scholarly journals Statistical Analyses of Satellite Cloud Object Data from CERES. Part II: Tropical Convective Cloud Objects during 1998 El Niño and Evidence for Supporting the Fixed Anvil Temperature Hypothesis

2007 ◽  
Vol 20 (5) ◽  
pp. 819-842 ◽  
Author(s):  
Kuan-Man Xu ◽  
Takmeng Wong ◽  
Bruce A. Wielicki ◽  
Lindsay Parker ◽  
Bing Lin ◽  
...  
Keyword(s):  
Physical Properties ◽  
Optical Depth ◽  
Convective Cloud ◽  
Tropical Pacific ◽  
Statistical Distributions ◽  
Size Category ◽  
High Cloud ◽  
Large Size ◽  
Precession Cycle ◽  
Macrophysical Properties

Abstract Characteristics of tropical deep convective cloud objects observed over the tropical Pacific during January–August 1998 are examined using the Tropical Rainfall Measuring Mission/Clouds and the Earth’s Radiant Energy System Single Scanner Footprint (SSF) data. These characteristics include the frequencies of occurrence and statistical distributions of cloud physical properties. Their variations with cloud object size, sea surface temperature (SST), and satellite precession cycle are analyzed in detail. A cloud object is defined as a contiguous patch of the earth composed of satellite footprints within a single dominant cloud-system type. It is found that statistical distributions of cloud physical properties are significantly different among three size categories of cloud objects with equivalent diameters of 100–150 (small), 150–300 (medium), and >300 km (large), except for the distributions of ice particle size. The distributions for the larger-size category of cloud objects are more skewed toward high SSTs, high cloud tops, low cloud-top temperature, large ice water path, high cloud optical depth, low outgoing longwave (LW) radiation, and high albedo than the smaller-size category. As SST varied from one satellite precession cycle to another, the changes in macrophysical properties of cloud objects over the entire tropical Pacific were small for the large-size category of cloud objects, relative to those of the small- and medium-size categories. This evidence supports the fixed anvil temperature hypothesis of Hartmann and Larson for the large-size category. Combined with the result that a higher percentage of the large-size category of cloud objects occurs during higher SST subperiods, this implies that macrophysical properties of cloud objects would be less sensitive to further warming of the climate. On the other hand, when cloud objects are classified according to SST ranges, statistical characteristics of cloud microphysical properties, optical depth, and albedo are not sensitive to the SST, but those of cloud macrophysical properties are dependent upon the SST. This result is related to larger differences in large-scale dynamics among the SST ranges than among the satellite precession cycles. Frequency distributions of vertical velocity from the European Centre for Medium-Range Weather Forecasts model that is matched to each cloud object are used to further understand some of the findings in this study.

scholarly journals Statistical Analyses of Satellite Cloud Object Data from CERES. Part III: Comparison with Cloud-Resolving Model Simulations of Tropical Convective Clouds

2007 ◽  
Vol 64 (3) ◽  
pp. 762-785 ◽  
Author(s):  
Yali Luo ◽  
Kuan-Man Xu ◽  
Bruce A. Wielicki ◽  
Takmeng Wong ◽  
Zachary A. Eitzen
Keyword(s):  
Physical Properties ◽  
Optical Depth ◽  
Weather Prediction ◽  
Cloud Microphysics ◽  
Retrieval Algorithm ◽  
Medium Size ◽  
Size Category ◽  
Cloud Optical Depth ◽  
Large Size ◽  
Cloud Resolving Model

