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At least 307 records · Page 17

Optimal design of solidification processes

An optimal design algorithm is presented for the analysis of general solidification processes, and is demonstrated for the growth of GaAs crystals in a Bridgman furnace. The system is optimal in the sense that the prespecified temperature distribution in the solidifying materials is obtained to maximize product quality. The optimization uses traditional numerical programming techniques which require the evaluation of cost and constraint functions and their sensitivities. The finite element method is incorporated to analyze the crystal solidification problem, evaluate the cost and constraint functions, and compute the sensitivities. These techniques are demonstrated in the crystal growth application by determining an optimal furnace wall temperature distribution to obtain the desired temperature profile in the crystal, and hence to maximize the crystal's quality. Several numerical optimization algorithms are studied to determine the proper convergence criteria, effective 1-D search strategies, appropriate forms of the cost and constraint functions, etc. In particular, we incorporate the conjugate gradient and quasi-Newton methods for unconstrained problems. The efficiency and effectiveness of each algorithm is presented in the example problem.

Dantzig, Jonathan A.↗

A Comprehensive Machine Learning Study to Classify Precipitation Type over Land from Global Precipitation Measurement Microwave Imager (GPM-GMI) Measurements

Precipitation type is a key parameter used for better retrieval of precipitation characteristics as well as to understand the cloud–convection–precipitation coupling processes. Ice crystals and water droplets inherently exhibit different characteristics in different precipitation regimes (e.g., convection, stratiform), which reflect on satellite remote sensing measurements that help us distinguish them. The Global Precipitation Measurement (GPM) Core Observatory’s microwave imager (GMI) and dual-frequency precipitation radar (DPR) together provide ample information on global precipitation characteristics. As an active sensor, the DPR provides an accurate precipitation type assignment, while passive sensors such as the GMI are traditionally only used for empirical understanding of precipitation regimes. Using collocated precipitation type flags from the DPR as the “truth”, this paper employs machine learning (ML) models to train and test the predictability and accuracy of using passive GMI-only observations together with ancillary information from a reanalysis and GMI surface emissivity retrieval products. Out of six ML models, four simple ones (support vector machine, neural network, random forest, and gradient boosting) and the 1-D convolutional neural network (CNN) model are identified to produce 90–94% prediction accuracy globally for five types of precipitation (convective, stratiform, mixture, no precipitation, and other precipitation), which is much more robust than previous similar effort. One novelty of this work is to introduce data augmentation (subsampling and bootstrapping) to handle extremely unbalanced samples in each category. A careful evaluation of the impact matrices demonstrates that the polarization difference (PD), brightness temperature (Tc) and surface emissivity at high-frequency channels dominate the decision process, which is consistent with the physical understanding of polarized microwave radiative transfer over different surface types, as well as in snow and liquid clouds with different microphysical properties. Furthermore, the view-angle dependency artifact that the DPR’s precipitation flag bears with does not propagate into the conical-viewing GMI retrievals. This work provides a new and promising way for future physics-based ML retrieval algorithm development.

machine learning/artificial intelligence↗

The response of lazy-2 tomato seedlings to curvature-inducing magnetic gradients is modulated by light

