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384 records · Page 22

Development of a triple-moment ice-phase cloud microphysics scheme and its application to the Single Column Atmosphere Model

Parameterization of cloud microphysics is critical for accurate simulation of weather and climate, in which the characteristics of cloud particle spectrum inevitably further affect climate simulation by changing the cloud evolution and cloud radiation effects. The popular currently used double-moment cloud microphysics schemes in numerical models can predict the intercept (N 0 ) and slope (λ) parameters of cloud particle spectrum but cannot predict the spectral shape parameter (μ), which hinders accurate description of cloud physical processes in climate models. Therefore, in the present study, we built upon the ideas of previously developed triple-moment cloud microphysics scheme, considered radar reflectivity factor as the third predictor in addition to number and mass concentration, and introduced its related prediction equation to the Single Column Atmosphere Model Version 5.3 (SCAM5.3). Moreover, the relevant microphysical process formulas in the model were revised, and a triple-moment ice-cloud microphysics scheme was constructed to predict the μ of ice particle spectrum. Based on this model, a 29-day case of the Atmospheric Radiation Measurement Program in the summer of 1997 (ARM97) was simulated, and the differences in cloud fraction and radiation simulations between the double- and triple-moment schemes were analysed. The μ of ice particle spectrum predicted by the triple-moment scheme mainly ranged from 0 to 4; the peak value was around 2, and at least 85% of the μ values were greater than the default 0. Therefore, the μ=0 setting in the double-moment scheme is unreasonable. Moreover, the developed triple-moment ice-cloud microphysics scheme yielded a narrower ice particle spectrum, which was closer to the observation results of previous studies, than the double-moment cloud microphysics scheme (e.g., height=233 hPa). Furthermore, compared with the double-moment scheme, the triple-moment scheme achieved closer simulations of the cloud fraction observations, particularly for ice clouds in the upper levels. Considering the close association between cloud fraction and radiation, the error with the triple-moment scheme was smaller than that with the double-moment scheme regardless of the shortwave (surface downward shortwave radiation, net downward shortwave radiation at the top of the atmosphere, and net shortwave radiation at the surface) or longwave (surface downward longwave radiation and net longwave radiation at the surface) flux density. Finally, the improvement mechanism of the triple-moment scheme on cloud fraction and radiation simulations was explored. The major reason is that the triple-moment scheme weakens the autoconversion of ice crystal to form snow and enhances the growth process of ice crystal deposition, thereby increasing the mass concentration of ice crystals and ice cloud fraction. Overall, the developed triple-moment ice-cloud microphysics scheme can help improve the simulation ability of models for cloud-climate feedback and other processes.

54 ENVIRONMENTAL SCIENCES↗

Cepheid Calibration of the Peak Brightness of SNe Ia.: SN 1989B in NGC 3627 - 9

Repeated imaging observations have been made of NGC 3627 with the Hubble Space Telescope in 1997/98, over an interval of 58 days. Images were obtained on 12 epochs in the F555W band and on five epochs in the F8141,V band. The galaxy hosted the prototypical, "Branch normal", type la supernova SN 1989B. A total of 83 variables have been found, of which 68 are definite Cepheid variables with periods ranging from 75 days to 3.85 days. The de-reddened distance modulus is determined to be (m - M)(sub 0) = 30.22 +/- 0.12 (internal uncertainty) using a subset of the Cepheid data whose reddening and error parameters are secure. The photometric data of Wells et al. (1994), combined with the Cepheid data for NGC 3627 give MB(max) = -19.36 +/- 0.18 and M(sub V)(max) = -19.34 +/- 0.16 for SN 1989B. Combined with the previous six calibrations in this program, plus two additional calibrations determined by others gives the mean absolute magnitudes at maximum of (M(sub B)) = -19.48 +/- 0.07 for "Brunch normal" SNe Ia at this interim stage in the calibration program. Using the argument by Wells et al. (1994) that SN 1989B here is virtually identical in decay rate and colors at maximum with SN 198ON in NGC 1316 in the Fornax cluster, and that such identity means nearly identical absolute magnitude, it follows that the difference in the distance modulus of NGC 3627 and NGC 1316 is 1.62 +/- 0.03 mag. Thus the NGC 3627 modulus implies that (m - M)(sub 0) = 31.84 for NGC 1316. The second parameter correlations of M(max) of blue SNe la with decay rate, color at maximum, and Hubble type are re-investigated. The dependence of (M(max)) on decay rate is non-linear, showing a minimum for decay rates between 1.0 less than ADelta(sub m)15 less than 1.6. Magnitudes corrected for decay rate show no dependence on Hubble type, but a dependence on color remains. Correcting both the fiducial sample of 34 SNe la with decay-rate data and the current eight calibrating SNe la for the correlation with decay rate as well as color gives H(sub 0) = 60 +/- 2 (internal) km/s Mpc, in both B and V. The same value to within 4% is obtained if only the SNe la in spirals (without second parameter corrections) are considered. The correlation of SNe la color at maximum with M(max) cannot be due to internal absorption because the slope coefficients in B, V, and I with the change in magnitude are far from or even opposite to the canonical reddening values. The color effect must be intrinsic to the supernova physics. "Absorption" corrections of distant blue SNe la will lead to incorrect values of H(sub 0). The Cepheid distances used in this series are insensitive to metallicity differences. The zeropoint of the P-L relation is based on an assumed LMC modulus of (m - M)(sub 0) = 18.50. As this may have to be increased by 0(sup m).06 to 0(sup m).08, all distances in this paper will follow and Ho will decrease by 3 - 4%.