Abstract The present study evaluates the ability of a cloud-resolving model (CRM) to simulate the physical properties of tropical deep convective cloud objects identified from a Clouds and the Earth’s Radiant Energy System (CERES) data product. The emphasis of this study is the comparisons among the small-, medium-, and large-size categories of cloud objects observed during March 1998 and between the large-size categories of cloud objects observed during March 1998 (strong El Niño) and March 2000 (weak La Niña). Results from the CRM simulations are analyzed in a way that is consistent with the CERES retrieval algorithm and they are averaged to match the scale of the CERES satellite footprints. Cloud physical properties are analyzed in terms of their summary histograms for each category. It is found that there is a general agreement in the overall shapes of all cloud physical properties between the simulated and observed distributions. Each cloud physical property produced by the CRM also exhibits different degrees of disagreement with observations over different ranges of the property. The simulated cloud tops are generally too high and cloud-top temperatures are too low except for the large-size category of March 1998. The probability densities of the simulated top-of-the-atmosphere (TOA) albedos for all four categories are underestimated for high albedos, while those of cloud optical depth are overestimated at its lowest bin. These disagreements are mainly related to uncertainties in the cloud microphysics parameterization and inputs such as cloud ice effective size to the radiation calculation. Summary histograms of cloud optical depth and TOA albedo from the CRM simulations of the large-size category of cloud objects do not differ significantly between the March 1998 and 2000 periods, consistent with the CERES observations. However, the CRM is unable to reproduce the significant differences in the observed cloud-top height while it overestimates the differences in the observed outgoing longwave radiation and cloud-top temperature between the two periods. Comparisons between the CRM results and the observations for most parameters in March 1998 consistently show that both the simulations and observations have larger differences between the large- and small-size categories than between the large- and medium-size, or between the medium- and small-size categories. However, the simulated cloud properties do not change as much with size as observed. These disagreements are likely related to the spatial averaging of the forcing data and the mismatch in time and space between the numerical weather prediction model from which the forcing data are produced and the CERES observed cloud systems.

scholarly journals Evaluation of Cloud Physical Properties of ECMWF Analysis and Re-Analysis (ERA) against CERES Tropical Deep Convective Cloud Object Observations

2009 ◽  
Vol 137 (1) ◽  
pp. 207-223 ◽  
Author(s):  
Kuan-Man Xu
Keyword(s):  
Physical Properties ◽  
Optical Depth ◽  
Large Scale ◽  
Grid Cell ◽  
Convective Cloud ◽  
Radiative Properties ◽  
Detection Rates ◽  
Cloud Optical Depth ◽  
Object A ◽  
Deep Convective Cloud

Abstract This study presents an approach that converts the vertical profiles of grid-averaged cloud properties from large-scale models to probability density functions (pdfs) of subgrid-cell cloud physical properties measured at satellite footprints. Cloud physical and radiative properties, rather than just cloud and precipitation occurrences, of assimilated cloud systems by the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis (EOA) and 40-yr ECMWF Re-Analysis (ERA-40) are validated against those obtained from Earth Observing System satellite cloud object data for the January–August 1998 and March 2000 periods. These properties include the ice water path (IWP), cloud-top height and temperature, cloud optical depth, and solar and infrared radiative fluxes. Each cloud object, a contiguous region with similar cloud physical properties, is temporally and spatially matched with EOA and ERA-40 data. Results indicate that most pdfs of EOA and ERA-40 cloud physical and radiative properties agree with those of satellite observations of the tropical deep convective cloud object type for the January–August 1998 period. There are, however, significant discrepancies in selected ranges of the cloud property pdfs such as the upper range of EOA cloud-top height. A major discrepancy is that the dependence of the pdfs on the cloud object size for both EOA and ERA-40 is not as strong as in the observations. Modifications to the cloud parameterization in ECMWF that occurred in October 1999 eliminate the clouds near the tropopause but shift power of the pdf to lower cloud-top heights and greatly reduce the ranges of IWP and cloud optical depth pdfs. These features persist in ERA-40 due to the use of the same cloud parameterizations. The less sophisticated data assimilation technique and the lack of snow water content information in ERA-40, not the larger horizontal grid spacing, are also responsible for the disagreements with observed pdfs of cloud physical properties, although the detection rates of cloud object occurrence are improved for small-size categories. A possible improvement to the convective parameterization is to introduce a stronger dependence of updraft penetration heights on grid-cell dynamics.