Shoots of the lazy-2 mutant of tomato (Lycopersicon esculentum Mill., cv. Ailsa Craig) exhibit negative gravitropism in the dark, but respond positively gravitropically in (red) light. In order to test whether high-gradient magnetic fields (HGMFs) exert only ponderomotive effects on amyloplasts or affect other physiological processes, we induced magnetophoretic curvature in wild-type (WT) and lazy-2 mutant seedlings. Straight hypocotyls of 4-d-old plants were selected and the tips of their hooks were placed in an HGMF near the edge of a magnetized ferromagnetic wedge [grad (H2/2) approximately 10(9)-10(10) Oe2/cm] and mounted on a 1-rpm clinostat. After 4 h in the dark, 85% of WT hypocotyls and 67% of mutant hypocotyls curved toward the wedge. When the seedlings were exposed to red light for 1 h prior to and during the application of the HGMF, 78% of the WT seedlings curved toward the magnetic gradient, but the majority of the lazy-2 seedlings (75%) curved away from the stronger field area. Intracellular amyloplast displacement in the HGMF was similar for both varieties and resembled the displacement after horizontal reorientation. The WT showed a distinct graviresponse pattern depending on the orientation of the hook, even after excision of the apex. Application of HGMFs to decapitated hypocotyls resulted in curvature consistent with that obtained after horizontal reorientation. After light exposure, decapitated lazy-2 seedlings did not respond positively gravitropically. The data imply that the lazy-2 mutants perceive the displacement of amyloplasts in a similar manner to the WT and that the HGMF does not affect the graviresponse mechanism. The study demonstrates that ponderomotive forces due to HGMFs are useful for the analysis of the gravity-sensing mechanism in plants.

NASA Discipline Plant Biology↗

Root gravitropism

When a plant root is reoriented within the gravity field, it responds by initiating a curvature which eventually results in vertical growth. Gravity sensing occurs primarily in the root tip. It may involve amyloplast sedimentation in the columella cells of the root cap, or the detection of forces exerted by the mass of the protoplast on opposite sides of its cell wall. Gravisensing activates a signal transduction cascade which results in the asymmetric redistribution of auxin and apoplastic Ca2+ across the root tip, with accumulation at the bottom side. The resulting lateral asymmetry in Ca2+ and auxin concentration is probably transmitted to the elongation zone where differential cellular elongation occurs until the tip resumes vertical growth. The Cholodny-Went theory proposes that gravity-induced auxin redistribution across a gravistimulated plant organ is responsible for the gravitropic response. However, recent data indicate that the gravity-induced reorientation is more complex, involving both auxin gradient-dependent and auxin gradient-independent events.

NASA Discipline Plant Biology↗

Magnetophoretic induction of curvature in coleoptiles and hypocotyls

Coleoptiles of barley (Hordeum vulgare) were positioned in a high gradient magnetic field (HGMF, dynamic factor gradient of H(2)/2 of 10(9)-10(10) Oe2 cm-1), generated by a ferromagnetic wedge in a uniform magnetic field and rotated on a 1 rpm clinostat. After 4 h 90% of coleoptiles had curved toward the HGMF. The cells affected by HGMF showed clear intracellular displacement of amyloplasts. Coleoptiles in a magnetic field next to a non-ferromagnetic wedge showed no preferential curvature. The small size of the area of nonuniformity of the HGMF allowed mapping of the sensitivity of the coleoptiles by varying the initial position of the wedge relative to the coleoptile apex. When the ferromagnetic wedge was placed 1 mm below the coleoptile tip only 58% of the coleoptiles curved toward the wedge indicating that the cells most sensitive to intracellular displacement of amyloplasts and thus gravity sensing are confined to the top 1 mm portion of barley coleoptiles. Similar experiments with tomato hypocotyls (Lycopersicum esculentum) also resulted in curvature toward the HGMF. The data strongly support the amyloplast-based gravity-sensing system in higher plants and the usefulness of HGMF to substitute gravity in shoots.

