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FINAL REPORT OF NSF AWARD ID 0240747: Active Layer Thickness and Moisture Content of Arctic Tundra

From SVAT/Radiobrightness Models and Assimilated 1.4 or 6.9 GHz Brightness A. W. England* and Roger DeRoo**

*Professor of Electrical Engineering and Computer Science, Professor of Atmospheric, Oceanic, and Space Sciences, and Associate Dean for Academic Affairs

**Assistant Research Scientist College of Engineering, University of Michigan

Section I. Context of the Investigation Data from the new generation of satellite radiometers will allow us to reliably detect seasonal

to decadal changes in the arctic hydrologic cycle as expressed in temporal and spatial patterns of moisture stored in soil and snow, and, through mass balance, in temporal and spatial patterns of freshwater runoff. With the deterioration of the arctic hydrographic monitoring networks (Vörösmarty et al, 2001), remote sensing will become an increasingly vital technology for hydrologic monitoring in the Arctic. A schematic summarizing the remote sensing concept as it has evolved within the remote sensing hydrology community is shown in Figure 1. Realization of this approach will yield higher fidelity lower boundaries of arctic atmospheric circulation models, a record of climate related changes in the permafrost active layer, and a means of estimating the temporal and spatial patterns of meltwater and rainwater runoff.

Figure 1. Strategy for remotely monitoring water stored in soil and snow. The Atmospheric Model (or observed weather) provides atmospheric lower boundary weather and downwelling short- and long-wavelength radiation as forcing to the SVAT Model. The SVAT Model provides soil, vegetation, and snow temperature and liquid moisture profiles that are used by the Radiobrightness Model to predict emitted microwave brightness, Tb. At low microwave frequencies, e.g. 1.4 GHz, the difference between observed brightness from a satellite and predicted brightness represents an error in the liquid water content of near-surface soils. This error is assimilated by the SVAT Model to improve the current estimate of near-surface soil moisture. Over several assimilation cycles, the SVAT model converges to an accurate moisture profile at depths below those sensed by microwave radiometry. The heavy rectangular boxes identify research that has been the focus of our group’s research. That is, we develop and calibrate SVAT and Radiobrightness Models for prairie and arctic terrains, and we develop the sensor technologies needed to make the observations.

Atmospheric Model

Weather & downwelling radiance

SVAT Model

Temperature & Moisture Profiles

Radiobrightness Model

Satellite L-band Radiometer

Tb (model)

Tb(observed)

Assimilate Tb(observed) - Tb(model)

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Key elements for this approach to succeed in the Arctic are: (1) near-daily satellite microwave brightness data at frequencies which are sensitivity to liquid water in the upper few centimeters of soil or in melting snow, (2) Soil Vegetation Atmosphere Transfer (SVAT) models linked to microwave brightness models for principal arctic terrains, (3) field radiometers for calibrating these models, and (4) validation of the concept in the Arctic. (1) Near-daily satellite radiobrightness data

The first key element, near-daily satellite microwave brightness data at frequencies that are sensitivity to liquid water in the upper few centimeters of soil or in melting snow, is based upon the sensitivity of 1.4 and 6.9 GHz brightness to soil moisture. This sensitivity derives from the large index of refraction of liquid water at frequencies below its Debye relaxation frequency, and the ability of lower frequency brightness to penetrate vegetation. These conditions are increasingly met as frequencies decrease below 10 GHz (e.g., Jackson and Schmugge, 1978; Ulaby et al, 1981; Jackson et al, 1984; Schmugge and O’Neill, 1986; Jackson and O’Neill, 1987; Schmugge and Jackson, 1992; Njoku and Entekhabi, 1996). The minimum usable frequency is 1.4 GHz. Below 1.4 GHz, galactic noise intrudes upon the thermally emitted brightness. The lowest satellite microwave brightness frequency is currently the Advanced Microwave Scanning Radiometer’s (AMSR’s) 6.9 GHz. AMSR, launched in May 2002 on NASA’s Aqua satellite, has approximately a 50 km spatial resolution at 6.9 GHz, and is a pathfinder for instruments that follow the Special Sensor Microwave/Imager (SSM/I), a series that began in 1987, whose lowest frequency of 19 GHz exhibits little useful sensitivity to soil moisture. The European Space Agency’s Soil Moisture Ocean Salinity (SMOS) sensor will be the first satellite 1.4 GHz imaging radiometer. SMOS, currently being developed for launch in 2008, will have a spatial resolution of approximately 50 km (http://www.sv.cict.fr/cesbio/smos). The objectives of this project were to complete much of the preparatory work needed to use AMSR and SMOS data to monitor the water content and thickness of the active layer throughout the pan-Arctic. Our findings appear in Section II.

