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NASA NTRS2002

Subtropical Gyre Variability Observed by Ocean Color Satellites

The subtropical gyres of the world are extensive, coherent regions that occupy about 40% of the surface of the earth. Once thought to be homogeneous and static habitats, there is increasing evidence that mid-latitude gyres exhibit substantial physical and biological variability on a variety of time scales. While biological productivity within these oligotrophic regions may be relatively small, their immense size makes their total contribution significant. Global distributions of dynamic height derived from satellite altimeter data, and chlorophyll concentration derived from satellite ocean color data, show that the dynamic center of the gyres, the region of maximum dynamic height where the thermocline is deepest, does not coincide with the region of minimum chlorophyll concentration. The physical and biological processes by which this distribution of ocean properties is maintained, and the spatial and temporal scales of variability associated with these processes, are analyzed using global surface chlorophyll-a concentrations, sea surface height, sea surface temperature and surface winds from operational satellite and meteorological sources, and hydrographic data from climatologies and individual surveys. Seasonal and interannual variability in the areal extent of the subtropical gyres are examined using 8 months (November 1996 - June 1997) of OCTS and nearly 5 years (September 1997 - June 02) of SeaWiFS ocean color data and are interpreted in the context of climate variability and measured changes in other ocean properties (i.e., wind forcing, surface currents, Ekman pumping, and vertical mixing). The North Pacific and North Atlantic gyres are observed to be shrinking over this period, while the South Pacific, South Atlantic, and South Indian Ocean gyres appear to be expanding.

McClain, Charles R.↗
NASA NTRS2008

The NPOESS Preparatory Project (NPP) Science Data Segment (SDS) Data Depository and Distribution Element (SD3E) System Architecture

The National Polar-orbiting Operational Environmental Satellite System (NPOESS), the U.S. Government's future low-Earth orbiting satellite system, will monitor global weather and environmental conditions. Serving as a risk reduction for NPOESS, the NPOESS Preparatory Project (NPP) will provide remotely sensed atmospheric, land, ocean, ozone, and sounder data that will serve the meteorological and global climate change scientific communities. The National Aeronautics and Space Administration (NASA) NPP Science Data Segment's (SDS) primary role is to independently assess the quality of the NPP science and environmental data records for their ability to support climate research. The SDS is composed of nine elements; an input element that receives data from the operational agencies and acts as a buffer, a calibration analysis element, five elements devoted to measurement based quality assessment, an element used to test algorithmic improvements, and an element that provides overall science direction. Each element requires a set of sensor specific science data products for their evaluation. There are four NPP sensors that will be flown on the NPP observatory. They are the Visible Infrared Imagining Radiometer Suite (VIIRS), the Advanced Technology Microwave Sounder (ATMS), the Cross-Track Infrared Sounder (CrIS), and the Ozone Mapper/Profiler Suite (OMPS). It is estimated that these four sensors combined will make daily data requests for approximately six terabytes of NPP science products from the operational data providers. As a result, issues associated with duplicate data requests, data transfers of large volumes of diverse products, and data transfer failures raised concerns with respect to the network traffic and bandwidth consumption. Therefore, a central data broker system for receiving and buffering data requests and data products for the SDS was developed. The data element for this system is called the SDS Data Depository and Distribution Element (SD3E). It supports science mission data assessment by assuring the timely and validated acquisition and subsequent transfer of the NPP Science Mission data to the SDS Elements and NPP Science Team. The six science elements that interface with the SD3E span across the NASA Goddard Space Flight Center (GSFC), the NASA Jet Propulsion Laboratory (JPL), and the University of Wisconsin. As the primary communication vehicle for the science elements and science team, the SD3E has an interface to the operational data providers: National Environment Satellite, Data, and Information Service (NESDIS) Interface Data Processing System (IDPS) and the National Oceanic Atmospheric Administration's (NOAA) Comprehensive Large Array-data Stewardship system (CLASS) Archive Data System (ADS), that are responsible for product generation and archive and distribution respectively. The SD3E is designed to be a semi-customizable and semi-automated system. This system is designed to provide flexibility and ease of use for the science users in accessing the latest data products by creating a rolling data cache that temporarily stores the products locally before transferring the data to the SDS Measurement based elements for the land, ocean, atmosphere, sounder, and ozone. This paper describes the design and architecture of one of the nine SDS elements, the SD3E, and how this system has provided a mechanism for efficient data exchange, how it has helped in alleviating some of the network traffic and usage, and how it has contributed to reducing operational costs.