NASA Discipline Plant Biology↗

Sensing Clouds via Spacecraft Radio Occultation Observations

The presence of clouds dramatically alters the opacity and radiative transfer within Earth's atmosphere at both short and long wavelengths. Knowledge of cloud top and base is needed to estimate the Outgoing Long wave Radiation (OLR) to space and the net radiation at the surface from a given atmospheric profile. Satellite observations are required to provide the global perspective needed for climate. Cloud top pressure can be determined to some accuracy from spaceborne radiance measurements when cloud opacities are sufficiently large and cloud top temperatures are sufficiently low to readily them from the surface. Cloud base is particularly difficult to determine from space. The relatively small sensitivity of long wavelengths must be used to penetrate the clouds while at the same time providing sufficient sensitivity to detect the cloud base. We are studying the indirect sensitivity of radio occultation observations to clouds through their impact on the refractivity structure. The tradewind inversion is an excellent example where a very sharp refractivity structure coincides with the top of the tradewind cumulus and stratus clouds. In general, any cloud with sufficient IR opacity will have large transmissivity gradient at cloud top (base) which will result in large cooling (heating) which will create a thermal inversion at cloud top (base). Both liquid and ice clouds can reach this critical opacity. The thermal inversion and sharp change in specific humidity will cause a sharp change in the refractivity gradient which can be identified in the radio occultation results, particularly the signal amplitude. The occultations yield very accurate information on the height of such features. The heating at cloud base drives convection causing the air to follow a moist adiabat within the Cloud which further helps constrain the interpretation of the observations. The upward expansion of such opaque clouds due to convection may be an important mechanism supplying moisture into the upper troposphere. We will present simulations using high resolution radiosondes from field campaigns representing the expected signatures of such features. We will also present initial results of comparisons between GPS observations and GOES-derived cloud tops to assess the utility of this concept.

Kursinski, E. R.↗

Remote Sensing-Driven Hydrodynamic Modeling in Data-Scarce Regions: Integrating ICESat-2, Sentinel-2, SWOT and Re-analysis Models for Coastal Monitoring

Hydrodynamic models in coastal and estuarine systems are typically constrained by sparse bathymetry, boundary, and validation data, especially in regions where field campaigns are costly or impractical. Here we develop and test a fully satellite-driven framework for hydrodynamic modeling in South Africa’s Langebaan Lagoon without using any local in situ measurements. Bathymetry is derived by training multispectral Sentinel-2 reflectance against ICESat-2 ATL24 photon-derived depths using an XGBoost model optimized with Bayesian search. The final satellite-derived bathymetry reproduces independent ATL24 points with RMSE = 0.45 m and R 2 = 0.97. This bathymetry was used in a depth-averaged Delft3D Flexible Mesh model driven at the open boundary by TPXO tidal harmonics and by ERA5 winds. We validate modeled water surface elevation against 16 SWOT low-rate (250 m, unsmoothed) passes in 2023. SWOT–model comparisons yield an overall RMSE of 0.11 m and R 2 = 0.61, with typical point differences <0.10 m (∼7% of the 1.5 m tidal range), and showed consistent spatial gradients in water level from the offshore boundary, through Saldanha Bay, and into the lagoon. At the offshore boundary, TPXO and SWOT sea surface heights agree closely (R 2 = 0.86). A simple phase adjustment of ∼26,min between TPXO and SWOT lowers the RMSE from 0.18,m to 0.11,m, showing that phase offset accounts for some of the discrepancy, with additional errors likely linked to non-tidal signals. Our results demonstrate that combining passive optical, photon-counting LiDAR, radar interferometry, and global tidal/atmospheric models enables robust, transferrable hydrodynamic modeling in data-scarce coastal systems, offering a cost-effective pathway for monitoring.

ICESat-2↗

Connecting Returned Apollo Soils and Remote Sensing: Application to the Diviner Lunar Radiometer

