosted payload on a commercial communications satellite has been designed and is “shovel-ready”. The objectives of such a mission could be to advance our understanding and modeling of storm processes that control rapid or explosive intensification of hurricanes, mesoscale convective systems, and extratropical cyclones, or it could be to support operational weather forecasting and nowcasting. Retrieval of temperature and water vapor profiles is possible even in the presence of moderate precipitation, and with the ability to derive horizontal wind vectors by tracking water vapor features, a rich set of parameters measuring the thermodynamics, dynamics and convection and sampled every 15 minutes, will enable significant progress in storm science and forecasting.

Lambrigtsen, Bjorn H↗

NASA NTRSDate not supplied

Bridging Current Indirect and Future Direct Estimates of Convective Mass Flux Toward Quantifying the Role of Convective Cores on Anvil Area Time Tendencies

Anvil cloud spatial extent is strongly driven by convective mass flux. However, the lack of convective mass flux observations precludes global analyses of the functional relationship between anvil cloud area growth tendencies and convective areal coverage and vertical mass flux. Partly informed by analyses of a hierarchy of WRF mesoscale convective system (MCS) simulations, in this presentation, we discuss new work on estimating convective mass flux by way of an approach that casts the problem of quantifying convective mass flux into terms related to diabatic heating vertical structure, convective area and tropospheric stability. We demonstrate the usefulness of this approach at the MCS spatial scale via development of a simple, robust model that analytically connects system-scale convective mass flux and anvil cloud area growth rates. We show that the model predicts anvil area size changes in agreement with those observed in a global convective system tracking database (TOOCAN). An additional advantage of this approach for estimating convective mass flux is that it bridges future satellite mission plans for directly observing convective mass flux (e.g., AOS) with longer-record observations made by TRMM, GPM and satellite sounder mission data (the latter used for estimating stability) that, when combined, can be used for inferring convective mass fluxes at the MCS spatial scale spanning slowly changing, diverse environments. An evaluation and bridging of both direct and indirect approaches supports convective process analyses varying over longer time periods in this “era of convection.”

convective mass flux↗

NASA NTRSDate not supplied

Bridging current indirect and future direct estimates of convective mass flux toward quantifying the role of convective cores on anvil area time tendencies

convective mass flux↗

NASA NTRS2024

Effective Visualization of Radar Data for Users Impacted By Color Vision Deficiency

Color Vision Deficiency (CVD) is a decreased ability to discern between particular colors. Eight percent of genetic males and half a percent of genetic females have some form of CVD, with many in the radar community falling into this group. When presenting data on a two-dimensional plane, it is common to use colors to represent values via a colormap. Colormap choice in the radar community is influenced by the ability to highlight scientifically interesting features in data, institutional choices, and domain dominance of legacy colormaps. The problem with these current colormaps is that many do not project well for those with CVD (i.e., green next to red). In working with the CVD community to address this problem, multiple colormaps for moments such as equivalent reflectivity factor and Doppler velocity were created for users with forms of CVD such as deuteranomaly, protanomaly, protanopia, and deuteranopia using Python tools such as colorspacious and viscm. We show how these colormaps can improve interpretability for four cases: a mesoscale convective system, a pyrocumulonimbus storm, a wintertime mid-latitude cyclone, and widespread storms with a large bird migration. These new radar equivalent reflectivity factor, Doppler velocity, and polarization colormaps are designed to highlight rain, frozen precipitation, non-meteorological targets, velocity-based items, be perceptually uniform, and visually friendly for those with CVD.