(2) SVAT models linked to microwave brightness models for principal arctic terrains The second key element of this vision is calibrated SVAT/Radiobrightness models for arctic

terrain. Highly parameterized SVAT models provide the lower boundary for Atmospheric General Circulation Models (AGCMs) (e.g., Trenberth, 1995). Examples of these include the Biosphere Atmosphere Transfer Scheme (BATS) (Dickinson et al., 1986, 1993) and the Simple Biosphere-2 (SiB-2) model (Sellers et al., 1986). Availability of greater computational power prompted more physically-based SVAT models like the Land Surface Model (LSM) (Bonan, 1996) and the Variable Infiltration Capacity (VIC) model (Liang et al., 1994, 1996). Special purpose SVAT models are also developed as diagnostic tools to test our understanding of land surface processes or to provide a unique class of state estimates for other purposes. The prairie Land Surface Process/Radiobrightness (LSP/R) model is such a model in that it relates moisture and temperature profiles in soil and vegetation to microwave brightness (England, 1990; Liou and England, 1996, 1998a, 1998b; Liou et al, 1999; and Judge et al, 1999, 2002a, 2002b).

The calibrated LSP/R model for prairie grassland exhibits excellent performance (Figures 2 and 3). When forced by accurate downwelling long- and short-wavelength radiation and observed weather, the model maintains reliable temporal estimates of temperature and moisture profiles of the upper meter of soil and predicts the consequent radiobrightness (Liou et al, 1999;

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Judge et al, 1999). With imperfect forcing, modeled temperature and moisture profiles and microwave brightness temperatures become unreliable. Assimilation of differences between predicted and observed 1.4 GHz brightness at near-daily intervals will immediately restore the accuracy of the moisture estimate in the upper 5 cm of soil. Over several assimilation cycles, modeled temperature and moisture profiles at depth will converge to observed profiles (e.g., Entekhabi et al, 1994; Houser et al, 1998; Galantowicz et al, 1999; Lakshmi, 2000; Reichle et al, 2001; Reichle and McLaughlin, 2001; Walker and Houser, 2001; Burke et al, 2001). For this to succeed, the SVAT/Radiobrightness model must accurately reflect the physics of the coupled temperature and moisture transport processes in the soil (Liou and England, 1998).

Figure 2. A comparison between observed and modeled temperatures in (a) canopy, and soil at (b) 3 cm and (c) 10 cm depths at the REBEX 5 site in wheat stubble, North Central Oklahoma. (Judge et al, 1999).

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Ter

rain

Bri

ghtn

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(K)

300298296294292290288

Julian Day from Jan 1, 1992

REBEX-1 LSP/R Prediction

19-GHz H-pol

(Oct 13) (Oct 27)

LAI=3Canopy Height=0.6m

Figure 3. A comparison of predicted and observed 19 GHz H-polarized brightness during REBEX 1 (England & Galantowicz, 1995).

SVAT/Radiobrightness models have emerged as powerful tools for prairie and agricultural hydrology because experimental data from a series of field campaigns in southern and mid-latitude prairie have enabled tests of schemes for modeling energy and moisture transport in prairie soils, and calibration of models of prairie terrains. Notable among the field campaigns have been the First ISLSCP Field Experiment (FIFE) in 1987 (e.g., Betts et al, 1996), Washita’92 (Jackson et al, 1995), and the Southern Great Plains Hydrology Experiments – SGP’97 – where our participation as our 5th Radiobrightness Energy Balance Experiment, REBEX-5, was reported by Judge et al (1999).

