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NASA NTRS1994

A satellite observational and numerical study of precipitation characteristics in western North Atlantic tropical cyclones

Special Sensor Microwave/Imager (SSM/I) observations were used to examine the spatial and temporal changes of the precipitation characteristics of tropical cyclones. SSM/I observations were also combined with the results of a tropical cyclone numerical model to examine the role of inner-core diabatic heating in subsequent intensity changes of tropical cyclones. Included in the SSM/I observations were rainfall characteristics of 18 named western North Atlantic tropical cyclones between 1987 and 1989. The SSM/I rain-rate algorithm that employed the 85-GHz channel provided an analysis of the rain-rate distribution in greater detail. However, the SSM/I algorithm underestimated the rain rates when compared to in situ techniques but appeared to be comparable to the rain rates obtained from other satellite-borne passive microwave radiometers. The analysis of SSM/I observations found that more intense systems had higher rain rates, more latent heat release, and a greater contribution from heavier rain to the total tropical cyclone rainfall. In addition, regions with the heaviest rain rates were found near the center of the most intense tropical cyclones. Observational analysis from SSM/I also revealed that the greatest rain rates in the inner-core regions were found in the right half of fast-moving cyclones, while the heaviest rain rates in slow-moving tropical cyclones were found in the forward half. The combination of SSM/I observations and an interpretation of numerical model simulations revealed that the correlation between changes in the inner core diabetic heating and the subsequent intensity became greater as the tropical cyclones became more intense.

Rodgers, Edward B.↗
NASA NTRS1995

Another look at the UBV variability of T Tauri stars

The UBV variability of classical T Tauri stars is investigated using a large data set compiled by Herbst et al. (1994). The analysis is based on the covariance of the UBV colors, which is independent of the obscuration and the temporal sampling, and is a powerful tool for finding trends that otherwise would be hidden in the complex time-dependence of the data. I find that there are two types of UBV variability and introduce the nomenclature 'ortho-' and 'para-UBV' variations, or in short 'type-O' and 'type-P' variations. Objects with a predominance of ortho-UBV variability show strong variability in both the Balmer and Paschen continua, whereas objects dominated by para-UBV changes vary mostly in the Paschen continuum. I show that type-O variations can be explained in terms of rotating spots, variable obscuration, or changes intrinsic to the source that obey the law Delta T(sub S)/T(sub S) varies as Delta n(sub H)/n(sub H), where T(sub S) and n(sub H) are, respectively, the gas temperature and the number density of hydrogen nuclei. Type-P variations can be explained only by changes intrinsic to the source with Delta T(sub S)/T(sub S) varies as - Delta n(sub H)/n(sub H), and I speculate on a possible origin for these changes. The covariance ellipse of the UBV colors is a versatile tool for studying the connection between variability and other spectral signatures of classical T Tauri stars; its use for this purpose is illustrated by studying the correlation between the presence of CO first-overtone bands in emission and the type of variability. I find that objects with CO band emission are also those with type-P variability and propose an observational test to validate this conclusion.

Safier, Pedro N.↗
NASA NTRS2017

Daily Ambient Air Pollution Metrics for Five Cities: Evaluation of Data Fusion-Based Estimates and Uncertainties

Spatiotemporal characterization of ambient air pollutant concentrations is increasingly relying on the combination of observations and air quality models to provide well-constrained, spatially and temporally complete pollutant concentration fields. Air quality models, in particular, are attractive, as they characterize the emissions, meteorological, and physiochemical process linkages explicitly while providing continuous spatial structure. However, such modeling is computationally intensive and has biases. The limitations of spatially sparse and temporally incomplete observations can be overcome by blending the data with estimates from a physically and chemically coherent model, driven by emissions and meteorological inputs. We recently developed a data fusion method that blends ambient ground observations and chemical transport-modeled (CTM) data to estimate daily, spatially resolved pollutant concentrations and associatedcorrelations. In this study, we assess the ability of the data fusion method to produce daily metrics (i.e., 1-hr max, 8-hr max, and 24-hr average) of ambient air pollution that capture spatiotemporal air pollution trends for 12 pollutants (CO, NO2, NOx, O3, SO2, PM (sub10), PM (sub 2.5), and five PM (sub 2.5) components) across five metropolitan areas (Atlanta, Birmingham, Dallas, Pittsburgh, and St. Louis), from 2002 to 2008. Three sets of comparisons are performed: (1) the CTM concentrations are evaluated for each pollutant and metropolitan domain, (2) the data fusion concentrations are compared with the monitor data, (3) a comprehensive cross-validation analysis against observed data evaluates the quality of the data fusion model simulations across multiple metropolitan domains. The resulting daily spatial field estimates of air pollutant concentrations and uncertainties are not only consistent with observations, emissions, andmeteorology, but substantially improve CTM-derived results for nearly all pollutants and all cities, with the exception of NO2 for Birmingham. The greatest improvements occur for O3 and PM (sub 2.5). Squared spatiotemporal correlation coefficients range between simulations and observations determined using cross-validation across all cities for air pollutants of secondary and mixed origins are R-squared equal to 0.88-0.93 (O3), 0.81-0.89 (SO4), 0.67-0.83 (PM (sub 2.5)), 0.52-0.72 (NO3), 0.43-0.80 (NH4), 0.32-0.51 (OC), and 0.14-0.71 (PM (sub 10)). Results for relatively homogeneous pollutants of secondary origin, tend to be better than those for more spatially heterogeneous (larger spatial gradients) pollutants of primary origin (NOx, CO, SO2 and EC). Generally, background concentrations and spatial concentration gradients reflect interurban airshed complexity and the effects of regional transport, whereas daily spatial pattern variability shows intra urban consistency in the fused data. With sufficiently high CTM spatial resolution, traffic-related pollutants exhibit gradual concentration gradients that peak toward the urban centers. Ambient pollutant concentration uncertainty estimates for the fused data are both more accurate and smaller than those for either the observations or the model simulations alone.

