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Active microwave measurements of sea ice under fall conditions: The RADARSAT/FIREX fall experiment

A series of measurements of the active microwave properties of sea ice under fall growing conditions was conducted. Ice in the inland waters of Mould Bay, Crozier Channel, and intrepid inlet and ice in the Arctic Ocean near Hardinge Bay was investigated. Active microwave data were acquired using a helicopter borne scatterometer. Results show that multiyear ice frozen in grey or first year ice is easily detected under cold fall conditions. Multiyear ice returns were dynamic due to response to two of its scene constituents. Floe boundaries between thick and thin ice are well defined. Multiyear pressure ridge returns are similar in level to background ice returns. Backscatter from homogeneous first year ice is seen to be primarily due to surface scattering. Operation at 9.6 GHz is more sensitive to the detailed changes in scene roughness, while operation at 5.6 GHz seems to track roughness changes less ably.

Onstott, R. G.↗

The Fall 2000 and Fall 2001 SOHO-Ulysses Quadratures

SOHO-Ulysses quadrature occurs when the SOHO-Sun-Ulysses included angle is 90 degrees. It is only at such times that the same plasma leaving the Sun in the direction of Ulysses can first be remotely analyzed with SOHO instruments and then later be sampled in situ by Ulysses instruments. The quadratures in December 2000 and 2001 are of special significance because Ulysses will be near the south and north heliographic poles, respectively, and the solar cycle will be near sunspot maximum. Quadrature geometry is sometimes confusing and observations are influenced by solar rotation. The Fall 2000 and 2001 quadratures are more complex than usual because Ulysses is not in a true polar orbit and the orbital speed of Ulysses about the Sun is becoming comparable to the speed of SOHO about the Sun. In 2000 Ulysses will always be slightly behind the pole but will appear to hang over the pole for over two months because it is moving around the Sun in the same direction as SOHO. In 20001, Ulysses will be slightly in front of the pole so that its footpoint will be directly observable. Detailed plots will be shown of the relative positions of SOHO and Ulysses will their relative positions. In neither case is true quadrature actually achieved, but this works to the observers advantage in 2001.

Suess, S. T.↗

The Fall 2000 and Fall 2001 SOHO-Ulysses Quadratures

SOHO-Ulysses quadrature occurs when the SOHO-Sun-Ulysses included angle is 90 degrees. It is only at such times that the same plasma leaving the Sun in the direction of Ulysses can first be remotely analyzed with SOHO instruments and then later be sampled in situ by Ulysses instruments. The quadratures in December 2000 and 2001 are of special significance because Ulysses will be near the south and north heliographic poles, respectively, and the solar cycle will be near sunspot maximum. Quadrature geometry is sometimes confusing and observations are influenced by solar rotation. The Fall 2000 and 2001 quadratures are more complex than usual because Ulysses is not in a true polar orbit and the orbital speed of Ulysses about the Sun is becoming comparable to the speed of SOHO about the Sun. In 2000 Ulysses will always be slightly behind the pole but will appear to hang over the pole for over two months because it is moving around the Sun in the same direction as SOHO. In 2001 Ulysses will be slightly in front of the pole so that its footpoint will be directly observable. Detailed plots will be shown of the relative positions of SOHO and Ulysses will their relative positions. In neither case is true quadrature actually achieved, but this works to the observers advantage in 2001.

Suess, S. T.↗

Morphological Comparison of Debris Recovered Searching for the 2018 Meteorite Fall into the Pacific with Those Recovered From the Purportedly Interstellar 2014 Fall

On 08 Jan 2014 a bolide was detected by US DoD sensors over the Pacific north of Papua New Guinea. A claim was subsequently made that this event arose from a meteoroid of interstellar origin based on fireball parameters, although that interpretation has been challenged. A seagoing expedition recovered material from the seafloor at a location calculated to be the fall site, and that material included small melted spherules. The spherules were claimed to be of extrasolar origin based on appearance and composition. A recent publication finds a favorable composition match between the retrieved spherules and coal ash, a ubiquitous contaminant on Earth’s surface and seafloor.

