1. SeaWiFS Views Equatorial Pacific Waves Gene Feldman NASA Goddard Space Flight Center, Lab. For Hydrospheric Processes, gene.feldman@gsfc.nasa.gov This 11-day SeaWiFS chlorophyll a composite (January 8–18, 2002) shows the rather remarkable development of a series of equatorial Pacific tropical instability waves. The enhanced chlorophyll concentrations associated with the waves extend from the region just west of the Galapagos Islands along the equator to the International Dateline—a distance of nearly 10,000 kilometers.

2. SeaWiFS Views Equatorial Pacific Waves Sydney January 30, 2002

3. A link is found between simulated Fram Strait sea ice export and variations in the phase of zonal wave 1 in Sea Level Pressure at high northern latitudes. Previous studies found no significant correlation between the Fram Strait ice flux and the NAO over time scales longer than the last two decades. Inconsistent and low correlations are also found between Fram Strait ice export and the Arctic Oscillation (AO). In contrast, the phase of wave 1 explains about 70% of the simulated ice export variance over the 40-year period 1958-1997 after the removal of two years having anomalous phases related to the breakdown of the wave 1 circulation in the mid 1960s. The plots compare January Fram Strait ice export with (A) the NAO index, (B) the AO index, (C) wave 1 phase, and (D) wave 1 phase minus data for 1966 and 1967. Contact: D. J. Cavalieri, Oceans and Ice Branch, Code 971, NASA GSFC. A Link Between Arctic Sea Ice Export Through Fram Strait and Atmospheric Planetary Wave Phase

4. Seasonal Snow Extent and Snow Mass in South America for the Period from 1988 –2001 James Foster NASA Goddard Space Flight Center, Lab. for Hydrospheric Processes, Hydrological Sciences Branch, james.l.foster@gsfc.nasa.gov Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Special Sensor Microwave Imagers (SSM/I) on board Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1988-2001, both snow cover extent and snow depth (snow mass) were investigated during the winter months (May-August) in the Patagonia region of Argentina. In nearly every year, the coldest winter month was found to be the month having the most extensive snow cover and also the month having the deepest snow. For the fourteen-year period of this study, the average snow cover extent (May-August) was about 0.46 million km 2, and the average monthly snow mass was about 1.18 x 10 13 kg. July 2000 was the month having the greatest snow extent (nearly 8.1 million km 2 ) and snow mass (approximately 2.8 x 10 13 kg). The winter having the least snow cover was 1996. In July of 1996, the snow covered approximately 3.46 x 10 5 km 2 of Patagonia and had a mass of 0.68 x 10 13 kg. Figures 1 and 2 show the snow distribution (in cm) for July 1996 and July 2000, respectively. For this investigation, brightness temperature differences between the 19 GHz and 37 GHz channels were multiplied by a coefficient related to the average grain size (1.60) to derive the thickness of the snow. The simple algorithm is then SD = 1.6 [(19 GHz - 37 GHz) –5] cm [1] Where SD is snow depth in cm and 19 GHz and 37 GHz are the brightness temperatures at 19 GHz and 37 GHz horizontal polarizations, respectively. To derive snow water equivalent (snow mass) the above algorithm can be multiplied by 3.0 – the average density of mid winter, mid latitude snowpacks is approximately 300 kg- 3. This is expressed as: SWE = 4.8 [(19 GHz - 37 GHz) –5] mm [2] Where, SWE is snow water equivalent in mm. If the 18 GHz channel is less than the 37 GHz channel, then the SWE is defined to be zero.

7. Hurricane Bonnie Rainbands Retrieved Profiles Hydrometeor Profile Retrievals Using Active and Passive Microwave Data G. Skofronick-Jackson/UMBC/GSFC, Lab. For Hydrospheric Processes, Microwave Sensors Branch, gail@sensor2.gsfc.nasa.gov EDOP = ER-2 Doppler Radar (ER-2 aircraft flies at 20 km) MIR = Millimeter-wave Imaging Radiometer AMPR = Advanced Microwave Precipitation Radiometer Note sensitivity of 150, 220, 340 GHz to anvil ice cloud. Anvil Region Convective Region Quasi-Stratiform 1. Algorithm: Minimized differences between observations and calculated values using the iteratively estimated profiles. 2. Resolution: 0.5km vertical, <3km horizontal. 3. Surface Wind Speeds: Varied as a function of distance from hurricane eye (about 55 km from right hand side of the EDOP image). 4. Validation: Used in situ measured size distributions and reserved T B observations. AMPR Liquid (a) and Frozen (b) Content (a) (b) MIR EDOP