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NASA NTRS2002

Thunderstorms Characteristics Observed By TRMM

The goal of the present study is to begin a more comprehensive examination of the spectrum of storm types and their attributes worldwide, and as a function of season, location, and convective regime using the observed lightning, microwave scattering, and reflectively signatures. A global, multi-year data set (1998-2000) is being assembled to further our understanding of convective processes in different climatological regimes. We find that the deepest thunderstorms (having reflectively in excess of 50 dBZ at 9 km altitude) occur in all the sub-tropical continents and occasionally over the open ocean. The most intense storms have the greatest lightning rates, lowest brightness temperatures and greatest depth of reflectively-all indicative of strong updrafts and a well-developed volume of precipitation-sized ice particles.

Goodman, Steven J.↗

NASA NTRS1984

Thunderstorm cloud top dynamics as inferred from satellite observations and models

Satellite observations of convective towers penetrating the tropopause are summarized. Three classes of thunderstorm cloud tops including storm tops that have a monotonic temperature-height pattern with the highest point being the coldest point (class 1), tops that have a colocated cold and high point with the warm point on the downward slope to the rear of the highest point (class 2), and tops in which the cold point is offset upwind from the high point, with a cold-warm couplet straddling the convective cloud top (class 3), are described. A one-dimensional cloud parcel model applied in the overshooting region is used to explore the causes of the storm top's unique temperature/height structures.

Adler, R. F.↗

NASA NTRS1978

The noon and midnight mid-latitude trough as seen by Ariel 4

The electron density data returned by the polar orbiting satellites Ariel 3 and Ariel 4 revealed that the midlatitude trough is one of the distinct large-scale features of the ionosphere at about 550 km. Recent work (e.g., Tulunay and Grebowsky, 1975) on the data included the investigation of the temporal development of the latitudinal position of the midlatitude electron density trough at dawn and dusk during the large magnetic storms of May 1967 and May 1972. Model calculations which assumed that the equatorial convection E-field varies in step with the Kp index reproduced on the average the observed behavior. In the present paper, trough observations made at noon and midnight during the period, 12-21 December 1971 which encompassed a relatively large magnetic storm are discussed. In this context, model calculations have been employed as a guide of average approximations of the actual situation in predicting the plasmapause location. It is also shown that the trough observed on the noon passes is not generally plasmapause-related as the nightside troughs are expected to be.

Tulunay, Y. K.↗

NASA NTRS2006

Convective Weather Forecast Quality Metrics for Air Traffic Management Decision-Making

