“OceanColor Web” Goes Live! Gene Feldman NASA GSFC, Laboratory for Hydrospheric Processes, SeaWiFS Project Office Just introduced to the public, the “OceanColor Web” site is intended to serve as the entry point into all of NASA’s ocean color-related activities as part of the evolution of the individual ocean mission-based activities into an integrated ocean measurement-based program. The process of integrating the various mission-specific services, information, and documentation that have been developed over a number of years, has just begun, so it is expected that this web site will be evolving quite rapidly. People are encouraged to use the online forum, which is linked through the Questions button, to provide feedback, ask questions, and offer suggestions to improve this innovative site.

“OceanColor Web” Goes Live!

Detection of Change in the Arctic using satellite and in situ data *J. C. Comiso, J. Yang, S. Honjo, and R.A. Krishfield, WHOI, Woodshole, MA *NASA GSFC/Laboratory for Hydrospheric Processes/ Oceans and Ice Branch The decade of the 1990s was the warmest decade of the last century while the year 1998 was the warmest year ever observed by modern techniques with 9 out of 12 months of the year being the warmest month. Satellite ice cover and surface temperature data, ECMWF wind, and ocean hydrographic data are examined to gain insights into this warming phenomenon and an apparent concurrent decline in the ice cover. Areas of ice free water in both western and eastern regions of the Arctic were found to follow a cyclical pattern with approximately decadal period but with a lag of about 3 years between the eastern and western regions. The pattern was interrupted by unusually large anomalies in 1993 and 1998 in the western region and in 1995 in the eastern region. The area of open water in 1998 was the largest ever observed in the western region up to this period and occurred concurrently with large surface temperature anomalies in the area and adjacent regions. This also occurred at a time the atmospheric circulation changed from predominantly cyclonic in 1996 to anti-cyclonic in 1997 and Detailed hydrographic measurements over the same general area in April 1996 and April 1997 indicate a warming and significant freshening in the top layer of the ocean suggesting increases in ice melt and/or river runoff. Continuous ocean temperature and salinity data from ocean buoys at depths of 8m, 45m, and 75m confirm these results and show large interannual changes during the 1996 to 1998 period. Surface temperature data show a general warming in the region that is highly correlated with observed decline in summer sea ice while the hydrographic data suggest that in 1997 and 1998, the upper part of the ocean was unusually fresh and warm compared to available data between 1956 to 1996.

The detection of Change in the Arctic Large interannual changes in the sea ice cover were observed in the 1990s; the period being a good example. During freeze-up in mid-October, the Central Arctic is usually mainly ice covered as in 1996, but in 1997 and 1998, the Chukchi and Beaufort Seas still had substantial open water. The interannual changes are shown to be highly correlated with surface temperature, wind circulation, surface ocean temperature and salinity Two decades of satellite data show rapid warming and a large decline in the ice cover while historical CTDs in the region show evidence of a freshening and warming of the ocean mixed layer. Ref. Comiso, J., J. Yang, S. Honjo, A. Krishfield, Dectection of change in the Arctic using satellite and in situ data, J. Geophys. Res., 108(12), 14-1 to 14-24, 2003.

Changes in the ocean, ice thickness, and the atmosphere Ice-Ocean Environmental Buoy (IOEP) data in the Beaufort Sea show significant increases in the temperature and decreases in salinity of the mixed layer (see a) from 1996 to Large inter-annual decrease in the ice thickness (see b) for the same period were also inferred. This phenomenon continued in ECMWF reanalysis data show a change in regional wind circulation from predominantly cyclonic in 1996 to anti-cyclonic in 1997 and Satellite infrared data show significant warming in the region during the same period that could in part cause more sea ice melt.

Quantifying the Uncertainty in Passive Microwave Snow Water Equivalent Observations *James L. Foster, Chaojiao Sun, Jeffrey P Walker, Richard Kelly, Alfred Chang, Jiarui Dong, and Hugh Powell NASA GSFC/Laboratory for Hydrospheric Processes, Hydrological Sciences Branch Passive microwave remote sensors onboard satellites provide an all-weather global snow mass (i.e., snow water equivalent) observation capability day and night. However, there are both systematic and random errors associated with the passive microwave measurements. The existence of these errors are well known but have thus far not been adequately quantified. Understanding these errors is important for correct interpretation of remotely sensed snow water equivalent (SWE) and the successful assimilation of such observations into numerical models. A novel approach was used in this study to quantify these errors in North America and to formulate a time-evolving algorithm that estimates remotely-sensed snow water equivalent observations more reliably in various climatic/geographic regions (Figure 1). The new algorithm takes into account the impact of vegetation cover and snow crystal evolution. The uncertainty analysis is based on error estimation theory, combined with detailed knowledge of various factors that impact passive microwave responses from snow. Among these factors are vegetation cover, snow morphology (crystal size) and errors related to brightness temperature calibration (Figure 2). Dense vegetation was shown to be the major source of systematic error, while assumptions about snow crystal size and how crystals evolve with the progression of the season also contribute significant biases. This method is applied to over twenty years of daily Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager (SSM/I) passive microwave measurements to produce an improved SWE dataset and annotated error maps for North America. These maps have been validated in tundra, taiga, prairie, and maritime regions of Canada using in situ SWE data from the Canadian Climate Centre (Figure 3).

Figure 1: SSM/I monthly SWE maps from October 1990 through May Quantifying the Uncertainty in Passive Microwave Snow Water Equivalent Observations October 1990 November 1990 January 1991 December1990 February 1991 May 1991 April 1991 March 1991

Figure 2. (a) Total error, (b) forest error, (c) grain error and (d) Tb error associated with the new SSM/I SWE algorithm for February (a) Total error (d) Tb error (b) Forest error (c) Grain error Quantifying the Uncertainty in Passive Microwave Snow Water Equivalent Observations

Figure 3: Comparison of observed in-situ SWE and SSM/I over the snow season Red curve denotes monthly mean MET station SWE. Red color bars denote RMS errors of the MET station data. Blue curve and error bars represent SSM/I estimates and uncertainty. Dashed blue dots are SWE estimates from the old algorithm. Quantifying the Uncertainty in Passive Microwave Snow Water Equivalent Observations