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We describe our efforts in studying and comparing the ocean color data derived from the Japanese Ocean Color and Temperature Scanner (OCTS) and the French Polarization and Directionality of the Earth's Reflectances (POLDER). OCTS and POLDER were both on board Japan's Sun-synchronous Advanced Earth Observing Satellite (ADEOS-1) from August 1996 to June 1997, collecting about 10 months of global ocean color data. This provides a unique opportunity for developing methods and strategies for the merging of ocean color data from multiple ocean color sensors. In this paper, we describe our approach in developing consistent data processing algorithms for both OCTS and POLDER and using a common in situ data set to vicariously calibrate the two sensors. Therefore, the OCTS and POLDER-measured radiances are effectively bridged through common in situ measurements. With this approach in processing data from two different sensors, the only differences in the derived products from OCTS and POLDER are the differences inherited from the instrument characteristics. Results show that there are no obvious bias differences between the OCTS and POLDER-derived ocean color products, whereas the differences due to noise, which stem from variations in sensor characteristics, are difficult to correct. It is possible, however, to reduce noise differences with some data averaging schemes. The ocean color data from OCTS and POLDER can therefore be compared and merged in the sense that there is no significant bias between two.

This document addresses the software requirements of the Geoscience Laser Altimeter System (GLAS) Standard Data Software (SDS) supporting the GLAS instrument on the EOS ICESat Spacecraft. This Software Requirements Document represents the initial collection of the technical engineering information for the GLAS SDS. This information is detailed within the second of four main volumes of the Standard documentation, the Product Specification volume. This document is a "roll-out" from the governing volume outline containing the Concept and Requirements sections.

A new method for analyzing nonlinear and nonstationary data has been developed. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum. Classical nonlinear system models are used to illustrate the roles played by the nonlinear and nonstationary effects in the energy-frequency-time distribution.

QuikSCAT backscatter and DMSP SSM/I radiance data are used to derive sea ice motion for both the Arctic and Antarctic region using wavelet analysis method. This technique provides improved spatial coverage over the existing array of Arctic Ocean buoys and better temporal resolution over techniques utilizing satellite data from Synthetic Aperture Radar (SAR). Sea ice motion of the Arctic for the period from October 1999 to March 2000 derived from QuikSCAT and SSM/I data agrees well with that derived from ocean buoys quantitatively. Thus the ice tracking results from QuikSCAT and SSM/I are complement to each other, Then, three sea-ice drift daily results from QuikSCAT, SSM/I, and buoy data can be merged to generate composite maps with more complete coverage of sea ice motion than those from single data source. A series of composite sea ice motion maps for December 1999 show that the major circulation patterns of sea ice motion are changing and shifting significantly within every four days and they are dominated by wind forcing. Sea-ice drift in the summer can not be derived from NSCAT and SSM/I data. In later summer of 1999 (in September), however, QuikSCAT data can provide good sea ice motion information in the Arctic. QuiksCAT can also provide at least partial sea ice motion information until June 15 in early summer 1999. For the Antarctic, case study shows that sea ice motion derived from QuikSCAT data is predominantly forced by and is consistent with wind field derived from QuikSCAT around the polar region. These calibrated/validated results indicate that QuikSCAT, SSM/I, and buoy 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.

Much of NASA's Arctic Research is run through its Cryospheric Sciences Program. Arctic research efforts to date have focused primarily on investigations of the mass balance of the largest Arctic land-ice masses and the mechanisms that control it, interactions among sea ice, polar oceans, and the polar atmosphere, atmospheric processes in the polar regions, energy exchanges in the Arctic. All of these efforts have been focused on characterizing, understanding, and predicting, changes in the Arctic. NASA's unique vantage from space provides an important perspective for the study of these large scale processes, while detailed process information is obtained through targeted in situ field and airborne campaigns and models. An overview of NASA investigations in the Arctic will be presented demonstrating how the synthesis of space-based technology, and these complementary components have advanced our understanding of physical processes in the Arctic.

