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Institution

Jet Propulsion Laboratory

FacilityLa Cañada Flintridge, California, United States
About: Jet Propulsion Laboratory is a facility organization based out in La Cañada Flintridge, California, United States. It is known for research contribution in the topics: Mars Exploration Program & Telescope. The organization has 8801 authors who have published 14333 publications receiving 548163 citations. The organization is also known as: JPL & NASA JPL.


Papers
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Journal ArticleDOI
TL;DR: In this paper, it was pointed out that the darkness of a sunspot on the visible hemisphere of the sun will reduce the solar irradiance on the earth, and a simple model for the reradiation necessary to balance the flux deficit was proposed.
Abstract: It is pointed out that the darkness of a sunspot on the visible hemisphere of the sun will reduce the solar irradiance on the earth. Approaches are discussed for obtaining a crude estimate of the irradiance deficit produced by sunspots and of the total luminosity reduction for the whole global population of sunspots. Attention is given to a photometric sunspot index, a global measure of spot flux deficit, and models for the compensating flux excess. A model is shown for extrapolating visible-hemisphere spot areas to the invisible hemisphere. As an illustration, this extrapolation is used to calculate a very simple model for the reradiation necessary to balance the flux deficit.

120 citations

Journal ArticleDOI
04 Nov 1983-Science
TL;DR: The deposition and erosion of thin deposits of bright red dust associated with global dust storms, and the removal of centimeter amounts of material in selected areas during a dust storm late in the third winter.
Abstract: The Mutch Memorial Station (Viking Lander 1) on Mars acquired imaging and meteorological data over a period of 2245 martian days (3:3 martian years). This article discusses the deposition and erosion of thin deposits (ten to hundreds of micrometers) of bright red dust associated with global dust storms, and the removal of centimeter amounts of material in selected areas during a dust storm late in the third winter. Atmospheric pressure data acquired during the period of intense erosion imply that baroclinic disturbances and strong diurnal solar tidal heating combined to produce strong winds. Erosion occurred principally in areas where soil cohesion was reduced by earlier surface sampler activities. Except for redistribution of thin layers of materials, the surface appears to be remarkably stable, perhaps because of cohesion of the undisturbed surface material.

120 citations

Proceedings ArticleDOI
26 Sep 2003
TL;DR: An overview of the Coupled Layered Architecture for Robotic Autonomy (CLARAty) is presented, which develops a framework for generic and reusable robotic components that can be adapted to a number of heterogeneous robot platforms.
Abstract: In this article, we will present an overview of the Coupled Layered Architecture for Robotic Autonomy. CLARAty develops a framework for generic and reusable robotic components that can be adapted to a number of heterogeneous robot platforms. It also provides a framework that will simplify the integration of new technologies and enable the comparison of various elements. CLARAty consists of two distinct layers: a Functional Layer and a Decision Layer. The Functional Layer defines the various abstractions of the system and adapts the abstract components to real or simulated devices. It provides a framework and the algorithms for low- and mid-level autonomy. The Decision Layer provides the system's high-level autonomy, which reasons about global resources and mission constraints. The Decision Layer accesses information from the Functional Layer at multiple levels of granularity. In this article, we will also present some of the challenges in developing interoperable software for various rover platforms. Examples will include challenges from the locomotion and manipulation domains

120 citations

Journal ArticleDOI
TL;DR: Using albedos from WISE/NEOWISE to separate distinct albedo groups within the Main Belt asteroids, the authors apply the Hierarchical Clustering Method to these subpopulations and identify dynamically associated clusters of asteroids.
Abstract: Using albedos from WISE/NEOWISE to separate distinct albedo groups within the Main Belt asteroids, we apply the Hierarchical Clustering Method to these subpopulations and identify dynamically associated clusters of asteroids. While this survey is limited to the ~35% of known Main Belt asteroids that were detected by NEOWISE, we present the families linked from these objects as higher confidence associations than can be obtained from dynamical linking alone. We find that over one-third of the observed population of the Main Belt is represented in the high-confidence cores of dynamical families. The albedo distribution of family members differs significantly from the albedo distribution of background objects in the same region of the Main Belt; however, interpretation of this effect is complicated by the incomplete identification of lower-confidence family members. In total we link 38,298 asteroids into 76 distinct families. This work represents a critical step necessary to debias the albedo and size distributions of asteroids in the Main Belt and understand the formation and history of small bodies in our solar system.

120 citations

Journal ArticleDOI
01 Jan 2001-Icarus
TL;DR: McEwen et al. as mentioned in this paper analyzed a collection of hyperspectral images of Io acquired by the near infrared mapping spectrometer (NIMS) of Galileo during the G2 to E16 orbits of Jupiter.

119 citations


Authors

Showing all 9033 results

NameH-indexPapersCitations
B. P. Crill148486111895
George Helou14466296338
H. K. Eriksen141474104208
Charles R. Lawrence141528104948
W. C. Jones14039597629
Gianluca Morgante13847898223
Jean-Paul Kneib13880589287
Kevin M. Huffenberger13840293452
Robert H. Brown136117479247
Federico Capasso134118976957
Krzysztof M. Gorski132380105912
Olivier Doré130427104737
Mark E. Thompson12852777399
Clive Dickinson12350180701
Daniel Stern12178869283
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023177
2022416
2021359
2020348
2019384
2018445