spatiotemporal fusion↗
NASA NTRS2005

Microwave Signatures of Melting/Refreezing Snow: Observations and Modeling Using Dense Medium Radiative Transfer Theory

Microwave brightness temperatures of snow covered terrains can be modeled by means of the Dense Radiative Transfer Medium Theory (DMRT). In a dense medium, such as snow, the assumption of independent scattering is no longer valid and the scattering of correlated scatterers must be considered. In the DMRT, this is done considering a pair distribution function of the particles position. In the electromagnetic model, the snowpack is simulated as a homogeneous layer having effective permittivity and albedo calculated through the DMRT. In order to account for clustering of snow crystals, a model of cohesive particles can be applied, where the cohesion between the particles is described by means of a dimensionless parameters called stickiness (z), representing a measure of the inversion of the attraction of the particles. The lower the z the higher the stickiness. In this study, microwave signatures of melting and refreezing cycles of seasonal snowpacks at high altitudes are studied by means of both experimental and modeling tools. Radiometric data were collected 24 hours per day by the University of Michigan Tower Mounted Radiometer System (TMRS). The brightness temperatures collected by means of the TMRS are simulated by means of a multi-layer electromagnetic model based on the dense medium theory with the inputs to the model derived from the data collected at the snow pits and from the meteorological station. The paper is structured as follows: in the first Section the temperature profiles recorded by the meteorological station and the snow pit data are presented and analyzed; in the second Section, the characteristics of the radiometric system used to collect the brightness temperatures are reported together with the temporal behavior of the recorded brightness temperatures; in the successive Section the multi-layer DMRT-based electromagnetic model is described; in the fourth Section the comparison between modeled and measured brightness temperatures is discussed. We dedicate the last Section to the conclusions and future works.

Tedesco, Marco↗
NASA NTRS2008

A Statistical Filtering Approach for Gravity Recovery and Climate Experiment (GRACE) Gravity Data

We describe and analyze a statistical filtering approach for GRACE data that uses a parametrized model for the temporal evolution of the GRACE coefficients. After least-squares adjustment, a statistical test is performed to assess the significance of the estimated parameters. If the test is passed, the parameters are used by the filter in the reconstruction of the field; otherwise they are rejected. The test is performed, and the filter is formed, separately for annual components of the model and the trend. This new approach is distinct from Gaussian smoothing since it uses the data themselves to test for specific components of the time-varying gravity field. The statistical filter appears inherently to remove most of the "stripes" present in the GRACE fields, although destriping the fields prior to filtering seems to help the trend recovery. We demonstrate that the statistical filter produces reasonable maps for the annual components and trend. We furthermore assess the statistical filter for the annual components using ground-based GPS data in South America by assuming that the annual component of the gravity signal is associated only with groundwater storage. The un-destriped, statistically filtered field has a X2 value relative to the GPS data consistent with the best result from smoothing. In the space domain, the statistical filters are qualitatively similar to Gaussian smoothing. Unlike Gaussian smoothing, however, the statistical filter has significant sidelobes, including large negative sidelobes on the north-south axis, potentially revealing information on the errors, and the correlations among the errors, for the GRACE coefficients.

