1. Graphical Analysis (graph on next slide): On a shot-by-shot basis, ICESat's 1064 nm data can now identify clouds that can impact elevation accuracy. The 1064 data has been used to determine the presence of clouds and their heights (magenta dots) in the vicinity of an area of elevation data offset and also elevation data loss. Elevation impacts in excess of a meter (green elevation offset profile) are due to the presence of thick clouds that were present during the acquisition of the Cycle 29 data. Note, not all of the Cycle 29 cloudy shots have an associated elevation impact meaning that some clouds were thin enough optically to have little to no impact on the elevation data. The Cycle 28 acquisition was virtually cloud-free by comparison. Conclusion: This 1064-only approach means that it should be possible to identify most of the elevation data that is impacted by atmospheric phenomena and to remove them if needed. In addition, it should be possible with a sufficient numbers of examples, to develop an algorithm that will correct elevation values for measured cloud impact. Cloud Clearing Using 1064 nm 40 Hz Data Christopher Shuman, Cryospheric Sciences Branch, Hydrospheric & Biospheric Sciences Laboratory, Earth-Sun Exploration Division (christopher.a.shuman@nasa.gov)

2. Cloud Clearing Using 1064 nm 40 Hz Data Chris Shuman - Deputy Project Scientist, Steve Palm - SSAI, and Vijay P. Suchdeo - NVI As shown in this plot, Track 091 was profiled on September 25 (blue, Cycle 28) and repeated 8 days later on October 3, 2003 (red, Cycle 29) during the early portion of the Laser 2a operations period.

3. Feasibility Study for Estimation of Water Vapor and Precipitation Parameters using a 3-frequency Radar Robert Meneghini, Instrumentation Sciences Branch, Hydrospheric & Biospheric Sciences Laboratory, Earth-Sun Exploration Division (robert.meneghini-1@nasa.gov) With a broadband power amplifier and antenna, the potential exists for measuring radar returns at multiple frequencies over bandwidths of up of 20% One possible application is estimation of water vapor and precipitation parameters with the following set of frequencies: –f c = 22.235 GHz (center of water vapor absorption line) –f l = 20.246 GHz (lower frequency) –f u = 24.694 GHz (upper frequency) –With (f u -f l )/f c =0.2 –k v (f u )=k v (f l ) [k v = specific absorption from water vapor dB/km] Feasibility study suggest that such measurements are possible from either ground-based or air-/space- borne geometries –Vertical profiles of water vapor are possible only in rain (which provides the backscattering medium) –Path-integral estimates are possible from air/spaceborne geom. using surface –Technical requirements are fairly demanding –Large numbers of independent samples are required to reduce variance of estimate

4. Top: Simulated fields of radar reflectivity factors at 22.235 GHz Second from top: Differential measured radar reflectivity factors between upper and lower frequencies (can be used to estimate median mass diameters of hydrometeors) Third from top:: Estimated differential water vapor absorption derived from a linear combination of the radar returns Bottom:: Assumed differential water vapor absorption Top: Specific absorption of water vapor (dB/km) versus frequency for several water vapor densities and the frequencies, indicated by the vertical lines, for which the absorption is equal for bandwidths of 10%, 20%, 30% Bottom: Upper and lower frequencies for which the water vapor absorptions are equal versus percent bandwidth