Since numerical weather prediction models are unable to accurately forecast the severity and the location of the storm cells several hours into the future when compared with observation data, there has been a growing interest in probabilistic description of convective weather. The classical approach for generating uncertainty bounds consists of integrating the state equations and covariance propagation equations forward in time. This step is readily recognized as the process update step of the Kalman Filter algorithm. The second well known method, known as the Monte Carlo method, consists of generating output samples by driving the forecast algorithm with input samples selected from distributions. The statistical properties of the distributions of the output samples are then used for defining the uncertainty bounds of the output variables. This method is computationally expensive for a complex model compared to the covariance propagation method. The main advantage of the Monte Carlo method is that a complex non-linear model can be easily handled. Recently, a few different methods for probabilistic forecasting have appeared in the literature. A method for computing probability of convection in a region using forecast data is described in Ref. 5. Probability at a grid location is computed as the fraction of grid points, within a box of specified dimensions around the grid location, with forecast convection precipitation exceeding a specified threshold. The main limitation of this method is that the results are dependent on the chosen dimensions of the box. The examples presented Ref. 5 show that this process is equivalent to low-pass filtering of the forecast data with a finite support spatial filter. References 6 and 7 describe the technique for computing percentage coverage within a 92 x 92 square-kilometer box and assigning the value to the center 4 x 4 square-kilometer box. This technique is same as that described in Ref. 5. Characterizing the forecast, following the process described in Refs. 5 through 7, in terms of percentage coverage or confidence level is notionally sound compared to characterizing in terms of probabilities because the probability of the forecast being correct can only be determined using actual observations. References 5 through 7 only use the forecast data and not the observations. The method for computing the probability of detection, false alarm ratio and several forecast quality metrics (Skill Scores) using both the forecast and observation data are given in Ref. 2. This paper extends the statistical verification method in Ref. 2 to determine co-occurrence probabilities. The method consists of computing the probability that a severe weather cell (grid location) is detected in the observation data in the neighborhood of the severe weather cell in the forecast data. Probabilities of occurrence at the grid location and in its neighborhood with higher severity, and with lower severity in the observation data compared to that in the forecast data are examined. The method proposed in Refs. 5 through 7 is used for computing the probability that a certain number of cells in the neighborhood of severe weather cells in the forecast data are seen as severe weather cells in the observation data. Finally, the probability of existence of gaps in the observation data in the neighborhood of severe weather cells in forecast data is computed. Gaps are defined as openings between severe weather cells through which an aircraft can safely fly to its intended destination. The rest of the paper is organized as follows. Section II summarizes the statistical verification method described in Ref. 2. The extension of this method for computing the co-occurrence probabilities in discussed in Section HI. Numerical examples using NCWF forecast data and NCWD observation data are presented in Section III to elucidate the characteristics of the co-occurrence probabilities. This section also discusses the procedure for computing throbabilities that the severity of convection in the observation data will be higher or lower in the neighborhood of grid locations compared to that indicated at the grid locations in the forecast data. The probability of coverage of neighborhood grid cells is also described via examples in this section. Section IV discusses the gap detection algorithm and presents a numerical example to illustrate the method. The locations of the detected gaps in the observation data are used along with the locations of convective weather cells in the forecast data to determine the probability of existence of gaps in the neighborhood of these cells. Finally, the paper is concluded in Section V.

Chatterji, Gano B.↗

NASA NTRS1982

Radar reflectivities and satellite imagery of severe storms 20 May 1977

Storms on 20 May 1977 generated a vast cirrus deck. Disturbed areas at storm top had equivalent black-body temperatures (T sub BB) much lower than the tropopause temperature, indicative of overshooting tops. The area of T sub BB not greater than -71 C represents the area of convective activity penetrating 2 km above the tropopause. This area was relatively large after cloud tops and radar reflectivities reached their maximum heights. It became much smaller during tornadoes when reflectivities were decreasing. T sub BB was at a minimum at the time of mesocyclone formation. The Del City storm had two periods of growth, as indicated both by reflectivities and the T sub BB areas. The mesocyclone was first detected during the second less intense period of growth; the tornado occurred during decreasing reflectivities. The maintenance of large areas of relatively low T sub BB after tornado dissipation is ascribed to continued convection on the flanks of the storm and to residual updrafts in a thick anvil cloud.

Wexler, R.↗

NASA NTRSDate not supplied

Storm Chasing from Space: Detecting severe weather phenomena from satellite platforms

Severe weather is an awe-inspiring phenomenon that affects the entire globe. Lightning, hail, damaging wind and tornadoes pose threats to society and challenges to the scientific community. Severe weather is annually responsible for tens of billions of dollars in insured losses to property, infrastructure, and agriculture. Satellite platforms offer a globally uniform approach to observing weather phenomena in remote or data-sparse regions and over the oceans. Severe convection exhibits distinct signatures in spaceborne datasets that we use to analyze severe storms. We leverage these signatures create climatologies, improve prediction, and provide a method of detection around the globe where traditional ground-based data (such as ground-based radar or human-spotter reports) are inconsistent or unavailable. Satellites in low-earth, sun-synchronous, and geostationary orbit provide a consistent, global view of severe weather from which we can examine the current global distribution, frequency, and severity of severe storms and establish a baseline to assess their future trend in a changing Earth system.

