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At least 163 records · Page 9

Imaging radar investigations of the Sudbury structure

This paper reports preliminary results of airborne imaging radar studies of the Sudbury structure carried out in preparation for a CCRS European Remote Sensing Satellite (ERS-1) investigation. The data used were synthetic aperture radar (SAR) C-band (5.66 cm) images acquired from about 6 km altitude in 1987. They cover the Sudbury area in both wide and narrow swath modes, with east-west flight paths and north-south illumination directions. Narrow swath resolution is 6 m in range and azimuth; wide swath resolution is 20 m in range and 10 m in azimuth. The STAR imagery has proven highly effective for field use, providing excellent rendition of topography and topographically expressed structure. Reasons for this include the illumination geometry, notably the look azimuth normal to the long axis of the Sudbury structure and Penokean fold axes, the good spatial resolution, and the short wavelength. Forested areas in the Sudbury area tend to be uniformly rough at C-band wavelength, with backscatter dominated by local incidence angle (i.e., topography). Field work using the SAR imagery has to date been concentrated in the North Range and Superior Province as far north as the Benny greenstone belt. This area was chosen for initial investigation of the original size and shape of the Sudbury structure because the effects of the Penokean Orogeny were minimal there. Field work using SAR indicates that there has been little postimpact deformation of the North Range or adjacent Superior Province rock. There appears to be no evidence for an outer ring concentric with the North Range as indicated by early Landsat imagery. The apparent ring shown by Landsat is visible on the SAR imagery as the intersection of two regional fracture patterns not related to the Sudbury structure. There is no outer ring visible southwest of the structure. This can reasonably be explained by Penokean deformation, but there is no outer ring to the northeast cutting the relatively undeformed Huronian sediments of the Cobalt Embayment.

Lowman, P. D.↗

Machine Learning Neutrino-Nucleus Cross Sections

Neutrino-nucleus scattering cross sections are critical theoretical inputs for long-baseline neutrino oscillation experiments. However, robust modeling of these cross sections remains challenging. For a simple but physically motivated toy model of the DUNE experiment, we demonstrate that an accurate neural-network model of the cross section—leveraging only Standard-Model symmetries— can be learned from near-detector data. We perform a neutrino oscillation analysis with simulated far-detector events, finding that oscillation analysis results enabled by our data-driven cross-section model approach the theoretical limit achievable with perfect prior knowledge of the cross section. We further quantify the effects of flux shape and detector resolution uncertainties as well as systematics from cross-section mismodeling. This proof-of-principle study highlights the potential of future neutrino near-detector datasets and data-driven cross-section models.

Tame-Narvaez, Karla [Fermilab] (ORCID:000000022249↗

Basic studies of baroclinic flows

A fully nonlinear 3-dimensional numerical model (GEOSIM), previously developed and validated for several cases of geophysical fluid flow, has been used to investigate the dynamical behavior of laboratory experiments of fluid flows similar to those of the Earth's atmosphere. The phenomena investigated are amplitude vacillation, and the response of the fluid system to uneven heating and cooling. The previous year's work included hysteresis in the transition between axisymmetric and wave flow. Investigation is also continuing of the flows in the Geophysical Fluid Flow Cell (GFFC), a low-gravity Spacelab experiment. Much of the effort in the past year has been spent in validation of the model under a wide range of external parameters including nonlinear flow regimes. With the implementation of a 3-dimensional upwind differencing scheme, higher spectral resolution, and a shorter time step, the model has been found capable of predicting the majority of flow regimes observed in one complete series of baroclinic annulus experiments of Pfeffer and co-workers. Detailed analysis of amplitude vacillation has revealed that the phase splitting described in the laboratory experiments occurs in some but not all cases. Through the use of animation of the models output, a vivid 3-dimensional view of the phase splitting was shown to the audience of the Southeastern Geophysical Fluid Dynamics Conference in March of this year. A study on interannual variability was made using GEOSIM with periodic variations in the thermal forcing. Thus far, the model has not predicted a chaotic behavior as observed in the experiments, although there is a sensitivity in the wavenumber selection to the initial conditions. Work on this subject, and on annulus experiments with non-axisymmetric thermal heating, will continue. The comparison of GEOSIM's predictions will result from the Spacelab 3 GFFC experiments continued over the past year, on a 'back-burner' basis. At this point, the study (in the form of a draft of a journal article) is nearly completed. The results from GEOSIM compared very well with the experiments, and the use of the model allows the demonstration of flow mechanics that were not possible with the experimental data. For example, animation of the model output shows that the forking of the spiral bands is a transient phenomenon, due to the differential east-west propagation of convection bands from different latitudes.