The Diviner Lunar Radiometer, onboard NASA's Lunar Reconnaissance Orbiter, has produced the first global, high resolution, thermal infrared observations of an airless body. The Moon, which is the most accessible member of this most abundant class of solar system objects, is also the only body for which we have extraterrestrial samples with known spatial context, returned Apollo samples. Here we present the results of a comprehensive study to reproduce an accurate simulated lunar environment, evaluate the most appropriate sample and measurement conditions, collect thermal infrared spectra of a representative suite of Apollo soils, and correlate them with Diviner observations of the lunar surface. It has been established previously that thermal infrared spectra measured in simulated lunar environment (SLE) are significantly altered from spectra measured under terrestrial or martian conditions. The data presented here were collected at the University of Oxford Simulated Lunar Environment Chamber (SLEC). In SLEC, we simulate the lunar environment by: (1) pumping the chamber to vacuum pressures (less than 10‐4 mbar) sufficient to simulate lunar heat transport processes within the sample, (2) cooling the chamber with liquid nitrogen to simulate radiation to the cold space environment, and (3) heating the samples with heaters and lamp to set‐up thermal gradients similar to those experienced in the upper hundreds of microns of the lunar surface. We then conducted a comprehensive suite of experiments using different sample preparation and heating conditions on Apollo soils 15071 (maria) and 67701 (highland) and compared the results to Diviner noontime data to select the optimal experimental conditions. This study includes thermal infrared SLE measurements of 10084 (A11 - LM), 12001 (A12 - LM), 14259 (A14 - LM), 15071 (A15 - S1), 15601 (A15 - S9a), 61141 (A16 - S1), 66031 (A16 - S6), 67701 (A16 - S11), and 70181 (A17 - LM). The Diviner dataset includes all six Apollo sites at approximately 200 m spatial resolution We find that analyses of Diviner observations of individual sampling stations and SLE measurements returned Apollo soils show good agreement, while comparisons to thermal infrared reflectance under ambient conditions do not agree well, which underscores the need for SLE measurements and validates the Diviner compositional measurement technique.

Greenhagen, B. T.↗

Curvature induced by amyloplast magnetophoresis in protonemata of the moss Ceratodon purpureus

After gravistimulation of Ceratodon purpureus (Hedw.) Brid. protonemata in the dark, amyloplast sedimentation was followed by upward curvature in the wild-type (WT) and downward curvature in the wwr mutant (wrong way response). We used ponderomotive forces induced by high-gradient magnetic fields (HGMF) to simulate the effect of gravity and displace the presumptive statoliths. The field was applied by placing protonemata either between two permanent magnets at the edge of the gap, close to the edge of a magnetized ferromagnetic wedge, or close to a small (<1 mm) permanent magnet. Continuous application of an HGMF in all three configurations resulted in plastid displacement and induced curvature in tip cells of WT and wwr protonemata. WT cells curved toward the HGMF, and wwr cells curved away from the HGMF, comparable to gravitropism. Plastids isolated from protonemal cultures had densities ranging from 1.24 to 1.38 g cm-3. Plastid density was similar for both genotypes, but the mutant contained larger plastids than the WT. The size difference might explain the stronger response of the wwr protonemata to the HGMF. Our data support the plastid-based theory of gravitropic sensing and suggest that HGMF-induced ponderomotive forces can substitute for gravity.

Non-NASA Center↗

Measurement of Atmospheric CO2 Column Concentrations to Cloud Tops With a Pulsed Multi-Wavelength Airborne Lidar

We have measured the column-averaged atmospheric CO2 mixing ratio to a variety of cloud tops by using an airborne pulsed multi-wavelength integrated-path differential absorption (IPDA) lidar. Airborne measurements were made at altitudes up to 13 km during the 2011, 2013 and 2014 NASA Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) science campaigns flown in the United States West and Midwest and were compared to those from an in situ sensor. Analysis of the lidar backscatter profiles shows the average cloud top reflectance was approx. 5% for the CO2 measurement at 1572.335 nm except to cirrus clouds, which had lower reflectance. The energies for 1 micro-s wide laser pulses reflected from cloud tops were sufficient to allow clear identification of CO2 absorption line shape and then to allow retrievals of atmospheric column CO2 from the aircraft to cloud tops more than 90% of the time. Retrievals from the CO2 measurements to cloud tops had minimal bias but larger standard deviations when compared to those made to the ground, depending on cloud top roughness and reflectance. The measurements show this new capability helps resolve CO2 horizontal and vertical gradients in the atmosphere. When used with nearby full-column measurements to ground, the CO2 measurements to cloud tops can be used to estimate the partial-column CO2 concentration below clouds, which should lead to better estimates of surface carbon sources and sinks. This additional capability of the range-resolved CO2 IPDA lidar technique provides a new benefit for studying the carbon cycle in future airborne and space-based CO2 missions.

