1. EOS Aqua AMSR-E Arctic Sea Ice Validation Field Campaign Principal Investigator: Donald Cavalieri NASA GSFC Code 614 Co-Principal Investigator: Thorsten Markus NASA Code 614 NASA P-3B at Fairbanks International Airport in March 2003

2. Project: The March 2006 campaign was the second of two coordinated Arctic field campaigns to validate the AMSR-E sea ice products which include sea ice concentration, snow depth on sea ice, and sea ice temperature. History: The first was successfully completed in March 2003 and provided an initial set of data. The 2006 campaign provided the first comprehensive data set with which to validate the snow depth product over areas of the Beaufort and Chukchi seas through the coordination of satellite, aircraft, and surface-based measurements. Instrumentation and Measurements: The NASA P-3B aircraft carried an AMSR-E simulator, a laser altimeter, a radar altimeter, and a wide-band radar, which measures snow thickness directly. The snow depth retrievals from these sensors were first validated using surface based measurements made near Barrow before being used to validate the AMSR-E snow depth retrievals directly. Surface measurements of snow and ice properties near Barrow were overflown by NASA’s P-3B in order to validate aircraft instrumentation before conducting large scale measurements over the Arctic Ocean (photo J. Maslanik). NASA P-3B flight paths covering the Barrow area and other regions of the Arctic having different snow depths are shown as well as a portion of an ICESat track that was underflown on March 24, 2006.

3. Seasonal and Interannual Variability of Calcite in the Vicinity of the Patagonian Shelf Break (38 o S – 52 o S) Chuck McClain, Ocean Sciences Branch, Hydrospheric & Biospheric Sciences Laboratory Motivation and Study Objective Previous studies have shown that the Patagonian shelf is a region of high phytoplankton productivity (very intense ocean blooms) and strong uptake of atmospheric CO 2. Our study focuses on the timing and duration of coccolithophore blooms along the Patagonian shelf break. Ocean Color Signature Coccolithophores are armored with miniature plates of calcite called coccoliths (see Figure 1) which are seen by true color satellite images as milky white or turquoise patches during intense coccolithophore blooms (see the elongated turquoise patch along the Patagonian shelf break as an example in Figure 2). Methodology Satellite-derived time series of chlorophyll, calcite, and sea-surface temperature, and historic hydrographic data were used to elucidate the blooms progression and extension. Figure 1. Electron microscope photograph (by Jeremy Young) of coccolith plates. Figure 2. SeaWiFS true color image (Nov 27, 2001) of the Patagonian region. Terms: Coccolithophore-microscopic single-celled marine algae (phytoplankton) which secrete carbonate plates known as coccoliths

4. Seasonal and Interannual Variability of Calcite in the Vicinity of the Patagonian Shelf Break (38 o S – 52 o S) (Continued…) Figure 3Figure 4 Figure 3 shows monthly SeaWiFS-derived composites of calcite (a,b,c) and Chl a (d,e,f) for Nov and Dec 2004, and January 2005. The white polygon delimits the portion of the Patagonian shelf break from which the data were extracted for analyses.  Chl a concentrations are high during November but are much lower during December and January  Almost no calcite was detected within the study region in November, but significant concentrations were detected by the calcite algorithm during December and January  This result from ocean color data analyses was verified with the November 2004 in situ data (vertical red lines in Figure 4). Figure 4 shows satellite-derived time series of Chl a, total calcite, percent of pixels containing coccolithophores (PPCC), SST, and PAR for September 1997- October 2005(January 1997 – December 2004 for SST). The total calcite (10 9 gC m -1 ) was obtained from the product of calcite concentration and the area of each pixel and then summed over the entire regional polygon (see Figure 3). Note that the Chl a starts rising every year around September and peaks around November, with a few exceptions (2001 and 2003) where the increase in Chl a started one or two months earlier. The calcite always reaches its peak after the maximum Chl a concentration has been reached. The time series of PPCC provides an independent evidence of the coccolithophore blooms and has interannual variability and timing remarkably similar to the calcite concentration. Also note that PAR leads SST by about 2 months, implying that light becomes available for the spring bloom before the MLD reaches a minimum value. Even though the timing of the phytoplankton blooms is almost always predictable, their intensity and duration are highly variable from year to year. Conclusions The primary mechanisms responsible for the variability and succession of phytoplankton groups (using calcite and Chl-a as biomarkers) along the edge of the continental shelf are seasonal changes in light intensity and nutrient supply within the mixed layer. The Patagonian shelf blooms occur during the austral spring-summer and are remarkably consistent in timing and duration.

