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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
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NASA NTRS2012

The View from the Top: CALIOP Ice Water Content in the Uppermost Layer of Tropical Cyclones

NASA's CALIPSO satellite carries both the Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP) and the Imaging Infrared Radiometer (IIR). The lidar is ideally suited to viewing the very top of tropical cyclones, and the IIR provides critical optical and microphysical information. The lidar and the IIR data work together to understand storm clouds since they are perfectly co-located, and big tropical cyclones provide an excellent complex target for comparing the observations. There is a lot of information from these case studies for understanding both the observations and the tropical cyclones, and we are just beginning to scratch the surface of what can be learned. Many tropical cyclone cloud particle measurements are focused on the middle and lower regions of storms, but characterization of cyclone interaction with the lowermost stratosphere at the upper storm boundary may be important for determining the total momentum and moisture transport budget, and perhaps for predicting storm intensity as well. A surprising amount of cloud ice is to be found at the very top of these big storms.

Avery, Melody A.↗
NASA NTRS2013

Tropical Ocean Surface Energy Balance Variability: Linking Weather to Climate Scales

Radiative and turbulent surface exchanges of heat and moisture across the atmosphere-ocean interface are fundamental components of the Earth s energy and water balance. Characterizing the spatiotemporal variability of these exchanges of heat and moisture is critical to understanding the global water and energy cycle variations, quantifying atmosphere-ocean feedbacks, and improving model predictability. These fluxes are integral components to tropical ocean-atmosphere variability; they can drive ocean mixed layer variations and modify the atmospheric boundary layer properties including moist static stability, thereby influencing larger-scale tropical dynamics. Non-parametric cluster-based classification of atmospheric and ocean surface properties has shown an ability to identify coherent weather regimes, each typically associated with similar properties and processes. Using satellite-based observational radiative and turbulent energy flux products, this study investigates the relationship between these weather states and surface energy processes within the context of tropical climate variability. Investigations of surface energy variations accompanying intraseasonal and interannual tropical variability often use composite-based analyses of the mean quantities of interest. Here, a similar compositing technique is employed, but the focus is on the distribution of the heat and moisture fluxes within their weather regimes. Are the observed changes in surface energy components dominated by changes in the frequency of the weather regimes or through changes in the associated fluxes within those regimes? It is this question that the presented work intends to address. The distribution of the surface heat and moisture fluxes is evaluated for both normal and non-normal states. By examining both phases of the climatic oscillations, the symmetry of energy and water cycle responses are considered.

Roberts, J. Brent↗
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 NTRS2014

On the Hiatus in the Acceleration of Tropical Upwelling Since the Beginning of the 21st Century

Chemistry-climate models predict an acceleration of the upwelling branch of the Brewer-Dobson circulation as a consequence of increasing global surface temperatures, resulting from elevated levels of atmospheric greenhouse gases. The observed decrease of ozone in the tropical lower stratosphere during the last decades of the 20th century is consistent with the anticipated acceleration of upwelling. However, more recent satellite observations of ozone reveal that this decrease has unexpectedly stopped in the first decade of the 21st century, challenging the implicit assumption of a continuous acceleration of tropical upwelling. In this study we use three decades of chemistry transport-model simulations (1980-2013) to investigate this phenomenon and resolve this apparent contradiction. Our model reproduces the observed tropical lower stratosphere ozone record, showing a significant decrease in the early period followed by a statistically robust trend-change after 2002. We demonstrate that this trend-change is correlated with corresponding changes in the vertical transport and conclude that a hiatus in the acceleration of tropical upwelling occurred during the last decade.

trends↗
NASA NTRS2014

Statistical Aspects of North Atlantic Basin Tropical Cyclones During the Weather Satellite Era, 1960-2013