Miller, Timothy L.↗

Combined Mesonet and Tracker

Title: Combined Mesonet and Trackers (UNL Mobile Mesonets) Authors University of Nebraska PI: Adam Houston, UNL Professor (ahouston2@unl.edu) Mailing Address: 126 Bessey Hall P.O. Box 880340 Lincoln, NE 68588-0340 CoMeT Overview The University of Nebraska-Lincoln operates three Combined Mesonet and Tracker (CoMeTs). CoMeTs are Ford Explorers (model years 2015, 2017, and 2019) with forward-mounted suites of meteorological sensors and dual moonroofs, combining the capability of a mobile mesonet to collect near-surface observations with the capability of an unmanned aircraft systems (UAS) tracker vehicle, which enables an observer in the second row of seats to see the aircraft and maintain compliance with Federal Aviation Administration policies on UAS operation. The CoMeTs collect observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155A, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, and vehicle heading using a KVH Industries C-100 fluxgate compass (Barbieri et al. 2019). The HMP155A and 109SS-L thermistor are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). This list of sensors is also included in the CoMeT data file metadata. Manufacturer specifications for these instruments are given in Table 1 of Hanft and Houston (2018). The reported measured quantities are summarized below.CoMeT-3 was funded through an equipment allocation included in the NSF TORUS award (AGS-1824649). Instrument Description The specific sensors included on each CoMeT are summarized in the table at the end of this section. In general each CoMeT collects observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210 barometer with a Gill pressure port, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, position using a Garmin 19x HVS receiver, and vehicle heading using a KVH Industries C-100 fluxgate compass. The HMP155 and 109SS are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). Fast temperature and corrected RH measurements (using sensors housed within the U-tube) have a time constant of 10-12 s based on data collected across a temperature and RH shock during the CLOUD-MAP 2017 calibration/validation tests on June 26, 2017. Vehicle speed was < 10 kts for this test. CoMeT-1 CoMeT-2 CoMeT-3 Slow Temperature Slow RH Vaisala HMP155A-L20-PT Part #: 22280-7 Vaisala HMP155E Part #: E1AA11A0B1A1A0A Vaisala HMP155E Part #: E1AA11A0B1A1A0A Fast temperature Campbell Scientific 109SS-L20-PT Part #: 21448-3 Campbell Scientific 109SS-L12-PW Part #: 21448-109 Campbell Scientific 109SS-L12-PW Part #: 21448-150 Pressure Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Wind RM Young 05103-L20-PT Part #: 18435-310 RM Young 05103-L20-PW Part #: 18435-244 RM Young 05103-L20-PW Part #: 18435-244 GPS Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Compass KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 Logger Campbell Scientific CR6-NA-XT-SW Part #: 28385-9 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Data Collection and Real-Time Processing The reported measured quantities are summarized in the table below. Quantity Units Source Epoch time Seconds GPS Latitude and longitude Degrees GPS Altitude m GPS Pressure hPa PTB210 Temperature (fast) deg C 109SS-L Temperature (slow) deg C HMP155 RH (slow) % HMP155 Vehicle speed m/s GPS Vehicle heading deg C-100 and GPS In addition to the measured variables, several derived variables are calculated. Corrected/fast relative humidity (%) Relative humidity is adjusted to the fast temperature following Richardson et al. (1998) and Houston et al. (2016). Water vapor mixing ratio (g/kg) Dew point temperature (&deg;C) Potential temperature (Kelvin) Virtual potential temperature (Kelvin) Equivalent potential temperature (Kelvin) Regular intercomparisons between all three CoMeTs were performed during TORUS 2019. Comparisons were also conducted between CoMeT-1 and CoMeT-2 during LAPSE-RATE (2018) on 14 July. In these intercomparisons, the vehicles were parked adjacent to each other aligned perpendicular to (and facing into) the wind. To minimize engine heating effects, intercomparisons were only conducted when the wind speed was >10 kts. Data Format Original data files for each deployment are saved as text files and then converted to NetCDF. NetCDF versions have units that are CF compliant and may not match the original units in the txt files. The naming convention for the NetCDF files is as follows: UNL.CoMeT3.{deployment date YYYYMMDD}.{start time of observation collection in UTC HHMM}.L2.{post-processing codes}.cdf example: UNL.CoMeT3.20190627.1931.L2.g1.f1.cdf Post-processing codes are included to track modifications to the raw data. These codes are closely connected to error flags associated with each record. Each letter corresponds to a particular instrument: g: GPS p: Barometer tf: Fast temperature ts: Slow temperature rh: Relative humidity f: Compass w: Wind monitor a: All instruments Each number corresponds to a particular post-processing action described more below. Measured and derived variables are included in the following table. Variable Heading Standard Name Units time Time seconds since 00:00:00, 01-01-1970 Alt Altitude meters lat Latitude degrees north lon Longitude degrees east fast_temp Air Temperature kelvin slow_temp Air Temperature kelvin pressure Air Pressure pascals logger_RH Relative Humidity percent calc_corr_RH Relative Humidity percent wind_speed Wind Speed meters per second wind_dir Wind From Direction degrees vehicle_dir Vehicle Direction degrees dewpoint Dew Point Temperature kelvin mixing_ratio Humidity Mixing Ratio g/g theta Air Potential Temperature kelvin theta_v Virtual Potential Temperature kelvin theta_e Equivalent Potential Temperature Kelvin error_flag The error_flag variable is a string that matches the post-processing codes listed above. All instruments will have an associated code, but will have a &ldquo;0&rdquo; if the datum is unchanged from the initial processed value. Error Codes The following table summarizes the error codes for data collected before 2020: Error Code Relevant CoMeT Description g1 1,2,3 Exact correction. GPS position and time reprocessed from raw data g2 1 As far as we can tell this is an exact correction to an error in the GPS time. During the correct time periods the time suddenly went backwards ~250s and stayed at this offset for 750s when it corrected itself. The offset was applied to the &ldquo;time warp&rdquo; period. p1 2 Approximate correction. Hole in the pressure tube connecting the pressure port to the barometer. Resulted in erroneously low air pressure measurements when the vehicle was in motion. Derived variables recalculated (dew point temperature [e depends on qv and p], water vapor mixing ratio, potential temperature, virtual potential temperature, equivalent potential temperature) a1 3 Exact correction. Missing data reprocessed from raw data a2 1 Bug fix to bias correction for ts1, ts2, and rh1: water vapor mixing ratio was off by a factor of 10 and virtual potential temperature was wrong because of this. f1 3 No correction, missing data. Fluxgate compass inoperable. Wind speed and direction calculated using GPS-derived vehicle heading instead. rh1 1 Approximate correction. Constant bias of +1.7% removed from relative humidity. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts1 1 Approximate correction. Constant bias of +0.6 K removed from slow temperature. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts2 1 Approximate correction. Constant bias of +1.0 K removed. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) References Bolton, D., 1980: The Computation of Equivalent Potential Temperature. Mon. Wea. Rev., 108, 1046&ndash;1053, https://doi.org/10.1175/1520-0493(1980)108<1046:TCOEPT>2.0.CO;2. Hanft, W., and A. L. Houston, 2018: An Observational and Modeling Study of Mesoscale Air Masses with High Theta-E. Mon. Wea. Rev., 146, 2503&ndash;2524, https://doi.org/10.1175/MWR-D-17-0389.1.Wexler Houston, A. L., R. J. Laurence III, T. W. Nichols, S. Waugh, B. Argrow, and C. L. Ziegler, 2016: Intercomparison of unmanned aircraft-borne and mobile mesonet atmospheric sensors. Journal of Atmospheric and Oceanic Technology. 33, 1569-1582, doi: 10.1175/JTECH-D-15-0178.1. Lowe, P. R., 1977: An Approximating Polynomial for the Computation of Saturation Vapor Pressure. J. Applied Meteorology, 16, 100&ndash;103. Richardson, S. J., S. E. Frederickson, F. V. Brock, and J. A. Brotzge, 1998: Combination temperature and relative humidity probes: Avoiding large air temperature errors and associated relative humidity errors. Preprints, 10th Symp. On Meteorological Observations and Instrumentation, Phoenix, AZ, Amer. Meteor. Soc., 278&ndash;283. Waugh, S., and S. E. Frederickson, 2010: An improved aspirated temperature system for mobile meteorological observations, especially in severe weather. 25th Conf. on Severe Local Storms, Denver, CO, Amer. Meteor. Soc., P5.2. [Available online at https://ams.confex.com/ams/25SLS/techprogram/paper_176205.htm.]