atmospheric↗

Water Vapor in Titan's Stratosphere from Cassini/CIRS Far-infrared Spectra

Since the first detection of water vapor in Titan's stratosphere by disk-average observations from the Infrared Space Observatory (Coustenis et al. 1998) we report here the successful detection of stratospheric water vapor using the Cassini Composite Infrared Spectrometer (CIRS, Flasar et al. 2004). CIRS senses water emissions in the far infrared spectral region near 50 microns, which we have modeled using two independent radiative transfer codes (NEMESIS, Irwin et al 2008 and ART, Coustenis et al. 2007, 2010). From the analysis of nadir spectra we have derived a mixing ratio of (0.14 0.05) ppb at an altitude of 97 kilometers, which corresponds to an integrated (from 0 to 600 kilometers) surface normalized column abundance of (3.7 plus or minus 1.3) x 10(exp 14) molecules per square centimeter. In the latitude range 80 S to 30 N we see no evidence for latitudinal variations in these abundances within the error bars. Using limb observations, we obtained mixing ratios of (0.13 plus or minus 0.04) ppb at an altitude of 115 kilometers and (0.45 plus or minus 0.15) ppb at an altitude of 230 kilometers, confirming that the water abundance has a positive vertical gradient as predicted by photochemical models (e.g. Lara et al. 1996, Wilson and Atreya 2004, Horst et al. 2008); retrieved scaling factors (from approximately 0.1 to approximately 0.6) to the water profile suggested by these models show that water vapor is present in Titan stratosphere with less abundance than predicted.

Cottini, V.↗

Application of Atmospheric Infrared Sounder (AIRS) Data to Climate Research

The application of hyper spectral radiometric data to climate research requires very high absolute radiometric accuracy and stability. We use cloud-free tropical ocean data from the Atmospheric InfraRed Sounder (AIR) Calibration Data Subset (ADCS) to show that the radiometric precision and stability required climate applications has been achieved. The sea surface skin temperatures derived from the AIRS 2616cm-1 super window channel are stable relative to the RTG.SST at the better than 8 mK/year level, and the spectral calibration is stable at the 1 ppm/year level. The excellent stability and accuracy are the result of the implementation of AIRS as a grating array spectrometer, which is cooled and stabilized within 10 mK at 155 K. Analysis of daily measurements of the temperature gradient between the surface and 7 km altitude show that the AIRS Calibration Data Subset has applications which extend its original intent for calibration support to climate research. The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua satellite was launched into polar orbit in May 2002. AIRS covers the spectral region from 640 to 2700 cm-1 with 2378 independent channels and represents the first of a new generation of hyper spectral resolution sounders in support of global sounding data for weather forecasting and climate research.

infrared↗

Using SMAP Level-4 Soil Moisture to Constrain MOD16 Evapotranspiration over the Contiguous USA

Evapotranspiration (ET) is a key hydrologic variable linking the Earth’s water, carbon and energy cycles. At large spatial scales, remote sensing-based (RS) models are often used to quantify ET. Despite the large number of RS ET models available, few include soil moisture as a key environmental input, which can degrade model accuracy and utility. Here, we use model assimilation enhanced soil moisture estimates from the NASA SMAP (Soil Moisture Active Passive) mission as a water supply control in the MOD16 ET algorithm framework. SMAP-derived daily surface (0-5cm depth) and root zone (0-1m depth) soil moisture are used with MODIS (Moderate Resolution Imaging Spectroradiometer) vegetation observations, and 4km gridded regional surface meteorology (Gridmet) as primary inputs for estimating daily ET and underlying model soil and stomatal conductance terms. We calibrated the model environmental response parameters using tower eddy covariance ET observations representing major North American biomes. The model ET results were validated using a holdout set of tower observations spanning a large regional climate gradient. The updated ET estimates outperform the baseline MOD16 product across all tower validation sites (RMSE = 0.758 vs 1.108 mm day-1; R2 = 0.68 vs0.45, respectively). Smaller relative improvements were obtained using a recalibrated model with 4km Gridmet meteorology, but no soil moisture control (RMSE = 0.813 mm day-1; R2 = 0.66), indicating that these changes are essential for the improved model performance. The soil moisture-constrained model improvements and relative benefits from the SMAP observations are greater in arid climates, consistent with stronger soil moisture control on ET in water-limited regions. The use of SMAP soil moisture as an additional model constraint improves MOD16 regional performance and provides a new framework for investigating both soil and atmosphere controls on ET.

