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At least 613 records · Page 34

Detection and Socio-Economic Attribution of Groundwater Depletion in India

Groundwater is a critical resource for both consumption and food security in India, where groundwater management faces significant challenges due to climate change and anthropogenic activities. Although several studies explored groundwater variability in India, few have focused on the socioeconomic attribution of these changes, utilizing data from industries, population and water demand. In this study, trends in groundwater storage were examined by leveraging the largest in situ dataset ever collated in India from ~27,000 groundwater wells, satellite-based terrestrial-water-storage estimates, and hydrological model simulations. Five major hotspots of groundwater depletion across India were identified using in situ measurements and previously untapped socioeconomic datasets to attribute these trends. Approximately 16% of Indian groundwater monitoring stations exhibited systematically decreasing trends in groundwater levels. These hotspots are primarily concentrated in the northern and northwestern parts of India as well as in the states of Chhattisgarh, West Bengal, and Kerala. The north/northwestern hotspots have experienced a staggering loss of ~6.46 × 10^10 m3 of water over the past two decades. The factors contributing to this depletion include population growth, rapid urbanization, proliferation of factories and the expansion of agriculture.

Gautam Kunwar↗

North Atlantic Aerosol Radiative Impacts Based on Satellite Measurements and Aerosol Intensive Properties from TARFOX and ACE-2

We estimate the impact of North Atlantic aerosols on the net short-wave flux at the tropopause by combining satellite-derived aerosol optical depth (AOD) maps with model aerosol properties determined via closure analyses in TARFOX and ACE 2. We exclude African dust, primarily by restricting latitudes to 25-60 N. The analyses use in situ aerosol composition measurements and air- and ship-borne sun-photometer measurements of AOD spectra. The aerosol model yields computed flux sensitivities (dFlux/dAOD) that agree with measurements by airborne flux radiometers in TARFOX. Its midvisible single-scattering albedo is 0.9. which is in the range obtained from in situ measurements of scattering and absorption in both TARFOX and ACE 2. Combining satellite-derived AOD maps with the aerosol model yields maps of 24-hour average net radiative flux changes. For simultaneous AVHRR, radiance measurements exceeded the sunphotometer AODs by about 0.04. However. shipboard sunphotometer and AVHRR AODs agreed Within 0.02 for data acquired during satellite overflights on two other days. We discuss attempts to demonstrate column closure within the MBL by comparing shipboard sunphotometer AODs and values calculated from simultaneous shipboard in-situ aerosol size distribution measurements. These comparisons were mostly unsuccessful, but they illustrate the difficulties inherent in this type of closure analysis. Specifically, AODs derived from near-surface in-situ size distribution measurements are extremely sensitive to the assumed hygroscopic growth model that itself requires an assumption of particle composition as a function of height and size, to the radiosonde-measured relative humidity, and to the vertical profile of particle number. We investigate further the effects of hygroscopic particle growth within the MBL by using shipboard lidar aerosol backscatter profiles together with the sunphotometer AOD.

Russell, P. B.↗

Toward Scientific Numerical Modeling

Ultimately, scientific numerical models need quantified output uncertainties so that modeling can evolve to better match reality. Documenting model input uncertainties and verifying that numerical models are translated into code correctly, however, are necessary first steps toward that goal. Without known input parameter uncertainties, model sensitivities are all one can determine, and without code verification, output uncertainties are simply not reliable. To address these two shortcomings, two proposals are offered: (1) an unobtrusive mechanism to document input parameter uncertainties in situ and (2) an adaptation of the Scientific Method to numerical model development and deployment. Because these two steps require changes in the computational simulation community to bear fruit, they are presented in terms of the Beckhard-Harris-Gleicher change model.