AISI TYPE S2

Alloy Digest ◽  
1982 ◽  
Vol 31 (12) ◽  
Keyword(s):  
Physical Properties ◽  
Tensile Properties ◽  
Tool Steel ◽  
Shock Loading ◽  
Heat Treating ◽  
Medium Size ◽  
Hard Case ◽  
Large Size ◽  
Steel Mills ◽  
Aisi Type

Abstract AISI Type S2 is a water-hardening tool steel with extreme toughness and resistance to shock loading. Even at a hardness of Rockwell C 59-60, it will bend before it breaks. When hardened in medium-size and large-size pieces, it acquires a hard case and a tough core. Sizes under 3/4-inch (19mm) diameter will water harden to the center. The extreme toughness of Type S2 makes it suitable for use in many applications where no other tool steel will hold up. Its many uses include chisels, rivet busters, spike mauls, screw drivers, punches and sledges. This datasheet provides information on composition, physical properties, hardness, elasticity, and tensile properties. It also includes information on forming, heat treating, machining, and joining. Filing Code: TS-408. Producer or source: Tool steel mills.

DART and LICIACUBE: Documenting Kinetic Impact

2021 ◽  
Author(s):  
Andrew Cheng ◽  
Elizabetta Dotto ◽  
Eugene Fahnestock ◽  
Vincenzo Della Corte ◽  
Nancy Chabot ◽  
...  
Keyword(s):  
Time Delay ◽  
Velocity Distribution ◽  
Physical Properties ◽  
Optical Depth ◽  
Depth Profiles ◽  
Full Characterization ◽  
Approach Distance ◽  
Impact Ejecta ◽  
The Impact

<p>The NASA Double Asteroid Redirection Test (DART) mission will demonstrate asteroid deflection by a kinetic impactor. DART will impact Dimorphos, the secondary member of the (65803) Didymos system, in late September to early October, 2022 in order to change the binary orbit period. DART will carry a 6U CubeSat called LICIACube, contributed by the Italian Space Agency, to document the DART impact and to observe the impact ejecta. LICIACube will be released by DART 10 days prior to Didymos encounter, and LICIACube will fly by Dimorphos at closest approach distance of about 51 km and with a closest approach time delay of about 167 s after the DART impact. LICIACube will observe the structure and evolution of the DART impact ejecta plume and will obtain images of the surfaces of both bodies at best ground sampling about 1.4 m per pixel. LICIACube imaging importantly includes the non-impact hemisphere of the target body, the side not imaged by DART.</p> <p> </p> <p>The LICIACube flyby trajectory, notably the closest approach distance and the time delay of closest approach, are designed to optimize the study of ejecta plume evolution without exposing the satellite to impact hazard. LICIACube imaging will determine the direction of the ejecta plume and the ejection angles, and will further help to determine the ejecta momentum transfer efficiency <em>β</em>. The ejecta plume structure, as it evolves over time, is determined by the amount of ejecta that has reached a given altitude at a given time. The LICIACube plume images enable characterization of the ejecta mass versus velocity distribution, which is strongly dependent on target properties like strength and porosity and is therefore a powerful diagnostic of the DART impact, complementary to measurements of the DART impact crater by the ESA Hera mission which will arrive at Didymos in 2026. Hera will measure crater radius and crater volume to determine the total volume of ejecta, which together with a ejecta mass-velocity distribution gives a full characterization of the DART impact.</p> <p> </p> <p>Models of the ejecta plume evolution as imaged by LICIACube show how LICIACube images can discriminate between different target physical properties (mainly strength and porosity), thereby allowing inferences of the magnitude of the ejecta momentum. Measured ejecta plume optical depth profiles can distinguish between gravity-controlled and strength-controlled impact cases and help determine target physical properties. LICIACube ejecta plume images further provide information on the direction of the ejecta momentum as well as the magnitude, requiring full 2-D simulations of the plume images. We will present new simulation model optical depth profiles across the plume at arbitrary positions.</p> <p><br />We thank NASA for support of the DART project at JHU/APL, under Contract # NNN06AA01C, Task Order # NNN15AA05T. The Italian LICIACube team acknowledges financial support from Agenzia Spaziale Italiana (ASI, contract No. 2019-31-HH.0 CUP<br />F84I190012600).</p>

scholarly journals Close-range remote sensing of Saturn’s rings during Cassini’s ring-grazing orbits and Grand Finale

