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Journal review on soil moisture memory Slide 1 Journal review on soil moisture memory Slide 2 Journal review on soil moisture memory Slide 3 Journal review on soil moisture memory Slide 4 Journal review on soil moisture memory Slide 5 Journal review on soil moisture memory Slide 6 Journal review on soil moisture memory Slide 7 Journal review on soil moisture memory Slide 8 Journal review on soil moisture memory Slide 9 Journal review on soil moisture memory Slide 10 Journal review on soil moisture memory Slide 11 Journal review on soil moisture memory Slide 12 Journal review on soil moisture memory Slide 13 Journal review on soil moisture memory Slide 14 Journal review on soil moisture memory Slide 15 Journal review on soil moisture memory Slide 16 Journal review on soil moisture memory Slide 17
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Journal review on soil moisture memory

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Reviewed two papers regarding soil moisture memory: Koster and Suarez (2000) and Ghannam et al. (2017)

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Journal review on soil moisture memory

  1. 1. Soil Moisture Memory 6 Nov, 2020 @ BGG 5th Meeting Ryoko Araki
  2. 2. What is soil moisture memory? Quantifying via autocorrelation 02 01 Quantifying via persistency 03 Challenges and opportunities 04
  3. 3. Extremely dry/wet condition persists
  4. 4. … because of soil moisture–atmosphere feedback Introduction Seneviratne et al., 2010 ② Decrease of actual ET ② Increase of sensible heat flux ③ Increase of temperature ④ Higher vapor deficit ① Dry soil condition
  5. 5. How long does the soil moisture ‘remember’ the anomaly state? Introduction Soil moisture memory • 2-3 months (Vinnikov and Yeserkoepora, 1991’s observation in Russia) • 2 month (Entin et al., 2000’s observation in China, Mongolia, and Illinois) Soil moisture feedback with temperature • Several months (Huang et al., 1996)
  6. 6. How to quantify the time-scale of soil moisture memory? • Autocorrelation • Persistency Introduction
  7. 7. Quantification via auto-correlation Method ・・・・・・・ https://www.youtube.com/watch?v=ZjaBn93 YPWo&t=480s
  8. 8. Quantification via auto-correlation Method Koster and Suarez (2000) • Time shift = 31days • Developed autocorrelation function for land-surface model, that includes non-stationality and persistency of climate inputs • Applied the method on AGCM-LSM
  9. 9. 1-month auto-correlation 9 Contribution of … ET Runoff Antecedent soil moisture Koster and Suarez (2000) Results
  10. 10. Challenges in quantification via auto-correlation Strength • Autocorrelation equation can be derived from stochastic land-surface model  prognostic analysis is possible Weakness • Dependency on the mean value in deriving covariance • Ignores positive/negative value of soil moisture change/value (pointed out in McColl et al., 2019)
  11. 11. Quantification via persistency Determined by telegraphic approximation, which allows to isolate event clustering without being influenced by event amplitudes Ghannam et al., (2017)
  12. 12. Quantification via persistency: Results Method Ghannam et al., (2017) • Examined persistency of in-situ soil moisture data • On-off switches of rainfall events do not coincide with the one of soil moisture  the precipitation features, or evaporation cycles • Persistence rainfall during dry period is shorter than that of the soil moisture  some implication to soil moisture-atm feedback??? • Soil moisture values are aggregated over entire soil layer  Analysis by different layer?
  13. 13. Challenges in quantification via persistency Strength • Able to investigate persistence of high-value period (wet) and low-value period (dry)  allows investigation of seasonal soil moisture feedback and its transition Weakness • Only diagnostic (not able to predict the future states)
  14. 14. Conclusion 14 • Time-scale of soil moisture memory is important to understand the soil moisture feedback processes, and to improve weather/drought prediction • Auto-correlation analysis  prognostic analysis of soil moisture memory based on LSM • Persistence analysis  diagnostic investigation of seasonal soil-moisture atmosphere feedback based on observed/simulated data
  15. 15. Discussion / question 15 • Can the autocorrelation analysis be applied to any other purposes? • If we have better understanding of soil moisture memory, will it improve the weather prediction? • Can the soil moisture memory be observed at watershed scale? • Is the map by Koster and Suarez (2000) reasonable? What pattern do you see? • Any point unclear?
  16. 16. References 16 Akbar, R., Short Gianotti, D. J., McColl, K. A., Haghighi, E., Salvucci, G. D., & Entekhabi, D. (2018). Estimation of Landscape Soil Water Losses from Satellite Observations of Soil Moisture. Journal of Hydrometeorology, 19(5), 871–889. https://doi.org/10.1175/JHM-D-17-0200.1 Entin, J. K., Robock, A., Vinnikov, K. Y., Hollinger, S. E., Liu, S., & Namkhai, A. (2000). Temporal and spatial scales of observed soil moisture variations in the extratropics. Journal of Geophysical Research, 105(D9), 11865–11877. https://doi.org/10.1029/2000JD900051 Ghannam, K., Nakai, T., Paschalis, A., Oishi, C. A., Kotani, A., Igarashi, Y., Kumagai, T. ’omi, & Katul, G. G. (2016). Persistence and memory timescales in root-zone soil moisture dynamics. Water Resources Research, 52(2), 1427–1445. https://doi.org/10.1002/2015WR017983 Koster, R. D., & Suarez, M. J. (2001). Soil moisture memory in climate models. Journal of Hydrometeorology, 2(6), 558–570. https://doi.org/10.1175/1525-7541(2001)002<0558:SMMICM>2.0.CO;2 McColl, K. A., He, Q., Lu, H., & Entekhabi, D. (2019). Short-Term and Long-Term Surface Soil Moisture Memory Time Scales Are Spatially Anticorrelated at Global Scales. Journal of Hydrometeorology, 20(6), 1165–1182. https://doi.org/10.1175/JHM-D-18-0141.1 McColl, K. A., Wang, W., Peng, B., & Akbar, R. (2017). Global characterization of surface soil moisture drydowns. Geophysical. https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2017GL072819 Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner, I., Orlowsky, B., & Teuling, A. J. (2010). Investigating soil moisture– climate interactions in a changing climate: A review. Earth-Science Reviews, 99(3-4), 125–161. https://doi.org/10.1016/j.earscirev.2010.02.004 Vinnikov, K. Y., Robock, A., Speranskaya, N. A., & Schlosser, C. A. (1996). Scales of temporal and spatial variability of midlatitude soil moisture. Journal of Geophysical Research, 101(D3), 7163–7174. https://doi.org/10.1029/95JD02753 Vinnikov, K. Y., & Yeserkepova, I. B. (1991). Soil Moisture: Empirical Data and Model Results. Journal of Climate, 4(1), 66–79. https://doi.org/10.1175/1520-0442(1991)004<0066:SMEDAM>2.0.CO;2
  17. 17. 17 Model Satellite observation In-situ observation Autocorrelation (monthly-scale) Vinnikov and Yeserkoepora (1991); Vinnikov et al., (1996); Entin et al., (2000) Autocorrelation (weekly-scale) Persistency (monthly-scale) Persistency (weekly-scale) Ghannum et al., (2018) McColl et al., (2019) Koster and Suarez., (2000) McColl et al., (2017) Akbar et al., (2018)

Reviewed two papers regarding soil moisture memory: Koster and Suarez (2000) and Ghannam et al. (2017)

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