Saha, A.↗

Supervisory Control with Dual Tasking in Post G-Transition Vehicle Landings

BACKGROUND Landing during exploration spaceflight may consist of both planned automated supervisory control and unplanned crew override. Supervisory control, particularly when performed under cognitive load with additional monitoring tasks, is essential for ensuring overall mission success during landing contingencies. Evaluating performance in a relevant Human Landing System (HLS) supervisory landing task after long-duration microgravity exposure can help identify potential risks from human error and sensorimotor alterations. Adaptive changes in the sensorimotor system can manifest during g-transitions as spatial disorientation. Although training and landing aids facilitate successful landings despite disorientation, these adaptive changes may heighten cognitive demand, which must be considered in the landing strategy. It is important to characterize these effects as soon as possible following the G-transition while the sensorimotor system remains in a state of adaptive flux to inform appropriate countermeasures. METHODS A Multi-attribute Lunar Table Battery (MALTB) task was developed for an iOS tablet device to provide flexible crew testing and training capabilities in-flight and on the ground. Elements of the tablet task were derived from the Multi-Attribute Task Battery (MATB, Cegarra et al. 2020). The task requires crew members to study a map of a planned landing site and memorizing the terrain and surface landmarks to inform potential divert maneuvers during landing. The user will oversee a series of approaches through touchdown simulations on the tablet with an external camera view of the Lunar surface. The primary responsibility of the crew member will be to execute a divert if the guidance recommended site is erroneous (e.g., the guidance projected landing target is not within 10m of the planned landing site center), or the projected landing site is no longer suitable due to surface obstacles. Considering vehicle maneuverability and fuel reserves, the divert capabilities will diminish as the task progresses. In cases where a divert is initiated, a new landing target will need to be designated by the user and will be evaluated for the proximity to the original pre-planned site. A secondary operational monitoring task will challenge the user's cognitive reserve by requiring the user to maintain several gauges within acceptable limits and respond to a visual indicator while completing the landing approach. Outcome measures include distance from the planned landing site to the user-initiate divert landing location, ground slope at the new landing site, time to divert, the ability to accomplish the secondary monitoring tasks, and perceived workload. The tablet task is being evaluated in a ground-based study to determine the learning effect of first-time users. The tablet task will be utilized in a flight study to test performance multiple times postflight. Future potential testing in-flight have been identified for capsules with iOS tablet devices. Multi-attribute Lunar Table Battery Task MALTB comprises video footage of thirty distinct landing conditions. The landing scenarios feature various landing sites (n = 3), hazardous object sizes (n = 6), sun azimuth degrees (n = 4), camera modes (i.e., fixed or gimbaled), and navigation bias (i.e., true or false). Each seventy second trial uses a sixty-degree constant glideslope trajectory. The application architecture and layout include user identification setup and data storing, a guided walkthrough of the task and interface components, practice mode for task familiarization, and a modified Bedford workload scale administered following task completion. The time-based dependent measures are saved locally to the iOS Files application and post-processing scripts have been developed to evaluate the remaining measures of performance. RELEVANCE This project will deliver an operational demonstration of crew monitoring capability following spaceflight and identify potential deficits that may require remediation. Comparison of individual vestibular and cognitive changes with crew performance will help better characterize the landing risks associated with sensorimotor alterations. ACKNOWLEDGEMENTS: This project is funded by NASA’s Human Research Program Human Health Countermeasures Element. REFERENCES Cegarra J, Valery B, Avril E, Calmettes C, Navarro J (2020) OpenMATB: A Multi-Attribute Task Battery promoting task customization, software extensibility and experiment replicability. Behav Res Methods 52:1980-1990 doi: 10.3758/s13428-020-01364-w