Ho, Evelyn L.↗
NASA NTRS2005

Assessments of Total Lightning Data Utility in Weather Forecasting

National Weather Service forecasters in Huntsville, Alabama have had access to total lightning data from the North Alabama Lightning Mapping Array (LMA) since 2003. Forecasters can monitor real-time total lightning observations on their AWIPS (Advanced Weather Interactive Processing System (AWIPS) workstations. The lightning data is used to supplement other observations such as radar and satellite data. The lightning data is updated every 2 min, providing more timely evidence of storm growth or decay than is available from 5 min radar scans. Total lightning observations have been used to positively impact warning decisions in a number of instances. A number of approaches are being pursued to assess the usefulness of total lightning measurements to the operational forecasting community in the warning decision process. These approaches, which include both qualitative and quantitative assessment methods, will be discussed. submitted to the American Meteorological Society (AMS) Conference on Meteorological Applications of Lightning Data to be held in San Diego, CA January 9-13,2005. This will be a presentation and an extended abstract will be published on a CD available from the AMS.

Buechler, Dennis E.↗
DOE OSTI2016

Low-CCN concentration air masses over the eastern North Atlantic: Seasonality, meteorology, and drivers

In this paper, a 20 month cloud condensation nucleus concentration (N CCN ) data set from Graciosa Island (39°N, 28°W) in the remote North Atlantic is used to characterize air masses with low cloud condensation nuclei (CCN) concentrations. Low-CCN events are defined as 6 h periods with mean N CCN <20 cm -3 (0.1% supersaturation). A total of 47 low-CCN events are identified. Surface, satellite, and reanalysis data are used to explore the meteorological and cloud context for low-CCN air masses. Low-CCN events occur in all seasons, but their frequency was 3 times higher in December–May than during June–November. Composites show that many of the low-CCN events had a common meteorological basis that involves southerly low-level flow and rather low wind speeds at Graciosa. Anomalously low pressure is situated to the west of Graciosa during these events, but back trajectories and lagged SLP composites indicate that low-CCN air masses often originate as cold air outbreaks to the north and west of Graciosa. Finally, low-CCN events were associated with low cloud droplet concentrations (N d ) at Graciosa, but liquid water path (LWP) during low-CCN events was not systematically different from that at other times. Satellite N d and LWP estimates from MODIS collocated with Lagrangian back trajectories show systematically lower N d and higher LWP several days prior to arrival at Graciosa, consistent with the hypothesis that observed low-CCN air masses are often formed by coalescence scavenging in thick warm clouds, often in cold air outbreaks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A harmonized global nighttime light dataset 1992–2018

Nighttime light (NTL) data from the Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership satellite provide a great opportunity for monitoring human activities from regional to global scales. Despite the valuable records of nightscape from DMSP (1992–2013) and VIIRS (2012–2018), the potential of the historical archive of NTL observations has not been fully explored because of the severe inconsistency between DMSP and VIIRS. In this study, we generated an integrated and consistent NTL dataset at the global scale by harmonizing the inter-calibrated NTL observations from the DMSP data and the simulated DMSP-like NTL observations from the VIIRS data. The generated global DMSP NTL time-series data (1992–2018) show consistent temporal trends. This temporally extended DMSP NTL dataset provides valuable support for various studies related to human activities such as electricity consumption and urban extent dynamics.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

The short-term prediction of universal time and length of day using atmospheric angular momentum

The ability to predict short-term variations in the Earth's rotation has gained importance in recent years owing to more precise spacecraft tracking requirements. Universal time (UT1), that component of the Earth's orientation corresponding to the rotation angle, can be measured by number of high-precision space geodetic techniques. A Kalman filter developed at the Jet Propulsion Laboratory (JPL) optimally combines these different data sets and generates a smoothed times series and a set of predictions for UT1, as well as for additional Earth orientation components. These UT1 predictions utilize an empirically derived random walk stochastic model for the length of the day (LOD) and require frequent and up-to-date measurements of either UT1 or LOD to keep errors from quickly accumulating. Recent studies have shown that LOD variations are correlated with changes in the Earth's axial atmospheric angular momentum (AAM) over timescales of several years down to as little as 8 days. AAM estimates and forecasts out to 10 days are routinely available from meteorological analysis centers; these data can supplement geodetic measurements to improve the short-term prediction of LOD and have therefore been incorporated as independent data types in the JPL Kalman filter. We find that AAM and, to a lesser extent, AAM forecast data are extremely helpful in generating accurate near-real-time estimates of UT1 and LOD and in improving short-term predictions of these quantities out to about 10 days.