54 ENVIRONMENTAL SCIENCES↗

Experimental test of the ratio method for nuclear-reaction analysis

Nuclear halos are exotic quantal structures observed far from stability. They are mostly studied through reactions. The ratio of angular cross sections for breakup and scattering is predicted to be independent of the reaction process and to be very sensitive to the halo structure. We test this new observable experimentally for the first time on the collision of 11 Be on C at 22.8 MeV/nucleon and using existing data on Pb at 19.1 MeV/nucleon. The theoretical predictions are verified, which offers the possibility to develop a new spectroscopic tool to study nuclear structure far from stability.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Hurricane Directional Wave Spectrum Spatial Variation in the Open Ocean and at Landfall

The sea surface directional wave spectrum was measured for the first time in all quadrants of a hurricane in open water using the NASA airborne scanning radar altimeter (SRA) carried aboard one of the NOAA WP-3D hurricane hunter aircraft at 1.5 km height. The SRA measures the energetic portion of the directional wave spectrum by generating a topographic map of the sea surface. At 8 Hz, the SRA sweeps a radar beam of 1 E half-power width (two-way) across the aircraft ground track over a swath equal to 0.8 of the aircraft height, simultaneously measuring the backscattered power at its 36 GHz (8.3 mm) operating frequency and the range to the sea surface at 64 positions. These slant ranges are multiplied by the cosine of the incidence angles to determine the vertical distances from the aircraft to the sea surface. Subtracting these distances from the aircraft height produces the sea surface elevation map. The sea surface topography is interpolated to a uniform grid, transformed by a two-dimensional FFT, and Doppler corrected. The open-ocean data were acquired on 24 August 1998 when hurricane Bonnie was east of the Bahamas and moving slowly to the north. Individual waves with heights up to 18 m were observed and the spatial variation of the wave field was dramatic. The dominant waves generally propagated at significant angles to the downwind direction. At some positions there were three different wave fields of comparable energy crossing each other. The NOAA aircraft spent over five hours within 180 km of the hurricane Bonnie eye, and made five eye penetrations. A 3-minute animation of the directional wave spectrum spatial variation over this period will be shown as well as summary plots of the wave field spatial variation. On 26 August 1998, the NOAA aircraft flew at 2.2 km height when hurricane Bonnie was making landfall near Wilmington, NC, documenting the directional wave spectrum in the region between Charleston, SC and Cape Hatteras, NC. The aircraft ground track included both segments along the shoreline and Pamlico Sound as well as far offshore. An animation of the directional wave spectrum spatial variation at landfall will be presented and contrasted with the spatial variation when Bonnie was in the open ocean on 24 August 1998.