Our investigations have extended to terrains beyond those of southern and mid-latitude prairie. REBEX-1 was a 7 month experiment in northern prairie grassland near Sioux Falls, South Dakota, during fall and winter of 1992-1993 (Galantowicz, 1995; Galantowicz and England, 1997). REBEX-3 was a 12 month experiment in tussock tundra near Toolik Lake, Alaska, during 1994-1995 (Kim and England, 1998; Kim, 1999, Kim and England, 2002). REBEX-4 was a summer study in northern prairie near Sioux Falls in 1996 (Judge et al, 1999; Judge et al, 2001). REBEX-7 and –8 were summer investigations in agricultural terrain (corn) near Ann Arbor, Michigan (Hornbuckle and England, 2002 a & b). REBEX-9, during late winter and early spring of 2003 near Fraser, CO, was our contribution to the Cold Lands Processes Experiment, CLPX.

REBEX-3 was a first step toward developing LSP/R models for arctic terrains. Our objective was to adapt a successful prairie LSP/R model to tussock tundra for the SSM/I frequencies of 19, 37, and 85 GHz. Key findings from that experiment were (Kim, 1999): • Data from the 19, 37, and 85 GHz REBEX radiometers, or from equivalent SSM/I channels,

clearly delineate the onset of spring thawing and fall freezing of the permafrost active layer. • Tundra in the vicinity of the REBEX-3 site was sufficiently homogeneous over scales of

meters to tens of kilometers that our 19 GHz and 37 GHz observations with footprints of 3 m closely matched the 19 GHz and 37 GHz SSM/I observations with footprints of 50 km and 25 km, respectively (Figure 6) (Kim and England, 2002).

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• Vegetation canopies on tussocks at the REBEX-3 site were sufficiently absorbing at 19 GHz, the most penetrating of the SSM/I channels, to cause 19 GHz brightness to become a non-linear average of the spatial distribution of emission from soil moisture within the footprint (Liou et al, 1998). This and the limited sensitivity of 19 GHz brightness to soil moisture render SSM/I data relatively useless as a quantitative measure of soil moisture in the Arctic.

• LSP/R models that worked so well for prairie could not be adapted effectively to tussock tundra. While we could force tantalizing fits between the observations and the model, the underlying biophysics, as expressed in the spatial structure and constitutive properties of soil and vegetation, were not realistic. Because the biophysics were inappropriate, it is unlikely that extrapolations either from the 19 GHz calibration frequency to 1.4 GHz, or from the REBEX-3 site to other arctic terrains would be reliable.

(3) Field radiometers for calibrating these models Field systems needed for SVAT/Radiobrightness calibration experiments include microwave

radiometers at the appropriate frequencies, polarizations, and incidence angles; instruments to record the radiance and meteorological forcings; and instruments to record the temperature and moisture response of soil and vegetation. We have grouped the radiometers and meteorological sensors into what has now become a Truck Mounted Radiometer System (TMRS3) (Figure 4) and Micrometeorological System (MMS) (Figure 5). TMRS3 consists of dual-polarized 1.4, 6.7, 19, and 37 GHz radiometers, a Thermal Infrared Radiometer (TIR), and a video scene grabber mounted on the 12 m hydraulic arm of a NorSTAR aerial lift diesel truck. The truck has a 7.5 kW diesel generator for autonomous operation and an electronic repair facility with diesel heating and electric air conditioning. The MMS includes a 10 m tower with an adjustable height trolley; 2 m and 10 wind speed, air temperature, and humidity probes; a Bowen ratio instrument; a 4-component radiometer; multiple soil moisture and temperature probes; multiple canopy or snow temperature probes; and a data logger (Hornbuckle et al, 2000). TMRS3 and MMS were deployed to the Toolik Lake area from late April through the end of June, 2004, in support of this experiment. We refer to the field experiment as REBEX-10.