Freedman, A. P.↗
NASA NTRS1984

Methods for Cloud Cover Estimation

Several methods for cloud cover estimation are described relevant to assessing the performance of a ground-based network of solar observatories. The methods rely on ground and satellite data sources and provide meteorological or climatological information. One means of acquiring long-term observations of solar oscillations is the establishment of a ground-based network of solar observatories. Criteria for station site selection are: gross cloudiness, accurate transparency information, and seeing. Alternative methods for computing this duty cycle are discussed. The cycle, or alternatively a time history of solar visibility from the network, can then be input to a model to determine the effect of duty cycle on derived solar seismology parameters. Cloudiness from space is studied to examine various means by which the duty cycle might be computed. Cloudiness, and to some extent transparency, can potentially be estimated from satellite data.

Glackin, D. L.↗
NASA NTRS1995

Interplanetary magnetic field control of mantle precipitation and associated field-aligned currents

Dayside reconnection, which is particularly effective for a southward interplanetary magnetic field (IMF), allows magnetosheath particles to enter the magnetosphere where they form the plasma mantle. The motions of the reconnected flux tube produce convective flows in the ionosphere. It is known that the convection patterns in the polar cap are skewed to the dawnside for a positive IMF B(sub y) (or duskside for a negative IMF B(sub y)) in the northern polar cap. Correspondingly, one would expect to find asymmetric distributions of mantle particle precipitation, but previous results have been unclear. In this paper the correlation between B(sub y) and the distribution of mantle particle precipitation is studied for steady IMF conditions with southward IMF. Ion and electron data from the Defense Meteorological Satellite Program (DMSP) F6 and F7 satellites are used to identify the mantle region and IMP 8 is used as a solar wind monitor to characterize the IMF. We study the local time extension of mantle precipitation in the prenoon and postnoon regions. We find that, in accordance with theoretical expectations for a positive (negative) IMF B(sub y), mantle particle precipitation mainly appears in the prenoon region of the northern (southern) hemisphere. The mantle particle precipitation can extend to as early as 0600 magnetic local time (MLT) in the prenoon region but extends over a smaller local time region in the postnoon sector (we did not find mantle plasma beyond 1600 MLT in our data set although coverage is scant in this area). Magnetometer data from F7 are used to determine whether part of the region 1 current flows on open field lines. We find that at times part of the region 1 sense current extends into the region of mantle particle precipitation, and is therefore on open field lines. In other cases, region 1 currents are absent on open field lines. Most of the observed features can be readily interpreted in terms of the open magnetosphere model.

Xu, Dingan↗
NASA NTRS2001

Ozone Loss From Quasi-Conservative Coordinate Mapping During the 1999-2000 SOLVE Campaign

During the winter of 1999-2000, the Sage III Ozone Loss and Validation Experiment (SOLVE) field experiment took place in Kiruna, Sweden. The purpose of SOLVE was to examine ozone depletion mechanisms in the Arctic stratosphere (from about 10 to 50 km altitude) during the winter and early spring, when a band of strong winds (the 'polar vortex') circle the pole. Measurements of stratospheric ozone were made by several different kinds of instruments in different meteorological situations. We analyzed these data using the 'quasi-conservative coordinate mapping' technique, in which the measurements are analyzed in terms of meteorological properties ('potential temperature' and 'potential vorticity') which tend not to change very much over a few days. This technique reduces or removes the changes that are associated with the polar vortex moving around. Over longer time periods, potential temperature and potential vorticity change as air cools and descends within the polar vortex. We account for these changes by calculating the trajectories of air parcels, and this enables us to extend the analysis over a ten-week period from January 10 to March 17, 2000. Using data from the NASA ER-2 aircraft, from the DIAL and AROTEL laser sounders on the NASA DC-8 aircraft, and balloon-borne ozonesondes, our analysis reveals changes in ozone which, because we have removed the effects of polar vortex motion and the descending air, indicate chemical destruction of ozone in early 2000. We find a peak decline rate of approximately 0.03 ppmv/day near 470 K of potential temperature (near 20 km) in mid-January which sinks in altitude to around 440 K (near 18 km) in mid-March.