Kleb, Bil↗

Joint Assimilation of Surface, GEO, and LEO CO, NO2, and O3 In Situ and Partial Column/Profile Retrievals with WRF-Chem/DART

Low earth orbiting (LEO) satellites like OMI or TROPOMI and geostationary satellites like TEMPO (to be launched January 2023) provide ozone (O3) retrieval profiles that extend into the stratosphere. Regional models like WRF-Chem generally do not include the stratosphere and have vertical grids that end near the tropopause. This causes difficulties when assimilating O3 retrievals (both column and profile retrievals) because the respective observation forward operators require model O3 profiles that extend into the stratosphere. In this presentation, we look at results from assimilating O3 observation from surface (in situ measurements), multiple LEO (profile retrievals), and GEO (proxy profile retrievals) platforms in as regional model where we use a global chemical transport model (GCTM) to provide O3 upper boundary conditions (BCs) to enable application of the O3 observation forward operators. We will also present results from assimilating O3 retrievals together with carbon monoxide (CO) observations from surface (in situ measurements) and multiple LEO platforms (column and profile retrievals), and nitrogen dioxide (NO2) observations from surface (in situ measurements), multiple LEO (column retrievals), and GEO (proxy column retrievals) platforms. Our joint assimilation experiments show that sometimes the observations complement each, e.g., when assimilating surface and satellite CO or NO2 observations, and sometimes the observations conflict with each other, e.g., when assimilating observations that are biased with respect to other observations (e.g., CO retrievals), or when the assimilation increments conflict due to their chemical interaction (e.g., surface O3 and NO2 retrievals). Results from assimilation of O3 retrieval profiles in regional model are preliminary and will also be discussed in our presentation. Our expectation is that using GCTM O3 as upper BCs in the regional model for evaluation of the O3 forward operator will improve our O3 forecasts. In summary, we will present results from jointly assimilating surface, LEO, and GEO CO, NO2, and O3 in situ and satellite observations in a regional model with dynamic emissions estimation. This study uses proxy GEO observations as a prelude to actual observations because the GEO platform will not be launched until after our presentation.

WRF-Chem/DART↗

Deep Ocean Warming Assessed from Altimeters, GRACE, 3 In-situ Measurements, and a Non-Boussinesq OGCM

Observational surveys have shown significant oceanic bottom water warming, but they are too spatially and temporally sporadic to quantify the deep ocean contribution to the present-day sea level rise (SLR). In this study, altimetry sea surface height (SSH), Gravity Recovery and Climate Experiment (GRACE) ocean mass, and in situ upper ocean (0-700 m) steric height have been assessed for their seasonal variability and trend maps. It is shown that neither the global mean nor the regional trends of altimetry SLR can be explained by the upper ocean steric height plus the GRACE ocean mass. A non-Boussinesq ocean general circulation model (OGCM), allowing the sea level to rise as a direct response to the heat added into the ocean, is then used to diagnose the deep ocean steric height. Constrained by sea surface temperature data and the top of atmosphere (TOA) radiation measurements, the model reproduces the observed upper ocean heat content well. Combining the modeled deep ocean steric height with observational upper ocean data gives the full depth steric height. Adding a GRACE-estimated mass trend, the data-model combination explains not only the altimetry global mean SLR but also its regional trends fairly well. The deep ocean warming is mostly prevalent in the Atlantic and Indian oceans, and along the Antarctic Circumpolar Current, suggesting a strong relation to the oceanic circulation and dynamics. Its comparison with available bottom water measurements shows reasonably good agreement, indicating that deep ocean warming below 700 m might have contributed 1.1 mm/yr to the global mean SLR or one-third of the altimeter-observed rate of 3.11 +/- 0.6 mm/yr over 1993-2008.

sea level↗

The 2019 Raikoke volcanic eruption -Part 2: Particle-phase dispersion and concurrent wildfire smoke emissions

Between 27 June and 14 July 2019 aerosol layers were observed by the United Kingdom (UK) Raman lidar network in the upper troposphere and lower stratosphere. The arrival of these aerosol layers in late June caused some concern within the London Volcanic Ash Advisory Centre (VAAC) as according to dispersion simulations the volcanic plume from the 21 June 2019 eruption of Raikoke was not expected over the UK until early July. Using dispersion simulations from the Met Office Numerical Atmospheric-dispersion Modelling Environment (NAME), and supporting evidence from satellite and in situ aircraft observations, we show that the early arrival of the stratospheric layers was not due to aerosols from the explosive eruption of the Raikoke volcano but due to biomass burning smoke aerosols associated with intense forest fires in Alberta, Canada, that occurred 4 d prior to the Raikoke eruption. We use the observations and model simulations to describe the dispersion of both the volcanic and forest fire aerosol clouds and estimate that the initial Raikoke ash aerosol cloud contained around 15 Tg of volcanic ash and that the forest fires produced around 0.2 Tg of biomass burning aerosol. The operational monitoring of volcanic aerosol clouds is a vital capability in terms of aviation safety and the synergy of NAME dispersion simulations, and lidar data with depolarising capabilities allowed scientists at the Met Office to interpret the various aerosol layers over the UK and attribute the material to their sources. The use of NAME allowed the identification of the observed stratospheric layers that reached the UK on 27 June as biomass burning aerosol, characterised by a particle linear depolarisation ratio of 9 %, whereas with the lidar alone the latter could have been identified as the early arrival of a volcanic ash–sulfate mixed aerosol cloud. In the case under study, given the low concentration estimates, the exact identification of the aerosol layers would have made little substantive difference to the decision-making process within the London VAAC. However, our work shows how the use of dispersion modelling together with multiple observation sources enabled us to create a more complete description of atmospheric aerosol loading.