M D Fries↗

Worldwide Weather Radar Imagery May Allow Substantial Increase in Meteorite Fall Recovery

Weather radar imagery is a valuable new technique for the rapid recovery of meteorite falls, to include falls which would not otherwise be recovered (e.g. Battle Mountain). Weather radar imagery reveals about one new meteorite fall per year (18 falls since 1998), using weather radars in the United States alone. However, an additional ~75 other nations operate weather radar networks according to the UN World Meteorological Organization (WMO). If the imagery of those radars were analyzed, the current rate of meteorite falls could be improved considerably, to as much as ~3.6 times the current recovery rate based on comparison of total radar areal coverage. Recently, the addition of weather radar imagery, seismometry and internet-based aggregation of eyewitness reports has improved the speed and accuracy of fresh meteorite fall recovery [e.g. 1,2]. This was demonstrated recently with the radar-enabled recovery of the Sutter's Mill fall [3]. Arguably, the meteorites recovered via these methods are of special scientific value as they are relatively unweathered, fresh falls. To illustrate this, a recent SAO/NASA ADS search using the keyword "meteorite" shows that all 50 of the top search results included at least one named meteorite recovered from a meteorite fall. This is true even though only ~1260 named meteorite falls are recorded among the >49,000 individual falls recorded in the Meteoritical Society online database. The US NEXRAD system used thus far to locate meteorite falls covers most of the United States' surface area. Using a WMO map of the world's weather radars, we estimate that the total coverage of the other ~75 national weather radar networks equals about 3.6x NEXRAD's coverage area. There are two findings to draw from this calculation: 1) For the past 16 years during which 18 falls are seen in US radar data, there should be an additional ~65 meteorite falls recorded in worldwide radar imagery. Also: 2) if all of the world's radar data could be analyzed, the rate of recovery of fresh meteorite falls can increase by as much as ~3.6x the current rate. The authors' experience to date indicates that the most effective course of action would be to have local meteorite research groups (outside of the US) form research consortia and develop a working relationship with their nation's weather bureau for access to data. These research consortia could utilize the same, proven methods used for US NEXRAD imagery, internet eyewitness report aggregation, seismometry analysis, etc. to locate meteorite falls. The consortia could then recover and analyze meteorite falls and enrich their own research efforts. It would be beneficial to conduct a global program to coordinate the development of methods and data tools, as well as to coordinate meteorite sample sharing and research. Perhaps an institution such as the Meteoritical Society could lead such an effort.

Fries, Marc↗

Detection Thresholds of Falling Snow from Satellite-Borne Active and Passive Sensors

Precipitation, including rain and snow, is a critical part of the Earth's energy and hydrology cycles. Precipitation impacts latent heating profiles locally while global circulation patterns distribute precipitation and energy from the equator to the poles. For the hydrological cycle, falling snow is a primary contributor in northern latitudes during the winter seasons. Falling snow is the source of snow pack accumulations that provide fresh water resources for many communities in the world. Furthermore, falling snow impacts society by causing transportation disruptions during severe snow events. In order to collect information on the complete global precipitation cycle, both liquid and frozen precipitation must be collected. The challenges of estimating falling snow from space still exist though progress is being made. These challenges include weak falling snow signatures with respect to background (surface, water vapor) signatures for passive sensors over land surfaces, unknowns about the spherical and non-spherical shapes of the snowflakes, their particle size distributions (PSDs) and how the assumptions about the unknowns impact observed brightness temperatures or radar reflectivities, differences in near surface snowfall and total column snow amounts, and limited ground truth to validate against. While these challenges remain, knowledge of their impact on expected retrieval results is an important key for understanding falling snow retrieval estimations. Since falling snow from space is the next precipitation measurement challenge from space, information must be determined in order to guide retrieval algorithm development for these current and future missions. This information includes thresholds of detection for various sensor channel configurations, snow event system characteristics, snowflake particle assumptions, and surface types. For example, can a lake effect snow system with low (approx 2.5 km) cloud tops having an ice water content (IWC) at the surface of 0.25 g / cubic m and dendrite snowflakes be detected? If this information is known, we can focus retrieval efforts on detectable storms and concentrate advances on achievable results. Here, the focus is to determine thresholds of detection for falling snow for various snow conditions over land and lake surfaces. The results rely on simulated Weather Research Forecasting (WRF) simulations of falling snow cases since simulations provide all the information to determine the measurements from space and the ground truth. Sensitivity analyses were performed to better ascertain the relationships between multifrequency microwave and millimeter-wave sensor observations and the falling snow/underlying field of view. In addition, thresholds of detection for various sensor channel configurations, snow event system characteristics, snowflake particle assumptions, and surface types were studied. Results will be presented for active radar at Ku, Ka, and W-band and for passive radiometer channels from 10 to 183 GHz.