Lait, L. R.↗
NASA NTRS2024

Revised estimates of NO 2 reductions during the COVID-19 lockdowns using updated TROPOMI NO 2 retrievals and model simulations

The TROPOspheric Monitoring Instrument (TROPOMI) observed unprecedented declines in NO 2 vertical column densities (VCD) over the world's most densely populated cities during the 2020 COVID-19 lockdowns. These favorable changes in NO 2 air quality were correlated with sharp reductions in traffic volume and economic activity during the lockdowns. In this comprehensive global study, we provide revised estimates of the declines in anthropogenic emissions for 36 megacities using a novel methodology for disentangling the anthropogenic emissions from the meteorological transport and natural variability. We further quantify the uncertainty associated with changes in the a priori profile shape information during the lockdowns due to reduced emissions. Satellite NO 2 retrieval techniques calculate an air mass factor that requires a priori NO 2 profile shape information representative of the local atmosphere. This information, which is typically obtained from a chemical transport model (CTM), was not available for the early studies. This study also accounts for the satellite sampling errors resulting from the selective sampling of non-cloudy scenes during the study period. For our analysis, we used CTM simulations that were generated with and without COVID-impacted emissions. We perform retrievals of tropospheric NO 2 columns with the NASA NO 2 algorithm, and then use observed and simulated data to disentangle the meteorological transport from the contribution due anthropogenic emissions. We found that the meteorological transport was most significant source of variability ranging between −35% and 22% of the change total tropospheric VCD. We also find that not accounting for changes in the a priori NO 2 profile shape information during the lockdowns resulted in systematic retrieval errors that were up to 12% of the estimated decline, and the elimination of cloud contaminated scenes resulted in sampling errors that in general ranged between varied ±15%.

NO2↗
NASA NTRS2010

Permanent Monitoring of the Reference Point of the 20m Radio Telescope Wettzell

To achieve the goals of the VLBI2010 project and the Global Geodetic Observing System (GGOS), an automated monitoring of the reference points of the various geodetic space techniques, including Very Long Baseline Interferometry (VLBI), is desirable. The resulting permanent monitoring of the local-tie vectors at co-location stations is essential to obtain the sub-millimeter level in the combinations. For this reason a monitoring system was installed at the Geodetic Observatory Wettzell by the Geodetic Institute of the University of Karlsruhe (GIK) to observe the 20m VLBI radio telescope from May to August 2009. A specially developed software from GIK collected data from automated total station measurements, meteorological sensors, and sensors in the telescope monument (e.g., Invar cable data). A real-time visualization directly offered a live view of the measurements during the regular observation operations. Additional scintillometer measurements allowed refraction corrections during the post-processing. This project is one of the first feasibility studies aimed at determining significant deformations of the VLBI antenna due to, for instance, changes in temperature.

Neidhardt, Alexander↗
DOE OSTI2017

Development of a Wind Plant Large-Eddy Simulation with Measurement-Driven Atmospheric Inflow: Preprint

This paper details the development of an aeroelastic wind plant model with large-eddy simulation (LES). The chosen LES solver is the Simulator for Wind Farm Applications (SOWFA) based on the OpenFOAM framework, coupled to NREL's comprehensive aeroelastic analysis tool, FAST. An atmospheric boundary layer (ABL) precursor simulation was constructed based on assessments of meteorological tower, lidar, and radar data over a 3-hour window. This precursor was tuned to the specific atmospheric conditions that occurred both prior to and during the measurement campaign, enabling capture of a night-to-day transition in the turbulent ABL. In the absence of height-varying temperature measurements, spatially averaged radar data were sufficient to characterize the atmospheric stability of the wind plant in terms of the shear profile, and near-ground temperature sensors provided a reasonable estimate of the ground heating rate describing the morning transition. A full aeroelastic simulation was then performed for a subset of turbines within the wind plant, driven by the precursor. Analysis of two turbines within the array, one directly waked by the other, demonstrated good agreement with measured time-averaged loads.