Martin J Osborne↗

Data Assimilation to Extract Soil Moisture Information From SMAP Observations

Statistical techniques permit the retrieval of soil moisture estimates in a model climatology while retaining the spatial and temporal signatures of the satellite observations. As a consequence, they can be used to reduce the need for localized bias correction techniques typically implemented in data assimilation (DA) systems that tend to remove some of the independent information provided by satellite observations. Here, we use a statistical neural network (NN) algorithm to retrieve SMAP (Soil Moisture Active Passive) surface soil moisture estimates in the climatology of the NASA Catchment land surface model. Assimilating these estimates without additional bias correction is found to significantly reduce the model error and increase the temporal correlation against SMAP CalVal in situ observations over the contiguous United States. A comparison with assimilation experiments using traditional bias correction techniques shows that the NN approach better retains the independent information provided by the SMAP observations and thus leads to larger model skill improvements during the assimilation. A comparison with the SMAP Level 4 product shows that the NN approach is able to provide comparable skill improvements and thus represents a viable assimilation approach.

NASA's Optical Measurement Program 2014

The Optical Measurements Group (OMG) within the NASA Orbital Debris Program Office (ODPO) addresses U.S. National Space Policy goals by monitoring and characterizing debris. Since 2001, the OMG has used the Michigan Orbital Debris Survey Telescope (MODEST) at Cerro Tololo Inter-American Observatory (CTIO) in Chile for general orbital debris surveys. The 0.6-m Schmidt MODEST provides calibrated astronomical data of GEO targets, both catalogued and uncatalogued debris, with excellent image quality. The data are utilized by the ODPO modeling group and are included in the Orbital Debris Engineering Model (ORDEM) v. 3.0. MODEST and the CTIO/SMARTS (Small and Moderate Aperture Research Telescope System) 0.9 m are both employed to acquire filter photometry data as well as synchronously observe targets in selected optical filters. Obtaining data synchronously yields data for material composition studies as well as longer orbital arc data on the same target without time delay or bias from a rotating, tumbling, or spinning target. Observations of GEO orbital debris using the twin 6.5-m Magellan telescopes at Las Campanas Observatory in Chile for deep imaging (Baade) and spectroscopic data (Clay) began in 2011. Through the data acquired on Baade, debris has been detected that reaches approx. 3 magnitudes fainter than detections with MODEST, while the spectral data from Clay provide better resolved information used in material characterization analyses. To better characterize and model optical data, the Optical Measurements Center (OMC) at NASA/JSC has been in operation since 2005, resulting in a database of comparison laboratory data. The OMC is designed to emulate illumination conditions in space using equipment and techniques that parallel telescopic observations and sourcetarget- sensor orientations. Lastly, the OMG is building the Meter Class Autonomous Telescope (MCAT) at Ascension Island. The 1.3-m telescope is designed to observe GEO and LEO targets, using a modified Ritchey-Chrétien configuration on a double horseshoe equatorial mount to allow tracking objects at LEO rates through the dome's keyhole at zenith. Through the data collection techniques employed at these unique facilities, NASA's ODPO has developed a multifaceted approach to characterize the orbital debris risk to satellites in various altitudes and provide insight leading toward material characterization of debris via photometric and spectroscopic measurements. Ultimately, the data are used in conjunction with in-situ and radar measurements to provide accurate data for models of our space environment and for facilitating spacecraft risk assessment.

Cowardin, H.↗

Analysis of Satellite and Sub-Orbital Measurements

The objective of this project is to support the INTEX aircraft mission by developing experience in the integrated analysis of existing sub-orbital observations and satellite observations with numerical models. Specific tasks include providing guidance to INTEX by identifying discrepancies in satellite observations with (1) in situ measurements, (2) bottom-up emission inventories of nitrogen oxides and volatile organic compounds, and (3) model calculations of the export of pollution from North America to the global atmosphere. An important focus area is developing and improving bottom-up emission inventories by combining top-down and bottom-up information.

Gleason, James↗

NASA's Optical Measurement Program 2014

The Optical Measurements Group (OMG) within the NASA Orbital Debris Program Office (ODPO) addresses U.S. National Space Policy goals by monitoring and characterizing debris. Since 2001, the OMG has used the Michigan Orbital Debris Survey Telescope (MODEST) at Cerro Tololo Inter-American Observatory (CTIO) in Chile for general orbital debris survey. The 0.6-m Schmidt MODEST provides calibrated astronomical data of GEO targets, both catalogued and uncatalogued debris, with excellent image quality. The data are utilized by the ODPO modeling group and are included in the Orbital Debris Engineering Model (ORDEM) v. 3.0. MODEST and the CTIO/SMARTS (Small and Moderate Aperture Research Telescope System) 0.9 m both acquire filter photometric data, as well as synchronously observing targets in selected optical filters. This information provides data used in material composition studies as well as longer orbital arc data on the same target, without time delay or bias from a rotating, tumbling, or spinning target. NASA, in collaboration with the University of Michigan, began using the twin 6.5-m Magellan telescopes at Las Campanas Observatory in Chile for deep imaging (Baade) and spectroscopic data (Clay) in 2011. Through the data acquired on Baade, debris have been detected that are ~3 magnitudes fainter than detections with MODEST, while the data from Clay provide better resolved information used in material characterization analyses via selected bandpasses. To better characterize and model optical data, the Optical Measurements Center (OMC) at NASA/JSC has been in operation since 2005, resulting in a database of comparison laboratory data. The OMC is designed to emulate illumination conditions in space using equipment and techniques that parallel telescopic observations and source-target-sensor orientations. Lastly, the OMG is building the Meter Class Autonomous Telescope (MCAT) at Ascension Island. The 1.3-m telescope is designed to observe GEO and LEO targets, using a modified Ritchey-Chrétien configuration on a double horseshoe equatorial mount to allow tracking objects at LEO rates through the dome's keyhole at zenith. Through the data collection techniques employed at these unique facilities, NASA's ODPO has developed a multi-faceted approach to characterize the orbital debris risk to satellites in various altitudes and provide material characterization of debris via photometric and spectroscopic measurements. Ultimately, the data are used in conjunction with in-situ and radar measurements to provide accurate data for models of our space environment and service spacecraft risk assessment.

Cowardin, H.↗

Using Leaf Chlorophyll to Parameterize Light-Use-Efficiency Within a Thermal-Based Carbon, Water and Energy Exchange Model

Chlorophylls absorb photosynthetically active radiation and thus function as vital pigments for photosynthesis, which makes leaf chlorophyll content (C(sub ab) useful for monitoring vegetation productivity and an important indicator of the overall plant physiological condition. This study investigates the utility of integrating remotely sensed estimates of C(sub ab) into a thermal-based Two-Source Energy Balance (TSEB) model that estimates land-surface CO2 and energy fluxes using an analytical, light-use-efficiency (LUE) based model of canopy resistance. The LUE model component computes canopy-scale carbon assimilation and transpiration fluxes and incorporates LUE modifications from a nominal (species-dependent) value (LUE(sub n)) in response to short term variations in environmental conditions, However LUE(sub n) may need adjustment on a daily timescale to accommodate changes in plant phenology, physiological condition and nutrient status. Day to day variations in LUE(sub n) were assessed for a heterogeneous corn crop field in Maryland, U,S.A. through model calibration with eddy covariance CO2 flux tower observations. The optimized daily LUE(sub n) values were then compared to estimates of C(sub ab) integrated from gridded maps of chlorophyll content weighted over the tower flux source area. The time continuous maps of daily C(sub ab) over the study field were generated by focusing in-situ measurements with retrievals generated with an integrated radiative transfer modeling tool (accurate to within +/-10%) using at-sensor radiances in green, red and near-infrared wavelengths acquired with an aircraft imaging system. The resultant daily changes in C(sub ab) within the tower flux source area generally correlated well with corresponding changes in daily calibrated LUE(sub n) derived from the tower flux data, and hourly water, energy and carbon flux estimation accuracies from TSEB were significantly improved when using C(sub ab) for delineating spatio-temporal variations in LUE(sub n). The results demonstrate the synergy between thermal infrared and shortwave reflective wavebands in producing valuable remote sensing data for operational monitoring of carbon and water fluxes.

