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Evaluation of Nearshore QuikSCAT 4.1 and ERA-5 Wind Stress and Wind Stress Curl Fields over Eastern Boundary Currents
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Mapping of ice layer extent and snow accumulation in the percolation zone of the Greenland ice sheet
The Greenland ice sheet underwent record extensive melt in 2002 and prolonged melt in 2003. The severe melting created a significant and extensive ice layer over the Greenland ice sheet. An innovative approach is developed to detect the ice layer formation using data acquired by the SeaWinds scatterometer on the QuikSCAT satellite. QuikSCAT backscatter together with in situ data from automatic weather stations of the Greenland Climate Network are used to map the extent of ice layer formation. The results reveal areas of extensive ice layer formed by the 2002 melt, which is consistent with the maximum melt extent in 2002. Moreover, during freezing seasons, QuikSCAT data show a linear decrease in backscatter (in decibels or dB) that is related to the amount of snow accumulation in the ice layer formation region. This snow accumulation signature is caused by the attenuation of radar waves in the snow layer, accumulating since the last major melt event, whose thickness appears as an exponential function in relation to the backscatter signature. We use the Greenland Climate Network data to calibrate the QuikSCAT accumulation rate in order to estimate and map snow accumulation. QuikSCAT results capture the extreme snowfall in mid-April 2003, which deposited more than 0.5 m of snow in a day as measured by the automated weather station at the NASA South East site. Large-scale QuikSCAT results show an anomalous increase of snow accumulation over the southeast region of Greenland during the 2002-2003 freezing season.
Combining New Satellite Tools and Models to Examine Role of Mesoscale Interactions in Formation and Intensification of Tropical Cyclones
The objective of this research is to start filling the mesoscale gap to improve understanding and probability forecasts of formation and intensity variations of tropical cyclones. Sampling by aircraft equipped to measure mesoscale processes is expensive, thus confined in place and time. Hence we turn to satellite products. This paper reports preliminary results of a tropical cyclone genesis and early intensification study. We explore the role of mesoscale processes using a combination of products from TRMM, QuikSCAT, AMSU, also SSM/I, geosynchronous and model output. Major emphasis is on the role of merging mesoscale vortices. These initially form in midlevel stratiform cloud. When they form in regions of lowered Rossby radius of deformation (strong background vorticity) the mesoscale vortices can last long enough to interact and merge, with the weaker vortex losing vorticity to the stronger, which can then extend down to the surface. In an earlier cyclongenesis case (Oliver 1993) off Australia, intense deep convection occurred when the stronger vortex reached the surface; this vortex became the storm center while the weaker vortex was sheared out as the major rainband. In our study of Atlantic tropical cyclones originating from African waves, we use QuikSCAT to examine surface winds in the African monsoon trough and in the vortices which move westward off the coast, which may or may not undergo genesis (defined by NHC as reaching TD, or tropical depression, with a west wind to the south of the surface low). We use AMSU mainly to examine development of warm cores. TRMM passive microwave TMI is used with SSM/I to look at the rain structure, which often indicates eye formation, and to look at the ice scattering signatures of deep convection. The TRMM precipitation radar, PR, when available, gives precipitation cross sections. So far we have detailed studies of two African-origin cyclones, one which became severe hurricane Floyd 1999, and the other reached TD2 in June 2000 and then died out. The atmosphere off West African is dry and stable. It becomes less so between June and September, as the SST and convection heat up. QuikSCAT shows the African monsoon trough and shear zone extend westward over the ocean to nearly 30 degrees West. The evidence is strong that the two cyclones had in common multiple midlevel mergers, which extended to the surface keeping the surface vortex strong. These continued until both systems were designated TD's by NHC. In the June 2000 case, the main reason for failure was the lower SST and dry, stable atmosphere. This is shown by the comparison of the equivalent potential temperature maps and profiles with those from pre-Floyd. In the vortex which became Floyd, QuikSCAT shows continuous importation of high theta e (warm, moist) air from the south. From September 2-8, this air flowed around the vortex center, building up a high theta-e pool to the north. Then late on September 9, a 100-km wide jet of high theta-e air penetrated the vortex core, a major convective burst' was observed, and an intensifying, more elevated warm core was seen on AMSU. Rapid pressure fall and wind intensification were underway by 0000 UTC on September 10. Floyd became a Hurricane at 1200 UTC on Sept 10, 1999, with successive convective bursts running the hurricane thermodynamic engine by intensifying the warm core. TD2 was a strong African vortex, sustained by moderate convection (up to about 12.5 km) offshore of Africa. It peaked on June 23, showing an apparent "eye" on passive microwave composites. However, it could not assemble the ingredients for a convective burst. Thus it failed to get the thermodynamic hurricane engine going before it moved too far west of the region of lowered Rossby radius. By June 26, cloud systems were dying out. On June 25, a surface vortex was no longer seen on QuikSCAT, although one continued above the surface on model profiles until June 27. One of our main findings so far is showing the role of the mesoscale vortex interactions in sustaining some African vortices far out in to the mid Atlantic, where under adequate thermal/moisture conditions the hurricane heat engine can sometimes be started. We are working on similar studies of Cindy and Irene 1999. Cindy illustrates a case of wind shear working against an early-stage hurricane heat engine, while Irene formed from a Caribbean wave. An enormous value of combinations of satellite tools is that tropical cyclones can be studied in all parts of the global oceans where they occur. Detailed studies like ours are labor intensive but many statistical studies can be based on physical postulates developed. There are other new tools such as MODIS on TERRA of the Earth Observing System (EOS) which can be used to study the microphysics of tropical cyclones world wide, in particular to investigate the presence of mixed phase and the impact of atmospheric aerosols on the hydrometeor structure and rainfall from tropical cyclones.