Figure 4. TMRS3 deployed at the shrub site near Toolik Lake, Alaska, in 2004 during REBEX-10.

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Figure 5. MMS in a corn field south of Ann Arbor, MI. The picture was taken during REBEX-7.

Research grade microwave radiometers are unique to their purpose and prohibitively expensive to obtain commercially. We build our own and provide radiometers for other research groups at the recurring cost of their fabrication. The TMRS3 19 and 37 GHz radiometers were repackaged from TMRS2 to incorporate cool-bias temperature control and FPGA-based internal intelligence. The 1.4 and 6.7 GHz radiometers were new instruments for REBEX-9 based upon the innovative design of the NSF-funded STAR-Light receivers. We chose 6.7 GHz rather than AMSR’s 6.9 GHz because there were cost advantages to using 6.7 GHz components. The difference of 200 MHz does not affect sensitivity to soil moisture.

(4) Validation of the Concept in the Arctic Validation of the SVAT/Radiobrightness

model/assimilation–based approach to estimating active layer thickness and water content serves four purposes. It (1) tests our 1st hypothesis that the tundra model and assimilated 1.4 or 6.9 GHz

brightness observations will yield reliable estimates of plot-scale active layer thickness and water content, (2) enables generation of a synthesized data set for a limited test of our 2nd hypothesis that the approach works at the scale of a satellite footprint, (3) provides some data on the temporal and spatial variability of 1.4 and 6.7 GHz brightness in the Arctic, and (4), because these will be the first plot-scale 1.4 and 6.7 GHz brightness observations in arctic tundra, generates an experience base for future investigations.

Section II. Achievements, Findings, and Products The REBEX-10 Field Experiment An enabling achievement of this investigation was successful completion of the REBEX-10 experiment. REBEX-10 constituted a necessary step toward implementing satellite remote sensing hydrology in the pan-Arctic. The experiment was conducted near Toolik Lake, as shown in Figure 6, and focused upon what we believe are 3 canonical terrain types from the perspective of microwave radiometry: Tussock tundra (Figure 7a), dry heath or shrub (Figure 7b), and wet sedge (Figure 7c). We had chosen the specific plot-scale study areas and buried TDR soil moisture probes, and temperature and heat flux sensors in the active layer during a visit to the area in August, 2003. Our observations began before snowmelt in April and extended through June.

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Figure 6. Location of REBEX-10, plot-scale sites.

Figure 7a. Plot-scale tussock tundra site. MMS instruments here included: Air temperature, relative humidity, wind speed and direction, net radiation, Bowen ratio, soil temperature, soil moisture, soil heat flux, vegetation leaf temperature, water temperature, and downwelling and upwelling shortwave radiation.

Plot-scale sites

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Figure 7b. Plot-scale shrub site. MMS instruments here included: Soil temperature, soil moisture, and heat flux. This site was within 100 m of the tussock tundra site so that weather and radiant energy observations at the tussock tundra site applied here as well.

Figure 7c. Plot-scale wet sedge. MMS instruments here included: Soil temperature and water temperature. This site was within 0.5 km of the tussock tundra site so that weather and radiant energy observations at the tussock tundra site applied here as well.

V- and H-polarized brightness data at 1.4, 6.7, 19, and 37 GHz were collected at the tussock tundra and shrub sites. The wet sedge site lay beyond a damaged area of the access road that could have easily damaged our field truck. Because the wet sedge site looked very much like standing water from the perspective of H-polarized microwave radiometry at the frequencies of interest, H-polarized satellite data are expected to be of greatest value, we knew water temperature, and the surface of the standing water was typically smooth relative to the microwave wavelengths of interest, we will be able to predict the microwave brightness of the