This Technical Publication (TP) is part 2 of a two-part study of the North Atlantic basin tropical cyclones that occurred during the weather satellite era, 1960-2013. In particular, this TP examines the inferred statistical relationships between 25 tropical cyclone parameters and 9 specific climate-related factors, including the (1) Oceanic Niño Index (ONI), (2) Southern Oscillation Index (SOI), (3) Atlantic Multidecadal Oscillation (AMO) index, (4) Quasi-Biennial Oscillation (QBO) index, (5) North Atlantic Oscillation (NAO) index of the Climate Prediction Center (CPC), (6) NAO index of the Climate Research Unit (CRU), (7) Armagh surface air temperature (ASAT), (8) Global Land-Ocean Temperature Index (GLOTI), and (9) Mauna Loa carbon dioxide (CO2) (MLCO2) index. Part 1 of this two-part study examined the statistical aspects of the 25 tropical cyclone parameters (e.g., frequencies, peak wind speed (PWS), accumulated cyclone energy (ACE), etc.) and provided the results of statistical testing (i.e., runs-testing, the t-statistic for independent samples, and Poisson distributions). Also, the study gave predictions for the frequencies of the number of tropical cyclones (NTC), number of hurricanes (NH), number of major hurricanes (NMH), and number of United States land-falling hurricanes (NUSLFH) expected for the 2014 season, based on the statistics of the overall interval 1960-2013, the subinterval 1995-2013, and whether the year 2014 would be either an El Niño year (ENY) or a non-El Niño year (NENY).

Wilson, Robert M.↗
NASA NTRS2013

Analyzing Tropical Waves Using the Parallel Ensemble Empirical Model Decomposition Method: Preliminary Results from Hurricane Sandy

In this study, we discuss the performance of the parallel ensemble empirical mode decomposition (EMD) in the analysis of tropical waves that are associated with tropical cyclone (TC) formation. To efficiently analyze high-resolution, global, multiple-dimensional data sets, we first implement multilevel parallelism into the ensemble EMD (EEMD) and obtain a parallel speedup of 720 using 200 eight-core processors. We then apply the parallel EEMD (PEEMD) to extract the intrinsic mode functions (IMFs) from preselected data sets that represent (1) idealized tropical waves and (2) large-scale environmental flows associated with Hurricane Sandy (2012). Results indicate that the PEEMD is efficient and effective in revealing the major wave characteristics of the data, such as wavelengths and periods, by sifting out the dominant (wave) components. This approach has a potential for hurricane climate study by examining the statistical relationship between tropical waves and TC formation.

PEEMD↗
NASA NTRS2014

The Role of Temperature and Humidity on Seasonal Influenza in Tropical Areas: Guatemala, El Salvador and Panama, 2008-2013

Background: The role of meteorological factors on influenza transmission in the tropics is less defined than in the temperate regions. We assessed the association between influenza activity and temperature, specific humidity and rainfall in 6 study areas that included 11 departments or provinces within 3 tropical Central American countries: Guatemala, El Salvador and Panama. Method/ Findings: Logistic regression was used to model the weekly proportion of laboratory-confirmed influenza positive samples during 2008 to 2013 (excluding pandemic year 2009). Meteorological data was obtained from the Tropical Rainfall Measuring Mission satellite and the Global Land Data Assimilation System. We found that specific humidity was positively associated with influenza activity in El Salvador (Odds Ratio (OR) and 95% Confidence Interval of 1.18 (1.07-1.31) and 1.32 (1.08-1.63)) and Panama (OR = 1.44 (1.08-1.93) and 1.97 (1.34-2.93)), but negatively associated with influenza activity in Guatemala (OR = 0.72 (0.6-0.86) and 0.79 (0.69-0.91)). Temperature was negatively associated with influenza in El Salvador's west-central departments (OR = 0.80 (0.7-0.91)) whilst rainfall was positively associated with influenza in Guatemala's central departments (OR = 1.05 (1.01-1.09)) and Panama province (OR = 1.10 (1.05-1.14)). In 4 out of the 6 locations, specific humidity had the highest contribution to the model as compared to temperature and rainfall. The model performed best in estimating 2013 influenza activity in Panama and west-central El Salvador departments (correlation coefficients: 0.5-0.9). Conclusions/Significance: The findings highlighted the association between influenza activity and specific humidity in these 3 tropical countries. Positive association with humidity was found in El Salvador and Panama. Negative association was found in the more subtropical Guatemala, similar to temperate regions. Of all the study locations, Guatemala had annual mean temperature and specific humidity that were lower than the others.