Walsh, E. J.↗

A multi-frequency study of the peculiar interacting system Arp 206

Arp 206 is a nearby, relatively large, and bright interacting system comprising unequal members: NGC 3432 and UGC 5983. A third anonymous galaxy, Arp 206c, is visible in the field. The CCD images show a well-developed bridge between NGC 3432 and UGC 5983. On the other hand, the complex H I tails are not visible in the optical. In the total H I map, the bridge is lost in a general envelope encompassing both galaxies. The bridge also appears to have some radio emission. On the Total H I map the system is rather edge-on, far more than it would appear in optical wavelengths. UGC 5983 falls exactly in line with NGC 3432. The velocity of the centers of mass of NGC 3432 and UGC 5983 are 530 km s(exp -1) and 630 km s(exp -1), respectively. In view of the considerable damage sustained by NGC 3432 and the apparent low mass of UGC 5983, it appears that the passage must have been at near parabolic speed, with a small pericentric distance and a very low inclination with rspect to the disk of NGC 3432. The apparent distribution of H I along the z axis of the galaxy could be accounted for by projection effects. The tidal appendage found at higher velocities, which rises at a P.A. approx. equal to 25 degrees west of the main body of the galaxy is probably the tail, the part of the tidal damage away from the perturbing companion. The bridge may be rising north-east from the galaxy and then continue under to the south of the galaxy. The relative sizes of the appendages would indicate that the pericenter was crossed recently. Any further inferences about the collision parameters will need to await the results of detailed computational modelling of the interaction. The authors also summarize the observational characteristics of NGC 3432, UGC 5983, and Arp 206c.

Noreau, Louis↗

A 2000 Solar Mass Rotating Molecular Disk Around NGC 6334A

We present millimeter and centimeter wave spectroscopic observations of the H II region NGC 6334A. We have mapped the source in several transitions of CO, CS, and NH3. The molecular emission shows a distinct flattened structure in the east-west direction. This structure is probably a thick molecular disk or torus (2.2 x 0.9 pc) responsible for the bipolarity of the near-infrared (NIR) and radio continuum emission which extends in two "lobes" to the north and south of the shell-like H II region. The molecular disk is rotating from west to east (omega approximately equals 2.4 km/s.pc) about an axis approximately parallel to the radio and NIR emission lobes. By assuming virial equilibrium, we find that the molecular disk contains approximately 2000 solar mass. Single-component gas excitation model calculations show that the molecular gas in the disk is warmer and denser (T(sub k) approximately equals 60 K, n approximately equals 3000/cc) than the gas to the north and south (T(sub k) approximately equals 50 K, n approximately equals 400/cc). High resolution (approximately 5 sec) NH3 (3, 3) images of NGC 6334A reveal several small (approximately 0.1 pc) clumps, one of which lies southwest of the radio continuum shell, and is spatially coincident with a near-infrared source, IRS 20. A second NH3 clump is coincident with an H2O maser and the center of a molecular outflow. The dense gas tracers, CS J = 5 approaches 4 and 7 approaches 6, peak near IRS 20 and the H2O maser, not at NGC 6334A. IRS 20 has a substantial far-infrared (FIR) luminosity L(sub FIR) approximately 10(exp 5) solar luminosity, which indicates the presence of an O 7.5 star but has no detected radio continuum (F(sub 6 cm) < 0.02 Jy). The combination of dense gas, a large FIR luminosity and a lack of radio continuum can best be explained if IRS 20 is a protostar. A third clump of NH3 emission lies to the west of IRS 20 but is not associated with any other molecular or continuum features. The star formation activity in the region has moved west of NGC 6334A to IRS 20 and the H2O maser position. We suggest that NGC 6334A, IRS 20, and the H2O maser spot are part of a "protocluster" of stars which is condensing from the massive molecular disk. The similarity between the structure around NGC 6334A and other large (r approximately 1 pc), massive (M approximately 10(exp 3) solar mass), rotating disks (K3-50A and G10.6-0.4) suggests that this may be a common mechanism by which open clusters form.