Davis. J. L.↗
NASA NTRS1994

Directions of Moving Plaids is Biased by Asymmetric Viewing Windows

Directionally selective V1 neurons are tuned to particular spatio-temporal frequencies and respond to local 1-D edge motion. At least some MT neurons however appear to respond to the actual velocity of moving 2D patterns. To better understand how the 1D local motion information available from VI is integrated to derive a 2D velocity signal we investigated human perception of moving plaids, 2-D patterns composed of the sum of two 1-D sinusoidal gratings of different orientations. We measured the effect of the shape of the viewing window on the perceived direction of plaid motion. The plaids were spatially windowed by 2-D Gaussians with unequal standard deviations (sigma 1, sigma 2). Four observers indicated perceived direction by adjusting a pointer. Direction errors were measured as a function of the difference between window orientation and true plaid direction (DELTA THETA) for several grating spatial frequencies (SF = 0.3, 0.6, 1.2 c/d) and window aspect ratios (AR = sigma 1/sigma 2 = 1, 1.4, 2, 4). Observers showed systematic errors in perceived direction (approx. 15 for AR = 4 and SF = 0.6 c/d) that peaked at DELTA THETA approx. 40. The errors increased for increasing aspect ratio and decreased for increasing spatial frequencies (or number of cycles). These results show that despite the unambiguous motion of the plaids, under these conditions human misperceive the motion. These data constrain models of motion integration from V1 to MT and, in particular, are inconsistent with algorithms that use either the Intersection of Constraints rule or cross correlation to compute the perceived direction of motion.

Beutter, B. R.↗
NASA NTRS2014

LADEE UVS (UltraViolet Visible Spectrometer) and the Search for Lunar Exospheric Dust: A Detailed Spectral Analysis

The Lunar Atmosphere and Dust Environment Explorer (LADEE) executed science observations in lunar orbit spanning 2013-Oct-16- 2014-04-18 UT. LADEE's Ultraviolet/Visible Spectrometer (UVS) studies the composition and temporal variations of the tenuous lunar exosphere and dust environment, utilizing two sets of optics: a limb-viewing telescope, and a solar-viewer. The limb-viewing telescope observes illuminated dust and emitting gas species while the Sun is just behind the lunar limb. The solar viewer, with its diffuser, allows UVS to also stare directly at the solar disk as it approaches the limb, sampling progressively lower exosphere altitudes. Solar viewer "Occultation" activities occur at the lunar sunrise limb, as the LADEE spacecraft passes into the lunar night side, facing the Sun (the spacecraft orbit is near-equatorial retrograde). A loss of transmission of sunlight occurs by the occultation of dust grains along the line-of-sight. So-called "Inertial Limb" activities have the limb-viewing telescope pointed at the lit exosphere just after the Sun has set. Inertial Limb activities follow a similar progression of diminishing sampling altitudes but hold the solar elongation angle constant so the zodiacal light contribution remains constant while seeking to observe the weak lunar horizon glow. On the dark side of the moon, "Sodium Tail" activities pointed the limb-viewing telescope in the direction of the Moon's sodium tail (similar to anti-sunward), during different lunar phases. Of the UVS data sets, these show the largest excess of scattered blue light, indicative of the presence of small (approximately 100 nm) dust grains in the tail. Correlations are sought between dust in the sodium tail and meteor streams and magnetotail crossings to investigate impact- versus electrostatic-lofting. Once lofted, nanoparticles can become charged and picked up by the solar wind. The LADEE UVS Occultation, Inertial Limb, and Sodium Tail spectral datasets provide evidence of a lunar dust exosphere.

LADEE↗
NASA NTRS2000

Sensitivity of Spacebased Microwave Radiometer Observations to Ocean Surface Evaporation

Ocean surface evaporation and the latent heat it carries are the major components of the hydrologic and thermal forcing on the global oceans. However, there is practically no direct in situ measurements. Evaporation estimated from bulk parameterization methods depends on the quality and distribution of volunteer-ship reports which are far less than satisfactory. The only way to monitor evaporation with sufficient temporal and spatial resolutions to study global environment changes is by spaceborne sensors. The estimation of seasonal-to-interannual variation of ocean evaporation, using spacebased measurements of wind speed, sea surface temperature (SST), and integrated water vapor, through bulk parameterization method,s was achieved with reasonable success over most of the global ocean, in the past decade. Because all the three geophysical parameters can be retrieved from the radiance at the frequencies measured by the Scanning Multichannel Microwave Radiometer (SMMR) on Nimbus-7, the feasibility of retrieving evaporation directly from the measured radiance was suggested and demonstrated using coincident brightness temperatures observed by SMMR and latent heat flux computed from ship data, in the monthly time scale. However, the operational microwave radiometers that followed SMMR, the Special Sensor Microwave/Imager (SSM/I), lack the low frequency channels which are sensitive to SST. This low frequency channels are again included in the microwave imager (TMI) of the recently launched Tropical Rain Measuring Mission (TRMM). The radiance at the frequencies observed by both TMI and SSM/I were simulated through an atmospheric radiative transfer model using ocean surface parameters and atmospheric temperature and humidity profiles produced by the reanalysis of the European Center for Medium Range Weather Forecast (ECMWF). From the same ECMWF data set, coincident evaporation is computed using a surface layer turbulent transfer model. The sensitivity of the radiance to evaporation over various seasons and geographic locations are examined. The microwave frequencies with radiance that are significant correlated with evaporation are identify and capability of estimating evaporation directly from TMI will be discussed.