Zachary Sherman↗

DOE OSTI2024

Bridging length scales in organic mixed ionic–electronic conductors through internal strain and mesoscale dynamics

Understanding the structural and dynamic properties of disordered systems at the mesoscale is crucial. This is particularly important in organic mixed ionic-electronic conductors (OMIECs), which undergo significant and complex structural changes when operated in an electrolyte. Here, in this study, we investigate the mesoscale strain, reversibility and dynamics of a model OMIEC material under external electrochemical potential using operando X-ray photon correlation spectroscopy. Our results reveal that strain and structural hysteresis depend on the sample's cycling history, establishing a comprehensive kinetic sequence bridging the macroscopic and microscopic behaviours of OMIECs. Furthermore, we uncover the equilibrium and non-equilibrium dynamics of charge carriers and material-doping states, highlighting the unexpected coupling between charge carrier dynamics and mesoscale order. These findings advance our understanding of the structure-dynamics-function relationships in OMIECs, opening pathways for designing and engineering materials with improved performance and functionality in non-equilibrium states during device operation. Understanding mesoscale structure and dynamics in organic mixed ionic-electronic conductors is crucial. Mesoscale strain kinetics and structural hysteresis have been studied, and they uncover the coupling between charge carrier dynamics and mesoscale order in organic mixed ionic-electronic conductors.

36 MATERIALS SCIENCE↗

NASA NTRS1981

A mesoscale sixth-order numerical modelling system

A numerical simulation system is currently under development for NASA which is intended to improve the modeling of subsynoptic and mesoscale adjustments associated with cyclogenesis, severe storm development and atmospheric transport processes. The model utilizes a standard hydrostatic sigma-p coordinate primitive equation set, with x,y-space differencing accurate to eighth order. A three-step dynamic initialization procedure is employed between the analysis of real-time data and grid interpolation. Results of an 18-hour simulation during which synoptic scale cyclogenesis, subsynoptic scale jet streak adjustments, mesoscale convergence zones and tornadic storms were observed have shown the present model to have the potential for simulating the fine-scale structure of features associated with cyclogenesis and intense squall-line development. The mesoscale model was also found to produce less truncation than the NWS LFM model, although a frictionless version of the mesoscale model somewhat overdeepens and overaccelerates features.

Kaplan, M. L.↗

NASA NTRS1979

Development of a severe local storm prediction system: A 60-day test of a mesoscale primitive equation model

The progress and problems associated with the dynamical forecast system which was developed to predict severe storms are examined. The meteorological problem of severe convective storm forecasting is reviewed. The cascade hypothesis which forms the theoretical core of the nested grid dynamical numerical modelling system is described. The dynamical and numerical structure of the model used during the 1978 test period is presented and a preliminary description of a proposed multigrid system for future experiments and tests is provided. Six cases from the spring of 1978 are discussed to illustrate the model's performance and its problems. Potential solutions to the problems are examined.

Paine, D. A.↗

NASA NTRS1993

Mesoscale simulations of the November 25-26 and December 5-6 cirrus cases using the RAMS model

The Regional Atmospheric Modeling System (RAMS), developed at Colorado State University, was used during the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE) 2 (13 Nov. through 6 Dec. 1991) to provide real time forecasts of cirrus clouds. Forecasts were run once a day, initializing with the 0000 UTC dataset provided by NOAA (Forecast Systems Laboratory (FSL) Mesoscale Analysis and Prediction System (MAPS)). In order to obtain better agreement with observations, a second set of simulations were done for the FIRE 2 cases that occurred on 25-26 Nov. and 5-6 Dec. In this set of simulations, a more complex radiation scheme was used, the Chen/Cotton radiation scheme, along with the nucleation of ice occurring at ice supersaturations as opposed to nucleation occurring at water supersaturations that was done in the actual forecast version. The runs using these more complex schemes took longer wall clock time (7-9 hours for the actual forecasts as compared to 12-14 hrs for the runs using the more complex schemes) however, the final results of the simulations were definitely improved upon. Comparisons between these two sets of simulations are given. Now underway are simulations of these cases using a closed analytical solution for the auto-conversion of ice from a pristine ice class (sizes less than about 50 microns in effective diameter) to a snow class (effective diameters on the order of several hundred microns). This solution is employed along with a new scheme for the nucleation of ice crystals due to Meyers et al and Demott et al. The scheme is derived assuming complete gamma distributions for both the pristine and snow classes. The time rate of change of the number concentration and mass mixing-ratio of each distribution is found by calculating either the flux of crystals that grow beyond a certain critical diameter by vapor deposition in an ice supersaturated regime or by calculating the flux of crystals that evaporate to sizes below that same critical effective diameter.

Harrington, J. L.↗