A major uncertainty in predicting sea level rise is the sensitivity of ice sheet mass balance to climate change, as well as the uncertainty in present mass balance. Since the annual water exchange is about 8 mm of global sea level equivalent, the 20% uncertainty in current mass balance corresponds to 1.6 mm/yr in sea level change. Furthermore, estimates of the sensitivity of the mass balance to temperature change range from perhaps as much as - 10% to + 10% per K. A principal purpose of obtaining ice sheet elevation changes from satellite altimetry has been estimation of the current ice sheet mass balance. Limited information on ice sheet elevation change and their implications about mass balance have been reported by several investigators from radar altimetry (Seasat, Geosat, ERS-1&2). Analysis of ERS-1&2 data over Greenland for 7 years from 1992 to 1999 shows mixed patterns of ice elevation increases and decreases that are significant in terms of regional-scale mass balances. Observed seasonal and interannual variations in ice surface elevation are larger than previously expected because of seasonal and interannUal variations in precipitation, melting, and firn compaction. In the accumulation zone, the variations in firn compaction are modeled as a function of temperature leaving variations in precipitation and the mass balance trend. Significant interannual variations in elevation in some locations, in particular the difference in trends from 1992 to 1995 compared to 1995 to 1999, can be explained by changes in precipitation over Greenland. Over the 7 years, trends in elevation are mostly positive at higher elevations and negative at lower elevations. In addition, trends for the winter seasons (from a trend analysis through the average winter elevations) are more positive than the corresponding trends for the summer. At lower elevations, the 7-year trends in some locations are strongly negative for summer and near zero or slightly positive for winter. These observations also demonstrate the potential for relating the variability in mass balance to changes in precipitation, temperature, and melting. Beginning in January 2002, NASA's ICESat laser altimeter mission will provide significantly better elevation accuracy and spatial coverage to 86E latitude and to the margins of the ice sheets.

The spatial and temporal variability of sea ice concentrations derived from passive microwave data is studied in conjunction with co-registered high resolution infrared and visible satellite data. Cloud free infrared and visible data provide surface temperature and large scale surface characteristics, respectively, that can be used to better understand regional and seasonal fluctuations in ice concentrations. Results from correlation analysis of ice concentration versus surface temperature data show the intuitively expected negative relationship but the strength in the relationship is unexpectedly very strong. In the Antarctic, the correlation is consistently very high spatially when yearly anomalies are used, and not so high in some areas when seasonal anomalies are used, especially during spring and summer. In the monthly anomalies, the correlation is also good, especially in dynamically active regions. The expanse in the anomalies in surface temperature are shown to go way beyond the sea ice regions into the open ocean and continental areas, suggesting strong atmospheric forcing. Weak correlations are normally found in highly consolidated areas, where large changes in temperature do not cause large changes in ice concentration on a short term, and in open ocean polynya areas, where the change in ice concentration may be cause by melt from the underside of the ice. In the Arctic, strong correlations between surface temperature and ice concentration are evident for all seasons except during the summer. In the summer, factors such as meltponding, surface wetness, and ice breakup, as detected by high resolution visible data, contributes to larger uncertainties in the determination of ice concentration and the lack of good correlation of the variables.

A new method, the Hilbert-Huang Transform, has been developed for analyzing nonlinear and nonstationary data. The key part of the method is the Empirical Mode Decomposition with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An M is defined as any function having the same numbers of zero-crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies'as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum. With this technique we can examine the detailed dynamics characteristics of a nonlinear system through the instantaneous frequency rather than harmonics. Thus it constitutes a new view of the nonlinear dynamics. Examples of classic nonlinear equations and other nonlinear and nonstationary data sets will be used as examples to illustrate the advantage of the application of this new data analysis method.

Analysis of a fifty-year record (1946-1995) of monthly-averaged sea level pressure data provides a link between the phases of planetary-scale sea level pressure waves and Arctic Ocean and ice variability. Results of this analysis show: (1) a breakdown of the dominant wave 1 pattern in the late 1960's, (2) shifts in the mean phase of waves 1 and 2 since this breakdown, (3) an eastward shift in the phases of both waves 1 and 2 during the years of simulated cyclonic Arctic Ocean circulation relative to their phases during the years of anticyclonic circulation, (4) a strong decadal variability of wave phase associated with simulated Arctic Ocean circulation changes. Finally, the Arctic atmospheric circulation patterns that emerge when waves 1 and 2 are in their extreme eastern and western positions suggest an alternative approach for determining significant forcing patterns of sea ice and high-latitude variability.

On 26 August 1998, the SRA at 2.2 km height documented the directional wave spectrum in the region between Charleston, SC, and Cape Hatteras, NC, as Hurricane Bonnie was making landfall near Wilmington, NC. The storm was similar in size during the two flights, but the maximum speed in the NOAA Hurricane Research Division surface wind analysis was 15% lower prior to landfall (39 m/s) than it had been in the open ocean (46 m/s). This was compensated for by its faster movement prior to landfall (9.5 m/s) than when it was encountered in the open ocean (5 m/s), significantly increasing the effective fetch and duration of waves near the peak of the spectrum which propagated in the direction of the storm track. The open ocean wave height variation indicated that Hurricane Bonnie would have produced waves of 11 m significant wave height on the shore northeast of Wilmington had it not been for the continental shelf. The bathymetry distributed the steepening and breaking process across the shelf so that the wavelength and wave height were reduced gradually as the shore was approached. The wave height 5 km from shore was about 4 in.