Liu, Timothy W.↗
NASA NTRS1998

Chicken (Gallus domesticus) inner ear afferents

Neurons from the vestibular (VG) and the statoacoustic (SAG) ganglion of the chick (Gallus domesticus) were evaluated histologically and morphometrically. Embryos at stages 34 (E8 days), 39 (E13 days) and 44 (E18 days) were sacrificed and temporal bones microdissected. Specimens were embedded in JB-4 methacrylate plastic, and stained with a mixture of 0.2% toluidine blue (TB) and 0.1% basic Fuschin in 25% ethanol or with a mixture of 2% TB and 1% paraphenylenediamine (PDA) for axon and myelin measurement study. Images of the VIIIth nerve were produced by a V150 (R) color imaging system and the contour of 200-300 neuronal bodies (perikarya) was traced directly on a video screen with a mouse in real time. The cross-sectional area of VG perikarya was 67.29 micrometers2 at stage 34 (E8), 128.46 micrometers2 at stage 39 (E13) and 275.85 micrometers2 at stage 44 (E18). The cross-sectional area of SAG perikarya was 62.44 micrometers2 at stage 34 (E8), 102.05 micrometers2 at stage 39 (E13) and 165.02 micrometers2 at stage 44 (E18). A significant cross-sectional area increase of the VG perikarya between stage 39 (E13) and stage 44 (E18) was determined. We randomly measured the cross-sectional area of myelin and axoplasm of hatchling afferent nerves, and found a correspondence between axoplasmic and myelin cross-sectional area in the utricular, saccular and semicircular canal nerve branches of the nerve. The results suggest that the period between stage 34 (E8) and 39 (E13) is a critical period for afferent neuronal development. Physiological and behavioral vestibular properties of developing and maturing hatchlings may change accordingly. The results compliment previous work by other investigators and provide valuable anatomical measures useful to correlate physiological data obtained from stimulation of the whole nerve or its parts.

NASA Discipline Neuroscience↗
NASA NTRS2013

Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties

Non-vascular plants (lichens and mosses) are significant components of tundra landscapes and may respond to climate change differently from vascular plants affecting ecosystem carbon balance. Remote sensing provides critical tools for monitoring plant cover types, as optical signals provide a way to scale from plot measurements to regional estimates of biophysical properties, for which spatial-temporal patterns may be analyzed. Gas exchange measurements were collected for pure patches of key vegetation functional types (lichens, mosses, and vascular plants) in sedge tundra at Barrow, AK. These functional types were found to have three significantly different values of light use efficiency (LUE) with values of 0.013 plus or minus 0.0002, 0.0018 plus or minus 0.0002, and 0.0012 plus or minus 0.0001 mol C mol (exp -1) absorbed quanta for vascular plants, mosses and lichens, respectively. Discriminant analysis of the spectra reflectance of these patches identified five spectral bands that separated each of these vegetation functional types as well as nongreen material (bare soil, standing water, and dead leaves). These results were tested along a 100 m transect where midsummer spectral reflectance and vegetation coverage were measured at one meter intervals. Along the transect, area-averaged canopy LUE estimated from coverage fractions of the three functional types varied widely, even over short distances. The patch-level statistical discriminant functions applied to in situ hyperspectral reflectance data collected along the transect successfully unmixed cover fractions of the vegetation functional types. The unmixing functions, developed from the transect data, were applied to 30 m spatial resolution Earth Observing-1 Hyperion imaging spectrometer data to examine variability in distribution of the vegetation functional types for an area near Barrow, AK. Spatial variability of LUE was derived from the observed functional type distributions. Across this landscape, a fivefold variation in tundra LUE was observed. LUE calculated from the functional type cover fractions was also correlated to a spectral vegetation index developed to detect vegetation chlorophyll content. The concurrence of these alternate methods suggest that hyperspectral remote sensing can distinguish functionally distinct vegetation types and can be used to develop regional estimates of photosynthetic LUE in tundra landscapes.