Gail Skofronick-Jackson↗

Meteorite Falls Observed in U.S. Weather Radar Data in 2015 and 2016 (To Date)

To date, over twenty meteorite falls have been located in the weather radar imagery of the National Oceanic and Atmospheric Administration (NOAA)'s NEXRAD radar network. We present here the most prominent events recorded since the last Meteoritical Society meeting, covering most of 2015 and early 2016. Meteorite Falls: The following events produced evidence of falling meteorites in radar imagery and resulted in meteorites recovered at the fall site. Creston, CA (24 Oct 2015 0531 UTC): This event generated 218 eyewitness reports submitted to the American Meteor Society (AMS) and is recorded as event #2635 for 2015 on the AMS website. Witnesses reported a bright fireball with fragmentation terminating near the city of Creston, CA, north of Los Angeles. Sonic booms and electrophonic noise were reported in the vicinity of the event. Weather radar imagery records signatures consistent with falling meteorites in data from the KMUX, KVTX, KHNX and KVBX. The Meteoritical Society records the Creston fall as an L6 meteorite with a total recovered mass of 688g. Osceola, FL (24 Jan 2016 1527 UTC): This daytime fireball generated 134 eyewitness reports on AMS report number 266 for 2016, with one credible sonic boom report. The fireball traveled roughly NE to SW with a terminus location north of Lake City, FL in sparsely populated, forested countryside. Radar imagery shows distinct and prominent evidence of a significant meteorite fall with radar signatures seen in data from the KJAX and KVAX radars. Searchers at the fall site found that recoveries were restricted to road sites by the difficult terrain, and yet several meteorites were recovered. Evidence indicates that this was a relatively large meteorite fall where most of the meteorites are unrecoverable due to terrain. Osceola is an L6 meteorite with 991 g total mass recovered to date. Mount Blanco, TX (18 Feb 2016 0343 UTC): This event produced only 39 eyewitness reports and is recorded as AMS event #635 for 2016. No reports of sonic booms or electrophonic noise are recorded in the AMS eyewitness reports, but videos of the event show a relatively long-lasting fireball with fragmentation. Evidence of falling meteorites is seen in radar imagery from the KAMA and KLBB radars defining a roughly WNW to ESE trend with the dominant wind direction. This event featured favorable search ground composed mostly of farmland and ranchland and was extensively searched. Rather surprisingly, only a single L5 chondrite of 36.2g has been recovered to date.

Fries, Marc↗

Passive Microwave Remote Sensing of Falling Snow and Associated GPM Field Campaigns

Retrievals of falling snow from space represent one of the next important challenges for the atmospheric, hydrological, and energy budget scientific communities. Historically, retrievals of falling snow have been difficult due to the relative insensitivity of satellite rain-based channels as used in the past. We emphasize the use of high frequency passive microwave channels (85-200 GHz) since these are more sensitive to the ice in clouds and have been used to estimate falling snow from space. While satellite-based remote sensing provides global coverage of falling snow events and the science is relatively new, retrievals are still undergoing development with challenges remaining. There are several current satellite sensors, though not specifically designed for estimating falling snow, are capable of measuring snow from space. These include NOAA's AMSU-B, the MHS sensors, and CloudSat radar. They use high frequency (greater than 85 GHz) passive and active microwave and millimeter-wave channels that are sensitive to the scattering from ice and snow particles in the atmosphere. Sensors with water vapor channels near 183 GHz center line provide opaqueness to the Earth's surface features that can contaminate the falling snow signatures, especially over snow covered surface. In addition, the Global Precipitation Measurement (GPM) mission scheduled for launch in 2013 is specifically designed to measure both liquid rain and frozen snow precipitation. Since falling snow from space is the next precipitation measurement challenge from space, information must be determined in order to guide retrieval algorithm development for these current and future missions. This information includes thresholds of detection for various sensor channel configurations, snow event system characteristics, and surface types. For example, can a lake effect snow system with low cloud tops having an ice water content (IWC) at the surface of 1.0 gram per cubic meter be detected? If this information is known, we can focus retrieval efforts on detectable storms and concentrate advances on achievable results. In this work, the focus is to determine thresholds of detection for falling snow for various snow conditions over land and lake surfaces. The results rely on simulated Weather Research Forecasting (WRF) simulations of falling snow cases [9] since simulations provide all the information to determine the measurements from space and the ground truth. This analysis relies on data from the Canadian CloudSat/CALIPSO Validation Program (C3VP) field campaign held from October 31, 2006 through March 1, 2007. In January 2012 GPM will return to the C3VP area for the GPM Cold Precipitation Experiment (GCPEx). This presentation will describe the thresholds-of-detection procedure and results, as well as the field campaign details.