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wet sedge using simple Fresnel theory. The combination of risk to the equipment and an anticipate low value of the data justified removing the wet sedge site from the observing rotation. Radio Frequency Interference (RFI) from defense radars on the North Slope of Alaska played havoc with our 1.4 GHz data records. The radar introduced intermittent pulse signals with a repetition rate of about once per second that were orders of magnitude greater than the thermal signal we were observing. In theory, we could observe between the pulses, but we had no way of timing the observations to avoid the pulses. There are RFI mitigation techniques that will allow meaningful 1.4 GHz brightness observations, but the chosen technique must be built into the control logic of the radiometer. This will be a condition of future 1.4 GHz observations. Figure 8 is an example of radiobrightness data collected at the tussock tundra site. Diurnal V- and H-polarized, 6.7, 19, and 37 GHz brightness temperatures and Thermal Infrared Radiant (TIR) temperatures exhibit decreasing brightness with decreasing frequency, a result of liquid water in and around the tussocks. We also observe diminished amplitude with decreasing frequency, a result of emission at depth within the tussock where the diurnal pulse is beginning to be subdued.

Figure 8. Diurnal temperatures at a 350 incidence angle for 6.7, 19. and 37 GHz brightness and for TIR. These are REBEX-10 data for tussock tundra

A comparison between REBEX-10 and AMSR Observations

The combination of REBEX-10 and AMSR data allow us to extend our plot-scale findings to satellite resolution-scale. Time-series comparisons of these data require synthesizing AMSR footprints centered on the REBEX-10 site. AMSR-E is in a Sun- synchronous low Earth orbit and scans along arcs of nadir-centered cones whose half angle is 550. The Instantaneous Field of View (IFOV), or footprint on the ground, along one of these scans is nearly elliptical with an aspect ratio of 1.66 and an orientation that varies by ~700 along a single scan. AMSR data at the lower frequencies are over-sampled permitting a Backus-Gilbert Equal Area Scaling–Grid (EASE-Grid) synthesis from elliptical swath footprints (Figure 9a), which move and rotate spatially from pass-to-pass, to circular synthetic footprints (Figure 9b), which are spatially stable and centered on the REBEX-10 site from pass-to-pass (Gu and England, 2004). These

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synthesized footprints are 45 km in diameter, representing a 15% improvement in spatial resolution relative to the swath data.

Figures 9a (left) and 9b (right) show the 6.9 GHz, H-pol footprint and the EASE-Grid synthetic footprint, respectively. Red rings delineate the 3 dB patterns in both figures. The 3 dB swath pattern in 9a is elliptical, and moves spatially and changes orientation from pass-to-pass. The 3 dB synthesized pattern in 9b is circular and stationary from pass-to-pass. Side-lobes generated in the synthesis pattern are ≥20 dB below the beam maximum and contribute negligibly to synthetic scene brightness.

Figure 10. 6.9 GHz AMSR data synthesized to be centered on the REBEX-10 field site. The plot also shows rain events during the period.

Figure 10, a plot of 6.9 GHz AMSR data synthesized to be centered on the REBEX-10 field site is included to show sensitivity to recent rainfall events. For example, note the ~10 Kelvins decrease in brightness after the event on day 168. We observed an even greater sensitivity of rainfall events in the site radiobrightness data.

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Figure 11. A comparison of AMSR data with plot-scale data for tussock tundra.

Figure 11 shows that REBEX-10 V-pol 37 and 19 GHz plot-scale data for tussock tundra compare well with the corresponding AMSR satellite resolution-scale data. The V-pol 6.7 GHz plot-scale data are ~4 Kelvin warmer than the V-pol 6.9 GHz AMSR data (the difference between 6.7 and 6.9 GHz cannot explain this brightness difference). H-polarized 37, 19, and 6.7 GHz plot-scale data are ~3, ~4, and ~11 Kelvin warmer than their corresponding AMSR data. The conclusions from REBEX-3 that 19 and 37 GHz scene brightness temperatures are the same at plot- and satellite resolution-scales are not valid for the H-pol data at this site. The REBEX-10 differences at 6.9 GHz suggest significant sub-pixel variability. The synthetic AMSR footprint at the REBEX-10 site includes tussock tundra, dry heath, and wet sedge. Wet sedge looks sufficiently like standing water to a microwave radiometer that we chose to observe only tussock tundra and dry heath at the plot-scale. We believe that area-weighted combinations of tussock tundra, dry heath, and standing water will explain the AMSR observations. We are currently testing this hypothesis. If it proves true, there is an optimal 3-part disaggregation of AMSR observations that corresponds to the 3 terrain types. Finding 1 – 6.9 GHz AMSR data is sensitive to moisture in the active layer. This suggests that

current satellite data could be providing useful hydrologic monitoring of the pan-Arctic if the necessary models and techniques were in place.