VEGETATION↗
NASA NTRS1994

Spectral evolution of microwaves and hard X-rays in the 1989 March 18 flare and its interpretation

We analyze the time variation of microwave spectra and hard X-ray spectra of 1989 March 18, which are obtained from the Solar Array at the Owens Valley Radio Observatory (OVRO) and the Hard X-Ray Burst Spectrometer (HXRBS) on the Solar Maximum Mission (SMM), respectively. From this observation, it is noted that the hard X-ray spectra gradually soften over 50 - 200 keV on-and-after the maximum phase while the microwaves at 1 - 15 GHz show neither a change in spectral shape nor as rapid a decay as hard X-rays. This leads to decoupling of hard X-rays from the microwaves in the decay phase away from their good correlation seen in the initial rise phase. To interpret this observation, we adopt a view that microwave-emitting particles and hard X-ray particles are physically separated in an inhomogeneous magnetic loop, but linked via interactions with the Whistler waves generated during flares. From this viewpoint, it is argued that the observed decoupling of microwaves from hard X-rays may be due to the different ability of each source region to maintain high energy electrons in response to the Whistler waves passing through the entire loop. To demonstrate this possibility, we solve a Fokker-Planck equation that describes evolution of electrons interacting with the Whistler waves, taking into account the variation of Fokker-Planck coefficients with physical quantities of the background medium. The numerical Fokker-Planck solutions are then used to calculate microwave spectra and hard X-ray spectra for agreement with observations. Our model results are as follows: in a sronger field region, the energy loss by electron escape due to scattering by the waves is greatly enhanced resulting in steep particle distributions that reproduce the observed hard X-ray spectra. In a region with weaker fields and lower density, this loss term is reduced allowing high energy electrons to survive longer so that microwaves can be emitted there in excess of hard X-rays during the decay phase of the flare. Our results based on spectral fitting of a flare event are discussed in comparison with previous studies of microwaves and hard X-rays based on either temporal or spatial information.

Lee, Jeongwoo W.↗
NASA NTRS2018

Quantifying Methane Leak Emissions by Fused Airborne Imaging Spectroscopy with in Situ Surface Mobile and Airborne Observations of a California Producing Oil Field

Methane (CH4) emission budgets remain uncertain and are projected to grow as oil and gas production from short-lived wells increases and their subsequent transport through aging gas distribution networks. Orders-of-magnitude variations in temporal, spatial, and emission scales present a key challenge to leak detection and quantification. Also, the probability distributions for large and stochastic, leaky systems such as geological reservoirs (by natural migration-seeps) and petroleum production from those reservoirs remain largely unknown, needed to address current approach limitations. The scale of many petroleum systems favors remote sensing, but the sensitivity of such systems often precludes detection of weak emissions. Consequently, an accurate evaluation requires that the relative contribution from the emission "tails" of small leaks also be quantified, which is best carried out using high-sensitivity in situ methods. Fusion of remote sensing and in situ approaches leverages complementary capabilities to address these limitations. We show results from mobile surface (AMOG) and airborne in situ (AJAX) and thermal-infrared (TIR) hyperspectral imaging spectroscopy (Mako) data applied to a producing oil field in the California Central Valley near Bakersfield. AMOG is an automobile-based mobile lab that measures 13 trace gases, aerosol size distributions and vertical profiles, 3D winds and other meteorology, and atmospheric column measurements by solar spectroscopy at highway speeds. AJAX measures 5 trace gases and 3D winds at ~140 m/s. Mako is a broad-area TIR imaging spectrometer that can discriminate multiple gases present in each pixel acquired. In situ-derived, total field emissions were 31±16 Gg/yr CH4. This was compared with Mako-derived emissions from all plumes identified across the study site. We found that super-emitters were not the dominant emissions mode and the spatial pattern of plume locations from production infrastructure was correlated to geological structures.

Leifer, Ira↗
NASA NTRS2015

Investigation of North American Vegetation Variability under Recent Climate: A Study Using the SSiB4/TRIFFID Biophysical/Dynamic Vegetation Model