Skofronick-Jackson, Gail↗

Observations of Precipitation Size and Fall Speed Characteristics within Coexisting Rain and Wet Snow

Ground-based measurements of particle size and fall speed distributions using a Particle Size and Velocity (PARSIVEL) disdrometer are compa red among samples obtained in mixed precipitation (rain and wet snow) and rain in the Oregon Cascade Mountains and in dry snow in the Rock y Mountains of Colorado. Coexisting rain and snow particles are distinguished using a classification method based on their size and fall sp eed properties. The bimodal distribution of the particles' joint fall speed-size characteristics at air temperatures from 0.5 to 0 C suggests that wet-snow particles quickly make a transition to rain once mel ting has progressed sufficiently. As air temperatures increase to 1.5 C, the reduction in the number of very large aggregates with a diame ter > 10 mm coincides with the appearance of rain particles larger than 6 mm. In this setting. very large raindrops appear to be the result of aggregates melting with minimal breakup rather than formation by c oalescence. In contrast to dry snow and rain, the fall speed for wet snow has a much weaker correlation between increasing size and increasing fall speed. Wet snow has a larger standard deviation of fall spee d (120%-230% relative to dry snow) for a given particle size. The ave rage fall speed for observed wet-snow particles with a diameter great er than or equal to 2.4 mm is 2 m/s with a standard deviation of 0.8 m/s. The large standard deviation is likely related to the coexistence of particles of similar physical size with different percentages of melting. These results suggest that different particle sizes are not required for aggregation since wet-snow particles of the same size can have different fall speeds. Given the large standard deviation of fa ll speeds in wet snow, the collision efficiency for wet snow is likely larger than that of dry snow. For particle sizes between 1 and 10 mm in diameter within mixed precipitation, rain constituted I % of the particles by volume within the isothermal layer at 0 C and 4% of the particles by volume for the region just below the isothermal layer where air temperatures rise from 0" to 0.5"C. As air temperatures increa sed above 0.5 C, the relative proportions of rain versus snow particl es shift dramatically and raindrops become dominant. The value of 0.5 C for the sharp transition in volume fraction from snow to rain is sl ightly lower than the range from 1 .l to 1.7 C often used in hydrolog ical models.

Yuter, Sandra E.↗

A Segmentation Algorithm for Characterizing Rise and Fall Segments in Seasonal Cycles: An Application to XCO2 to Estimate Benchmarks and Assess Model Bias

There is more useful information in the time series of satellite-derived column-averaged carbon dioxide (XCO2) than is typically characterized. Often, the entire time series is treated at once without considering detailed features at shorter timescales, such as nonstationary changes in signal characteristics – amplitude, period and phase. In many instances, signals are visually and analytically differentiable from other portions in a time series. Each rise (increasing) and fall (decreasing) segment in the seasonal cycle is visually discernable in a graph of the time series. The rise and fall segments largely result from seasonal differences in terrestrial ecosystem production, which means that the segment's signal characteristics can be used to establish observational benchmarks because the signal characteristics are driven by similar underlying processes. We developed an analytical segmentation algorithm to characterize the rise and fall segments in XCO2 seasonal cycles. We present the algorithm for general application of the segmentation analysis and emphasize here that the segmentation analysis is more generally applicable to cyclic time series. We demonstrate the utility of the algorithm with specific results related to the comparison between satellite- and model-derived XCO2 seasonal cycles (2009–2012) for large bioregions across the globe. We found a seasonal amplitude gradient of 0.74–0.77 ppm for every 10∘ of latitude in the satellite data, with similar gradients for rise and fall segments. This translates to a south–north seasonal amplitude gradient of 8 ppm for XCO2, about half the gradient in seasonal amplitude based on surface site in situ CO2 data (∼19 ppm). The latitudinal gradients in the period of the satellite-derived seasonal cycles were of opposing sign and magnitude (−9 d per 10∘ latitude for fall segments and 10 d per 10∘ latitude for rise segments) and suggest that a specific latitude (∼2∘ N) exists that defines an inversion point for the period asymmetry. Before (after) the point of asymmetry inversion, the periods of rise segments are lesser (greater) than the periods of fall segments; only a single model could reproduce this emergent pattern. The asymmetry in amplitude and the period between rise and fall segments introduces a novel pattern in seasonal cycle analyses, but, while we show these emergent patterns exist in the data, we are still breaking ground in applying the information for science applications. Maybe the most useful application is that the segmentation analysis allowed us to decompose the model biases into their correlated parts of biases in amplitude, period and phase independently for rise and fall segments. We offer an extended discussion on how such information about model biases and the emergent patterns in satellite-derived seasonal cycles can be used to guide future inquiry and model development.