The MODIS (Moderate Resolution Imaging Spectroradiometer) sensor on the NASA EOS (Earth Observing System) Terra spacecraft has completed more than one year of on-orbit operation since the instrument opened its Nadir door for the scene data collection on 24 February 2000. Its 20 reflective solar bands, from VIS (visible) to SWIR (shortwavelength infrared) (0.41 to 2.1 micron), are calibrated on-orbit by a solar diffuser (SD) and a solar diffuser stability monitor (SDSM). Degradation in the reflective solar bands has been observed in the reflectance of the on board solar diffuser and for the MODIS optics. Variations in degradation of up to 3% are evident between the two sides of the MODIS scan mirror. Degradation of the SD is tracked with the solar diffuser stability monitor, and degradation of the entire MODIS system is tracked by SD observations, adjusted for SD changes. Overall degradation at the shortest wavelengths (near 400 nm) are up to 3% for SD, and in excess of 10% for the MODIS system. Degradation of the SD and full MODIS system for the sensor's reflective solar bands will be described in this report.

We are midway into our 5th consecutive year of nearly continuous, high quality ocean color observations from space. The Ocean Color and Temperature Scanner/Polarization and Directionality of the Earth's Reflectances (OCTS/POLDER: Nov. 1996 - Jun. 1997), the Sea-viewing Wide Field-of-view Sensor (SeaWiFS: Sep. 1997 - present), and now the Moderate Resolution Imaging Spectrometer (MODIS: Sep. 2000 - present) have and are providing unprecedented views of chlorophyll dynamics on global scales. Global synoptic views of ocean chlorophyll were once a fantasy for ocean color scientists. It took nearly the entire 8-year lifetime of limited Coastal Zone Color Scanner (CZCS) observations to compile seasonal climatologies. Now SeaWIFS produces comparably complete fields in about 8 days. For the first time, scientists may observe spatial and temporal variability never before seen in a synoptic context. Even more exciting, we are beginning to plausibly ask questions of interannual variability. We stand at the beginning of long-time time series of ocean color, from which we may begin to ask questions of interdecadal variability and climate change. These are the scientific questions being addressed by users of the 18-year Advanced Very High Resolution Radiometer time series with respect to terrestrial processes and ocean temperatures. The nearly 5-year time series of ocean color observations now being constructed, with possibilities of continued observations, can put us at comparable standing with our terrestrial and physical oceanographic colleagues, and enable us to understand how ocean biological processes contribute to, and are affected by global climate change.

Satellite passive-microwave data have been used to calculate sea ice extents over the period 1979-1999 for the north polar sea ice cover as a whole and for each of nine regions. Over this 21-year time period, the trend in yearly average ice extents for the ice cover as a whole is -32,900 +/- 6,100 sq km/yr (-2.7 +/- 0.5 %/decade), indicating a reduction in sea ice coverage that has decelerated from the earlier reported value of -34,000 +/- 8,300 sq km/yr (-2.8 +/- 0.7 %/decade) for the period 1979-1996. Regionally, the reductions are greatest in the Arctic Ocean, the Kara and Barents Seas, and the Seas of Okhotsk and Japan, whereas seasonally, the reductions are greatest in summer, for which season the 1979-1999 trend in ice extents is -41,600 +/- 12,900 sq km/ yr (-4.9 +/- 1.5 %/decade). On a monthly basis, the reductions are greatest in July and September for the north polar ice cover as a whole, in September for the Arctic Ocean, in June and July for the Kara and Barents Seas, and in April for the Seas of Okhotsk and Japan. Only two of the nine regions show overall ice extent increases, those being the Bering Sea and the Gulf of St. Lawrence.For neither of these two regions is the increase statistically significant, whereas the 1079 - 1999 ice extent decreases are statistically significant at the 99% confidence level for the north polar region as a whole, the Arctic Ocean, the Seas of Okhotsk and Japan, and Hudson Bay.

Ozonesonde measurements of the polar atmosphere obtained at Andenes, Norway during July 1999 showed unusual characteristics when compared with mid- or low-latitude ozone profiles. A minimum of two ozonesondes each day were released, one in late afternoon and one in early evening. A very well-defined ledge in the ozone profile corresponding to the tropopause appears to form as a result of transport. The ozone amount increases four to five times, from about 30 nb at the tropopause to 120 nb at a pressure about 10-20 hPa lower. The typical peak ozone value, although at a higher altitude than the ledge, appears at a much lower pressure (approx. 140 hPa) than found in midor low-latitudes (approx. 18-25 hPa), Total column ozone amounts are consistently higher than 300 DU. Analysis of the variation with regard to wind conditions will be discussed.

The morphological difference between the electromagnetic radiation-field waveforms of "first" and "subsequent" return strokes in cloud-to-ground lightning flashes is well known and can be used to identify the formation of new channels to ground. This difference is generally believed due to the existence of branches on first-stroke channels, whereas subsequent strokes re-illuminate only the main channel of a previous stroke; but experimental evidence for this hypothesis is relatively weak. It has been argued for the influence of channel geometry on the fine structure of radiation from subsequent return strokes by comparing the field-change waveforms recorded at the same station from strokes within the same flash and between different flashes of both natural and triggered lightning. The present paper introduces new evidence for both of these hypotheses from a comparison of waveforms between sensors in different directions from the same stroke.