Recent studies have shown that current dynamic vegetation models have serious weaknesses in reproducing the observed vegetation dynamics and contribute to bias in climate simulations. This study intends to identify the major factors that underlie the connections between vegetation dynamics and climate variability and investigates vegetation spatial distribution and temporal variability at seasonal to decadal scales over North America (NA) to assess a 2-D biophysical model/dynamic vegetation model's (Simplified Simple Biosphere Model version 4, coupled with the Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID)) ability to simulate these characteristics for the past 60 years (1948 through 2008). Satellite data are employed as constraints for the study and to compare the relationships between vegetation and climate from the observational and the simulation data sets. Trends in NA vegetation over this period are examined. The optimum temperature for photosynthesis, leaf drop threshold temperatures, and competition coefficients in the Lotka-Volterra equation, which describes the population dynamics of species competing for some common resource, have been identified as having major impacts on vegetation spatial distribution and obtaining proper initial vegetation conditions in SSiB4/TRIFFID. The finding that vegetation competition coefficients significantly affect vegetation distribution suggests the importance of including biotic effects in dynamical vegetation modeling. The improved SSiB4/TRIFFID can reproduce the main features of the NA distributions of dominant vegetation types, the vegetation fraction, and leaf area index (LAI), including its seasonal, interannual, and decadal variabilities. The simulated NA LAI also shows a general increasing trend after the 1970s in responding to warming. Both simulation and satellite observations reveal that LAI increased substantially in the southeastern U.S. starting from the 1980s. The effects of the severe drought during 1987-1992 and the last decade in the southwestern U.S. on vegetation are also evident from decreases in the simulated and satellite-derived LAIs. Both simulated and satellite-derived LAIs have the strongest correlations with air temperature at northern middle to high latitudes in spring reflecting the effect of these climatic variables on photosynthesis and phenological processes. Meanwhile, in southwestern dry lands, negative correlations appear due to the heat and moisture stress there during the summer. Furthermore, there are also positive correlations between soil wetness and LAI, which increases from spring to summer. The present study shows both the current improvements and remaining weaknesses in dynamical vegetation models. It also highlights large continental-scale variations that have occurred in NA vegetation over the past six decades and their potential relations to climate. With more observational data availability, more studies with differentmodels and focusing on different regions will be possible and are necessary to achieve comprehensive understanding of the vegetation dynamics and climate interactions.

climate variability↗
NASA NTRS2006

Vertical Moist Thermodynamic Structure and Spatial-Temporal Evolution of the MJO in AIRS Observations

The atmospheric moisture and temperature profiles from the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit on the NASA Aqua mission, in combination with the precipitation from the Tropical Rainfall Measuring Mission (TRMM), are employed to study the vertical moist thermodynamic structure and spatial-temporal evolution of the Madden-Julian oscillation (MJO). The AIRS data indicate that, in the Indian Ocean and western Pacific, the temperature anomaly exhibits a trimodal vertical structure: a warm (cold) anomaly in the free troposphere (800-250 hPa) and a cold (warm) anomaly near the tropopause (above 250 hPa) and in the lower troposphere (below 800 hPa) associated with enhanced (suppressed) convection. The AIRS moisture anomaly also shows markedly different vertical structures as a function of longitude and the strength of convection anomaly. Most significantly, the AIRS data demonstrate that, over the Indian Ocean and western Pacific, the enhanced (suppressed) convection is generally preceded in both time and space by a low-level warm and moist (cold and dry) anomaly and followed by a low-level cold and dry (warm and moist) anomaly. The MJO vertical moist thermodynamic structure from the AIRS data is in general agreement, particularly in the free troposphere, with previous studies based on global reanalysis and limited radiosonde data. However, major differences in the lower-troposphere moisture and temperature structure between the AIRS observations and the NCEP reanalysis are found over the Indian and Pacific Oceans, where there are very few conventional data to constrain the reanalysis. Specifically, the anomalous lower-troposphere temperature structure is much less well defined in NCEP than in AIRS for the western Pacific, and even has the opposite sign anomalies compared to AIRS relative to the wet/dry phase of the MJO in the Indian Ocean. Moreover, there are well-defined eastward-tilting variations of moisture with height in AIRS over the central and eastern Pacific that are less well defined, and in some cases absent, in NCEP. In addition, the correlation between MJO-related mid-tropospheric water vapor anomalies and TRMM precipitation anomalies is considerably more robust in AIRS than in NCEP, especially over the Indian Ocean. Overall, the AIRS results are quite consistent with those predicted by the frictional Kelvin-Rossby wave/conditional instability of the second kind (CISK) theory for the MJO.

troposhere↗
NASA NTRSDate not supplied

Exploring the Elevated Water Vapor Signal Associated With the Free Tropospheric Biomass Burning Plume Over the Southeast Atlantic Ocean