Houlborg, Rasmus↗

NASA Downscaling Project: Final Report

A team of researchers from NASA Ames Research Center, Goddard Space Flight Center, the Jet Propulsion Laboratory, and Marshall Space Flight Center, along with university partners at UCLA, conducted an investigation to explore whether downscaling coarse resolution global climate model (GCM) predictions might provide valid insights into the regional impacts sought by decision makers. Since the computational cost of running global models at high spatial resolution for any useful climate scale period is prohibitive, the hope for downscaling is that a coarse resolution GCM provides sufficiently accurate synoptic scale information for a regional climate model (RCM) to accurately develop fine scale features that represent the regional impacts of a changing climate. As a proxy for a prognostic climate forecast model, and so that ground truth in the form of satellite and in-situ observations could be used for evaluation, the MERRA and MERRA - 2 reanalyses were used to drive the NU - WRF regional climate model and a GEOS - 5 replay. This was performed at various resolutions that were at factors of 2 to 10 higher than the reanalysis forcing. A number of experiments were conducted that varied resolution, model parameterizations, and intermediate scale nudging, for simulations over the continental US during the period from 2000 - 2010. The results of these experiments were compared to observational datasets to evaluate the output.

dynamical downsizing↗

The Relationship of Subvisible Cirrus Clouds Observed During NASA's Tropical Ozone

Thin, subvisible cirrus (SVC) clouds at the tropical tropopause have been observed by a number of methods in a variety of observational programs, including in situ sampling and aircraft and space-based lidar. Modeling studies suggest that these clouds play an important role in dehydrating tropospheric air as it enters the stratosphere. This is because particles large enough to have significant fall speeds can form under the conditions of slow cooling that are implied by the large horizontal extent of the SVC sheets. The IRA radiation that these clouds absorb, and the upward vertical motion this implies, also make them candidates for a tropical troposphere-to-stratosphere mass transfer mechanism. These sheets were observed on five flights during the Tropical Ozone Transport Experiment (TOTE) by the NASA Langley DIAL lidar aboard NASA's DC-8 research aircraft, operating during December 1995 and February 1996 south of Hawaii (12 S to 21 N). This experiment provided a unique look at these clouds since temperature profiles were available for all the SVC observations. Thus, the observed distributions of SVC's can be compared with the position of the tropopause to establish whether the SVC's are tropospheric or stratospheric. It also allows comparison of TOTE observations with in situ experiments, where water and cloud particle data is available as a function of temperature and potential temperature.

Pfister, L.↗

Improved Calibration of Modeled Discharge and Storage Change in the Atchafalaya Floodplain Using SAR Interferometry

This study focuses on the feasibility of using SAR interferometry to support 2D hydrodynamic model calibration and provide water storage change in the floodplain. Two-dimensional (2D) flood inundation modeling has been widely studied using storage cell approaches with the availability of high resolution, remotely sensed floodplain topography. The development of coupled 1D/2D flood modeling has shown improved calculation of 2D floodplain inundation as well as channel water elevation. Most floodplain model results have been validated using remote sensing methods for inundation extent. However, few studies show the quantitative validation of spatial variations in floodplain water elevations in the 2D modeling since most of the gauges are located along main river channels and traditional single track satellite altimetry over the floodplain are limited. Synthetic Aperture Radar (SAR) interferometry recently has been proven to be useful for measuring centimeter-scale water elevation changes over the floodplain. In the current study, we apply the LISFLOOD hydrodynamic model to the central Atchafalaya River Basin, Louisiana, during a 62 day period from 1 April to 1 June 2008 using two different calibration schemes for Manning's n. First, the model is calibrated in terms of water elevations from a single in situ gauge that represents a more traditional approach. Due to the gauge location in the channel, the calibration shows more sensitivity to channel roughness relative to floodplain roughness. Second, the model is calibrated in terms of water elevation changes calculated from ALOS PALSAR interferometry during 46 days of the image acquisition interval from 16 April 2008 to 1 June 2009. Since SAR interferometry receives strongly scatters in floodplain due to double bounce effect as compared to specular scattering of open water, the calibration shows more dependency to floodplain roughness. An iterative approach is used to determine the best-fit Manning's n for the two different calibration approaches. Results suggest similar floodplain roughness but slightly different channel roughness. However, application of SAR interferometry provides a unique view of the floodplain flow gradients, not possible with a single gauge calibration. These gradients, allow improved computation of water storage change over the 46-day simulation period. Overall, the results suggest that the use of 2D SAR water elevation changes in the Atchafalaya basin offers improved understanding and modeling of floodplain hydrodynamics.