SMAP↗

Evaluation and Applications of Multi-Instrument Boundary-Layer Thermodynamic Retrievals

Recent reports have highlighted the need for improved observations of the boundary layer. In this study, we explore the combination of ground-based active and passive remote sensors deployed for thermodynamic profiling to analyze various boundary-layer observation strategies. Optimal-estimation retrievals of thermodynamic profiles from Atmospheric Emitted Radiance Interferometer (AERI) observed spectral radiance are compared with and without the addition of active sensor observations from a May–June 2017 observation period at the Atmospheric Radiation Measurement–Southern Great Plains Site. In all, three separate thermodynamic retrievals are considered here: retrievals including AERI data only, retrievals including AERI data and Vaisala water vapour differential absorption lidar data, and retrievals including AERI data and Raman lidar data. First, the three retrievals are compared to each other and to reference radiosonde data over the full observation period to get a bulk understanding of their differences and characterize the impact of clouds on these retrieved profiles. These analyses show that the most significant differences are in the water vapour field, where the active sensors are better able to represent the moisture gradient in the entrainment zone near boundary layer top. We also explore how differences in retrievals may impact results of applied analyses including land–atmosphere coupling, convection indices, and severe storm environmental characterization. Overall, adding active sensors to the optimal-estimation retrieval showed some added information, particularly in the moisture field. Given the costs of such platforms, the value of that added information must be weighed for the application at hand.

boundary-layer observation↗

A Micromechanical INS/GPS System for Small Satellites

The cost and complexity of large satellite space missions continue to escalate. To reduce costs, more attention is being directed toward small lightweight satellites where future demand is expected to grow dramatically. Specifically, micromechanical inertial systems and microstrip global positioning system (GPS) antennas incorporating flip-chip bonding, application specific integrated circuits (ASIC) and MCM technologies will be required. Traditional microsatellite pointing systems do not employ active control. Many systems allow the satellite to point coarsely using gravity gradient, then attempt to maintain the image on the focal plane with fast-steering mirrors. Draper's approach is to actively control the line of sight pointing by utilizing on-board attitude determination with micromechanical inertial sensors and reaction wheel control actuators. Draper has developed commercial and tactical-grade micromechanical inertial sensors, The small size, low weight, and low cost of these gyroscopes and accelerometers enable systems previously impractical because of size and cost. Evolving micromechanical inertial sensors can be applied to closed-loop, active control of small satellites for micro-radian precision-pointing missions. An inertial reference feedback control loop can be used to determine attitude and line of sight jitter to provide error information to the controller for correction. At low frequencies, the error signal is provided by GPS. At higher frequencies, feedback is provided by the micromechanical gyros. This blending of sensors provides wide-band sensing from dc to operational frequencies. First order simulation has shown that the performance of existing micromechanical gyros, with integrated GPS, is feasible for a pointing mission of 10 micro-radians of jitter stability and approximately 1 milli-radian absolute error, for a satellite with 1 meter antenna separation. Improved performance micromechanical sensors currently under development will be suitable for a range of micro-nano-satellite applications.