During the Southern Great Plains experiment, the synthetic aperture radiometer, ESTAR, mapped L-band brightness temperature over a swath about 50 km wide and about 300 km long extending west from Oklahoma City to El Reno and north from the Little Washita River watershed to the Kansas border. ESTAR flew on the NASA P-3B Orion aircraft at an altitude of 7.6 km and maps were made on 7 days between July 8-20, 1999. The brightness temperature maps reflect the patterns of soil moisture expected from rainfall and are consistent with values of soil moisture observed at the research sites within the SGP99 study area and with previous measurements in this area. The data add to the resources for hydrologic modeling in this area and are further validation of the technology represented by ESTAR as a potential path to a future mission to map soil moisture globally from space.

The sea surface directional wave spectrum was measured for the first time in all quadrants of a hurricane in open water using the NASA scanning radar altimeter (SRA) carried aboard one of the NOAA WP-3D hurricane research aircraft at 1.5 kilometer height. The SRA measures the energetic portion of the directional wave spectrum by generating a topographic map of the sea surface. The data were acquired on 24 August 1998 when Hurricane Bonnie was 400 km east of Abaco Island, Bahamas. Individual waves with heights up to 19 meters were observed and the spatial variation of the wave field was dramatic. The dominant waves generally propagated at significant angles to the downwind direction. At one position, three different wave systems of comparable energy and wavelength crossed each other. The aircraft spent over five hours within 180 kilometers of the Hurricane Bonnie eye and made five eye penetrations. On 26 August 1998, the SRA at 2.2 kilometer height documented the directional wave spectrum in the region between Charleston, SC, and Cape Hatteras, NC, as Hurricane Bonnie was making landfall near Wilmington, NC. The storm was similar in size during the two flights, but the maximum speed in the NOAA Hurricane Research Division surface wind analysis was 15% lower prior to landfall (39 meters per second) than it had been in the open ocean (46 meters per second). This was compensated for by its faster movement prior to landfall (9.5 meters per second) than when it was encountered in the open ocean (5 meters per second), significantly increasing the effective fetch and duration of waves near the peak of the spectrum which propagated in the direction of the storm track. The open ocean wave height variation indicated that Hurricane Bonnie would have produced waves of 11 meters significant wave height on the shore northeast of Wilmington had it not been for the continental shelf. The bathymetry distributed the steepening and breaking process across the shelf so that the wavelength and wave height were reduced gradually as the shore was approached. The wave height 5 kilometers from shore was about 4 meters.

The Terra MODIS (Moderate Resolution Imaging Spectroradiometer) was launched on December 18, 1999 and acquired the first scene data on February 24, 2000. It has 36 spectral bands covering spectral range from 0.41 to 14.2 microns and provides spatial resolutions of 250 (2 bands), 500 (5 bands), and 1000 m at Nadir. The instrument on-orbit calibration and characterization are determined and monitored through the use of a number of on-board calibrators (OBC). Radiometric calibration for the reflective solar bands (B1-B19, B26), from VIS (visible) to SWIR (short wavelength infrared) (0.41 to 2.1 microns), uses a Spectralon (tm) solar diffuser (SD) and a solar diffuser stability monitor (SDSM). For the thermal emissive bands (B20-B25, B27-B36), from MWIR (medium wavelength infrared) to LWIR (long wavelength infrared) (3.75 to 14.2 micron), a V-grooved flat panel blackbody is used. The instrument spectral for the VIS to SWIR bands and spatial co-registration characterizations for all bands are monitored on-orbit by the spectral radiometric calibration assembly (SRCA). In this report, we discuss the application and performance of the key MODIS on-board calibrators and their impacts on the instrument system calibration and characterization.

A methodology for retrieving surface soil moisture and vegetation optical depth from satellite microwave radiometer data is presented. The procedure is tested with historical 6.6 GHz brightness temperature observations from the Scanning Multichannel Microwave Radiometer over several test sites in Illinois. Results using only nighttime data are presented at this time, due to the greater stability of nighttime surface temperature estimation. The methodology uses a radiative transfer model to solve for surface soil moisture and vegetation optical depth simultaneously using a non-linear iterative optimization procedure. It assumes known constant values for the scattering albedo and roughness. Surface temperature is derived by a procedure using high frequency vertically polarized brightness temperatures. The methodology does not require any field observations of soil moisture or canopy biophysical properties for calibration purposes and is totally independent of wavelength. Results compare well with field observations of soil moisture and satellite-derived vegetation index data from optical sensors.