Sarah D. Bang↗

NASA NTRSDate not supplied

Storm Chasing from Space: Detecting Severe Weather Phenomena from Satellite Platforms

Sarah D Bang↗

DOE OSTI2024

Causally‐Informed Deep Learning to Improve Climate Models and Projections

Abstract Climate models are essential to understand and project climate change, yet long‐standing biases and uncertainties in their projections remain. This is largely associated with the representation of subgrid‐scale processes, particularly clouds and convection. Deep learning can learn these subgrid‐scale processes from computationally expensive storm‐resolving models while retaining many features at a fraction of computational cost. Yet, climate simulations with embedded neural network parameterizations are still challenging and highly depend on the deep learning solution. This is likely associated with spurious non‐physical correlations learned by the neural networks due to the complexity of the physical dynamical system. Here, we show that the combination of causality with deep learning helps removing spurious correlations and optimizing the neural network algorithm. To resolve this, we apply a causal discovery method to unveil causal drivers in the set of input predictors of atmospheric subgrid‐scale processes of a superparameterized climate model in which deep convection is explicitly resolved. The resulting causally‐informed neural networks are coupled to the climate model, hence, replacing the superparameterization and radiation scheme. We show that the climate simulations with causally‐informed neural network parameterizations retain many convection‐related properties and accurately generate the climate of the original high‐resolution climate model, while retaining similar generalization capabilities to unseen climates compared to the non‐causal approach. The combination of causal discovery and deep learning is a new and promising approach that leads to stable and more trustworthy climate simulations and paves the way toward more physically‐based causal deep learning approaches also in other scientific disciplines.

Meteorology & Atmospheric Sciences↗

NASA NTRS2004

The Sensitivity of Simulated Storm Structure and Intensity to the Temperature at the Lifted Condensation Level

Prior parameter space studies of simulated deep convection are extended to embrace variations in the ambient temperature at the Lifted Condensation Level (LCL). Within the context of the parameter space study design, changes in LCL temperature are roughly equivalent to changes in the ambient precipitable water. Two series of simulations are conducted, one with a warm LCL that is associated with approximately 60 mm of precipitable water, and another with LCL temperatures 8 C cooler, so that PW is reduced to roughly 30 mm. The sets of simulations include tests of the impact of changes in the buoyancy and shear profile shapes and of changes in mixed and moist layer depths, all of which have been shown to be important in prior work. Simulations discussed here feature values of bulk convective available potential energy (CAPE) of 800, 2000, or 3200 Joules per kilogram, and a single semicircular hodograph having radius of 12 meters per second, but with variable vertical shear. The simulations reveal a consistent trend toward stronger peak updraft speeds for the cooler LCL temperature (reduced PW) cases, if all other environmental parameters are held constant. Roughly comparable increases in updraft speeds are noted for all combinations of LCL and level of free convection heights. These increases in updraft strength are evidently the result of both the reduction of condensate loading aloft and the lower altitudes at which the latent heat release by freezing and deposition commences in the cooler, low-PW environments. Because the latent heat of fusion adds relatively more energy to the updrafts at low CAPE, those storms show more strengthening at low PW than do the larger CAPE storms. As expected, maximum storm precipitation rates tend to diminish as PW is decreased, but only slightly, and by amounts not proportionate to the decrease in PW. The low-PW cases thus actually feature larger environment-relative precipitation efficiency than do the high-PW cases. In addition, more hail reaches the surface in the low-PW cases because of reduced melting in the cooler environments.

McCaul, Eugene W., Jr.↗

DOE OSTI2022

Disentangling the Influences of Storm-Relative Flow and Horizontal Streamwise Vorticity on Low-Level Mesocyclones in Supercells