Science ◽  
2019 ◽  
Vol 364 (6445) ◽  
pp. eaau1017 ◽  
Author(s):  
Matthew S. Tiscareno ◽  
Philip D. Nicholson ◽  
Jeffrey N. Cuzzi ◽  
Linda J. Spilker ◽  
Carl D. Murray ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Physical Properties ◽  
Optical Depth ◽  
Spectral Properties ◽  
Dynamical Processes ◽  
Ring Structures ◽  
Close Range ◽  
Saturn’S Rings ◽  
F Ring ◽  
Saturn's Rings

Saturn’s rings are an accessible exemplar of an astrophysical disk, tracing the Saturn system’s dynamical processes and history. We present close-range remote-sensing observations of the main rings from the Cassini spacecraft. We find detailed sculpting of the rings by embedded masses, and banded texture belts throughout the rings. Saturn-orbiting streams of material impact the F ring. There are fine-scaled correlations among optical depth, spectral properties, and temperature in the B ring, but anticorrelations within strong density waves in the A ring. There is no spectral distinction between plateaux and the rest of the C ring, whereas the region outward of the Keeler gap is spectrally distinct from nearby regions. These results likely indicate that radial stratification of particle physical properties, rather than compositional differences, is responsible for producing these ring structures.

LUCEFIN GROUP 42CrMo4 (1.7225), 42CrMoS4 (1.7227)

Alloy Digest ◽  
2020 ◽  
Vol 69 (3) ◽  
Keyword(s):  
Physical Properties ◽  
Carbon Content ◽  
Induction Hardening ◽  
High Strength ◽  
Medium Carbon ◽  
Large Size ◽  
Content Classification ◽  
Alloy Steels ◽  
Flame Hardening ◽  
Strength And Toughness

Abstract Lucefin Group 42CrMo4 and 42CrMoS4 are medium-carbon, 1% chromium-molybdenum, direct hardening, alloy steels that are also suitable for flame hardening, induction hardening, and nitriding. These steels are medium hardenability steels in the 0.40 to 0.42 mean carbon content classification. In general, they are used for medium and large size parts requiring high strength and toughness. This datasheet provides information on composition, physical properties, hardness, and elasticity. It also includes information on forming, machining, and joining. Filing Code: SA-861. Producer or source: Lucefin S.p.A.

LUCEFIN 50CrMo4 (1.7228)

Alloy Digest ◽  
2021 ◽  
Vol 70 (11) ◽  
Keyword(s):  
Physical Properties ◽  
Carbon Content ◽  
High Hardness ◽  
Induction Hardening ◽  
High Strength ◽  
Heat Treating ◽  
Medium Carbon ◽  
Large Size ◽  
Content Classification ◽  
Flame Hardening

Abstract Lucefin 50CrMo4 is a medium-carbon, chromium-molybdenum direct hardening alloy steel that is also suitable for flame hardening, induction hardening, and nitriding. This steel is a medium hardenability steel in the 0.45 to 0.50 mean carbon content classification. In general, it is used for medium and large size parts requiring high hardness as well as high strength and good toughness. A minimum of 90% martensite in the as-quenched condition is desirable. This datasheet provides information on composition, physical properties, hardness, elasticity, and tensile properties. It also includes information on forming, heat treating, machining, and joining. Filing Code: SA-877. Producer or source: Lucefin S.p.A.

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