Satellite data can be used to observe the sea ice distribution around the continent of Antarctica on a daily basis and hence to determine how many days a year have sea ice at each location. This has been done for each of the 21 years 1979-1999. Mapping the trends in these data over the 21-year period reveals a detailed pattern of changes in the length of the sea ice season around Antarctica. Most of the Ross Sea ice cover has undergone a lengthening of the sea ice season, whereas most of the Amundsen Sea ice cover and almost the entire Bellingshausen Sea ice cover have undergone a shortening of the sea ice season. Results around the rest of the continent, including in the Weddell Sea, are more mixed, but overall, more of the Southern Ocean experienced a lengthening of the sea ice season than a shortening. For instance, the area experiencing a lengthening of the sea ice season by at least 1 day per year is 5.8 x 10(exp 6) sq km, whereas the area experiencing a shortening of the sea ice season by at least 1 day per year is less than half that, at 2.8 x 10(exp 6) sq km. This contrasts sharply with what is happened over the same period in the Arctic, where, overall, there has been some depletion of the ice cover, including shortened sea ice seasons and decreased ice extents.

Satellite passive-microwave measurements of sea ice have provided global or near-global sea ice data for most of the period since the launch of the Nimbus 5 satellite in December 1972, and have done so with horizontal resolutions on the order of 25-50 km and a frequency of every few days. These data have been used to calculate sea ice concentrations (percent areal coverages), sea ice extents, the length of the sea ice season, sea ice temperatures, and sea ice velocities, and to determine the timing of the seasonal onset of melt as well as aspects of the ice-type composition of the sea ice cover. In each case, the calculations are based on the microwave emission characteristics of sea ice and the important contrasts between the microwave emissions of sea ice and those of the surrounding liquid-water medium.

Large changes in the sea ice cover have been observed recently. Because of the relevance of such changes to climate change studies it is important that key ice concentration data sets used for evaluating such changes are interpreted properly. High and medium resolution visible and infrared satellite data are used in conjunction with passive microwave data to study the true characteristics of the Antarctic sea ice cover, assess errors in currently available ice concentration products, and evaluate the applications and limitations of the latter in polar process studies. Cloud-free high resolution data provide valuable information about the natural distribution, stage of formation, and composition of the ice cover that enables interpretation of the large spatial and temporal variability of the microwave emissivity of Antarctic sea ice. Comparative analyses of co-registered visible, infrared and microwave data were used to evaluate ice concentrations derived from standard ice algorithms (i.e., Bootstrap and Team) and investigate the 10 to 35% difference in derived values from large areas within the ice pack, especially in the Weddell Sea, Amundsen Sea, and Ross Sea regions. Landsat and OLS data show a predominance of thick consolidated ice in these areas and show good agreement with the Bootstrap Algorithm. While direct measurements were not possible, the lower values from the Team Algorithm results are likely due to layering within the ice and snow and/or surface flooding, which are known to affect the polarization ratio. In predominantly new ice regions, the derived ice concentration from passive microwave data is usually lower than the true percentage because the emissivity of new ice changes with age and thickness and is lower than that of thick ice. However, the product provides a more realistic characterization of the sea ice cover, and are more useful in polar process studies since it allows for the identification of areas of significant divergence and polynya activities. Also, heat and salinity fluxes are proportionately increased in these areas compared to those from the thicker ice areas. A slight positive trend in ice extent and area from 1978 through 2000 is observed consistent with slight continental cooling during the period. However, the confidence in this result is only moderate because the overlap period for key instruments is just one month and the sensitivity to changes in sensor characteristics, calibration and threshold for the ice edge is quite high.

Measurements of the neutral atmosphere and their relationship to electrodynamic conditions in the mesosphere have been of interest for many years. Inflatable falling sphere measurements along with electrodynamic measurements were obtained in conjunction with the occurrence of PMSE and NLC during the DROPPS/MIDAS Campaign conducted in July 1999 from Andenes Rocket Range, Norway. The inflatable failing sphere measurements in conjunction with a PMSE event on 5-6 July and with a NLC event on 14 July are used to infer thermal advection and its influence on the clouds' maintenance. Hodograph analysis, an early tropospheric tool used by analyst and forecasters, will be used to determine the magnitude and direction of thermal advection from measured wind data. Analysis of the wind structure through the use of hodographs and some assumptions can determine thermal advection, wind shear, and possible vertical motion. Changes in the temperature structure between allied observations were subtle which may be explained by advection. Because of meteorological instabilities in the mesosphere it is possible that hodograph analysis may not fully work. It is our intention to show that such analysis has value and has a place in the mesosphere.

Clouds interfere with the distribution of short-wave and long-wave radiations over sea ice, and thereby strongly affect the surface energy balance in polar regions. To evaluate the overall effects of clouds on climatic feedback processes in the atmosphere-ice-ocean system, the challenge is to observe sea ice surface thermal states under both clear sky and cloudy conditions. From laboratory experiments, we show that C-band radar (transparent to clouds) backscatter is very sensitive to the surface temperature of first-year sea ice. The effect of sea ice surface temperature on the magnitude of backscatter change depends on the thermal regimes of sea ice thermodynamic states. For the temperature range above the mirabilite (Na2SO4.10H20) crystallization point (-8.2 C), C-band data show sea ice backscatter changes by 8-10 dB for incident angles from 20 to 35 deg at both horizontal and vertical polarizations. For temperatures below the mirabilite point but above the crystallization point of MgCl2.8H2O (-18.0 C), relatively strong backwater changes between 4-6 dB are observed. These backscatter changes correspond to approximately 8 C change in temperature for both cases. The backscattering mechanism is related to the temperature which determines the thermodynamic distribution of brine volume in the sea ice surface layer. The backscatter is positively correlated to temperature and the process is reversible with thermodynamic variations such as diurnal insolation effects. From two different dates in May 1993 with clear and overcast conditions determined by the Advanced Very High Resolution Radiometer (AVHRR), concurrent Earth Resources Satellite 1 (ERS-1) C-band ice observed with increases in backscatter over first-year sea ice, and verified by increases in in-situ sea ice surface temperatures measured at the Collaborative-Interdisciplinary Cryosphere Experiment (C-ICE) site.

The microphysical parameterization of clouds and rain-cells plays a central role in atmospheric forward radiative transfer models used in calculating passive microwave brightness temperatures. The absorption and scattering properties of a hydrometeor-laden atmosphere are governed by particle phase, size distribution, aggregate density., shape, and dielectric constant. This study identifies the sensitivity of brightness temperatures with respect to the microphysical cloud parameterization. Cloud parameterizations for wideband (6-410 GHz observations of baseline brightness temperatures were studied for four evolutionary stages of an oceanic convective storm using a five-phase hydrometeor model in a planar-stratified scattering-based radiative transfer model. Five other microphysical cloud parameterizations were compared to the baseline calculations to evaluate brightness temperature sensitivity to gross changes in the hydrometeor size distributions and the ice-air-water ratios in the frozen or partly frozen phase. The comparison shows that, enlarging the rain drop size or adding water to the partly Frozen hydrometeor mix warms brightness temperatures by up to .55 K at 6 GHz. The cooling signature caused by ice scattering intensifies with increasing ice concentrations and at higher frequencies. An additional comparison to measured Convection and Moisture LA Experiment (CAMEX 3) brightness temperatures shows that in general all but, two parameterizations produce calculated T(sub B)'s that fall within the observed clear-air minima and maxima. The exceptions are for parameterizations that, enhance the scattering characteristics of frozen hydrometeors.

Water balance considerations at the soil surface lead to an equation that relates the autocorrelation of soil moisture in climate models to (1) seasonality in the statistics of the atmospheric forcing, (2) the variation of evaporation with soil moisture, (3) the variation of runoff with soil moisture, and (4) persistence in the atmospheric forcing, as perhaps induced by land atmosphere feedback. Geographical variations in the relative strengths of these factors, which can be established through analysis of model diagnostics and which can be validated to a certain extent against observations, lead to geographical variations in simulated soil moisture memory and thus, in effect, to geographical variations in seasonal precipitation predictability associated with soil moisture. The use of the equation to characterize controls on soil moisture memory is demonstrated with data from the modeling system of the NASA Seasonal-to-Interannual Prediction Project.

In this report, we describe results from the first three years of global Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) ocean chlorophyll and land plant measurements. This time period covered the end of one of the largest El Nino events in the past century and a strong La Nina. During this transition, terrestrial plant photosynthesis exhibited only a small change, whereas a significant increase in oceanic photosynthesis was observed. Latitudinal distributions of ocean production indicated that this increase in photosynthesis during the La Nina was distributed in the equatorial belt as well as in high production areas. The analysis also illustrated the large 'missing bloom' in ocean phytoplankton in the southern ocean. While land photosynthesis remained fairly steady during the third year of SeaWiFS measurements, ocean phytoplankton production continued to increase, albeit at a lower rate than from 1997 to 1999. Our results represent the first quantification of interannual variability in global scale ocean productivity. Significant Findings: An increase in ocean production during the first three years of the SeaWiFS mission; a strong hemispheric difference in the latitudinal distribution of ocean photosynthesis.

The spectral window at L-band (1.4 GHz) is important for passive remote sensing of parameters such as soil moisture and ocean salinity best measured at long wavelengths. At L-band, radiation from extraterrestrial (galactic) sources is strong enough to warrant inclusion in calibration and retrieval algorithms and unlike the constant cosmic background is spatially variable. Previous estimates of the magnitude and distribution of this background radiation have been rather coarse, However, recent surveys of the radio sky at 1.4 GHz have made it possible to produce maps with sufficient spatial and radiometric accuracy to be relevant to remote sensing applications. This is of particular concern for remote sensing of sea surface salinity because the surface (water) is a good reflector and the salinity signal is relatively small. This paper presents a modem map of the radiometric sky at L-band and a solution to the problem of determining the portion of the sky seen by a radiometer in orbit. The data is derived from recent radio astronomy surveys and is presented as equivalent brightness temperature suitable for remote sensing applications. Examples using orbits and antennas representative of those contemplated for remote sensing of soil moisture and sea surface salinity from space are presented to illustrate the signal levels to be expected. Radiation near the galactic plane can exceed several kelvin.

The information obtained from deployment of instrumented meteorological rockets provides middle atmospheric data in a region that is difficult to measure by other means. In the last two decades, in-situ measurements of the middle atmosphere have become less frequent and only originate from a handful of locations. However, the value of these measurements continues to be proven through the validation of remote sensing techniques, support of other payloads sampling the region, and as importantly, the continued study of the rocket datasets with the details and trends that they hold. Wallops Island (37.8 N, 75.5 W) has one of the longest meteorological rocket data records available with relatively few system changes. Two particular periods from this record are studied: (1) January/February and (2) July/August, 1977. Both data sets consist of Super-Loki meteorological rockets with a Datasonde and Starute payload, which yield temperature and wind profiles. The January/February set consists of almost daily launches with days with multiple launches interspersed through January. In the July/August set, rockets were launched for thirty consecutive days at nearly the same time daily from Wallops Island. This campaign was immediately followed by sets of multiple launches with up to six launches per day separated by hours and in some cases minutes. The unique nature of the data allows a detailed examination of the atmosphere's short-term variability. These results are compared to the current views of middle atmospheric dynamics and turbulence from altitudes in the range of 20-60 km.

The Los Alamos National Laboratory (LANL) Sferic Array has recorded electric-field-change waveforms simultaneously at several stations surrounding the ground-strike points of numerous return strokes in cloud-to-ground lightning flashes. Such data are available from the five-station sub-networks in both Florida and New Mexico. With these data it has been possible for the first time to compare the waveforms radiated in different directions by a given stroke. Such comparisons are of interest to assess both the effects of channel geometry on the fine structure of subsequent-stroke radiation fields and the role of branches in the more jagged appearance of first-stroke waveforms. This paper presents multiple-station, time-domain waveforms with a 200 Hz to 500 kHz pass-band from both first and subsequent return strokes at ranges generally between 100 and 200 km. The differences among waveforms of the same stroke received at stations in different directions from the lightning channel are often obvious. These differences are illustrated and interpreted in the context of channel tortuosity and branches.

The presentation will include an overview of leading Earth Science scientific problems that can be addressed using microwave remote sensing, including soil moisture, precipitation, sea salinity, sea surface winds, atmospheric profiling, etc. Using this basis of scientific measurement, the presentation will outline current technological impediments to implementing new measurement system, concentrating on a few example approaches to new technology, such as the conceptual design tradeoffs and capability improvements represented by a fleet of inexpensive nano-satellites, versus geostationary large aperture sensing systems. The outlook for measurement capabilities will be traded against the expected technological hurdles.

The use of microwave radiometry for remote sensing is a relatively young field. As a result, there are no standard definitions of many frequently used technical terms; a lot of which are conventional usages carried-over from optical remote sensing, and a lot more are shared with electrical or microwave engineering. Sometimes the divergent notions and assumptions originating from a different field may cause ambiguity or confusions. It is proposed that we establish a list of frequently used terms, together with their 'standard' definitions and hope that they will gradually gain general acceptance by the remote sensing community. It would be even more useful if the IEEE community can set up a standard committee of sort to develop and maintain the standards. To minimize the effort, the existing terms should be kept or reinterpreted as much as possible. For example, the term 'Instantaneous Field of View' (IFOV), originally coming from the optical remote sensing field, is now appearing in microwave remote sensing literature frequently. The IFOV refers to the 'beam width' or the 'diameter' of the beam's geometrical projection on earth surface. Since the definition of 'beam width' is different for an optical system versus a microwave antenna, the use of IFOV in microwave radiometry needed to be clarified. Also, the meaning of the IFOV will be different depending upon whether the beam is scanning or not, and how the scanning takes place, e.g. 'continuous scanning' vs 'stare-and-step scan.' From this one term alone, it is clear that more subtle meanings must be spell out in detail and a 'standard' definition would help in understanding and comparing systems and data in the literature. A selected list of terms with their suggested definitions will be discussed in this presentation.

Initial precipitation forecasts of the January 2000 blizzard were unable to adequately alert emergency response along the eastern seaboard. Cyclogenesis, over the Gulf of Mexico was a contributing cause of that problem. We present distributions of precipitation derived from spaceborne microwave measurements from the Special Sensor Microwave/ Imager (SSM/I) and the TRMM Microwave Imager (TMI) supplemented by NWS operational radar and the National lightning Detection Network (NLDN) Long-Range (LR) product. The combined NWS radar and NLDN-LR data revealed the location of precipitation between 1/23 and 1/27/2000 over the US, the Gulf and the Atlantic Ocean. The remotely sensed precipitation distributions are compared to the precipitation inferred from coincident TMI observations.