Barbour, N.↗

MESSENGER Searches for Less Abundant or Weakly Emitting Species in Mercury's Exosphere

Mercury's exosphere is composed of material that originates at the planet's surface, whether that material is native or delivered by the solar wind and micrometeoroids. Many exospheric species have been detected by remote sensing, including H and He by Mariner 10, Na, K, and Ca by ground-based observations, and H, Na, Ca, Mg, and Ca+ by the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft. Other exospheric species, including Fe, AI, Si, 0, S, Mn, CI, Ti, OH, and their ions, are expected to be present on the basis of MESSENGER surface measurements and models of Mercury's surface chemistry. Here we report on searches for these species made with the Ultraviolet and Visible Spectrometer (UVVS) channel of the Mercury Atmospheric and Surface Composition Spectrometer (MASCS). No obvious signatures of the listed species have yet been observed in Mercury's exosphere by the UVVS as of this writing. It is possible that detections are elusive because the optimum regions of the exosphere have not been sampled. The Sun-avoidance constraints on MESSENGER place tight limits on instrument boresight directions, and some regions are probed infrequently. If there are strong spatial gradients in the distribution of weakly emitting species, a high-resolution sampling of specific regions may be required to detect them. Summing spectra over time will also aid in the ability to detect weaker emission. Observations to date nonetheless permit strong upper limits to be placed on the abundances of many undetected species, in some cases as functions of time and space. As those limits are lowered with time, the absence of detections can provide insight into surface composition and the potential source mechanisms of exospheric material.

Vervack, Ronald J., Jr.↗

Eyjafjallajokull Volcano Plume Particle-Type Characterization from Space-Based Multi-angle Imaging

The Multi-angle Imaging SpectroRadiometer (MISR) Research Aerosol algorithm makes it possible to study individual aerosol plumes in considerable detail. From the MISR data for two optically thick, near-source plumes from the spring 2010 eruption of the Eyjafjallaj kull volcano, we map aerosol optical depth (AOD) gradients and changing aerosol particle types with this algorithm; several days downwind, we identify the occurrence of volcanic ash particles and retrieve AOD, demonstrating the extent and the limits of ash detection and mapping capability with the multi-angle, multi-spectral imaging data. Retrieved volcanic plume AOD and particle microphysical properties are distinct from background values near-source, as well as for overwater cases several days downwind. The results also provide some indication that as they evolve, plume particles brighten, and average particle size decreases. Such detailed mapping offers context for suborbital plume observations having much more limited sampling. The MISR Standard aerosol product identified similar trends in plume properties as the Research algorithm, though with much smaller differences compared to background, and it does not resolve plume structure. Better optical analogs of non-spherical volcanic ash, and coincident suborbital data to validate the satellite retrieval results, are the factors most important for further advancing the remote sensing of volcanic ash plumes from space.

Kahn, Ralph A.↗

Dynamics of the transition zone in coastal zone color scanner-sensed ocean color in the North Pacific during oceanographic spring

A transition zone in phytoplankton concentration running across the North Pacific basin at 30 deg to 40 deg north latitude corresponds to a basin-wide front in surface chlorophyll observed in a composite of coastal zone color scanner (CZCS) images for May, June, and July 1979-1986. This transition zone with low chlorophyll to the south and higher chlorophyll to the north can be simulated by a simple model of the concentration of phytoplankton, zooplankton, and dissolved nutrient (nitrate) in the surface mixed layer of the ocean applied to the North Pacific basin for the climatological conditions during oceanographic springtime (May, June, and July). The model is initialized with a 1 deg x 1 deg gridded estimate of wintertime (February, March, and April) mixed layer nitrate concentrations calculated from an extensive nutrient database and a similarly gridded mixed layer depth data set. Comparison of model predictions with CZCS data provides a means of evaluating the dynamics of the transition zone. We conclude that in the North Pacific, away from major boundary currents and coastal upwelling zones, wintertime vertical mixing determines the total nutrient available to the plankton ecosystem in the spring. The transition zone seen in basin-scale CZCS images is a reflection of the geographic variation in the wintertime mixed layer depth and the nitracline, leading to a latitudinal gradient in phytoplankton chlorophyll.

Glover, David M.↗