Calle, Leonardo↗

A Segmentation Algorithm for Characterizing Rise and Fall Segments in Seasonal Cycles: an Application to Xco2 to Estimate Benchmarks and Assess Model Bias

There is more useful information in the time series of satellite-derived column-averaged carbon dioxide (XCO2) than is typically characterized. Often, the entire time series is treated at once without considering detailed features at shorter timescales, such as nonstationary changes in signal characteristics – amplitude, period and phase. In many instances, signals are visually and analytically differentiable from other portions in a time series. Each rise (increasing) and fall (decreasing) segment in the seasonal cycle is visually discernable in a graph of the time series. The rise and fall segments largely result from seasonal differences in terrestrial ecosystem production, which means that the segment's signal characteristics can be used to establish observational benchmarks because the signal characteristics are driven by similar underlying processes. We developed an analytical segmentation algorithm to characterize the rise and fall segments in XCO2 seasonal cycles. We present the algorithm for general application of the segmentation analysis and emphasize here that the segmentation analysis is more generally applicable to cyclic time series. We demonstrate the utility of the algorithm with specific results related to the comparison between satellite- and model-derived XCO2 seasonal cycles (2009–2012) for large bioregions across the globe. We found a seasonal amplitude gradient of 0.74–0.77 ppm for every 10∘ of latitude in the satellite data, with similar gradients for rise and fall segments. This translates to a south–north seasonal amplitude gradient of 8 ppm for XCO2, about half the gradient in seasonal amplitude based on surface site in situ CO2 data (∼19 ppm). The latitudinal gradients in the period of the satellite-derived seasonal cycles were of opposing sign and magnitude (−9 d per 10∘ latitude for fall segments and 10 d per 10∘ latitude for rise segments) and suggest that a specific latitude (∼2∘ N) exists that defines an inversion point for the period asymmetry. Before (after) the point of asymmetry inversion, the periods of rise segments are lesser (greater) than the periods of fall segments; only a single model could reproduce this emergent pattern. The asymmetry in amplitude and the period between rise and fall segments introduces a novel pattern in seasonal cycle analyses, but, while we show these emergent patterns exist in the data, we are still breaking ground in applying the information for science applications. Maybe the most useful application is that the segmentation analysis allowed us to decompose the model biases into their correlated parts of biases in amplitude, period and phase independently for rise and fall segments. We offer an extended discussion on how such information about model biases and the emergent patterns in satellite-derived seasonal cycles can be used to guide future inquiry and model development.

segmentation algorithm↗

Antarctic iron meteorites: An unexpectedly high proportion of falls of unusual interest

The inhabited and explored areas of Earth have contributed 725 iron meteorites, accounting for 28% of the 2611 authenticated meteorites known of all types. Observed fall statistics give a much different view of relative abundance. The 42 historic iron meteorite falls spanning 230 years suggests a frequency of one fall per 5.6 years and represents only 4.9% of the total 853 known falls. Antarctic iron meteorite recoveries offer promise of providing a new perspective on the influx problem. At least 42 iron meteorite specimens were found during the last 25 years by various field teams working in Antarctica. Most of these specimens were not described in detail, but the available data indicates that 21 separate falls are represented, 50% of the number of recovered specimens. Twelve of the 21 falls were both structurally classified and placed into chemical groups. They are listed in order of increasing structural complexity and/or Ni content.