In southern Africa, widespread agricultural fires produce substantial biomass burning (BB) emissions over the region. The seasonal smoke plumes associated with these emissions are then advected westward over the persistent stratocumulus cloud deck in the southeast Atlantic (SEA) Ocean, resulting in aerosol effects which vary with time and location. Much work has focused on the effects of these aerosol plumes, but previous studies have also described an elevated free tropospheric water vapor signal over the SEA. Water vapor influences climate in its own right, and it is especially important to consider atmospheric water vapor when quantifying aerosol–cloud interactions and aerosol radiative effects. Here we present airborne observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign over the SEA Ocean. In observations collected from multiple independent instruments on the NASA P-3 aircraft (from near-surface to 6–7 km), we observe a strongly linear correlation between pollution indicators (carbon monoxide (CO) and aerosol loading) and atmospheric water vapor content, seen at all altitudes above the boundary layer. The focus of the current study is on the especially strong correlation observed during the ORACLES-2016 deployment (out of Walvis Bay, Namibia), but a similar relationship is also observed in the August 2017 and October 2018 ORACLES deployments. Using reanalyses from the European Centre for Medium-Range Weather Forecasts (ECMWF) and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and specialized WRF-Chem simulations, we trace the plume–vapor relationship to an initial humid, smoky continental source region, where it mixes with clean, dry upper tropospheric air and then is subjected to conditions of strong westward advection, namely the southern African easterly jet (AEJ-S). Our analysis indicates that air masses likely left the continent with the same relationship between water vapor and carbon monoxide as was observed by aircraft. This linear relationship developed over the continent due to daytime convection within a deep continental boundary layer (up to ∼5–6 km) and mixing with higher-altitude air, which resulted in fairly consistent vertical gradients in CO and water vapor, decreasing with altitude and varying in time, but this water vapor does not originate as a product of the BB combustion itself. Due to a combination of conditions and mixing between the smoky, moist continental boundary layer and the dry and fairly clean upper-troposphere air above (∼6 km), the smoky, humid air is transported by strong zonal winds and then advected over the SEA (to the ORACLES flight region) following largely isentropic trajectories. Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) back trajectories support this interpretation. This work thus gives insights into the conditions and processes which cause water vapor to covary with plume strength. Better understanding of this relationship, including how it varies spatially and temporally, is important to accurately quantify direct, semi-direct, and indirect aerosol effects over this region.

Kristina Pistone↗
NASA NTRS2023

Comparison of Dust Optical Depth From Multi-Sensor Products and MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) Dust Reanalysis Over North Africa, the Middle East, and Europe

Aerosol reanalysis datasets are model-based, observationally constrained, continuous 3D aerosol fields with a relatively high temporal frequency that can be used to assess aerosol variations and trends, climate effects, and impacts on socioeconomic sectors, such as health. Here we compare and assess the recently published MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) high-resolution regional desert dust reanalysis over northern Africa, the Middle East, and Europe (NAMEE) with a combination of ground-based observations and space-based dust retrievals and products. In particular, we compare the total and coarse dust optical depth (DOD) from the new reanalysis with DOD products derived from MODIS (MODerate resolution Imaging Spectroradiometer), MISR (Multi-angle Imaging SpectroRadiometer), and IASI (Infrared Atmospheric Sounding Interferometer) spaceborne instruments. Despite the larger uncertainties, satellite-based datasets provide a better geographical coverage than ground-based observations, and the use of different retrievals and products allows at least partially overcoming some single-product weaknesses in the comparison. Nevertheless, limitations and uncertainties due to the type of sensor, its operating principle, its sensitivity, its temporal and spatial resolution, and the methodology for retrieving or further deriving dust products are factors that bias the reanalysis assessment. We, therefore, also use ground-based DOD observations provided by 238 stations of the AERONET (AErosol RObotic NETwork) located within the NAMEE region as a reference evaluation dataset. In particular, prior to the reanalysis assessment, the satellite datasets were evaluated against AERONET, showing moderate underestimations in the vicinities of dust sources and downwind regions, whereas small or significant overestimations, depending on the dataset, can be found in the remote regions. Taking these results into consideration, the MONARCH reanalysis assessment shows that total and coarse-DOD simulations are consistent with satellite- and ground-based data, qualitatively capturing the major dust sources in the area in addition to the dust transport patterns. Moreover, the MONARCH reanalysis reproduces the seasonal dust cycle, identifying the increased dust activity that occurred in the NAMEE region during spring and summer. The quantitative comparison between the MONARCH reanalysis DOD and satellite multi-sensor products shows that the reanalysis tends to slightly overestimate the desert dust that is emitted from the source regions and underestimate the transported dust over the outflow regions, implying that the model's removal of dust particles from the atmosphere, through deposition processes, is too effective. More specifically, small positive biases are found over the Sahara desert (0.04) and negative biases over the Atlantic Ocean and the Arabian Sea (−0.04), which constitute the main pathways of the long-range dust transport. Considering the DOD values recorded on average there, such discrepancies can be considered low, as the low relative bias in the Sahara desert (< 50 %) and over the adjacent maritime regions (< 100 %) certifies. Similarly, over areas with intense dust activity, the linear correlation coefficient between the MONARCH reanalysis simulations and the ensemble of the satellite products is significantly high for both total and coarse DOD, reaching 0.8 over the Middle East, the Atlantic Ocean, and the Arabian Sea and exceeding it over the African continent. Moreover, the low relative biases and high correlations are associated with regions for which large numbers of observations are available, thus allowing for robust reanalysis assessment.

