Search NASA⌕ Search

SEARCH · Search NASA

Results for “Maritime”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5

CARACaS multi-agent maritime autonomy for unmanned surface vehicles in the Swarm II harbor patrol demonstration

This paper describes new autonomy technology that enabled a team of unmanned surface vehicles (USVs) to execute cooperative behaviors in the USV Swarm II harbor patrol demonstration and provides a description of autonomy performance in the event. The new developments extend the NASA Jet Propulsion Laboratory’s CARACaS (Control Architecture for Robotic Agent Command and Sensing) autonomy architecture, which pro- vides foundational software infrastructure, core executive functions, and several default robotic technology mod- ules. In Swarm II, CARACaS demonstrated higher levels of autonomy and more complex cooperation than previous on-water exercises, using full-sized vehicles and real-world sensing and communication. The core au- tonomous behaviors to support the harbor patrol scenario included Patrol, Track, Inspect, and Trail, providing the capability of finding all vessels entering the patrol area, keeping track of them, inspecting them to infer intent, and trailing suspect vessels. Significantly, CARACaS assumed responsibility for not only executing tasks safely and efficiently but also recognizing what tasks needed to be accomplished, given the current state of the world. Since the heterogeneous USV teams shared world model that evolved, such as due to (dis)appearance of vessels in the area or a change in health or availability of a USV, CARACaS replanned to generate and reallocate the new task list. Thus, human intervention was never required in the loop to task USVs during mission execution, though a supervisory role was supported in the autonomy system for mission monitoring and exception handling. Finally, CARACaS also ensured the USVs avoided hazards and obeyed the applicable rules of the road, using its local motion planning modules.

Sandoval, Michael↗

Automated Tracking of Shallow Maritime Clouds on Geostationary Imagery to Extract Lifecycle Characteristics

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Satellites have provided many statistics on shallow clouds, such as size, structure, and geographical coverage, from static views of recurring cloud fields. But determining why certain cloud features appear and persist for different periods requires a time-evolving view of their behaviors. Geostationary satellites provide a unique opportunity to follow the time evolution of individual convective features, given their enhanced spatial and temporal sampling. A cloud-tracking tool was developed to identify properties of cloud lifecycle from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2EX) field campaign of 2019. The mission conducted intensive sampling of shallow cumulus in the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus was segmented according to thresholds in 0.5-km visible reflectance and with blurring techniques. Despite being limited to daytime hours, the segmentations yielded the best resolution possible for capturing cloud initiation and decay. The tracking procedure is based on a computer vision package that includes Kalman filters for motion prediction, object overlap search, and the Hungarian (or Kuhn-Munkres) matching algorithm for track designation. AHI radiances available within the tracked cloud boundaries are assembled to form individual spectral histories. The resulting catalog provides thousands of cloud histories for domains measuring only a few degrees in latitude and longitude. We present an overview of the cloud-tracking tool, strategies to identify development stages from cloud tracks, and preliminary results that document cumulus lifecycle properties from satellite. The application of AHI 0.5-km reflectance has both strengths and limitations when attempting to track lifecycles of the smallest resolvable clouds. We show that by aggregating cloud tracks from a few case studies of CAMP2EX, we can discern differences in cloud lifetime and development according to ensembles selected from areas of interest. The results demonstrate an ability to quantify lifetimes and assess rates of change in cloud characteristics that are likely controlled by the surrounding environment and meteorology.

Cloud Tracking↗

Automated Tracking of Shallow Maritime Clouds on Geostationary Imagery to Extract Lifecycle Characteristics

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Satellites have provided valuable insight on shallow clouds, such as size, structure, and geographical coverage, from static views of recurring cloud fields. But determining why certain cloud features appear and persist for different periods requires a time-evolving view of their behaviors. Geostationary satellites provide a unique opportunity to follow the time evolution of individual convective features, given their enhanced spatial and temporal sampling. A cloud-tracking tool was developed to identify properties of cloud lifecycle from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2EX) field campaign of 2019. The mission conducted intensive sampling of shallow cumulus in the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus were segmented according to thresholds in 0.5-km visible reflectance and with blurring techniques. Despite being limited to daytime hours, the segmentations yielded the best resolution available for capturing cloud initiation, growth, and decay. The tracking procedure is based on a computer vision package that includes Kalman filters for motion prediction, object overlap search, and the Hungarian (or Kuhn-Munkres) matching algorithm for track designation. AHI radiances available within the tracked cloud boundaries are assembled to form individual spectral histories. The resulting catalog provides thousands of cloud histories for domains measuring only a few degrees in latitude and longitude. We present an overview of the cloud-tracking tool and its results for cloud fields sampled throughout CAMP2EX by the airborne P-3. Cloud tracks were selected from about 10 flights to form ensembles, specific groups of tracks occurring in a region with airborne sampling. Cloud lifecycle properties, including duration and maximum area, are calculated for all ensemble members, and analyzed for cloud behavior and P-3 coincidences. By following this strategy, we quantitatively assess the degree of airborne sampling for specific cloud classes defined by the lifecycle calculations. We can summarize which cloud classes had more sampling, the stage of development during sampling, and general differences in character (e.g., isolated congestus vs. cold-pool producer).