Kraemer, Kathleen E.↗

Global Positioning System (GPS) Precipitable Water in Forecasting Lightning at Spaceport Canaveral

Using meteorology data, focusing on precipitable water (PW), obtained during the 2000-2003 thunderstorm seasons in Central Florida, this paper will, one, assess the skill and accuracy measurements of the current Mazany forecasting tool and, two, provide additional forecasting tools that can be used in predicting lightning. Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) are located in east Central Florida. KSC and CCAFS process and launch manned (NASA Space Shuttle) and unmanned (NASA and Air Force Expendable Launch Vehicles) space vehicles. One of the biggest cost impacts is unplanned launch scrubs due to inclement weather conditions such as thunderstorms. Each launch delay/scrub costs over a quarter million dollars, and the need to land the Shuttle at another landing site and return to KSC costs approximately $ 1M. Given the amount of time lost and costs incurred, the ability to accurately forecast (predict) when lightning will occur can result in significant cost and time savings. All lightning prediction models were developed using binary logistic regression. Lightning is the dependent variable and is binary. The independent variables are the Precipitable Water (PW) value for a given time of the day, the change in PW up to 12 hours, the electric field mill value, and the K-index value. In comparing the Mazany model results for the 1999 period B against actual observations for the 2000-2003 thunderstorm seasons, differences were found in the False Alarm Rate (FAR), Probability of Detection (POD) and Hit Rate (H). On average, the False Alarm Rate (FAR) increased by 58%, the Probability of Detection (POD) decreased by 31% and the Hit Rate decreased by 20%. In comparing the performance of the 6 hour forecast period to the performance of the 1.5 hour forecast period for the Mazany model, the FAR was lower by 15% and the Hit Rate was higher by 7%. However, the POD for the 6 hour forecast period was lower by 16% as compared to the POD of the 1.5 hour forecast period. Neither forecast period performed at the accuracy measures expected. A 2-Hr Forecasting Tool was developed to support a Phase I Lightning Advisory, which requires a 30-minute lead time for predicting lightning.

Kehrer, Kristen↗

TRMM Observations of Convective Regimes in the Amazon

This study utilizes TRMM satellite precipitation radar, lightning imaging sensor, and passive microwave imager data together with ground-based lightning data to investigate the vertical structure, lightning, and rainfall characteristics of Amazonian and central South American convection for three separate wet-seasons. These characteristics are partitioned as a function of 850 mb zonal wind direction, motivated by observations collected during the six-week TRMM-LBA field campaign. The TRMM-LBA field campaign observations suggest that systematic variations in Amazonian convective vertical structure, lightning, and rainfall are all linked to bimodal variations in the low-level zonal wind (e.g., easterly and westerly regimes). The more spatially and temporally comprehensive TRMM dataset used in this study extends the TRMM-LBA observations by examining regime variability in Amazonian and South American convective structure over a continental scale domain. On a continental-scale, patterns of east and west regime 850 mb winds combined with LIS lightning flash densities suggest the presence of synoptic-scale controls (e.g., intrusion of extratropical frontal systems and interaction with the SACZ) on regional-scale variability in convective vertical structure. TRMM PR, TMI and ground-based lightning data suggest that regional variability in wet-season convective structure is most evident over the southern Amazon, Mato Grosso, Altiplano, southern Brazil, and eastern coastal regions of central and southern South America. Convective vertical structure, rain fall rates, and lightning activity are all more pronounced during easterly (westerly) regimes over the southern Amazon and Mato Grosso (Altiplano, and southern Brazil). Importantly, when considered with case-study results from TRMM-LBA, the systematic differences in convective structure that occur as a function of regime suggest that associated regime-differences may exist in the vertical distribution of diabatic heating. Hence the discrimination of convective vertical structure "regimes" over parts of the Amazon and vicinity based on a resolved variable such as the 850 mb zonal wind direction, while far from being perfect, may have important applications to the problems of cumulus parameterization, rainfall estimation and retrievals of latent heating over the Amazon.

Petersen, W. A.↗

Africa's Megafans and Their Tectonic Setting

Megafans are a really extensive continental sediment bodies, fluvially derived, and fan-shaped in planform. Only those >80 km long were included in this study. Africa's megafans were mapped for purposes of both comprehensive geomorphic description and as a method of mapping by remote sensing large probable fluvial sediment bodies (we exclude sediment bodies deposited in well defined, modern floodplains and coastal deltas). Our criteria included a length dimension of >80 km and maximum width >40 km, partial cone morphology, and a radial drainage pattern. Visible and especially IR imagery were used to identify the features, combined with topographic SRTM data. We identified 99 megafans most of which are unstudied thus far. Their feeder rivers responsible for depositing megafan sediments rise on, and are consequent drainages oriented down the slopes of the swells that have dominated African landscapes since approximately 34 Ma (the high points in Africa's so-called basin-and-swell topography [1]). Most megafans (66%) have developed along these consequent rivers relatively near the swell cores, oriented radially away from the swells. The vast basins between the swells provide accommodation for megafan sediment wedges. Although clearly visible remotely, most megafans are inactive as a result of incision by the feeder river (which then no longer operates on the fan surface). Two tectonic settings control the location of Africa's megafans, 66% on swell flanks, and 33% related to rifts. (i) Swell flanks Most megafans are apexed relatively near the core of the parent swell, and are often clustered in groups: e.g., six on the west and north flanks of the Hoggar Swell (Algeria), seven on the north and south flanks of the Tibesti Swell (Libya-Chad borderlands), twelve on the west flank of the Ethiopian Swell, four on the east flank of the East African Swell (Kenya), Africa's largest, and eight around Angola's Bié Swell (western Zambia, northern Namibia). A cluster of possible fans lies on the western margin of the Congo Basin (Mayombe Swell), and on the coastal slopes of the Namibia Swell. Sheer size may have militated aginst the recognition of many megafans: the largest in the Sahara are the Teghahart (378 km, Hoggar Swell, Algeria), and the Wadi Albalata (340 km, Uweinat Swell, Egypt). In southern Africa the largest are the Cubango (320 km, Bié Swell, Angola/ Namibia), and the Limpopo (230 km, Mozambique). (ii) Rift zones (a) Steer's horns basins-wide depressions centered on rifts. The largest contiguous group (n=14) developed in a steer's-horns basin occupies the wide Muglad depression (200-350 km, South Sudan). Four rift-related megafans lie SE of Lake Chad (Chad). Nine megafans occupy the complex Anza Rift in Kenya/South Somalia. The Salamat megafan (Chad), is unusual because it oriented parallel with the linked Salamat, Doseo and Doba rift axes, and is consequently one of the longest in Africa (465 km). (b) Rift depressions sensu stricto. Most rifts are too narrow to provide a transverse dimension large enough to accommodate megafans. Although well-known, the Okavango Rift (NW Botswana, NE Namibia) is unique in Africa in hosting three megafans within identifiable faulted margins. The Nile megafan is Africa's largest (476 km) and comprises the vast Sudd wetland (South Sudan). An explanation for its remarkable size may be its location in a depression at the junction of two conducive tectonic zones, the East African Swell margin and the Muglad steer's-horns depression. Discharge of the River Nile, the largest in the region, has allowed the Nile megafan to outcompete neighboring megafans for space.

