Results for “Convective storms” — Page 25

NASA NTRS2012

The Tropical Subseasonal Variability Simulated in the NASA GISS General Circulation Model

The tropical subseasonal variability simulated by the Goddard Institute for Space Studies general circulation model, Model E2, is examined. Several versions of Model E2 were developed with changes to the convective parameterization in order to improve the simulation of the Madden-Julian oscillation (MJO). When the convective scheme is modified to have a greater fractional entrainment rate, Model E2 is able to simulate MJO-like disturbances with proper spatial and temporal scales. Increasing the rate of rain reevaporation has additional positive impacts on the simulated MJO. The improvement in MJO simulation comes at the cost of increased biases in the mean state, consistent in structure and amplitude with those found in other GCMs when tuned to have a stronger MJO. By reinitializing a relatively poor-MJO version with restart files from a relatively better-MJO version, a series of 30-day integrations is constructed to examine the impacts of the parameterization changes on the organization of tropical convection. The poor-MJO version with smaller entrainment rate has a tendency to allow convection to be activated over a broader area and to reduce the contrast between dry and wet regimes so that tropical convection becomes less organized. Besides the MJO, the number of tropical-cyclone-like vortices simulated by the model is also affected by changes in the convection scheme. The model simulates a smaller number of such storms globally with a larger entrainment rate, while the number increases significantly with a greater rain reevaporation rate.

Kim, Daehyun↗

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 NTRSDate not supplied

History of NASA Global Lightning Observations

Why does NASA study lightning from space? • Lightning is a natural hazard - threatening lives, damaging infrastructure, causing wildfires, and posing a risk to NASA rocket launches. • Lightning is related to processes within deep convection, and by studying lightning we learn more about how storms impact Earth’s weather and climate. • Lightning produces nitrogen oxides, which modulate ozone levels in the atmosphere. These gases are important for biogeochemical cycles and Earth’s climate. • Lightning affects regions beyond Earth’s troposphere and occurs on other planets.

Timothy Lang↗

NASA NTRSDate not supplied

The Convective Nature of the Tropical Cyclone Lifecycle via GLM and GPM Observations

This study examines the convective nature of the tropical cyclone (TC) lifecycle from tropical storm through extratropical transition. We analyze lightning observations collected from the Geostationary Lightning Mapper (GLM) on the GOES-16 satellite in combination with coincident passive microwave and Ku-band radar observations collected from Global Precipitation Measurement (GPM) mission satellites. A unique aspect of this study, which spans the Atlantic basin hurricane seasons 2018-2020, is that it provides the first known total lightning observations in TCs throughout their extratropical (ET) transition. Analysis of Tropical Storm (TS), Category 1-2 hurricanes (CAT12), Category 3-5 hurricanes (CAT35), and ET time periods, which are grouped by storm-motion and shear-relative characteristics, show that lightning maxima generally occur regimes of down-motion (up-shear), consistent (inconsistent) with previous studies. Further analysis also breaks down time periods by geographic location (e.g., land, coast, ocean) and shear strength; shifting lightning patterns are observed with increasing shear. The lightning maxima are also generally collocated with minima in 37-GHz brightness temperature observations, which is indicative of precipitation-sized ice. DPR Ku-band reflectivity profiles from the GPM Precipitation Feature (PF) database exhibit distinct differences in depth and intensity for electrically active PFs vs those that are not. On average, PFs defined by a rain rate threshold are larger for hurricane strength ITPs (CAT12, CAT35) as compared to either TS or ET ITPs. This indicates that during the hurricane strength ITPs, PFs may be capturing the entire, symmetric rain shield.

hurricane↗

NASA NTRS1980

Detection of heavy convective precipitation using rapid interval digital radar and satellite data

A study was carried out to investigate the evolution of thunderstorms with short-interval (5 min) geosynchronous digital satellite data and with digital radar data (12 min interval) in order to determine the potential and limitations of using the satellite data to detect regions of heavy convective precipitation. Initial results indicate that satellite-based estimates of thunderstorm updraft intensity are related to storm precipitation rate as indicated in the digital radar data. The conclusions give support to the effort to use satellite data for detection of heavy convective precipitation, but emphasize the need for high time resolution (5 min) data.

Negri, A. J.↗

NASA NTRS1979

Lightning as an indication of storm severity

There is a substantial case for the theory that cloud electrification is related primarily to strong convection and the sizeable relative air motion that it implies; therefore, the electrification and subsequent discharge rates can be related to the air motion environment of thunderstorms. The isoceraunic contour map used by the WMO for observing and measuring thunderstorm occurrence contains no information on flash rates, flash density, flash relationship to storm severity, or flash variation with meteorological environment. A constant-view geosynchronous lightning mapper would permit simultaneous studies of the lightning discharge patterns and the meteorological environment of storms, thus establishing whether or not there is a reliable enough relationship to use the observed flash rates and characteristics as supplemental guidance for storm forecast refinement.

Dodge, J. C.↗

NASA NTRS1983

Meso beta-scale thunderstorm/environment interactions during AVE-SESAME V (20-21 May 1979)

The atmospheric variability in a convective area was examined with data from the AVE-SESAME V experiment. Temperature increases were observed in the upper troposphere during storm development, coupled with cooling near the surface and in the lower stratosphere. A mesohigh was detected at 200 mb over the convected area, and upper level winds increased speed north of the area. Wind velocity decreases occurred at the 200 mb level, reaching a 50 percent decrease, during the 3 hr period coinciding with most storms, and a simultaneous increase (doubling) was found in the wind speeds at the 400 mb level. Other phenomena present after the storms began included low-level convergence, upper level divergence, and ascending motion.