Impact of SeaWinds Scatterometer Data on Numerical Weather Prediction
Scatterometer observations of the ocean surface wind speed and direction improve the depiction and prediction of storms at sea. These data are especially valuable where observations are otherwise sparse - mostly in the Southern Hemisphere and tropics, but also on occasion in the North Atlantic and North Pacific. The SeaWinds scatterometer on the QuikScat satellite was launched in June 1999 and it represents a dramatic departure in design from the other scatterometer instruments launched during the past decade (ERS-1,2 and NSCAT). More details on the SeaWinds instrument can be found in Atlas et a1 (2001) and Bloom et al. (1999). At the time of this writing, SeaWinds scatterometer data from the ADEOS 2 satellite are not yet available . Therefore this paper will be limited to results from the SeaWinds scatterometer on Quikscat. This presentation shows the influence of QuikScat data in data assimilation systems both from the NASA Data Assimilation Office (GEOS-3) and from NCEP (GDAS).
Vibration and Acoustic Testing for Mars Micromission Spacecraft
The objective of the Mars Micromission program being managed by the Jet Propulsion Laboratory (JPL) for NASA is to develop a common spacecraft that can carry telecommunications equipment and a variety of science payloads for exploration of Mars. The spacecraft will be capable of carrying robot landers and rovers, cameras, probes, balloons, gliders or aircraft, and telecommunications equipment to Mars at much lower cost than recent NASA Mars missions. The lightweight spacecraft (about 220 Kg mass) will be launched in a cooperative venture with CNES as a TWIN auxiliary payload on the Ariane 5 launch vehicle. Two or more Mars Micromission launches are planned for each Mars launch opportunity, which occur every 26 months. The Mars launch window for the first mission is November 1, 2002 through April 2003, which is planned to be a Mars airplane technology demonstration mission to coincide with the 100 year anniversary of the Kittyhawk flight. Several subsequent launches will create a telecommunications network orbiting Mars, which will provide for continuous communication with lenders and rovers on the Martian surface. Dedicated science payload flights to Mars are slated to start in 2005. This new cheaper and faster approach to Mars exploration calls for innovative approaches to the qualification of the Mars Micromission spacecraft for the Ariane 5 launch vibration and acoustic environments. JPL has in recent years implemented new approaches to spacecraft testing that may be effectively applied to the Mars Micromission. These include 1) force limited vibration testing, 2) combined loads, vibration and modal testing, and 3) direct acoustic testing. JPL has performed nearly 200 force limited vibration tests in the past 9 years; several of the tests were on spacecraft and large instruments, including the Cassini and Deep Space One spacecraft. Force limiting, which measures and limits the spacecraft base reaction force using triaxial force gages sandwiched between the spacecraft and the test fixture, alleviates the severe overtest at spacecraft resonances inherent in rigid fixture vibration tests. It has the distinct advantage over response limiting that the method is not dependent on the accuracy of a detailed dynamic model of the spacecraft. Combined loads, vibration, and modal testing were recently performed on the QuikSCAT spacecraft. The combined tests were performed in a single test setup per axis on a vibration shaker, reducing test time by a factor of two or three. Force gages were employed to measure the true c.g. acceleration of the spacecraft for structural loads verification using a sine burst test, to automatically notch random vibration test input accelerations at spacecraft resonances based on predetermined force limits, and to directly measure modal masses in a base drive modal test. In addition to these combined tests on the shaker, the QuikSCAT spacecraft was subjected to a direct field acoustic test by surrounding the spacecraft, still on the vibration shaker, with rock concert type acoustic speakers. Since the spacecraft contractor does not have a reverberant field acoustic test facility, performing a direct field acoustic test -saved the program nearly two weeks schedule time that would have been required for packing / unpacking and shipping of the spacecraft. This paper discusses the rationale behind and advantages of the above test approaches and provides examples of their actual implementation and comparisons to flight data. The applicability of the test approaches to Mars Micromission spacecraft qualification is discussed.
