1. SeaWiFS Highlights November 2001 SeaWiFS Views the Colors of Spring Off the coast of Argentina, SeaWiFS viewed very colorful springtime waters on November 22, 2001. In some areas, the water goes from deep blue to bright aquamarine to rich green and back to deep blue within the space of a few kilometers. The city of Buenos Aires, Argentina is visible as a gray splotch on the western shore of the light brown Rio de la Plata near the top of the image. The Falkland Islands is visible through the clouds near the bottom of the image. POC: 970.2/Gene Feldman gene@seawifs.gsfc.nasa.gov

2. SeaWiFS Views the Colors of Spring November 22, 2001 Falkland Islands Buenos Aires

3. NEW ICEBERG RELEASED Pine Island Glacier, Antarctica Eos article submitted 12/4/01 (MISR images from D. Diner, JPL) POC: 971/R. Bindschadler bob@igloo.gsfc.nasa.gov

4. A First Look at Output from the Global Land Data Assimilation System Matthew Rodell, Paul Houser, Urszula Jambor, Jon Gottschalck, and Jon Radakovich Motivation: Surface stores of water and energy (e.g., soil moisture and temperature) regulate atmospheric conditions, so that accurate representation of these stores in weather and climate models is crucial for producing reliable predictions. However, global, observation-based data fields for model initialization are scarce. Fortunately, many innovative new ground- and satellite-based observation systems that may be useful in constraining modeled land surface states are now becoming mature. At the same time, modeling and assimilation techniques have continued to evolve, aided by increases in computing capacity and affordability. Goal: To develop a 1/4 to 1/8 degree resolution Global Land Data Assimilation System (GLDAS), which makes use of data from advanced observing systems within a land data assimilation framework, in order to produce optimal output fields of land surface states and fluxes in near-real time. Status: At present, GLDAS is able to run at 1/4 degree resolution using atmospheric forcing fields from either of two general circulation models (GCMs). Drivers for two land surface models have been installed, and at least three others are planned. Subgrid spatial variability is simulated using a tiling approach based on the quantitative distribution of vegetation types within each 1/4 degree land surface pixel. Figures 1 & 2 display global patterns of two static input parameters, and figures 3 & 4 show two output fields. Current Objectives: Several potential sources of observation-derived forcing fields, such as remotely sensed precipitation and solar radiation, have been identified. Modeled input fields will be replaced by these observations, as available, in the near future. A data assimilation algorithm, whereby model predicted moisture and energy states will be constrained by observations, and a runoff routing scheme will be implemented. After the development phase is complete several studies will be performed. GLDAS products will be made available in near-real time over the internet. For more information, please visit http://ldas.gsfc.nasa.gov.

5. A First Look at Output from the Global Land Data Assimilation System Figure 1: Vegetated fraction (a static parameter). Figure 3: Soil moisture in the top 1m (mm), instantaneous, 0Z 26 March 2001. Figure 4: Average surface temperature (K), instantaneous, 1Z 02 March 2001. Figure 2: Fraction of sand in soil (a static parameter).