Central America↗
NASA NTRS2014

Calibrating Historical IR Sensors Using GEO, and AVHRR Infrared Tropical Mean Calibration Models

Long-term, remote-sensing-based climate data records (CDRs) are highly dependent on having consistent, wellcalibrated satellite instrument measurements of the Earth's radiant energy. Therefore, by making historical satellite calibrations consistent with those of today's imagers, the Earth-observing community can benefit from a CDR that spans a minimum of 30 years. Most operational meteorological satellites rely on an onboard blackbody and space looks to provide on-orbit IR calibration, but neither target is traceable to absolute standards. The IR channels can also be affected by ice on the detector window, angle dependency of the scan mirror emissivity, stray-light, and detector-to-detector striping. Being able to quantify and correct such degradations would mean IR data from any satellite imager could contribute to a CDR. Recent efforts have focused on utilizing well-calibrated modern hyper-spectral sensors to intercalibrate concurrent operational IR imagers to a single reference. In order to consistently calibrate both historical and current IR imagers to the same reference, however, another strategy is needed. Large, well-characterized tropical-domain Earth targets have the potential of providing an Earth-view reference accuracy of within 0.5 K. To that effort, NASA Langley is developing an IR tropical mean calibration model in order to calibrate historical Advanced Very High Resolution Radiometer (AVHRR) instruments. Using Meteosat-9 (Met-9) as a reference, empirical models are built based on spatially/temporally binned Met-9 and AVHRR tropical IR brightness temperatures. By demonstrating the stability of the Met-9 tropical models, NOAA-18 AVHRR can be calibrated to Met-9 by matching the AVHRR monthly histogram averages with the Met-9 model. This method is validated with ray-matched AVHRR and Met-9 biasdifference time series. Establishing the validity of this empirical model will allow for the calibration of historical AVHRR sensors to within 0.5 K, and thereby establish a climate-quality IR data record.

Scarino, Benjamin↗
NASA NTRS2015

Monitoring Changes of Tropical Extreme Rainfall Events Using Differential Absorption Barometric Radar (DiBAR)

This work studies the potential of monitoring changes in tropical extreme rainfall events such as tropical storms from space using a Differential-absorption BArometric Radar (DiBAR) operating at 50-55 gigahertz O2 absorption band to remotely measure sea surface air pressure. Air pressure is among the most important variables that affect atmospheric dynamics, and currently can only be measured by limited in-situ observations over oceans. Analyses show that with the proposed radar the errors in instantaneous (averaged) pressure estimates can be as low as approximately 5 millibars (approximately 1 millibar) under all weather conditions. With these sea level pressure measurements, the forecasts, analyses and understanding of these extreme events in both short and long time scales can be improved. Severe weathers, especially hurricanes, are listed as one of core areas that need improved observations and predictions in WCRP (World Climate Research Program) and NASA Decadal Survey (DS) and have major impacts on public safety and national security through disaster mitigation. Since the development of the DiBAR concept about a decade ago, our team has made substantial progress in advancing the concept. Our feasibility assessment clearly shows the potential of sea surface barometry using existing radar technologies. We have developed a DiBAR system design, fabricated a Prototype-DiBAR (P-DiBAR) for proof-of-concept, conducted lab, ground and airborne P-DiBAR tests. The flight test results are consistent with our instrumentation goals. Observational system simulation experiments for space DiBAR performance show substantial improvements in tropical storm predictions, not only for the hurricane track and position but also for the hurricane intensity. DiBAR measurements will lead us to an unprecedented level of the prediction and knowledge on tropical extreme rainfall weather and climate conditions.

Lin, Bing↗
NASA NTRS2017

Using CYGNSS to Observe Convectively Driven Near-Surface Winds in Tropical Precipitation Systems During Madden-Julian Oscillation Events

The Cyclone Global Navigation OKLMA 1411 UTC Satellite System (CYGNSS) is a multi-satellite constellation that launched 15 December 2016. The primary objective of CYGNSS is to use bistatic Global Positioning System (GPS) reflectometry to accurately measure near-surface wind speeds within the heavily raining inner core of tropical cyclones. CYGNSS also features rapid revisit times over a given region in the tropics - ranging from several minutes to a few hours, depending on the constellation geometry at that time. Despite the focus on tropical cyclones, the ability of CYGNSS to provide rapid updates of winds, unbiased by the presence of precipitation, has many other potential applications related to general tropical convection.