Finding 2 – 6.9 GHz plot-scale data for tussock tundra and shrub are sensitive to moisture in the active layer. These observations are consistent with the satellite observation being composed of an aggregate of emission from tussock tundra, shrub, and standing water terrains.

Finding 3 – The V-pol 19 and V- and H-pol 37 GHz data appear the same at plot- and satellite-scales. This is consistent with REBEX-3 observations that these frequencies and polarizations are primarily sensitive to the vegetation.

Finding 4 – The H-pol 19 and V- and H-pol 6.7 GHz data differ between plot- and satellite-scales. The 19 GHz conclusion differs from a conclusion of REBEX-3. These observations

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are consistent with the lower frequencies being sensitive to sub-pixel variations in water storage in the active layer.

Finding 5 – The satellite observations of the Alaskan North Slope are likely to be explained by a area-weighted aggregate of tussock tundra, shrub, and standing water. The hypothesis is being tested. If tests prove it to be true, the combination of SVAT models for tussock tundra and shrub will permit an optimum 2-part disaggregation of the satellite data.

Finding 6 – To be useful, 1.4 GHz observations must employ a mitigation technique that excludes pulse RFI from defense radars in the Arctic.

Products – In addition to the Findings, this investigation provides a dataset that will allow validation of SVAT models for tussock tundra and shrub. These data will be archived as part of Ms. Haley Gu’s dissertation under a new digital dissertation opportunity. We had planned to complete these SVAT models as part of this investigation. The need to develop a new model for the thermal conductivity and moisture retention of organic soils (Gu et al, 2006), and the opportunity to develop a scheme for synthesizing a circular footprints at improved spatial resolution forced us to delay development of the SVAT models until the next project. A proposal has been submitted to NASA to use data from this investigation to complete the two SVAT models.

Section III. Broader Impacts The proposed project spanned two departments of the College of Engineering at the University of Michigan, the Departments of Atmospheric, Oceanic, and Space Sciences and the Department of Electrical Engineering and Computer Science. It provided several undergraduate environmental scientists and electrical engineers opportunities to work in a team environment on an exciting environmental project that would have significant impact. We participated in the NSF OPP TREC Program where a middle-school science teacher joined us for two months at the Toolik Lake LTER. She was able to broadcast live video of our work near Toolik Lake to her class in Wisconsin and to other classes participating in the TREC Project. Two female graduate students participated in the Project. Ms. Haley Gu was lead on the REBEX-10 field experiment, developed the optimal footprint synthesis technique for AMSR data, and will complete test of the canonical terrain type hypothesis as part of her Ph.D. dissertation. Ms. Hanh Pham developed and calibrated the fully-polarimetric, 6.7 GHz radiometer for REBEX-9 and REBEX-10, and participated in the REBEX-10 field experiment. One female undergraduate participated in the Project. Ms. Nupur Srivastava helped us develop the new TIR and video sensors on TMRS3. The PI also gave frequent talks at the pre-college level about his experiences in science and as an astronaut. The objective was to motivate student interest in the STEM fields.

Section IV. Journal Articles, Conference Proceedings, and Abstracts (additional journal articles are in preparation)

Gu, H., T-Y Lin, J. Judge, A.W. England, and J.J. Casanova, Estimating soil thermal conductivity and water retention from readily available soil properties, submitted to Water Resources Res, February 2006.

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Kim, E.J., and A.W. England, Passive microwave remote sensing of land surface conditions in arctic tundra regions, Proc. of 6th Circumpolar Symposium on Remote Sensing of Polar Environments, Yellowknife, NWT, Canada, June 12-14, 2000.

Kim, E.J., and A.W. England, Diurnal and Seasonal Cold Lands Signatures in SSM/I-scale Microwave Radiometry of the North Slope of Alaska, Proc. IGARSS’01, Sidney Australia, July 9-13, 2001.

England, A.W., and R.D. DeRoo, STAR-Light: An enabling technology for modeling arctic land surface hydrology, Proc. IGARSS’02, Toronto, Canada, June 24-28, 2002. [invited]

van Nieuwstadt, L., R. De Roo, D. Boprie, R. Rizor, P. Hansen, A.W. England, H. Pham, and B. Lim, A compact direct detection receiver for L-band STAR radiometry, Proc. IEEE MTT, Philadelphia, PA, June 10-13, 2003.

Pham, H., R. DeRoo, A.W. England, L. van Nieuwstadt, and J. Glettler, A C-Band radiometer based on STAR-Light receivers: design approach, implementation, and performance evaluation, Proc. IGARSS’03, Toulouse, France, July 21-25, 2003.

Gu, H., and A.W. England. Backus-Gilbert resampling of AMSR data to synthesize circular footprints with potentially improved spatial resolution, Proc. IGARSS’04, Anchorage, Alaska, September 20-24, 2004.

Pham, H., A.W. England, V. Solo, and E.J. Kim, Experimental and modeling investigation of microwave radiometer noise statistics for Earth remote sensing, Proc. IGARSS’05, Seoul, Korea, 25-29 July, 2005.

De Roo, R.D, A.W. England, Haoyu Gu, Hanh Pham, and H. Elsaadi, Ground-based Radiobrightness Observations of the Active Layer Growth on the North Slope near Toolik Lake, Alaska, Proc. IGARSS’06, Denver, CO, July 31 – August 4, 2006.

Kim, E., A.W. England, and J. Judge, Scaling Issues between plot and satellite radiobrightness observations of arctic tundra, AGU Fall Meeting, San Francisco, CA, December 15-19, 2000.

England, A.W., STAR-Light, an enabling technology for arctic land surface hydrology, Earth System Science Institute Colloquium, University of Reading, England, July 5, 2001, [invited].

DeRoo, R., A.W. England, C. Ruf, L. Van Nieuwstadt, P. Hansen, T. Rashid, J. Harvey, R. Miller, and D. Boprie, STAR-Light: An airborne L-Band synthetic thinned aperture direct sampling digital radiometer for soil moisture monitoring in the Arctic, Specialist Meeting on Microwave Remote Sensing, Boulder, Colorado, November 5-9, 2001.

England, A.W., and R. DeRoo, STAR-Light: Enabling a new vision for land surface hydrology in the Arctic, AGU Fall Meeting, San Francisco, CA, December 10-14, 2001.

De Roo, R., A.W. England, C. Ruf, L. Van Nieuwstadt, P. Hansen, T. Rashid, J. Harvey, R. Miller, and D. Boprie, STAR-Light: An airborne L-band synthetic thinned aperture direct sampling digital radiometer for soil moisture monitoring in the Arctic, 3rd SMOS Cal-Val Workshop, Oberfaffenhofen, Germany, December 10-12, 2001.

England, A.W., STAR-Light: An enabling technology for arctic land surface hydrology, seminar at NSF, Washington, DC, May 20, 2002 [invited].

England, A.W., and R.D. DeRoo, STAR-Light: An enabling technology for modeling arctic land

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surface hydrology, (invited) IGARSS’02, Toronto, Canada, June 24-28, 2002. England, A.W., The impact of remote sensing upon global hydrology, U. of Michigan Society of

Fellows Lecture, November 11, 2002 [invited]. Gu, H., H. Pham, Y.C. Chung, and A.W. England, Model-Based Monitoring of Pan-Arctic

Tundra, The Arctic Forum 2003, ARCUS, Arlington, VA, April 28-29, 2003. Gu, H., and A.W. England, A Backus-Gilbert resampling scheme for AMSR-E Data that offers

improved footprint shape and spatial resolution, Proc. IGARSS’04, Anchorage, Alaska, September 20-24, 2004.

Gu, H., H. Pham, Y-C Chung, R.D. DeRoo, and A.W. England, Model-Based Monitoring of Pan-Arctic Tundra, ARCSS All Hands Meeting, Seattle, WA, June 1-3, 2005.

Gu, Haley, Tzu-yun Lin, Jasmeet Judge, and A.W. England, A Soil Thermal Conductivity Model Based upon Component Conductivities and Fractions for use in Soil-Vegetation-Atmosphere Transfer Models, AGU Fall Meeting, San Francisco, CA, Dec 5-9, 2005.

Pham, H., R. D. De Roo, and A.W. England, Simple calibration scheme for a fully polarimetric correlating radiometer, MicroRad’06, San Juan, Puerto Rico, Feb 28-Mar 3, 2006.

Section V. References Betts, A., S. Hong, and H. Pan, 1996. Comparison of NCEP/NCAR reanalysis with 1987 FIFE

data, Monthly Weather Review, 124(3): 362-383. Bonan, G., 1996. A Land Surface Model (LSM Version 1.0) for ecological, hydrological, and

atmospheric studies: Technical description and user’s guide, Tech. Rep. NCAR/TN-417+STR, Climate and Global Dynamics Division, NCAR.

Burke, E., W. Shuttleworth, K. Lee, and L. Bastidas, 2001. Using area-average remotely sensed surface soil moisture in multipatch land data assimilation systems, IEEE Trans. Geosci. Remote Sensing, 39, pp. 2091-2100.

Davis, D.T., Zhengxiao Chen, Hwang, J-N., Tsang, L., and Njoku, E. (1995). Solving inverse problems by Bayesian iterative inversion of a forward model with applications to parameter mapping using SMMR remote sensing data, IEEE Trans. Geosci. and Remote Sens., 33, 1182-1193.

Dickinson, R., A. Henderson-Sellers, and P. Kennedy, 1993. Biosphere-atmosphere transfer scheme (BATS) version 1e as coupled to the NCAR Community Climate Model, Tech. Rep. NCAR/TN-387+STR, Climate and Global Dynamics Division, NCAR.

Dickinson, R., A. Henderson-Sellers, P. Kennedy, and M. Wilson, 1986. Biosphere-atmosphere transfer scheme (BATS) for the NCAR Community Climate Model, Tech. Rep. NCAR/TN-275+STP, Atmospheric Analysis and Prediction Division, NCAR.

England, A.W., 1990. Radiobrightness of diurnally heated, freezing soil, IEEE Trans.Geosci. Remote Sensing, 28, pp.464-476.

England, A.W., and Galantowicz, J.F. (1994). A volume emission model for the radiobrightness of prairie grass, Proc. of IGARSS'94, Pasadena, CA, August 8-12.

England, A. and J.F. Galantowicz, 1995. Observed and modeled radiobrightness of prairie grass in early fall,” Proc. of IGARSS’95, IEEE GRSS, Florence, Italy, July 10-12.

Entekhabi, D., H. Nakamura, and E. G. Njoku, 1994. Solving the inverse problem for soil moisture and temperature profiles by sequential assimilation of multifrequency remote sensing observations, IEEE Trans. of Geoscience and Remote Sens., 32, pp. 438-448.

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Galantowicz, J. F., D. Entekhabi, and E. G. Njoku, 1999. Tests of Sequential Data Assimilation for Retrieving Profile Soil Moisture and Temperature from Observed L-Band Radiobrightness, IEEE Trans. on Geoscience and Remote Sens., vol. 37, pp. 1860-1870.

Gu, H., and A.W. England, 2004. Backus-Gilbert resampling of AMSR data to synthesize circular footprints with potentially improved spatial resolution, Proc. IGARSS’04, Anchorage, Alaska, September 20-24.

Gu, H., T-Y Lin, J. Judge, A.W. England, and J.J. Casanova, Estimating soil thermal conductivity and water retention from readily available soil properties, submitted to Water Resources Res, February 2006.

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