Analysis and Forecast of Two Storms Characterized by Extreme Deepening Rates
Between 25 and 27 December 1999 two very intense cyclones, named Lothar and Martin, swept across northern and western France causing substantial life and property loss. In this work, the finite volume general circulation model and data assimilation system (fvDAS) developed at the Data Assimilation Office of the NASA Goddard Space and Flight Center is being used to investigate these storms. In the first part of this article the dynamics of the storms is analyzed, and some important mechanisms are unveiled. The second part describes a set of eleven data assimilation experiments to study the impact of different data types on the automated analyses. Cloud-track winds provided by EUMETSAT and surface winds from QuikSCAT are being used. These data are assimilated with a range of different parameter settings of the forecast error covariance model. The results show that generally the additional wind data set have positive impacts on the analyses: particularly, the analysis of Lothar can be slightly improved by using the Eumetsat winds, and the analysis of Martin can be strongly improved by using the full-resolution QuikSCAT winds with a more localized influence. The third part of this article is focused on the forecast of Lothar which is very well predicted in the 1-5 day range by the fvDAS system.
Applications of Sea-Ice Motion and Deformation Derived from Satellite Data
QuikSCAT backscatter, AMSR and DMSP SSM/I radiance data have been used to derive sea ice motion for both the Arctic and Antarctic region using the wavelet analysis tracking method. All results from QuikSCAT, AMSR and SSM5 are compatible with buoys and can then be merged by data fusion method to generate composite sea ice motion maps for more complete coverage. Furthermore, based on this merged data set daily sea-ice deformation (shear, and convergence) maps have been produced and show consistent spatial and temporal patterns. Temporal correlation maps between ice deformation and SSM/II ice concentration show interesting results in the Arctic, especially the coast area. In this study, principal component analysis for both the merged ice tracking result from satellite data and pressure field from buoy have also been examined for the relationship between the principal components and eigenvectors from these two data sets. While the result shows that principal components of modes 1 and 2 from two data sets are highly correlated which confirms that wind forcing is a major factor driving the ice drift, it also reveals that other high energy modes are not highly correlated which maybe caused by coastal effects. Principal component analysis of Arctic sea-ice motion during fall/winter period in different years shows the reverse of dominant modes or patterns is related to the Arctic Oscillation.
Multisensor Fire Observations
This DVD includes animations of multisensor fire observations from the following satellite sources: Landsat, GOES, TOMS, Terra, QuikSCAT, and TRMM. Some of the animations are included in multiple versions of a short video presentation on the DVD which focuses on the Hayman, Rodeo-Chediski, and Biscuit fires during the 2002 North American fire season. In one version of the presentation, MODIS, TRMM, GOES, and QuikSCAT data are incorporated into the animations of these wildfires. These data products provided rain, wind, cloud, and aerosol data on the fires, and monitored the smoke and destruction created by them. Another presentation on the DVD consists of a panel discussion, in which experts from academia, NASA, and the U.S. Forest Service answer questions on the role of NASA in fighting forest fires, the role of the Terra satellite and its instruments, including the Moderate Resolution Imaging Spectroradiometer (MODIS), in fire fighting decision making, and the role of fire in the Earth's climate. The third section of the DVD features several animations of fires over the years 2001-2003, including animations of global and North American fires, and specific fires from 2003 in California, Washington, Montana, and Arizona.