Sufficient low-level storm-relative flow is a necessary ingredient for sustained supercell thunderstorms and is connected to supercell updraft width. Assuming a supercell exists, the role of low-level storm-relative flow in regulating supercells’ low-level mesocyclone intensity is less clear. One possibility considered in this article is that storm-relative flow controls mesocyclone and tornado width via its modulation of overall updraft extent. This hypothesis relies on a previously postulated positive correspondence between updraft width, mesocyclone width, and tornado width. An alternative hypothesis is that mesocyclone characteristics are primarily regulated by horizontal streamwise vorticity irrespective of storm-relative flow. A matrix of supercell simulations was analyzed to address the aforementioned hypotheses, wherein horizontal streamwise vorticity and storm-relative flow were independently varied. Among these simulations, mesocyclone width and intensity were strongly correlated with horizontal streamwise vorticity, and comparatively weakly correlated with storm-relative flow, supporting the second hypothesis. Accompanying theory and trajectory analysis offers the physical explanation that, when storm-relative flow is large and updrafts are wide, vertically tilted streamwise vorticity is projected over a wider area but with a lesser average magnitude than when these parameters are small. These factors partially offset one another, degrading the correspondence of storm-relative flow with updraft circulation and rotational velocity, which are the mesocyclone attributes most closely tied to tornadoes. In conclusion, these results refute the previously purported connections between updraft width, mesocyclone width, and tornado width, and emphasize horizontal streamwise vorticity as the primary control on low-level mesocyclones in sustained supercells.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2004

Sensitivity of a Cloud-Resolving Model to the Bulk and Explicit Bin Microphysical Schemes: Validations with a PRE-STORM Case - Part 1

A cloud-resolving model is used to study sensitivities of two different microphysical schemes, one is the bulk type, and the other is an explicit bin scheme, in simulating a mid-latitude squall line case (PRE-STORM, June 10-11, 1985). Simulations using different microphysical schemes are compared with each other and also with the observations. Both the bulk and bin models reproduce the general features during the developing and mature stage of the system. The leading convective zone, the trailing stratiform region, the horizontal wind flow patterns, pressure perturbation associated with the storm dynamics, and the cool pool in front of the system all agree well with the observations. Both the observations and the bulk scheme simulation serve as validations for the newly incorporated bin scheme. However, it is also shown that, the bulk and bin simulations have distinct differences, most notably in the stratiform region. Weak convective cells exist in the stratiform region in the bulk simulation, but not in the bin simulation. These weak convective cells in the stratiform region are remnants of the previous stronger convections at the leading edge of the system. The bin simulation, on the other hand, has a horizontally homogeneous stratiform cloud structure, which agrees better with the observations. Preliminary examinations of the downdraft core strength, the potential temperature perturbation, and the evaporative cooling rate show that the differences between the bulk and bin models are due mainly to the stronger low-level evaporative cooling in convective zone simulated in the bulk model. Further quantitative analysis and sensitivity tests for this case using both the bulk and bin models will be presented in a companion paper.

Li, Xiao-Wen↗

NASA NTRS1973

Satellite studies of magnetospheric substorms on August 15, 1968. III - Some features of magnetospheric convection.

New details of unsteady magnetospheric convection and gradual erosion of the plasmasphere during a weak magnetic storm are revealed in the light of presented ground data and OGO-4 and OGO-5 data for August 13-15, 1968. These new findings suggest that westward electric fields of the order of 0.5 mv/m were present in the midnight sector during the substorms studied.

Carpenter, D. L.↗

NASA NTRS1985

LAMPS software and mesoscale prediction studies

The full-physics version of the LAMPS model has been implemented on the Perkin-Elmer computer. In Addition, LAMPS graphics processors have been rewritten to the run on the Perkin-Elmer and they are currently undergoing final testing. Numerical experiments investigating the impact of convective parameterized latent heat release on the evolution of a precipitating storm have been performed and the results are currently being evaluated. Curent efforts include the continued evaluation of the impact of initial conditions on LAMPS model results. This work will help define measurement requirements for future research field projects as well as for observations in support of operational forecasts. Also, the impact of parameterized latent heat on the evolution of precipitating systems is continuing. This research is in support of NASA's proposed Earth Observation Mission (EOM).