Jung, Hahn Chul↗

Challenges to Aboveground Biomass Prediction from Waveform Lidar

Accurate accounting of aboveground biomass density (AGBD) is crucial for carbon cycle, biodiversity, and climate change science. The Global Ecosystem Dynamics Investigation (GEDI), which maps global AGBD from waveform lidar, is the first of a new generation of Earth observation missions designed to improve carbon accounting. This paper explores the possibility that lidar waveforms may not be unique to AGBD—that forest stands with different AGBD may produce highly similar waveforms—and we hypothesize that non-uniqueness may contribute to the large uncertainties in AGBD predictions. Our analysis integrates simulated GEDI waveforms from 428 in situ stem maps with output from an individual-based forest gap model, which we use to generate a database of potential forest stands and simulate GEDI waveforms from those stands. We use this database to predict the AGBD of the 428 in situ stem maps via two different methods: a linear regression from waveform metrics, and a waveform-matching approach that accounts for waveform-AGBD non-uniqueness. We find that some in situ waveforms are more unique to AGBD than others, which notably impacts AGBD prediction uncertainty (7–411 Mg ha−1, average of 167 Mg ha−1). We also find that forest structure complexity may influence the non-uniqueness effect; stands with low structural complexity are more unique to AGBD than more mature stands with multiple cohorts and canopy layers. These findings suggest that the non-uniqueness phenomena may be introduced by the measuring characteristics of waveform lidar in combination with how forest structure manifests at small scales, and we discuss how this complexity may complicate uncertainty estimation in AGBD prediction. This analysis suggests a limit to the accuracy and precision of AGBD predictions from lidar waveforms seen in empirical studies, and underscores the need for further exploration of the relationships between lidar remote sensing measurements, forest structure, and AGBD.

GEDI↗

Observations of Subvisible Cirrus Clouds and Gravity Waves at the Tropical Tropopause

Thin, subvisible cirrus (SVC) clouds at the tropical tropopause have been observed by a number of methods in a variety of observational programs, including in situ sampling and aircraft and space-based lidar. Modeling studies suggest that these clouds play an important role in dehydrating tropospheric air as it enters the stratosphere. This is because particles large enough to have significant fall speeds can form under the conditions of slow cooling that are implied by the large horizontal extent of the SVC sheets. The IR radiation that these clouds absorb, and the upward vertical motion this implies, also makes them candidates for a tropical troposphere-to-stratosphere mass transfer mechanism. They may also play a role in the earth's radiation budget. These sheets were observed on five flights during the Tropical Ozone Transport Experiment (TOTE) by the NASA Langley DIAL lidar aboard NASA's DC-8 research aircraft operating during December 1995 and February 1996 south of Hawaii. The relationship of the SVC's observed during TOTE to convection was not a simple one. One class of SVC's are within 1000 km of the persistent strong convection near 15S (the SPCZ). Trajectory analyses indicated that the SVC air masses have in fact passed through the SPCZ within a few days of observation. These clouds are very close to the tropopause, with maximum potential temperatures not much higher than 370K, consistent with in situ water and total water measurements near the tropopause made during the Stratosphere Troposphere Exchange Project in January 1987 at Darwin, Australia. A second class of SVC's are not immediately downstream of convection. These clouds tend to be higher, reaching potential temperatures of 390K or more. Trajectory analyses indicate that the air in these SVC's originates either in the equatorial western Pacific or along the subtropical jet. In any case, the warm temperatures the SVC air masses encounter just prior to the observation time along the back trajectory imply that the clouds cannot be residual particles from cirrus blowoff, but must form locally as the air move upward and equatorward south of Hawaii. Since all the parcels have encountered colder temperatures than those at the time of observation early in their history, subsynoptic scale temperatures colder than the analysis temperatures appear to be required to explain the formation of ice particles. In fact, the sloping shapes of the SVC's do suggest that they are gravity or inertia-gravity waves. In situ meteorological measurements made by the ER-2 within a day of the DC-8 remote lidar observations show a gravity wave structure near the equator with an estimated period of about 30 hours. This is sufficiently long to allow large particles to form and fall out (thus allowing dehydration). Other ER-2 flights south of Hawaii at other times of year show gravity and inertia-gravity waves with a poleward wavenumber component and significant (5 degrees peak to peak) temperature perturbation.