Wilkinson, M. J.↗

The Origins Space Telescope: Mission Concept Overview

The Origins Space Telescope (OST) will trace the history of our origins from the time dust and heavy elements permanently altered the cosmic landscape to present-day life. How did the universe evolve in response to its changing ingredients? How common are life-bearing planets? To accomplish its scientific objectives, OST will operate at mid- and far-infrared wavelengths and offer superlative sensitivity and new spectroscopic capabilities. The OST study team will present a scientifically compelling, executable mission concept to the 2020 Decadal Survey in Astrophysics. To understand the concept solution space, our team studied two alternative mission concepts. We report on the study approach and describe both of these concepts, give the rationale for major design decisions, and briefly describe the mission-enabling technology.

Leisawitz, D.↗

Crustal flushing and its relationship to magnetic and hydrothermal processes on the East Pacific Rise crest

The deep-towed Argo I optical/acoustical vehicle and a geographic information system (GIS) have been used to establish the abundance, widths, and spatial distribution of fissures, as well as the relative age distribution of lavas along the narrow (less than 500 m wide) axial zone of the East Pacific Rise (EPR) from 9 deg 12 min to 9 deg 54 min N. On a second-order scale (approximately 78 km long), wider but less numerous fissures are found in the northern portion of the survey area; this changes to narrower, more abundant fissures in the south. A profile of the cumulative width added by fissures to the axial zone exhibits minima in three areas along strike (near 9 deg 49 min, 9 deg 35 min, and 9 deg 15 min N), where the most recent eruptions have occurred above sites of magmatic injection from the upper mantle, filling and covering older fissures. On a fourth-order scale (5-15 km long) the mean density of fissuring on a given segment is greater where relative axial lava age is greater. Fissure density also correlates with hydrothermal vent abundance and type. Increased cracking toward segment tips is observed at the second-order scale, whereas fourth-order segments tend to be more cracked in the middle. Cracking on a fourth-order scale may be driven by the propagation of dikes, rather than by the far-field plate stresses. The above relations constrain the model of Haymon et al. (1991) in which individual fourth-order segments are in different phases of a volcanic-hydrothermal-tectonic cycle.

Wright, Dawn J.↗

Experimental Test of the Ratio Method for Nuclear-Reaction Analysis

Nuclear halos are exotic quantal structures observed far from stability. They are mostly studied through reactions. The ratio of angular cross sections for breakup and scattering is predicted to be independent of the reaction process and to be very sensitive to the halo structure. Here, we test this new observable experimentally for the first time on the collision of 11 Be on C at 22.8 MeV/nucleon and using existing data on Pb at 19.1 MeV/nucleon. The theoretical predictions are verified, which offers the possibility of developing a new spectroscopic tool to study nuclear structure far from stability.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Observations and seismoacoustic simulations of earthquake-generated infrasound waves in non-epicentral regions