Cloud Tracking↗

Global Precipitation during the 1997-98 El Nino and Initiation of the 1998-99 La Nina

The 1997-99 ENSO (El nino Southern Oscillation) cycle was very powerful, but also well observed. The best satellite rainfall estimates combined with gauge observations allow for a global analysis of precipitation anomalies accompanying the 1997-98 El Nino and initiation of the 1998-99 La Nina. For the period April 1997 to March 1998 the central to eastern Pacific, southeastern and western U.S., Argentina, eastern Africa, South China, eastern Russia, and North Atlantic were all more than two standard deviations wetter than normal. During the same year the Maritime Continent, eastern Indian Ocean, subtropical North Pacific, northeastern South America, and much of the mid- latitude southern oceans were more than two standard deviations drier than normal. An analysis of the evolution of the El Nino and accompanying precipitation anomalies revealed that a dry Maritime Continent led the formation of the El Nino SST (Sea Surface Temperature), while in the central Pacific, precipitation anomalies lagged the El Nino SST by a season. A rapid transition from El Nino to La Nina occurred in May 1998, but as early as October-November 1997 precipitation indices captured precursor changes in Pacific rainfall anomalies. Differences were found between observed and modeled [NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis] precipitation anomalies for 1997 and 98. In particular, the model had a bias towards positive precipitation anomalies and the magnitudes of the anomalies in the equatorial Pacific were small compared to the observations. Also, the evolution of the precipitation field, including the drying of the Maritime Continent and eastward progression of rainfall in the equatorial Pacific, was less pronounced for the model compared to the observations. One degree daily estimates of rainfall show clearly the MaddenJulian Oscillation and related westerly wind burst events over the Maritime Continent, which are key indicators for the onset of El Nino.

Curtis, Scott↗

Aerosols in polluted versus nonpolluted air masses Long-range transport and effects on clouds

To assess the influence of anthropogenic aerosols on the physics and chemistry of clouds in the northeastern United States, aerosol and cloud-drop size distributions, elemental composition of aerosols as a function of size, and ionic content of cloud water were measured on Whiteface Mountain, NY, during the summers of 1981 and 1982. In several case studies, the data were cross-correlated with different air mass types - background continental, polluted continental, and maritime - that were advected to the sampling site. The results are the following: (1) Anthropogenic sources hundreds of kilometers upwind cause the small-particle (accumulation) mode number to increase from hundreds of thousands per cubic centimeter and the mass loading to increase from a few to several tens of micrograms per cubic meter, mostly in the form of sulfur aerosols. (2) A significant fraction of anthropogenic sulfur appears to act as cloud condensation nuclei (CCN) to affect the cloud drop concentration. (3) Clouds in Atlantic maritime air masses have cloud drop spectra that are markedly different from those measured in continental clouds. The drop concentration is significantly lower, and the drop size spectra are heavily skewed toward large drops. (4) Effects of anthropogenic pollutants on cloud water ionic composition are an increase of nitrate by a factor of 50, an increase of sulfate by more than one order of magnitude, and an increase of ammonium ion by a factor of 7. The net effect of the changes in ionic concentrations is an increase in cloud water acidity. An anion deficit even in maritime clouds suggests an unknown, possibly biogenic, source that could be responsible for a pH below neutral, which is frequently observed in nonpolluted clouds.

Pueschel, R. F.↗

Observations of anthropogenic cloud condensation nuclei

Cloud Condensation Nuclei (CCN) concentrations and spectral measurements obtained with the DRI instantaneous CCN spectrometer (Hudson, 1989) over the last few years are presented. The climatic importance of cloud microphysics has been pointed out. The particles which affect cloud microphysics are cloud condensation nuclei (CCN). The commonly-observed order of magnitude difference in cloud droplet concentrations between maritime and continental air masses (i.e., Squires, 1958) was determined to be caused by systematic differences in the concentrations of CCN between continental and maritime air masses (e.g., Twomey and Wojciechowski, 1969). Twomey (1977) first pointed out that cloud microphysics also affects the radiative properties of clouds. Thus continental and anthropogenic CCN could affect global temperature. Resolution of this Twomey effect requires answers to two questions - whether antropogenic CCN are a significant contribution to atmospheric CCN, and whether they are actually affecting cloud microphysics to an extent which is of climatic importance. The reasons for the contrast between continental and maritime CCN concentration are not understood. The question of the relative importance of anthropogenic CCN is addressed. These observations should shed light on this complex question although further research is being conducted in order to produce more quantitative answers. Accompanying CN measurements made with a TSI 3020 condensation nucleus (CN) counter are also presented.

Hudson, James G.↗