17 WIND ENERGY↗
NASA NTRS1978

Wind profiles for Space Shuttle loads analysis

The small scale wind velocity perturbations in vertical wind profiles at Cape Kennedy, Florida were analyzed in order to derive information for simulations of space shuttle ascent through the perturbed atmosphere. The available statistical data does not permit specification of various aspects of idealized singularities and wavelike perturbations with a reasonable degree of confidence. The information developed as a result of the analysis described in Section 3 of this report is suitable for the further development of idealized models. The term perturbation is used instead of the more common term, gust. According to the conventional approach, a gust profile is calculated by applying a high pass digital filter to a Jimsphere profile; all the speeds in the filtered profile are defined as gusts. The high pass filtered profile is defined as a residual profile and the maximum residual in the vicinity of a specified reference height is defined as the gust. Gusts defined in this manner represent the perturbation peaks. A detailed discussion of the calculation of residual profiles and gusts is given. The meteorological coordinate system, the data sample, and Jimsphere profiles are also described. Recommendations and conclusions are presented.

Adelfang, S. I.↗
NASA NTRS2023

Ames Contrail Simulation Model: Modeling Aviation Induced Contrails and the Computation of Contrail Radiative Forcing Using Air Traffic Data

NASA is developing traffic flow management strategies to reduce the impact of aviation on climate and improve efficiency of aircraft routes in the presence of limited airport and airspace capacity constraints, which are partly due to convective weather and natural calamities. Development of Strategic Traffic Flow Management (STFM) requires models of aircraft emissions and contrails, and models of their effect on climate. There is extensive literature on the modeling of contrails and the Radiative Forcing (RF) associated with contrails. This report captures the latest NASA developments in this research area and describes the integrated modeling, analysis, and software development to support STFM. Aircraft contrails are long, thin and often linear clouds triggered by aircraft engine exhausts in the high-altitude ice-saturated atmosphere. Contrails, similar to that of natural cirrus clouds, can impact global climate by reflecting shortwave radiation and trapping longwave radiation. Recent studies from the Intergovernmental Panel on Climate Change (IPCC) have shown that aircraft contrails are estimated to have greater impact on global warming than aircraft CO 2 emissions. The Ames Contrail Simulation Model (ACSM) presented in this report simulates the full life cycle of aircraft contrails, including their formation, dynamic evolution, and dissipation, and calculates the associated RF with actual meteorological and air traffic data. ACSM combines models from previous studies that focus on contrail formation and persistence based on the Schmidt-Appleman theoretical criteria, and it incorporates elements of cloud dynamics, microphysics, and climate modeling found in other surveyed contrail models, while also making adjustment for improved computational efficiency. In addition, ACSM is integrated with NASA's state-of-the-art flight simulation software for rapid assessment of aircraft contrail impacts. Applications include assessments of long-term global climate impact resulting from aviation-induced contrails and the design of optimal contrail-mitigation aircraft operation strategies.

aviation contrails↗
DOE OSTI2018

Anomalous cluster detection in spatiotemporal meteorological fields

Finding anomalous regions in spatiotemporal climate data is an important problem with a need for greater accuracy. The collective and contextual nature of anomalies (e.g., heat waves) coupled with the real‐valued, seasonal, multimodal, highly correlated, and gridded nature of climate variable observations poses a multitude of challenges. Existing anomaly detection methods have limitations in the specific setting of real‐valued areal spatiotemporal data. In this paper, we develop a method for extreme event detection in meteorological datasets that follows from well known distribution‐based anomaly detection approaches. The method models spatial and temporal correlations explicitly through a piecewise parametric assumption and generalizes the Mahalanobis distance across distributions of different dimensionalities. The result is an effective method to mine contiguous spatiotemporal anomalous regions from meteorological fields which improves upon the current standard approach in climatology. The proposed method has been evaluated on a real global surface temperature dataset and validated using historical records of extreme events.

Ramachandra, Bharathkumar↗
DOE OSTI2013

Probabilistic Hazard Assessment for Tornadoes, Straight-line Wind, and Extreme Precipitation at the Savannah River Site