Perkey, D. J.↗

NASA NTRS1987

Temperature anisotropies in the terrestrial ionosphere and plasmasphere

Theoretical work in which the solution of closed sets of transport equations has predicted the existence of temperature anisotropies in the terrestrial ionosphere-plasmasphere system is discussed, considering only thermal (less than 1 eV) particle populations. Various models used to predict ion and electron temperature anisotropies, including kinetic, semikinetic, hydromagnetic, and generalized transport models, predict temperature anisotropies in the polar wind, along plasmapause field lines, during the refilling of the outer plasmasphere after depletion by a magnetic storm, and at F region altitudes in regions of rapid plasma convection. However, only some of the theoretical predictions agree with experimental evidence. Other models predict isotropic temperature distributions in regions where observations indicated the presence of temperature anisotropies.

Demars, H. G.↗

NASA NTRS1988

The magnetosphere of Mercury

Data provided by the Mariner-10 spacecraft on the properties of Mercurian magnetosphere are examined. These observations indicate that the Mercurian magnetosphere has a magnetopause and a bow shock which are quite similar to their terrestrial counterparts, although much smaller. However, due to the absence of any significant atmosphere or ionosphere, the flow of current in the Mercurian magnetosphere is different from the patterns at the earth. Many questions regarding the intrinsic magnetic field properties of Mercury remain unanswered, such as the existence of radiation belts, magnetic storms, the size of auroral regions, the mechanism of global magnetospheric convection, and the source of plasma.

Russell, C. T.↗

NASA NTRS1989

Lightning trends as a precursor to microbursts

The feasibility of using lightning-rate data to aid in the early warning of microburst occurrence in moist environments is illustrated. Convective tendency images were generated for a small microburst-producing storm that developed in northern Alabama on July 20, 1986 during the Cooperative Huntsville Meteorological Experiment. Radar observations were obtained from the NCAR CP2 10-cm dual-polarization Doppler radar, while the measurements of total lightning activity were provided by the National Severe Storm Laboratory, a mobile laboratory that was located under the storm throughout its lifetime. The scenario for the evolution of wet microburst producing thunderstorms is described.

Buechler, Dennis E.↗

NASA NTRS1990

Convective dynamics

In addressing meteorological processes, including convection, it is convenient to separate these processes into their kinematic, dynamic, and microphysical components. Dynamic processes deal with the forces that initiate and sustain or alter motion, while kinematic processes describe the motion field. Microphysical processes address the distribution of water substance. This review of convective dynamics is organized along the following lines. First is an assessment of radar capability, particularly the use of one or more Doppler radars, to portray the wind field. Then various types of precipitating moist convection are reviewed. Each type or mode of convection results from a distinct environment. The principal interest of dynamics here is its role in the convection's evolution, structure, and movement. Thus, the important processes of storm rotation, splitting and propagation, including tornadogenesis, are examined.

Ray, Peter S.↗

NASA NTRS2008

The 2008 Super Tuesday Tornado Outbreak: Overview of the Tornadoes and their Parent Storms

The cold-season Tornado outbreak that occurred over the Southeast on 5-6 February 2008 was significant for the following reasons: about 84 tornadoes were documented over a 15 h period between late afternoon on 5 February and early morning on 6 February 2008; a wide variety of parent storms were associated with the tornadoes; a total of five EF-4 tornadoes occurred, with two forming over Alabama during the early morning hours prior to sunrise; there was a significant lull period between the initial convective and the early morning activity over Alabama 10 hours later; and, a wide spectrum of storm types, ranging from isolated supercell storms to QLCS bow echoes, accompanied the tornadoes. The goal of this paper is to provide a general description of the outbreak including the distribution of tornadoes and supercell storms over the region, a detailed map of the tornado tracks, time series of tornadoes and parent storms, and general characteristics of all parent tornado storms. The total number of major storms (duration greater than 3 h, at least three tornadoes produced) was seven. Several noteworthy storms are described: a long track (198 km long) tornado and its parent storm over Arkansas; a prolific supercell storm persisted for 7-8 hours and produced 16 tornadoes from north-central Mississippi to southern KY; and, bow echo storms (QLCS's) were simultaneous over KY and produced 16 tornadoes.

Knupp, Kevin R.↗