We analysed infrasound waves associated with the Gyeongju earthquake (ML 5.8) that occurred on 2016 September 12, in the southeastern Korean Peninsula. For infrasound wave detection, the Progressive Multichannel Correlation method was applied to the infrasound data set recorded at seven arrays operating in South Korea at epicentral distances ranging from 178 to 472 km. Based on the back-projection method constrained by array-dependent celerity and azimuth deviation models, the source regions were identified in both the epicentral and non-epicentral regions. Remarkably, the non-epicentral secondary sources of this earthquake were located in regions with shallow water depths: (i) the western coastal area in the Yellow Sea and (ii) the shallow ocean basin and bank in the East Sea. The location results obtained from the earthquake could be corroborated through its foreshock (ML 5.1), yielding location results consistent with those of the main shock. The generation of infrasound waves over shallow water depths was fortuitously validated by direct recordings of dominant single-frequency (~0.3 Hz) infrasound waves at close range via temporary sensors near the ocean basin and bank. We interpreted that low-frequency infrasound signals could be generated from interactions among the ocean floor, shallow seawater and atmosphere. We performed numerical simulations of seismoacoustic fields to predict ground motions on the seafloor and acoustic transmission efficiency between the water and air interface. The simulations quantified the energy transfer through different media and clarified our observational results. We found that because this solid Earth‒water‒atmosphere coupled air wave has a relatively low frequency (~0.3 Hz), it can survive propagation over long distances compared with high-frequency infrasound waves generated in inland and mountain regions. In this study, we extend our understanding of water‒atmosphere coupling and the monitoring framework for earthquake-associated non-epicentral infrasound waves, encompassing not only inland ground shaking but also shallow sea regions located far from the epicentre.

Earthquake monitoring and test-ban treaty verifica↗

A Combined Observational and Modeling Approach to Study Modern Dust Transport from the Patagonia Desert to East Antarctica

The understanding of present atmospheric transport processes from Southern Hemisphere (SH) landmasses to Antarctica can improve the interpretation of stratigraphic data in Antarctic ice cores. In addition, long range transport can deliver key nutrients normally not available to marine ecosystems in the Southern Ocean and may trigger or enhance primary productivity. However, there is a dearth of observational based studies of dust transport in the SH. This work aims to improve current understanding of dust transport in the SH by showing a characterization of two dust events originating in the Patagonia desert (south end of South America). The approach is based on a combined and complementary use of satellite retrievals (detectors MISR, MODIS, GLAS ,POLDER, OMI,), transport model simulation (HYSPLIT) and surface observations near the sources and aerosol measurements in Antarctica (Neumayer and Concordia sites). Satellite imagery and visibility observations confirm dust emission in a stretch of dry lakes along the coast of the Tierra del Fuego (TdF) island (approx.54deg S) and from the shores of the Colihue Huapi lake in Central Patagonia (approx.46deg S) in February 2005. Model simulations initialized by these observations reproduce the timing of an observed increase in dust concentration at the Concordia Station and some of the observed increases in atmospheric aerosol absorption (here used as a dust proxy) in the Neumayer station. The TdF sources were the largest contributors of dust at both sites. The transit times from TdF to the Neumayer and Concordia sites are 6-7 and 9-10 days respectively. Lidar observations and model outputs coincide in placing most of the dust cloud in the boundary layer and suggest significant de- position over the ocean immediately downwind. Boundary layer dust was detected as far as 1800 km from the source and approx.800 km north of the South Georgia Island over the central sub-Antarctic Atlantic Ocean. Although the analysis suggests the presence of dust at approx.1500 km SW of South Africa five days after, the limited capabilities of existing satellite platforms to differentiate between aerosol types do not permit a definitive conclusion. In addition, the model simulations show dust lifting to the free troposphere as it travels south but it could not be confirmed by the satellite observations due to cloudiness. This work demonstrates that complementary information from existing transport models, satellite and surface data can yield a consistent picture of the dust transport from the Patagonia desert to Antarctica. It also illustrates the limitation of using any of these approaches individually to characterize the transport of dust in a heavily cloudy area.

Gasso, S.↗

Land-Based Wind Market Report: 2021 Edition

The U.S. Department of Energy's 2021 edition of its land-based wind market report provides an overview of key trends in the U.S. wind power market, with a focus on 2020. You can find a report, data file and presentation on the Files tab, below. Additionally, several data visualizations are available on the Visualizations tab. Highlights of this year’s update include: -Wind comprises a growing share of electricity supply: U.S. wind power capacity grew at a record pace in 2020, with 25 billion dollars invested in 16.8 GW of capacity. Wind energy output rose to account for more than 8% of the entire nation’s electricity supply, and is more than 20% in 10 states. At least 209 GW of wind are seeking transmission interconnection; 61 GW of this capacity are offshore wind and 13 GW are hybrid plants that pair wind with storage or PV. -Wind project performance has increased over time: The average capacity factor among recently built projects was over 40%, considerably higher than projects built earlier. The highest capacity factors are seen in the interior ‘wind belt’ of the country. -Turbines continue to get larger: Improved plant performance has been driven by larger turbines mounted on taller towers and featuring longer blades. In 2010, no turbines employed blades that were 115 meters in diameter or larger, but in 2020, 91% of newly installed turbines featured such rotors. Proposed projects indicate that total turbine height will continue to rise. -Low wind turbine pricing has pushed down installed project costs over the last decade: Wind turbine prices are averaging 775–850 dollars/kW. The average installed cost of wind projects in 2020 was 1,460 dollars/kW, down more than 40% since the peak in 2010, though stable for the last three years. The lowest costs were found in Texas and the (non-ISO) West. -Wind energy prices remain low, around 20 dollars/MWh in the interior of the country: After topping out at 70 dollars/MWh for power purchase agreements (PPAs) executed in 2009, the national average price of wind PPAs has dropped. In the interior ‘wind belt’ of the country, recent pricing is around 20 dollars/MWh. In the West and East, prices tend to average 30 dollars/MWh or more. These prices, which are possible in part due to federal tax support, fall below the projected future fuel costs of gas-fired generation. -Wind PPA prices are often attractive compared to wind’s grid-system market value: The value of wind in wholesale power markets is affected by the location of wind plants, their hourly output profiles, and how those characteristics correlate with real-time electricity prices and capacity markets. The market value of wind declined in 2020, following natural gas prices lower and averaging under 15 dolalrs/MWh in ERCOT, MISO, NYISO and SPP; higher values were seen in CAISO, ISO-NE and PJM. -The average levelized cost of wind energy is down to 33 dollars/MWh: Levelized costs, which exclude the impacts of federal tax incentives, vary across time and geography, but the national average stood at 33 dollars/MWh in 2020—down substantially historically, though consistent with the previous two years. Levelized costs were lowest in ERCOT, SPP, and the (non-ISO) West. -The health and climate benefits of wind in 2020 were larger than its grid-system value, and the combination of all three far exceeds the current levelized cost of wind: Wind generation reduces power-sector emissions of carbon dioxide, nitrogen oxides, and sulfur dioxide. These reductions, in turn, provide public health and climate benefits that vary regionally, but together are economically valued at an average of 76 dollars/MWh-wind nationwide in 2020. -The domestic supply chain for wind equipment is diverse: For wind projects recently installed in the U.S., domestically manufactured content is highest for nacelle assembly (>85%), towers (60-75%), and blades and hubs (30-50%), but is much lower for most components internal to the nacelle.