Matthew McDonnell↗

Terrain-Influenced Winds and Fire-Fire Interactions in Wildland Fire Simulations [Dissertation]

Ensemble-based approaches to prescribed fire planning cannot be supported by computational fluid dynamics based models like FIRETEC and the Wildland-Urban Interface Fire Dynamics Simulator (WFDS) because they are too computationally expensive and cannot leverage large eddy simulation approaches like CAWFE and WRF-SFIRE because they have too coarse of resolution. QUIC-Fire was developed to fill this gap but it cannot currently address complex terrain, that is typical for instance in the Western United States. This dissertation describes a variety of improvements made to QUIC-Fire and its various incorporated algorithms in an effort to make it a viable tool in simulating wildland and prescribed fires on terrain. The modifications made to QUIC-Fire are described in three chapters. The first chapter describes the extension of the diagnostic wind model QUIC-URB, the wind engine of QUIC-Fire, to a terrain-following coordinate system. The terraininfluenced winds it generates are analyzed and compared. In particular, this chapter presents the mathematical derivation of the wind solver leading to a linear system of equations that are solved through the successive over-relaxation method. The model is validated against a standard test used in previous works (the Askervein Hill) and against a new dataset from measurements in the Socorro Mountains, New Mexico. The terrain-following implementation captures the correct phenomenology for the isolated Askervein Hill, with a wind speed up at the top of the hill. The model agrees well with measurements on the upwind side of the peak, but overestimates speed-up on the downwind side of the hill. This is due to the inability of the model to generate flow separation and wake-eddy dynamics. On a common laptop, the divergence-free wind field is obtained in 6 s, making the solver appealing for coupled fire-atmosphere simulations. The Socorro Mountain is highly complex, with many cliff faces, peaks, and valleys. Although the model captures the magnitude and direction of inlet and outlet areas of the domain, it performs rather poorly in the valley region and in the regions near the steep cliffs. Hence, the model shows good agreement with data in areas of open sloped terrain but lacks in areas where flow separation and thermally driven effects may be present (neither effect is addressed in this work). In the second chapter the implementation of the terrain-following version of QUIC-URB into QUIC-Fire, and the necessary changes needed to include terrain are described. No changes to the underlying fire spread algorithm are made other than what is required to correctly account for the inclusion of terrain. Previously published FIRETEC results that use five different topographies that share the same centerline profile are compared to simulation results from the modified QUIC-Fire that use the same topographies and fuels. QUIC-Fire results show overall similar behaviors in terms of how the topographies affect fire shapes and trends in spread rates. Due to the terrain-following version of QUIC-URB being unable to generate flow separations at the crest of hills, fire spread rates in these regions across all topographies are over-predicted when compared to FIRETEC. Lateral fire growth shows similar trends with FIRETEC between topographies but does not capture the increase in spread due to a diagonal interface between grassland and forested fuel region of the domain. These results suggest that there are three algorithms within QUIC-Fire that could use improvement: how flame tilt angle is accounted for, the incorporation of non-local drag effects, and the inclusion of the wake-eddy parameterizations that are used in QUIC-URB. Lastly, the third chapter describes a modification to the initial guess used for the calculation of the QUIC-URB mass-conserved wind solution during fire simulations. The modification is aimed at improving fire-fire interactions in QUIC-Fire simulations. The modification consists of using the solution from the previous timestep as the starting point for the calculation of the solution for the next timestep. Fire-fire interactions is greatly improved by the change but a new source of error is introduced. Due to how plumes are modelled in QUIC-Fire the new solution contains errors where gaps in the plume structure are present. However, these errors are mostly limited to the upper atmosphere, where they do not affect fire behavior at the surface, and their magnitude isn’t significant enough to discount the amount of new fire phenomenology now captured in QUIC-Fire with the change.