Data from generation of satellite microwave radiometer will allow the detection of seasonal to decadal changes in the arctic hydrology cycle as expressed in temporal and spatial patterns of moisture stored in soil and snow This nw capability will require calibrated Land Surface Process/Radiobrightness (LSP/R) model for the principal terrains found in the circumpolar Arctic. These LSP/R models can than be used in weak constraint. Dimensional Data Assimilation (DDA)of the daily satellite observation to estimate temperature and moisture profiles within the permafrost in active layer.

The Goddard Institute for Space Studies global climate model (GISS GCM) is used to examine the sensitivity of the simulated climate to sea ice concentration specifications in the type of simulation done in the Atmospheric Modeling Intercomparison Project (AMIP), with specified oceanic boundary conditions. Results show that sea ice concentration uncertainties of +/- 7% can affect simulated regional temperatures by more than 6 C, and biases in sea ice concentrations of +7% and -7% alter simulated annually averaged global surface air temperatures by -0.10 C and +0.17 C, respectively, over those in the control simulation. The resulting 0.27 C difference in simulated annual global surface air temperatures is reduced by a third, to 0.18 C, when considering instead biases of +4% and -4%. More broadly, least-squares fits through the temperature results of 17 simulations with ice concentration input changes ranging from increases of 50% versus the control simulation to decreases of 50% yield a yearly average global impact of 0.0107 C warming for every 1% ice concentration decrease, i.e., 1.07 C warming for the full +50% to -50% range. Regionally and on a monthly average basis, the differences can be far greater, especially in the polar regions, where wintertime contrasts between the +50% and -50% cases can exceed 30 C. However, few statistically significant effects are found outside the polar latitudes, and temperature effects over the non-polar oceans tend to be under 1 C, due in part to the specification of an unvarying annual cycle of sea surface temperatures. The +/- 7% and 14% results provide bounds on the impact (on GISS GCM simulations making use of satellite data) of satellite-derived ice concentration inaccuracies, +/- 7% being the current estimated average accuracy of satellite retrievals and +/- 4% being the anticipated improved average accuracy for upcoming satellite instruments. Results show that the impact on simulated temperatures of imposed ice concentration changes is least in summer, encouragingly the same season in which the satellite accuracies are thought to be worst. Hence the impact of satellite inaccuracies is probably less than the use of an annually averaged satellite inaccuracy would suggest.

Two types of microwave radiometry--synthetic thinned array radiometry (STAR) and fully-polarimetric (FP) radiometry--have received increasing attention during the last several years. STAR radiometers offer a technological solution to achieving high spatial resolution imaging from orbit without requiring a filled aperture or a moving antenna, and FP radiometers measure extra polarization state information upon which entirely new or more robust geophysical retrieval algorithms can be based. Radiometer configurations used for both STAR and FP instruments share one fundamental feature that distinguishes them from more 'standard' radiometers, namely, they measure correlations between pairs of microwave signals. The calibration requirements for correlation radiometers are broader than those for standard radiometers. Quantities of interest include total powers, complex correlation coefficients, various offsets, and possible nonlinearities. A candidate for an ideal calibration source would be one that injects test signals with precisely controllable correlation coefficients and absolute powers simultaneously into a pair of receivers, permitting all of these calibration quantities to be measured. The complex nature of correlation radiometer calibration, coupled with certain inherent similarities between STAR and FP instruments, suggests significant leverage in addressing both problems together. Recognizing this, a project was recently begun at NASA Goddard Space Flight Center to develop a compact low-power subsystem for spaceflight STAR or FP receiver calibration. We present a common theoretical framework for the design of signals for a controlled correlation calibration source. A statistical model is described, along with temporal and spectral constraints on such signals. Finally, a method for realizing these signals is demonstrated using a Matlab-based implementation.

The Arctic Ocean is the smallest of the Earth's four major oceans, covering 14x10(exp 6) sq km located entirely within the Arctic Circle (66 deg 33 min N). It is a major player in the climate of the north polar region and has a variable sea ice cover that tends to increase its sensitivity to climate change. Its temperature, salinity, and ice cover have all undergone changes in the past several decades, although it is uncertain whether these predominantly reflect long-term trends, oscillations within the system, or natural variability. Major changes include a warming and expansion of the Atlantic layer, at depths of 200-900 m, a warming of the upper ocean in the Beaufort Sea, a considerable thinning (perhaps as high as 40%) of the sea ice cover, a lesser and uneven retreat of the ice cover (averaging approximately 3% per decade), and a mixed pattern of salinity increases and decreases.