Convection↗
NASA NTRS2020

El Niño Related Tropical Land Surface Water and Energy Response in MERRA-2

Though El Niño events each have distinct evolutionary character they typically provide systematic large scale forcing for warming and increased drought frequency across the tropical continents. We assess this response in the MERRA-2 reanalysis and in a ten-member model AMIP ensemble. The lagged response (3-4 months) of mean tropical land temperature to El Niño warming in the Pacific Ocean is well represented. MERRA-2 reproduces the patterns of precipitation in the tropical regions, while the AMIP ensemble reproduces some regional responses better than others. Model skill is dependent on event forcing strength and temporal proximity to the peak of the sea surface warming. A composite approach centered on maximum Niño3.4 SSTs and lag relationships to energy fluxes and transports is used to identify mechanisms supporting tropical land warming. The composite necessarily moderates weather scale variability of the individual events, while retaining the systematic features across all events. We find that that reduced continental upward motions lead to reduced cloudiness and more shortwave radiation at the surface, as well as reduced precipitation. The increased shortwave heating at the land surface, along with reduced soil moisture leads to warmer surface temperature, more sensible heating and warming of the lower troposphere. While the composite provides a broad picture of the mechanisms governing the hydrologic response to El Niño forcing, the regional and temporal response in any given event can be quite variable. The 2015-16 El Niño, one of the strongest events, demonstrates some of the forced response noted in the composite, but with shifts in the evolution that depart from the composite, demonstrating the limitations of the composite and individuality of El Niño.

Michael G Bosilovich↗
NASA NTRS2019

Lightning NOx Production in the Tropics as Determined Using OMI NO2 Retrievals and WWLLN Stroke Data

Nitrogen oxide (NOx) production by lightning in the tropics is estimated using tropospheric NOx amounts (LNOx*) over deep convective grid boxes derived from OMI (Ozone Monitoring Instrument) nitrogen dioxide (NO2) slant columns and detection efficiency adjusted WWLLN (World Wide Lightning Location Network) flashes. The lightning NOx production efficiency (LNOx PE) in the tropics is determined for the austral and boreal summers of 2007 to 2011 by regressing regional mean daily values of LNOx* for individual seasons against daily flash totals during flash windows prior to the OMI overpass. LNOx PE is determined to be approximately two times larger over marine locations than over continental locations possibly because marine flashes are more energetic. Overall, the mean LNOx PE for the tropics is calculated to be 170 ± 100 mol per flash with values over the tropical Pacific (low flash rate region) being largest. The main contributors to uncertainties in PE are uncertainties in WWLLN flash detection efficiency, upper tropospheric NOx lifetime in the near field of convection, and air mass factor biases.

Dale J. Allen↗
NASA NTRS2015

Gravity Waves and Vertical Mixing in the Tropical Tropopause Layer during ATTREX

Vertical mixing in the Tropical Tropopause Layer is thought to be weak outside regionsof convective injection. Nevertheless, some studies indicate a rolefor nonconvective vertical mixing processes in maintaining tracer distributions.The TTL also has a broad spectrum of high amplitude gravity waves, which havebeen shown to play an important role in the water vapor distribution. These gravitywaves, a result of tropical convection, also havesubstantial shears associated with them (which may produce turbulent mixing). Recent aircraft experiments, specificallythe Airborne Tropical TRopopause EXperiment (ATTREX), have yielded an unprecendentedmeteorological dataset in the TTL, including not only the temperatures and horizontalwinds (which can be obtained from radiosondes), but high frequency vertical winds. These highfrequency measurements yield an opportunity to study turbulence in the nonconvectiveenvironment. The numerous vertical profiles, essentially producing curtains of high resolutionmeasurements across broad regions of the tropics, also yield an opportunity to obtain bothhorizontal and vertical information about medium scale gravity waves.This presentation examines three phases of ATTREX (fall, 2011, winter 2013, and winter 2014) inthe eastern and western Pacific. The focus will be on high amplitude wave motions, theirstructure, and turbulence.

Pfister, Leonhard↗
NASA NTRS2019

NASA Global Satellite and Model Data Products and Services for Tropical Cyclone Research

The lack of observations over vast tropical oceans is a major challenge for tropical cyclone research. Satellite observations and model reanalysis data play an important role in filling these- gaps. Established in the mid-1980's, the Goddard Earth Sciences Data and Information Services Center (GES DISC), as one of the 12 NASA data centers, archives and distributes data from several Earth science disciplines such as precipitation, atmospheric dynamics, atmospheric composition, hydrology, including well-known NASA satellite missions (e.g. TRMM, GPM) and model assimilation projects (MERRA-2). Acquiring datasets suitable for tropical cyclone research in a large data archive is a challenge for many, especially for those who are not familiar with satellite or model data. Over the years, the GES DISC has developed user-friendly data services. For example, Giovanni is an online visualization and analysis tool, allowing users to visualize and analyze over 2000 satellite- and model-based variables with a Web browser, without downloading data and software. In this chapter, we will describe data and services at the GES DISC with emphasis on tropical cyclone research. We will also present two case studies and discuss future plans.