58 GEOSCIENCES↗

First Year Wilkinson Microwave Anisotropy Probe (WMAP)Observations: Preliminary Maps and Basic Results

We present full sky microwave maps in five frequency bands (23 to 94 GHz) from the WMAP first year sky survey. Calibration errors are less than 0.5% and the low systematic error level is well specified. The cosmic microwave background (CMB) is separated from the foregrounds using multifrequency data. The sky maps are consistent with the 7 in. full-width at half-maximum (FWHM) Cosmic Background Explorer (COBE) maps. We report more precise, but consistent, dipole and quadrupole values. The CMB anisotropy obeys Gaussian statistics with -58 less than f(sub NL) less than 134 (95% CL). The 2 less than or = l less than or = 900 anisotropy power spectrum is cosmic variance limited for l less than 354 with a signal-to-noise ratio greater than 1 per mode to l = 658. The temperature-polarization cross-power spectrum reveals both acoustic features and a large angle correlation from reionization. The optical depth of reionization is tau = 0.17 +/- 0.04, which implies a reionization epoch of t(sub r) = 180(sup +220, sub -80) Myr (95% CL) after the Big Bang at a redshift of z(sub r) = 20(sup +10, sub -9) (95% CL) for a range of ionization scenarios. This early reionization is incompatible with the presence of a significant warm dark matter density. A best-fit cosmological model to the CMB and other measures of large scale structure works remarkably well with only a few parameters. The age of the best-fit universe is t(sub 0) = 13.7 +/- 0.2 Gyr old. Decoupling was t(sub dec) = 379(sup +8, sub -7)kyr after the Big Bang at a redshift of z(sub dec) = 1089 +/- 1. The thickness of the decoupling surface was Delta(sub z(sub dec)) = 195 +/- 2. The matter density of the universe is Omega(sub m)h(sup 2) = 0.135(sup +0.008, sub -0.009) the baryon density is Omega(sub b)h(sup 2) = 0.0224 +/- 0.0009, and the total mass-energy of the universe is Omega(sub tot) = 1.02 +/- 0.02. There is progressively less fluctuation power on smaller scales, from WMAP to fine scale CMB measurements to galaxies and finally to the Ly-alpha forest. This is accounted for with a running spectral index, significant at the approx. 2(sigma) level. The spectral index of scalar fluctuations is fit as n(sub s) = 0.93 +/-0.03 at wavenumber k(sub o) = 0.05/Mpc ((sub eff) approx. = 700), with a slope of dn(sub s)/d I(sub nk) = -0.031(sup + 0.016, sub -0.018) in the best-fit model.

Bennett, C. L.↗

Statistical Correlation of Heliostat Pointing Deviation With Wind

This work was carried out as part of the Heliostat Consortium (HelioCon) Field Deployment subtask with the aim to develop a reduced order model framework for correlating wind speed and pointing deviation of a heliostat facet. There are only sparse field measurements of heliostat pointing deviations and accompanying wind conditions published in the literature. Heliostat test standards, such as IEC 62862-4-3, propose a suite of tests including laser pointing repeatability at wind speeds below 4 m/s, and provide technical requirements for heliostat slope and tracking deviations in coarse average wind speed bins of 4 m/s, 6 m/s, and 8 m/s. In addressing the gap of the variation of heliostat pointing deviation with wind speed, field measurements of laser pointing on a grid target and wind conditions were analyzed in this study at the Third-Party Metrology Platform at the National Laboratory of the Rockies (NLR) Flatirons Campus. Horizontal pointing deviations were found to follow a logarithmic relationship with peak wind speed, whereas vertical pointing deviations follow an exponential relationship with peak wind speed. Both horizontal and vertical pointing deviations also follow a second order polynomial relationship, as expected from the proportionality of elastic loads and deformations with the square of wind speed. The results indicate that heliostat facet pointing deviations in the vertical direction increase at a faster rate than in the horizontal direction with increasing wind speed over the tested range, however these are dependent on the heliostat structural design. Next steps are recommended for additional field measurements to confirm a linear relationship of pointing deviation with applied moment on a heliostat facet, and to distinguish between gravity-induced and wind-induced pointing deviations at different elevation angles. The derived correlations in the preliminary analysis in this report serve as a case study for heliostat developers and plant operators to estimate the wind-induced pointing deviations and their variation with peak gust wind speed. Next steps in future work would recommend higher resolution and longer duration datasets for different elevation angles and wind directions to reduce uncertainties and variance of collected laser beam spot data and their correlations with bin-averaged wind speed.

17 WIND ENERGY↗