5. GRACE Holds Promise for Satellite Based Monitoring of Ground Water Matthew Rodell, Hydrological Sciences Branch, (matthew.rodell@nasa.gov) Hydrospheric & Biospheric Sciences Laboratory, Earth-Sun Exploration Division Background Gravity Recovery and Climate Experiment (GRACE) Satellites have been providing global maps of Earth’s gravity field on a near-monthly basis since April, 2002. The high precision of the GRACE measurement technique enables detection of tiny gravitational variations. Over land, gravitational variations are caused mainly by redistributions of terrestrial water and atmospheric mass. We can predict atmospheric circulation reasonably well using numerical models, so that its contribution to the gravity changes observed by GRACE can be removed from the measured fields. Thus variations in terrestrial water storage (the sum of ground water, soil moisture, snow, ice, and surface water) can be mapped based on GRACE gravity measurements. groundwater + soil moisture + snow + ice + surface water = Terrestrial Water Storage Ground water is a crucial resource which is difficult to monitor at large scales and particularly in regions of the world where levels are either not systematically recorded or access is limited by political barriers. GRACE is the only current or planned remote sensing mission capable of detecting water stored below the first few centimeters of soil, including ground water. Objective and Method: Here we compare terrestrial water storage (TWS) anomalies (deviations from the mean) derived from GRACE with ground water storage anomalies averaged over the Mississippi River basin. The GRACE based estimates were computed using a new technique, developed by colleagues at the University of Texas Center for Space Research, which incorporates satellite laser ranging (SLR) estimates of the degree 1 (geocenter) and degree 2 gravity field terms. Furthermore, a minimum averaging radius of 400 km was applied in order to reduce the errors associated with the high degree harmonics. Ground water storage anomalies were calculated based on data from over 40 observation wells which were collected and archived by the United States Geological Survey. The map on the figure page (next slide) shows the locations of the wells and the Mississippi River basin (blue shaded region). Results and Discussion: GRACE-derived TWS anomalies and ground water storage anomalies (as equivalent heights of water) are plotted for April 2002 through December 2003. The correlation between the two time series is strong, with ground water slightly lagging TWS, as is expected of this deep, slowly varying component. The apparent contribution of ground water to total terrestrial water storage variations is large. These facts suggest that GRACE holds promise for satellite based monitoring of ground water. However, in order to make that promise a reality, methods are needed for separating the contributions of soil moisture, snow, and surface water from the ground water storage signal. Assimilating land surface models, also being developed by the PI, show strong potential in that regard.

6. Comparison of GRACE-Derived Terrestrial Water Storage with Ground Water Observations in the Mississippi River Basin Black bars = GRACE derived terrestrial water storage Blue line = observation based ground water

7. The Relationship of the Terra MODIS Fire Product and Anthropogenic features in the Central Siberian Landscape Katalin Kovacs (kkovacs@ltpmail.gsfc.nasa.gov), Biosphere Sciences Branch, Hydrospheric & Biospheric Sciences Laboratory, Earth-Sun Exploration Division The area of this study is located in Central Siberia, covering parts of the West Siberian Basin and the Central Siberian Plateau, ranging from 80 to 100 degrees East in longitude and from 50 to 75 degrees North in latitude and covering >5.8 Million km 2 Hot Spots Detected by Terra MODIS for 2001, 2002, and 2003: Superimposed over the previous map showing roads and rail lines. Magenta points represent 2001 hot spots, orange points show 2002 hot spots, and red points highlight 2003 hot spots.

8. Roads Railroads Cities and Towns Histograms of the distance ( 0.92 km pixels) between anthropogenic features and LCTAs. Roads, Railroads, Cities and Towns. Continuous, unlimited buffer zones from human settlements (yellow) with 2001 LCTAs (red) overlaid. Terms: LCTA-land-cover thermal anomaly

9. Correlation matrix showing the correlation values between the buffer zones of the features All three LCTA types in all three years have a strong, positive correlation with some anthropogenic features, such as roads, human settlements, and mineral industry locations and in the high fire year of 2003 these relationships seem to be in general stronger. Forest thermal anomalies show a stronger positive spatial correlation with roads (r 2 2001 =0.81, r 2 2002 =0.90, r 2 2003 =0.88) than any forest pixel (r 2 =0.52) in all three years, indicating that forests near roads are more likely to burn than any forest in the study area. This is also true for railroads, settlements and mining industry locations. Forest thermal anomalies show a stronger positive spatial correlation with agricultural thermal anomalies (r 2 2001 =0.93, r 2 2002 =0.87, r 2 2003 =0.94) than any forest pixel (r 2 =0.53) indicating that forests near burning crop lands are more likely to burn than any forest in the study area. These results suggest a strong link of human activity to land cover fires as identified by the MODIS Thermal anomaly data. Whether or not and how human presence and activity causes more land cover fires to occur in Central Siberia is a different question and answering it would require more in depth understanding of cultural practices in the area.