Michail Mytilinaios↗
NASA NTRS1993

Transport and residence times of tropospheric aerosols inferred from a global three-dimensional simulation of Pb-210

A global three-dimensional model is used to investigate the transport and tropospheric residence time of Pb-210, an aerosol tracer produced in the atmosphere by radioactive decay of Rn-222 emitted from soils. The model uses meteorological input with 4 deg x 5 deg horizontal resolution and 4-hour temporal resolution from the Goddard Institute for Space Studies general circulation model (GCM). It computes aerosol scavenging by convective precipitation as part of the wet convective mass transport operator in order to capture the coupling between vertical transport and rainout. Scavenging in convective precipitation accounts for 74% of the global Pb-210 sink in the model; scavenging in large-scale precipitation accounts for 12%, and scavenging in dry deposition accounts for 14%. The model captures 63% of the variance of yearly mean Pb-210 concentrations measured at 85 sites around the world with negligible mean bias, lending support to the computation of aerosol scavenging. There are, however, a number of regional and seasonal discrepancies that reflect in part anomalies in GCM precipitation. Computed residence times with respect to deposition for Pb-210 aerosol in the tropospheric column are about 5 days at southern midlatitudes and 10-15 days in the tropics; values at northern midlatitudes vary from about 5 days in winter to 10 days in summer. The residence time of Pb-210 produced in the lowest 0.5 km of atmosphere is on average four times shorter than that of Pb-210 produced in the upper atmosphere. Both model and observations indicate a weaker decrease of Pb-210 concentrations between the continental mixed layer and the free troposphere than is observed for total aerosol concentrations; an explanation is that Rn-222 is transported to high altitudes in wet convective updrafts, while aerosols and soluble precursors of aerosols are scavenged by precipitation in the updrafts. Thus Pb-210 is not simply a tracer of aerosols produced in the continental boundary layer, but also of aerosols derived from insoluble precursors emitted from the surface of continents. One may draw an analogy between Pb-210 and nitrate, whose precursor NO(sub x) is sparingly soluble, and explain in this manner the strong correlation observed between nitrate and Pb-210 concentrations over the oceans.

Balkanski, Yves J.↗
NASA NTRS2021

Observation of absorbing aerosols above clouds over the South-East Atlantic Ocean from the geostationary satellite SEVIRI - Part 2: Comparison with MODIS and aircraft measurements from the CLARIFY-2017 field campaign

To evaluate the SEVIRI retrieval for aerosols above clouds presented in Part 1 of the companion paper, the algorithm is applied over the south-east Atlantic Ocean during the CLARIFY-2017 field campaign period. The first step of our analysis compares the retrieved aerosol and cloud properties against equivalent products from the MODIS MOD06ACAERO retrieval (Meyer et al., 2015). While the correlation between the two satellite retrievals of the above-cloud aerosol optical thickness (AOT) is good (R = 0.78), the AOT retrieved by SEVIRI is 20.3 % smaller than that obtained from the MODIS retrieval. This difference in AOT is attributed mainly to the more absorbing aerosol model assumed for the SEVIRI retrieval compared to MODIS. The underlying cloud optical thickness (COT) derived from the two satellites is in good agreement (R = 0.90). The cloud droplet effective radius (CER) retrieved by SEVIRI is consistently smaller than MODIS by 2.2 µm, which is mainly caused by the use of different spectral bands of the satellite instruments. In the second part of our analysis, we compare the forecast water vapour profiles used for the SEVIRI atmospheric correction as well as the aforementioned aerosol and cloud products with in situ measurements made from the Facility for Airborne Atmospheric Measurements (FAAM) aircraft platform during the CLARIFY-2017 campaign. Around Ascension Island, the column water vapour used to correct the SEVIRI signal is overestimated by 3.1 mm in the forecast compared to that measured by dropsondes. However, the evidence suggests that the accuracy of the atmospheric correction improves closer to the African coast. Consistency is observed between the SEVIRI above-cloud AOT and in situ measurements (from cavity ring-down spectroscopy instruments) when the measured single-scattering albedo is close to that assumed in the retrieval algorithm. On the other hand, the satellite retrieval overestimates the AOT when the assumed aerosol model is not absorbing enough. Consistency is also found between the cloud properties retrieved by SEVIRI and the CER measured by a cloud droplet probe and the liquid water path derived from a microwave radiometer. Despite the instrumental limitations of the geostationary satellite, the consistency obtained between SEVIRI, MODIS and the aircraft measurements demonstrates the ability of the retrieval in providing additional information on the temporal evolution of the aerosol properties above clouds.

absorbing aerosols↗