Clarke, R. S., Jr.↗

Detection Thresholds of Falling Snow from Satellite-Borne Active and Passive Sensors

Precipitation, including rain and snow, is a critical part of the Earth's energy and hydrology cycles. In order to collect information on the complete global precipitation cycle and to understand the energy budget in terms of precipitation, uniform global estimates of both liquid and frozen precipitation must be collected. Active observations of falling snow are somewhat easier to estimate since the radar will detect the precipitation particles and one only needs to know surface temperature to determine if it is liquid rain or snow. The challenges of estimating falling snow from passive spaceborne observations still exist though progress is being made. While these challenges are still being addressed, knowledge of their impact on expected retrieval results is an important key for understanding falling snow retrieval estimations. Important information to assess falling snow retrievals includes knowing thresholds of detection for active and passive sensors, various sensor channel configurations, snow event system characteristics, snowflake particle assumptions, and surface types. For example, can a lake effect snow system with low (~2.5 km) cloud tops having an ice water content (Iwe) at the surface of 0.25 g m-3 and dendrite snowflakes be detected? If this information is known, we can focus retrieval efforts on detectable storms and concentrate advances on achievable results. Here, the focus is to determine thresholds of detection for falling snow for various snow conditions over land and lake surfaces. The analysis relies on simulated Weather Research Forecasting (WRF) simulations of falling snow cases since simulations provide all the information to determine the measurements from space and the ground truth. Results are presented for active radar at Ku, Ka, and W-band and for passive radiometer channels from 10 to 183 GHz (Skofronick-Jackson, et al. submitted to IEEE TGRS, April 2012). The notable results show: (1) the W-Band radar has detection thresholds more than an order of magnitude lower than the future GPM sensors, (2) the cloud structure macrophysics influences the thresholds of detection for passive channels, (3) the snowflake microphysics plays a large role in the detection threshold for active and passive instruments, (4) with reasonable assumptions, the passive 166 GHz channel has detection threshold values comparable to the GPM DPR Ku and Ka band radars with ~0.05 g m-3 detected at the surface, or an ~0.5-1 mm hr-l melted snow rate (equivalent to 0.5-2 cm hr-l solid fluffy snowflake rate).

Jackson, Gail↗

Meteoritic Material Recovered from the 07 March 2018 Meteorite Fall into the Olympic Coast National Marine Sanctuary

On 07 March 2018 at 20:05 local time (08 March 03:05 UTC), a dramatic meteor occurred over Olympic Coast National Marine Sanctuary (OCNMS) off of the Washington state coast (“OCNMS fall”, henceforth). Data to include seismometry (from both on-shore and submarine seismometers), weather radar imagery (Figure 1), and a moored weather buoy, were used to accurately identify the fall site. The site was visited by the exploration vessel E/V Nautilus (Ocean Exploration Trust) on 01 July 2018 [1] and by the research vessel R/V Falkor (Schmidt Ocean Institute) from 03-06 June 2019. Remotely operated vehicles (ROVs) from both vessels were used to search for meteorites and sample seafloor sediments. These expeditions performed the first attempts to recover meteorites from a specific observed fall in the open ocean. Analysis of weather radar data indicates that this fall was unusually massive and featured meteorites of unusually high mechanical toughness, such that large meteorites were disproportionately produced compared to other meteorite falls (Figure 2)[2-4]. We report the recovery of many (>100) micrometeorite-sized melt spherules and other fragments, and one small (~1mm3 ) unmelted meteorite fragment identified to date. Approximately 80% of the fragments were recovered from a single sample, collected from a round pit in the seafloor sediment. Melt spherules are almost exclusively type I iron-rich spherules with little discernible oxidation. Analyses are currently underway to attempt to answer the primary science question by identifying the parent meteorite type. Also, differences in the number and nature of samples collected by Nautilus and Falkor reveal a distinct loss rate to oxidation over the 15 months following the fall that is useful to inform future recovery efforts.

Fries, M.↗

A Review of Twenty-Six Years of U.S. Weather Radar Detection of Meteorite Falls

Weather radars have proven to be a valuable tool for detection, rapid recovery, and analysis of meteorite falls and fall statistics. The U.S. operates a nationwide weather radar network (NEXRAD) which will be discussed here, but it is important to acknowledge that weather radars operate worldwide and efforts are underway to utilize this rich resource. By the author’s count, since the NEXRAD system came online in the late 1990s it has detected 34 recovered meteorite falls and another 33 unrecovered probable falls. Weather radars are powerful tools because they directly detect meteorites falling after the end of their luminous flight, during the "dark flight" period. This allows rapid recovery through detection and modeling of fall locations down to as little as tens of meters. They are also the only tool that analyzes meteorites that survive their parent fireball, before many or all of them are lost to terrain. This allows direct measurement of meteorite mass, particle size distribution, and with additional work should allow calculation of pre-atmospheric mass and a measure of whole-body strength.