17 WIND ENERGY↗

Land-Based Wind Market Report: 2022 Edition

The U.S. Department of Energy's 2022 edition of its Land-Based Wind Market Report provides an overview of key trends in the U.S. wind power market, with a focus on 2021. You can find a report, data file and presentation on the Files tab, below. Additionally, several data visualizations are available on the Visualizations tab. Despite ongoing supply chain challenges, wind energy in 2021 continued to see strong growth, technology improvements, and low prices in the U.S. Key highlights include: Wind comprises a growing share of electricity supply: U.S. wind power capacity grew at a strong pace in 2021, with the 13.4 GW of new additions representing a $\$20$ billion investment and 32% of all newly added U.S. generation capacity. Wind energy output rose to account for more than 9% of the entire nation’s electricity supply. At least 247 GW of wind are seeking transmission interconnection; 77 GW of this capacity are offshore wind and 19 GW are hybrid plants that pair wind with storage or solar PV. Wind project performance has increased over the decades: The average capacity factor among recently built projects was nearly 40%, considerably higher than projects built earlier. The highest capacity factors are seen in the interior ‘wind belt’ of the country. Turbines continue to get larger: Improved plant performance has been driven by larger turbines mounted on taller towers and featuring longer blades. In 2011, no turbines employed blades that were 115 meters in diameter or larger, but in 2021, 89% of newly installed turbines featured such rotors. Proposed projects indicate that total turbine height will continue to rise. Low wind turbine pricing has pushed down installed project costs over the last decade: Wind turbine prices averaged $\$800$–$\$950$/kW in 2021, a 5% to 10% increase from the year prior but substantially lower than in 2010. The average installed cost of wind projects in 2021 was $\$1,500$/kW, down more than 40% since the peak in 2010, though relatively stable in recent years. The lowest costs were found in Texas and the (non-ISO) West. Wind energy prices are on the rise, but generally remain low, around $\$20$/MWh in the interior of the country with higher prices in the West and East. After topping out above $\$75$/MWh for power purchase agreements (PPAs) executed in 2009, the national average price of wind PPAs has dropped—though supply-chain pressures have resulted in increased prices in recent years. In the interior ‘wind belt’ of the country, recent pricing is around $\$20$/MWh. In the West and East, prices tend to average above $\$30$/MWh. These prices, which are possible in part due to federal tax support, fall below the projected future fuel costs of gas-fired generation. Wind PPA prices are often attractive compared to wind’s grid-system market value: The value of wind in wholesale power markets is affected by the location of wind plants, their hourly output profiles, and how those characteristics correlate with real-time electricity prices and capacity markets. The market value of wind increased in 2021, averaging $\$16$/MWh in MISO, $\$19$/MWh in SPP, $\$23$/MWh in NYISO, $\$31$/MWh in ERCOT, $\$33$/MWh in PJM, $\$44$/MWh in ISO-NE, and $\$48$/MWh in CAISO. The average levelized cost of wind energy was $\$32$/MWh for plants built in 2021: Levelized costs, which exclude the impacts of federal tax incentives, vary across time and geography. The national average stood at $\$32$/MWh in 2021—down substantially historically, though relatively stable in recent years. Levelized costs were lowest in ERCOT, SPP, and the (non-ISO) West. The health and climate benefits of wind in 2021 were larger than its grid-system value, and the combination of all three far exceeds the current levelized cost of wind: Wind generation reduces power-sector emissions of carbon dioxide, nitrogen oxides, and sulfur dioxide. These reductions, in turn, provide public health and climate benefits that vary regionally, but together are economically valued at an average of over $\$90$/MWh-wind for plants built in 2021.

17 WIND ENERGY↗