Pfister, Leonhard↗

Long term microparticle impact fluxes on LDEF determined from optical survey of Interplanetary Dust Experiment (IDE) sensors

Many of the IDE metal-oxide-silicon (MOS) capacitor-discharge impact sensors remained active during the entire Long Duration Exposure Facility (LDEF) mission. An optical survey of impact sites on the active surfaces of these sensors has been extended to include all sensors from the low-flux sides of LDEF (i.e. the west or trailing side, the earth end, and the space end) and 5-7 active sensors from each LDEF's high-flux sides (i.e. the east or leading side, the south side, and the north side). This survey was facilitated by the presence of a relatively large (greater than 50 micron diameter) optical signature associated with each impact site on the active sensor surfaces. Of the approximately 4700 impacts in the optical survey data set, 84% were from particles in the 0.5 to 3 micron size range. An estimate of the total number of hypervelocity impacts on LDEF from particles greater than 0.5 micron diameter yields a value of approximately 7 x 10(exp 6). Impact feature dimensions for several dozen large craters on MOS sensors and germanium witness plates are also presented. Impact fluxes calculated from the IDE survey data closely matched surveys of similar size impacts (greater than or equal to 3 micron diameter craters in Al, or marginal penetrations of a 2.4 micron thick Al foil) by other LDEF investigators. Since the first year IDE data were electronically recorded, the flux data could be divided into three long term time periods: the first year, the entire 5.8 year mission, and the intervening 4.8 years (by difference). The IDE data show that there was an order of magnitude decrease in the long term microparticle impact flux on the trailing side of LDEF, from 1.01 to 0.098 x 10(exp -4) m(exp 2)/s, from the first year in orbit compared to years 2-6. The long term flux on the leading edge showed an increase from 8.6 to 11.2 x 10(exp -4) m(exp -2)/s over this same time period. (Short term flux increases up to 10,000 times the background rate were recorded on the leading side during LDEF's first year in orbit.) The overall east/west ratio was 44, but during LDEF's first year in orbit the ratio was 8.5, and during years 2-6 the ratio was 114. Long term microparticle impact fluxes on the space end decreased from 1.12 to 0.55 x 10(exp -4) m(exp -2)/s from the first year in orbit compared to years 2-6. The earth end showed the opposite trend with an increase from 0.16 to 0.38 x 10(exp -4) m(exp -2)/s. Fluxes on rows 6 and 12 decreased from 6.1 to 3.4 and 6.7 to 3.7 x 10(exp -4) m(exp -2)/s, respectively, over the same time periods. This resulted in space/earth microparticle impact flux ratios of 7.1 during the first year and 1.5 during years 2-6, while the south/north, space/north and space/south ratios remained constant at 1.1, 0.16 and 0.17, respectively, during the entire mission. This information indicates the possible identification of long term changes in discrete microparticle orbital debris component contributions to the total impact flux experienced by LDEF. A dramatic decrease in the debris population capable of striking the trailing side was detected that could possibly be attributed to the hiatus of western launch activity experienced from 1986-1989. A significant increase in the debris population that preferentially struck the leading side was also observed and could possibly be attributed to a single breakup event that occurred in September of 1986. A substantial increase in the microparticle debris population that struck the earth end of LDEF, but not the space end, was also detected and could possibly be the result of a single breakup event at low altitude. These results point to the importance of including discrete orbital debris component contribution changes in flux models in order to achieve accurate predictions of the microparticle environment that a particular spacecraft will experience in earth orbit. The only reliable, verified empirical measurements of these changes are reported in this paper. Further time-resolved in-situ measurements of these debris populations are needed to accurately assess model predictions and mitigation practices.

Simon, C. G.↗