M D Fries↗

The accumulation rate of meteorite falls at the earth's surface - The view from Roosevelt County, New Mexico

The discovery of 154 meteorite fragments within an 11-sq km area of wind-excavated basins in Roosevelt County, New Mexico, permits a new calculation of the accumulation rate of meteorite falls at the earth's surface. Thermoluminescence dating of the coversand unit comprising the prime recovery surface suggests the maximum terrestrial age of the meteorites to be about 16.0 ka. The 68 meteorite fragments subjected to petrological analyses represent a minimum of 49 individual falls. Collection bias has largely excluded carbonaceous chondrites and achondrites, requiring the accumulation rate derived from the recovered samples to be increased by a factor of 1.25. Terrestrial weathering destroying ordinary chondrites can be modeled as a first-order decay process with an estimated half-life of 3.5 + or - 1.9 ka on the semiarid American High Plains. Having accounted for the age of the recovery surface, area of field searches, pairing of finds, collection bias and weathering half-life, an accumulation rate of 940 falls/a per 10 to the 6th sq km is calculated for falls greater than 10 g total mass. This figure exceeds the best-constrained previous estimate by more than an order of magnitude. One possible reason for this disparity may be the extraordinary length of the fall record preserved in the surficial geology of Roosevelt County. The high accumulation rate determined for the past 16 ka may point to the existence of periods when the meteorite fall rate was significantly greater than at present.

Zolensky, Michael E.↗

HALOE Temperature Data Comparison with Rocket-Borne Falling Sphere Temperatures

Recent comparison of upper stratospheric and mesospheric temperatures measured with the HALOE instrument on UARS and the rocket-borne passive inflatable falling sphere launched from Wallops Island reveals a temperature bias of up to 10 K between about 66 and 72 km. Falling sphere measurements analyzed between 1991 and 1995 were used in the comparison, however, these measurements were processed with an earlier version of the reduction software that included temperature bias in the region of 70 km. The bias arose from a discontinuity in the falling sphere drag table. This discontinuity occurs when the sphere's fall velocity changes from the supersonic to the subsonic flow regime and has been called the MACH 1 problem. Improvement to the software employed and the availability of a new atmospheric model is now used to initiate reduction of the radar tracking data. It is possible new reduction of the existing data will reduce the bias currently observed. We plan to show changes, if any, in the size of the bias between HALOE and the falling sphere temperatures after reprocessing of the sphere measurements.

Schmidlin, F. J.↗

Data Comparison: Satellite and Falling Sphere Temperatures

Small meteorological rocketsondes providing temperature data have beam used for comparison with, and validation of measurements from satellite-borne instruments. A significant number of rocket-borne falling spheres were launched in conjunction with the Upper Atmosphere Research Satellite (UARS) for validation of the Halogen Occultation Experiment (HALOE), High Resolution Doppler Interferometer (HRDI), and the Microwave Limb Sounder (MLS) instruments. Upper stratosphere and mesosphere temperatures measured with these instruments on UARS are compared with inflatable spheres launched from Wallops Island (1992-1999), Brazil (1994), Hawaii (1992), Norway (1992), and Sweden (1993 and 1996). Time and space differences varied between the satellite measurement and the rocketsonde launch, for example HALOE overpasses occurred within 5 days and in some cases there were spatial differences of up to 30 degrees longitude. Validation measurements of the HRDI instrument occurred at Wallops Island when it passed within 20 minutes and 330 kilometers of the launch site. Because of discontinuity in the falling sphere drag coefficients when fall speed neared MACH 1 falling sphere temperatures near 70 kilometers attitude are biased toward lower temperatures. Availability of improved software and a new atmospheric model have helped to reduce this bias. The validated remote instrument measurements permit a new perspective of atmospheric structure to be formed, not always possible with the limited number of falling sphere measurements. Features of the remote measurement temperature profiles and their possible use to extend the climatological data base at the rocketsonde sites will be discussed.

Schmidlin, Francis J.↗