Liu, Zhong↗
NASA NTRS2020

Deepti: Deep-Learning-Based Tropical Cyclone Intensity Estimation System

Tropical cyclones are one of the costliest natural disasters globally because of the wide range of associated hazards. Thus, an accurate diagnostic model for tropical cyclone intensity can save lives and property. There are a number of existing techniques and approaches that diagnose tropical cyclone wind speed using satellite data at a given time with varying success. This paper presents a deep learning-based objective, diagnostic estimate of tropical cyclone intensity from infrared satellite imagery with 13.24 kt Root Mean Squared Error (RMSE). In addition, a visualization portal in a production system is presented that displays deep learning output and contextual information for end users, one of the first of its kind.

Manil Maskey↗
NASA NTRS2019

A Large Source of Cloud Condensation Nuclei from New Particle Formation in the Tropics

Cloud condensation nuclei (CCN) can affect cloud properties and therefore the Earth’s radiative balance. New particle formation (NPF) from condensable vapours in the free troposphere has been suggested to contribute to CCN, especially in remote, pristine atmospheric regions, but direct evidence is sparse, and the magnitude of this contribution is uncertain. Here we use in-situ aircraft measurements of vertical profiles of aerosol size distributions to present a global-scale survey of NPF occurrence. We observed intense NPF occurring at high altitude in tropical convective regions over both the Pacific and Atlantic Oceans. Together with the results of chemical-transport models, our findings indicate that NPF persists at all longitudes as a global-scale band in the tropical upper troposphere, covering about 40% of the Earth’s surface. Furthermore, we find that this NPF in the tropical upper troposphere is a globally important source of CCN in the lower troposphere, where they can affect cloud properties. Our findings suggest that the production of CCN, as these new particles descend towards the surface, is currently not adequately captured in global models, because they tend to underestimate both the magnitude of tropical upper tropospheric NPF and the subsequent growth to CCN sizes. This has potential implications for cloud albedo and the global radiative balance.

Atmospheric chemistry↗
NASA NTRS2023

Seasonality of the Migrating Semidiurnal Tide in the Tropical Upper Mesosphere and Lower Thermosphere and its Thermodynamic and Momentum Budget

This work uses the Specified Dynamics-Whole Atmosphere Community Climate Model with Ionosphere/Thermosphere eXtension (SD-WACCM-X) to determine and explain the seasonality of the migrating semidiurnal tide (SW2) components of tropical upper mesosphere and lower thermosphere (UMLT) temperature, zonal wind, and meridional wind. This work also quantifies aliasing due to SW2 in satellite-based tidal estimates. Results show that during equinox seasons, the vertical profiles of tropical UMLT temperature SW2 and zonal-wind SW2’s amplitudes have a double-peak structure while they, along with meridional-wind SW2, have a single-peak structure in their amplitudes in June solstice. Hough mode reconstruction reveals that a linear combination of five SW2 Hough modes cannot fully reproduce these features. Tendency analysis reveals that for temperature, the adiabatic term, nonlinear advection term, and linear advection term are important. For the winds, the classical terms, nonlinear advection term, linear advection term, and gravity wave drag are important. Results of our alias analysis then indicate that SW2 can induce an ∼60% alias in zonal-mean and DW1 components calculated from sampling like that of the Thermosphere–Ionosphere–Mesosphere Energetics and Dynamics satellite and the Aura satellite. This work concludes that in situ generation by wave–wave interaction and/or by gravity waves plays significant roles in the seasonality of tropical UMLT temperature SW2, zonal-wind SW2, and meridional-wind SW2. The alias analysis further adds that one cannot simply assume that SW2 in the tropical UMLT is negligible.

Tides↗
NASA NTRSDate not supplied

Objectively Identifying Transverse Cirrus Bands in Tropical Cyclones using a Convolutional Neural Network

Transverse cirrus bands (TCBs) are a phenomenon that occurs in many mesoscale and synoptic weather systems, including tropical cyclones. TCBs are defined as "Bands of clouds oriented perpendicular to the flow in which they are embedded" (NOAA) and can be associated with low static stability and high environmental vertical wind shear in the upper levels (Kawashima 2021). TCBs in tropical cyclones are of particular interest due to their apparent occurrence and potential linkage to the tropical cyclone diurnal cycle, stronger tropical cyclones, and rapid intensification, where rapid intensification is an intensification rate of 30 knots or more in 24 hours (NHC).

John Mark Mayhall↗