Fuelberg, H. E.↗

NASA NTRS2014

Demonstration of AIRS Total Ozone Products to Operations to Enhance User Readiness

Cyclogenesis is a key forecast challenge at operational forecasting centers such as WPC and OPC, so these centers have a particular interest in unique products that can identify key storm features. In some cases, explosively developing extratropical cyclones can produce hurricane force, non-convective winds along the East Coast and north Atlantic as well as the Pacific Ocean, with the potential to cause significant damage to life and property. Therefore, anticipating cyclogenesis for these types of storms is crucial for furthering the NOAA goal of a "Weather Ready Nation". Over the last few years, multispectral imagery (i.e. RGB) products have gained popularity among forecasters. The GOES-R satellite champion at WPC/OPC has regularly evaluated the Air Mass RGB products from GOES Sounder, MODIS, and SEVIRI to aid in forecasting cyclogenesis as part of ongoing collaborations with SPoRT within the framework of the GOES-R Proving Ground. WPC/OPC has used these products to identify regions of stratospheric air associated with tropopause folds that can lead to cyclogenesis and hurricane force winds. RGB products combine multiple channels or channel differences into multi-color imagery in which different colors represent a particular cloud or air mass type. Initial interaction and feedback from forecasters evaluating the legacy Air Mass RGBs revealed some uncertainty regarding what physical processes the qualitative RGB products represent and color interpretation. To enhance forecaster confidence and interpretation of the Air Mass RGB, NASA SPoRT has transitioned a total column ozone product from AIRS retrievals to the WPC/OPC. The use of legacy AIRS demonstrates future JPSS capabilities possible with CrIS or OMPS. Since stratospheric air can be identified by anomalous potential vorticity and warm, dry, ozone-rich air, hyperspectral infrared sounder ozone products can be used in conjunction with the Air Mass RGB for identifying the role of stratospheric air in explosive cyclogenesis and hurricane force wind events. Currently, forecasters at WPC/OPC are evaluating the Air Mass RGB imagery in conjunction with the AIRS total column ozone to aid forecasting cyclogenesis and high wind forecasts. One of the limitations of the total ozone product is that it is difficult for forecasters to determine whether elevated ozone concentrations are related to stratospheric air or climatologically high values of ozone in certain regions. To address this limitation, SPoRT created an AIRS ozone anomaly product which calculates the percent of normal ozone based on a global stratospheric ozone mean climatology. With the knowledge that ozone values 125 percent of normal and greater typically represent stratospheric air; the anomaly product can be used with the total column ozone product to confirm regions of stratospheric air on the Air Mass RGB. This presentation describes the generation of these products along with forecaster feedback concerning the use of the AIRS ozone products in conjunction with the Air Mass RGB product for the unique forecast challenges WPC/OPC face. Additionally examples of CrIS ozone and anomaly products will be shown to further demonstrate the utility and capability of JPSS in forecasting unique events.

Berndt, Emily↗

NASA NTRS2015

Development and Application of Hyperspectral Infrared Ozone Retrieval Products for Operational Meteorology

Cyclogenesis is a key forecast challenge at operational forecasting centers such as WPC and OPC, so these centers have a particular interest in unique products that can identify key storm features. In some cases, explosively developing extratropical cyclones can produce hurricane force, non-convective winds along the East Coast and north Atlantic as well as the Pacific Ocean, with the potential to cause significant damage to life and property. Therefore, anticipating cyclogenesis for these types of storms is crucial for furthering the NOAA goal of a "Weather Ready Nation". Over the last few years, multispectral imagery (i.e. RGB) products have gained popularity among forecasters. The GOES-R satellite champion at WPC/OPC has regularly evaluated the Air Mass RGB products from GOES Sounder, MODIS, and SEVIRI to aid in forecasting cyclogenesis as part of ongoing collaborations with SPoRT within the framework of the GOES-R Proving Ground. WPC/OPC has used these products to identify regions of stratospheric air associated with tropopause folds that can lead to cyclogenesis and hurricane force winds. RGB products combine multiple channels or channel differences into multi-color imagery in which different colors represent a particular cloud or air mass type. Initial interaction and feedback from forecasters evaluating the legacy Air Mass RGBs revealed some uncertainty regarding what physical processes the qualitative RGB products represent and color interpretation. To enhance forecaster confidence and interpretation of the Air Mass RGB, NASA SPoRT has transitioned a total column ozone product from AIRS retrievals to the WPC/OPC. The use of legacy AIRS demonstrates future JPSS capabilities possible with CrIS or OMPS. Since stratospheric air can be identified by anomalous potential vorticity and warm, dry, ozone-rich air, hyperspectral infrared sounder ozone products can be used in conjunction with the Air Mass RGB for identifying the role of stratospheric air in explosive cyclogenesis and hurricane force wind events. Currently, forecasters at WPC/OPC are evaluating the Air Mass RGB imagery in conjunction with the AIRS total column ozone to aid forecasting cyclogenesis and high wind forecasts. One of the limitations of the total ozone product is that it is difficult for forecasters to determine whether elevated ozone concentrations are related to stratospheric air or climatologically high values of ozone in certain regions. To address this limitation, SPoRT created an AIRS ozone anomaly product which calculates the percent of normal ozone based on a global stratospheric ozone mean climatology. With the knowledge that ozone values 125 percent of normal and greater typically represent stratospheric air; the anomaly product can be used with the total column ozone product to confirm regions of stratospheric air on the Air Mass RGB. This presentation describes the generation of these products along with forecaster feedback concerning the use of the AIRS ozone products in conjunction with the Air Mass RGB product for the unique forecast challenges WPC/OPC face. Additionally examples of CrIS ozone and anomaly products will be shown to further demonstrate the utility and capability of JPSS in forecasting unique events.

Berndt, Emily↗

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

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 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.↗

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↗