5. Corn growing season vegetation effects on L band soil surface emission Alicia T. Joseph, (Code 614.3) Hydrological Sciences Branch Background: With the expected launch of the Aquarius mission in 2009 and the Soil Moisture and Ocean Salinity (SMOS) mission in 2007, new opportunities for global scale soil moisture monitoring will emerge. Much research is available on developing vegetation correction methods, but the accuracy assessment of these methodologies has often been performed with data sets that include only a part of the growing season. In this investigation the vegetation effects on the soil surface emission will be analyzed for the complete corn growing season based on L band observations collected during the passive/active microwave remote sensing OPE 3 (Optimizing Production inputs for Economic and Environmental Enhancement) experiment. The OPE 3 experiment was conducted between May 10 and October 2, 2002 on a corn field in Beltsville, Maryland. Objective and Method: The objective is to derive vegetation parameters at various corn growth stages based on the L band brightness temperatures collected during the OPE 3 field campaign and to quantify the reliability of these parameterizations in retrieving soil moisture at each growth stage. The following methods will be used:  a widely used vegetation correction algorithm will be employed  the active microwave data will be employed to analyze the vegetation effects on the bare soil emission using a discrete scattering approach. With the launch of the Aquarius mission the development of a truly combined passive/active microwave soil moisture retrieval algorithm will become possible because data will be available at the same frequency and from the same satellite. Results: Preliminary analysis of the OPE 3 observations have shown that the ground data collected are robust, meaning that the soil moisture and temperature data collected are representative for the radiometer and radar footprints. Further, initial radiative transfer computations have shown that a first order approach can be used to study the vegetation effects on L band soil surface emission, which indicates a view angle dependency of the single scattering albedo, an important variable for soil moisture retrieval. Future work will focus on:  incorporating the V-polarized observations into a dual polarized retrieval algorithm  quantifying the uncertainty in the brightness temperature by different crop row orientations  implementation of active microwave remotely sensed vegetation parameters into a passive microwave retrieval algorithm.

6. Outline of the OPE 3 experimentMicrowave Instruments Corn growing season vegetation effects on L band soil surface emission Soil moisture measurements May 6 July 10 July 24 August 21 October 1 Corn Growth Cycle

7. VWC =3.0 kg m -2 Corn growing season vegetation effects on L band soil surface emission Initial investigations were focused on retrieving the vegetation transmissivity, a crucial parameter for soil moisture estimation. 1.Surface emission absorbed by vegetation; 2.Vegetation emission; 3.Surface emission scattered within the vegetation layer. Surface emission = f (soil moisture) 12 3 Vegetation layer The discrepancy between the theoretical and retrieved vegetation transmissivity can be explained by the scattering within the canopy, parameterized by the single scattering albedo (ω). Angular dependence of the single scattering albedo The angular dependence of ω results in an uncertainty in the retrieved soil moisture At low VWC (< 1.0 kg m -2 ), the uncertainty in soil moisture is less than 0.01 cm 3 cm -3 ; At higher VWC (>1.0 kg m-2), the uncertainty in soil moisture ranges from 0.02- 0.045 cm 3 cm -3 ; A) B) C) D) VWC =0.1 kg m -2 VWC =0.3 kg m -2 retrieved values theoretical values + o - + o - + o - + o - VWC =2.0 kg m -2 Key result: The single scattering albedo is angular dependent, which is not incorporated in the current soil moisture retrieval algorithms. This variation in the single scattering albedo results in an uncertainty in retrieved soil moisture of less than 0.01 cm 3 cm -3 for low VWC ( 2.0 kg m -2 ). July 24 May 6 August 21 + o - 35 degrees 45 degrees 60 degrees Key: