Jenkins MacedoChristina Geller

GEOG392November 4, 2013

Discussion Questions: Monitoring of Surface and Groundwater Resources

Choi et al., 20081. On page 2, the authors explain the problems with the three measurement systems for calculating

soil moisture. What problems do you think are more concerning than others? What problems will carry over in a mixed analysis scheme?

2. On page 4, Choi et al. explain how the vegetation temperature and the surface temperature are assumed to be the same in the calculation of soil moisture by AMSR­E. Do you agree with this assumption? Why or why not?

3. Given what you learned about the Common Land Model during our discussion of surface albedo from our discussion of surface albedo and the results from this study, would you push for further utilization of CLM? Why or why not?

4. The authors suggest developing a better understanding of the impact of slope and elevation on soil moisture estimations. Given what you know already, what impacts would you expect to see?

5. Table 3 on page 8 shows how the correlation coefficient (R2) declined when CLM AMSR­E are used together yet the Root Mean Squared Error (RMSE) typically improved. Why do you think that is?

Reichle et al., 2007

1. On page 1, the authors’ claimed that “satellite retrievals alone; however, are not sufficient for weather and climate forecast initialization because of gaps in spatial and temporal coverage and because model variables, such as deeper root zone soil moisture cannot be observed from space.” Given what we’ve have learned thus far, do you agree or disagree? What are the associated complexities of using meteorological forcing inputs from land surface model with satellite­driven soil moisture retrievals?

2. On page 2, it is stated that “via the land surface model, the system propagates the surface information the satellite into deeper soil and thereby provides improved estimates of root zone soil moisture.” What do you would be some of the setbacks with this approach? How would this approach be applicable in ecosystems with dense forest canopy and those with lesser canopy coverage?

3. On page 2, the authors noted that rescaling satellite data prior to the assimilation process by matching the satellite data’s cumulative distribution function to the model’s climatology builds heavily on the anomaly time series, which is the basis for forecast initialization, instead of relying on the mean square error measures, which cannot be validated. Are four years of data sufficient ground to make this assertion about the validation process? Do you agree with their claim? Why or why not?

4. On page 2 in the second column in the 3rd paragraph under satellite retrievals, the authors described that the AMSR­E satellite retrievals of surface soil moisture data used are from NASA Level­2B AMSR­E “AE_Land” product, which includes measurements of surface soil moisture, a vegetation/roughness correction, and “quality control variables.” What are the quality control variables? Do you think the authors’ could have deliberated on these variables a little more?

5. What are your critiques about the structure of the paper and the way in which results were presented? Who do you think are the targeted audience for such a paper apart from just the fact that it was published in the Journal of Geophysical Research?

Swenson et al., 2008

1. Who do you think are the targeted audience of this paper and why? Was the subject matteradequately assessed?

2. Given the scope of the data used, do you think the authors did a great job explaining the data,methods, results, and purpose of the research adequately?

3. On page 2 in the second column, the authors claim that “the methods described account fordeeper soil moisture is applied to the region of the Southern Great Plains of the U.S., but isapplicable to other observational data sets, whether in situ or remotely sensed data.” Do youagree with this claim given the challenges in many developing countries where in situ andremotely sensed data acquisition is not only a logistical problem?

4. What are some of the complexities in monitoring and assessing groundwater resources; giventhe potential for groundwater to extend beyond geographic boundaries of states and regions?

Syed et al., 20081. Who do you think are the targeted audience of this paper? Why?2. What are some of the major challenges/advantages of this approach?3. Do you agree with the authors’ claim that with longer time series, GRACE will contribute to

improved the understanding of how terrestrial water storage respond to climate change variability?

4. Are the results from their analyses compelling enough to warrant the advancement of this science?

5. If you were to make a constructive input to the methodology in the advancement of this

approach, what would your recommendation be and why?

de Jeu et al., 20081. On page 408, the authors explain that “a data mask was developed on the AMSR­E data

products to eliminate those data cells where data values were either meaningless due to frozen soil conditions, snow cover or excessive vegetation”. What biases do you see arising from the use of this data mask?

2. The AMSR­E developed by NSIDC had a correlation coefficient of ­0.01 in the France study area and 0.00 for Spain. Because of this, the authors decided to exclude AMSR­E (NSIDC) from their comparison analysis. What do you think the authors might have missed contributing to the field by excluding this soil moisture product?

3. This study pointed out a strong similarity between both products in sparse to moderate vegetated regions with an average correlation coefficient of 0.83. Given this similarity, do you see a benefit of further developing one product or using one product over the other?

4. Do you agree with the authors’ suggestion of combining the two products?5. The authors explain the reasons why low correlations may be found in densely vegetated areas

and deserts. Are there other reasons you think are missing from their explanation?

General Questions

1. If remote sensing of soil moisture is primarily capable of representing variation in near surfacewetness (e.g. upper 5 to 10 cm of soil) and not wetness deeper in the rooting zone, what doesthis mean for the processes that can be well­presented by this product?

2. Does satellite­based microwave remote sensing of soil moisture have an adequate spatialresolution for representing the processes in which we are interested? How does its spatialrepresentativeness compare to other products we are used to dealing with (e.g. NDVI, surfacetemperature, etc.)?

3. Does gravity­based remote sensing of terrestrial water storage have a spatial resolutionadequate for representing the processes of interest? What processes can and cannot becharacterized at this resolution?

4. What are some of the potential challenges with integrating soil moisture or terrestrial waterstorage products with the VI or surface temperature products that are also used forcharacterizing evapotranspiration and the surface water status?

Bibliography

Choi, M., Jacobs, J.M., and Bosch, D.D. (2008). Remote Sensing Observatory Validation of Surface SoilMoisture using Advanced Microwave Scanning Radiometer E, Common Land Model, and Ground­basedData: Case Study in SMEX03 Little River Region, Georgia, U.S. Water Resources Research, Vol. 44, pg.1­14.

de Jeu, A.M., Wagner, W., Holmes, T.R.H., Dolman, A.J., van de Giesen, N.C., and Friesen, J.(2008). Global Soil Moisture Patterns Observed by Space Borne Microwaves Radiometers andScatterometers. Survey Geophysics, Vol. 29, pg. 399­420.

Reichle, R.H., Koster, R.D., Lui, P., Mahanama, S.P.P., Njoku, E.G., and Owe, M., (2007).Comparison and Assimilation of Global Soil Moisture Retrievals from the Advanced Microwave ScanningRadiometer for the Earth Observing System (AMSR­E) and the Scanning Multichannel MicrowaveRadiometer (SMMR). Journal of Geophysical Research, Vol. 112, pg. 1­14.

Swenson, S., Famiglietti, J., Basara, J., and Wahr, J. (2008). Estimating Profile Soil Moisture andGroundwater Variations using Gravity Recovery and Climate Experiment (GRACE) and Oklahoma MesonetSoil Moisture Data. Water Resource Research, Vol. 44, pg. 1­12.

Syed, T.H., Famiglietti, J.S., Rodell, M., Chen, J., and Wilson, C.R. (2008). Analysis of TerrestrialWater Storage Changes from Gravity Recovery and Climate Experiment (GRACE) and Global Land DataAssimilation System (GLDAS). Water Resources Research, Vol. 44, pg. 1­15.