Annual Cycles of Multiyear Sea Ice Coverage of the Arctic Ocean: 1999-2003
For the years 1999-2003, we estimate the time-varying perennial ice zone (PIZ) coverage and construct the annual cycles of multiyear (MY, including second year) ice coverage of the Arctic Ocean using QuikSCAT backscatter, MY fractions from RADARSAT, and the record of ice export from satellite passive microwave observations. An area balance approach extends the winter MY coverage from QuikSCAT to the remainder of the year. From these estimates, the coverage of MY ice at the beginning of each year is 3774 x 10(exp 3) sq km (2000), 3896 x 10(exp 3) sq km (2001), 4475 x 10(exp 3) sq km (2002), and 4122 x 10(exp 3) sq km (2003). Uncertainties in coverage are approx.150 x 10(exp 3) sq km. In the mean, on 1 January, MY ice covers approx.60% of the Arctic Ocean. Ice export reduces this coverage to approx.55% by 1 May. From the multiple annual cycles, the area of first-year (FY) ice that survives the intervening summers are 1192 x 10(exp 3) sq km (2000), 1509 x 10(exp 3) sq km (2001), and 582 x 10(exp 3) sq km (2002). In order for the MY coverage to remain constant from year to year, these replenishment areas must balance the overall area export and melt during the summer. The effect of the record minimum in Arctic sea ice area during the summer of 2002 is seen in the lowest area of surviving FY ice of the three summers. In addition to the spatial coverage, the location of the PIZ is important. One consequence of the unusual location of the PIZ at the end of the summer of 2002 is the preconditioning for enhanced export of MY ice into the Barents and Kara seas. Differences between the minimums in summer sea ice coverage from our estimates and passive microwave observations are discussed.
Hurricane Data Analysis Tool
In order to facilitate Earth science data access, the NASA Goddard Earth Sciences Data Information Services Center (GES DISC) has developed a web prototype, the Hurricane Data Analysis Tool (HDAT; URL: http://disc.gsfc.nasa.gov/HDAT), to allow users to conduct online visualization and analysis of several remote sensing and model datasets for educational activities and studies of tropical cyclones and other weather phenomena. With a web browser and few mouse clicks, users can have a full access to terabytes of data and generate 2-D or time-series plots and animation without downloading any software and data. HDAT includes data from the NASA Tropical Rainfall Measuring Mission (TRMM), the NASA Quick Scatterometer(QuikSCAT) and NECP Reanalysis, and the NCEP/CPC half-hourly, 4-km Global (60 N - 60 S) IR Dataset. The GES DISC archives TRMM data. The daily global rainfall product derived from the 3-hourly multi-satellite precipitation product (3B42 V6) is available in HDAT. The TRMM Microwave Imager (TMI) sea surface temperature from the Remote Sensing Systems is in HDAT as well. The NASA QuikSCAT ocean surface wind and the NCEP Reanalysis provide ocean surface and atmospheric conditions, respectively. The global merged IR product, also known as, the NCEP/CPC half-hourly, 4-km Global (60 N -60 S) IR Dataset, is one of TRMM ancillary datasets. They are globally-merged pixel-resolution IR brightness temperature data (equivalent blackbody temperatures), merged from all available geostationary satellites (GOES-8/10, METEOSAT-7/5 & GMS). The GES DISC has collected over 10 years of the data beginning from February of 2000. This high temporal resolution (every 30 minutes) dataset not only provides additional background information to TRMM and other satellite missions, but also allows observing a wide range of meteorological phenomena from space, such as, hurricanes, typhoons, tropical cyclones, mesoscale convection system, etc. Basic functions include selection of area of interest and time, single imagery, overlay of two different products, animation,a time skip capability and different image size outputs. Users can save an animation as a file (animated gif) and import it in other presentation software, such as, Microsoft PowerPoint. Since the tool can directly access the real data, more features and functionality can be added in the future.
Diurnal Variations of Melt Regions on the Greenland Ice Sheet
Melt regions on Greenland ice are mapped daily with the SeaWinds wideswath Ku-band scatterometer on the QuikSCAT satellite.
Anomalous snow accumulation over the southeast region of the Greenland ice sheet during 2002-2003 snow season
Our objective is to determine seasonal snow accumulation in the percolation zone of the Greenland ice sheet on the daily-weekly basis over the large scale. Our approach utilizes data from the Greenland Climate Network (GC-Net) and from the SeaWinds Scatterometer on the QuikSCAT satellite (QSCAT) to measure snow accumulation (SA) in the percolation zone of the Greenland ice sheet. GC-Net measurements provide crucial in-situ data to facilitate the interpretation of QSCAT backscatter signature for the development of an algorithm to map SA.
A Probabilistic Technique for Improving the Mid-Swath Wind Direction Accuracy of Scanning Pencil Beam Scatterometers
The SeaWinds on QuikSCAT scatterometer is a device developed by NASA JPL to measure the speed adn direction of ocean surface winds.