Recent data sets for three meteorological phenomena with the potential to inflict damage on SRS facilities - tornadoes, straight winds, and heavy precipitation - are analyzed using appropriate statistical techniques to estimate occurrence probabilities for these events in the future. Summaries of the results for DOE-mandated return periods and comparisons to similar calculations performed in 1998 by Weber, et al., are given. Using tornado statistics for the states of Georgia and South Carolina, we calculated the probability per year of any location within a 2⁰ square area surrounding SRS being struck by a tornado (the ‘strike’ probability) and the probability that any point will experience winds above set thresholds. The strike probability was calculated to be 1.15E-3 (1 chance in 870) per year and wind speeds for DOE mandated return periods of 50,000 years, 125,000 years, and 1E+7 years (USDOE, 2012) were estimated to be 136 mph, 151 mph and 221 mph, respectively. In 1998 the strike probability for SRS was estimated to be 3.53 E-4 and the return period wind speeds were 148 mph every 50,000 years and 180 mph every 125,000 years. A 1E+7 year tornado wind speed was not calculated in 1998; however a 3E+6 year wind speed was 260 mph. The lower wind speeds resulting from this most recent analysis are largely due to new data since 1998, and to a lesser degree differences in the models used. By contrast, default tornado wind speeds taken from ANSI/ANS-2.3-2011 are somewhat higher: 161 mph for return periods of 50,000 years, 173 mph every 125,000 years, and 230 mph every 1E+7 years (ANS, 2011). Although the ANS model and the SRS models are very similar, the region defined in ANS 2.3 that encompasses the SRS also includes areas of the Great Plains and lower Midwest, regions with much higher occurrence frequencies of strong tornadoes. The SRS straight wind values associated with various return periods were calculated by fitting existing wind data to a Gumbel distribution, and extrapolating the values for any return period from the tail of that function. For the DOE mandated return periods, we expect straight winds of 123 mph every 2500 years, and 132mph every 6250 years at any point within the SRS. These values are similar to those from the W98 report (which also used the Gumbel distribution for wind speeds) which gave wind speeds of 115mph and 122 mph for return periods of 2500 years and 6250 years, respectively. For extreme precipitation accumulation periods, we compared the fits of three different theoretical extreme-value distributions, and in the end decided to maintain the use of the Gumbel distribution for each period. The DOE mandated 6-hr accumulated rainfall for return periods of 2500 years and 6250 years was estimated as 7.8 inches and 8.4 inches, respectively. For the 24-hr rainfall return periods of 10,000 years and 25,000 years, total rainfall estimates were 10.4 inches and 11.1 inches, respectively. These values are substantially lower than comparable values provided in the W98 report. This is largely a consequence of the W98 use of a different extreme value distribution with its corresponding higher extreme probabilities.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Space-based surface wind vectors to aid understanding of air-sea interactions

A novel and unique ocean-surface wind data-set has been derived by combining the Defense Meteorological Satellite Program Special Sensor Microwave Imager data with additional conventional data. The variational analysis used generates a gridded surface wind analysis that minimizes an objective function measuring the misfit of the analysis to the background, the data, and certain a priori constraints. In the present case, the European Center for Medium-Range Weather Forecasts surface-wind analysis is used as the background.

Atlas, R.↗
NASA NTRS2000

Sea Ice Motion from Wavelet Analysis of Satellite Data

Wavelet analysis of NASA scatterometer (NSCAT) backscatter and Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) radiance data can be used to obtain daily sea ice drift information for the Arctic region. This technique provides improved spatial coverage over the existing array of Arctic Ocean buoys and better temporal resolution over techniques utilizing data from satellite synthetic aperture radars. Comparisons with ice motion derived from ocean buoys give good quantitative agreement. Both comparison results from NSCAT and SSM/I are compatible, and the results from NSCAT can definitely complement that from SSM/I when there are cloud or surface effects. Then three sea-ice drift daily results from NSCAT, SSM/I, and buoy data can be merged as a composite map by some data fusion techniques. The ice flow streamlines are highly correlated with surface air pressure contours. Examples of derived ice-drift maps in December 1996 illustrate large-scale circulation reversals over a period of four days. A method for deriving divergence and shear at the large-scale has been developed and comparison between buoys and satellite results shows a good agreement. These calibrated/validated results indicate that NSCAT, SSM/I merged daily ice motion are suitably accurate to identify and closely locate sea ice processes, and to improve our current knowledge of sea ice drift and related processes through the data assimilation of ocean-ice numerical model. For demonstration purpose, the ice velocities derived from satellite data are compared with the ice velocities derived from a coupled ice-ocean interaction model. The comparison reveals that the general circulation patterns of the two are quite similar but the ice velocity differences between the two are quite significant. In order to quantify the wind effects on ice motion, empirical orthogonal functions (EOF) are used in the principal component analysis for both ice motion and pressure field. Some preliminary results of sea-ice motion from QuikScat will also be presented.

Liu, Antony K.↗