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Keywords:

  • soil moisture feedbacks;
  • regional climate modeling;
  • summer light precipitation variability

Abstract

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Approach
  5. 3. Results
  6. 4. Conclusions
  7. Acknowledgements
  8. References

This study investigates the role of soil moisture feedbacks in influencing interannual variability of summer light precipitation frequency over East Asia by analyzing two long-term simulations with and without interactive soil moisture using the Weather Research and Forecasting model coupled with the Noah land model. It is shown that soil moisture–atmosphere coupling significantly amplifies interannual variability of summer light precipitation frequency over many areas, in particular the climatic and ecological transition zones, contributing to 30–60% of the variance. The results suggest that soil moisture-atmosphere coupling constitutes an important cause explaining the variations of summer light precipitation events over East Asia. Copyright © 2012 Royal Meteorological Society


1. Introduction

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Approach
  5. 3. Results
  6. 4. Conclusions
  7. Acknowledgements
  8. References

Precipitation is one of the most important variables describing our climate. Summer precipitation, which supplies necessary water for growing crops, is critical to human life and entire ecosystem. There are numerous studies exploring its changes, effects, mechanisms and prediction. Most of them focused on summer heavy or extreme precipitation, which can lead to a local flooding and runoff in a short period of time and thus bring tremendous losses of economy (e.g. Easterling et al., 2000; Gong and Wang, 2000; Zhai et al., 2005; Trenberth, 2011). However, light precipitation has received little concerns. Light precipitation allows water more time to soak into the soil and result in little surface runoff and streamflow, leaving soils much wetter at the end of day (Trenberth et al., 2003; Sun et al., 2006). Some studies have reported that the reduction of light precipitation frequency can cause occurrence of drought events (e.g. Yan and Yang, 2000; Qian et al., 2009, 2010; Lei and Duan, 2011; Lei et al., 2011). These facts thus highlight the need for improving our understanding of summer light precipitation variations.

Summer light precipitation frequency, which makes a major contribution to total precipitation frequency, has experienced evident interannual and decadal variations over East Asia during the last several decades. (e.g. Yan and Yang, 2000; Gong et al., 2004; Liu et al., 2005, 2011; Qian et al., 2007, 2009, 2010; Ren et al., 2010; Lei et al., 2011). Summer light precipitation variations over East Asia has been previously attributed to changes in the atmospheric circulation (e.g. Gong et al., 2004; Zhou and Yu, 2005; Qian et al., 2010), global or regional warming and changes in aerosols (e.g. Gong and Wang, 2000; Zhao et al., 2006; Qian et al., 2007, 2009, 2010; Liu et al., 2009; Lei et al., 2011; Liu et al., 2011). Recently, soil moisture–atmosphere coupling has been demonstrated to play a key role in influencing summer precipitation variability over particular areas (e.g. Koster et al., 2004; Zhang et al., 2008a, 2008b; Seneviratne et al., 2010). However, the role of soil moisture feedbacks in summer light precipitation is not clearly identified. In this study, we use two Weather Research and Forecasting (WRF) model simulations described by Zhang et al. (2011) to investigate the role of soil moisture–atmosphere coupling in influencing interannual variability of summer light precipitation frequency over East Asia.

2. Approach

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Approach
  5. 3. Results
  6. 4. Conclusions
  7. Acknowledgements
  8. References

In this study, two regional climate model simulations are examined, employing the WRF model coupled with the Noah land model (Zhang et al., 2011). The model domain spans 8160 km (west–east) by 5760 km (south–north) at 60 km grid spacing, centered at eastern China. The control run (CTL) integrates for the period of January 1979 to December 1999, driven with the National Centers for Environmental Prediction (NCEP)-Department of Energy (DOE) reanalysis. The other experiment (SoilM) repeats summer simulation with the same model setup, except that soil moisture value at each time step is prescribed as the climatology of CTL. The climatology of CTL is produced by averaging hourly soil moisture data for 1980–1999, which keeps diurnal and subseasonal evolutions but removes interannual variability. For more details of model configuration refer to Zhang et al. (2011).

The 0.5 °C gridded daily precipitation data set from the East Asia gauge-based analysis (Xie et al., 2007) is used to investigate simulated summer light precipitation of CTL. The data set has been constructed using the optimal interpolation-based technique to gauge observations at over 2200 stations collected from several individual sources. In this study, we analyze summer (June–July–August) light precipitation events with daily precipitation less than and equal to 2 mm (p≤2 mm day−1), 5 mm (p≤5 mm day−1) and 10 mm (p≤10 mm day−1). The variance analyses are applied to objectively quantify the contribution of soil moisture feedbacks to the interannual variability of summer light precipitation frequency.

3. Results

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Approach
  5. 3. Results
  6. 4. Conclusions
  7. Acknowledgements
  8. References

Figure 1 compares geographic distributions of summer mean light precipitation frequency over East Asia during 1980–1999 between observations and WRF model simulations. The observed summer mean light precipitation frequency with p≤2 mm day−1, p≤5 mm day−1 and p≤10 mm day−1 exhibits a similar pattern. The observed summer light precipitation frequency is relatively high over the Northwest and relatively low over the tropics and southern China. The WRF model captures the observed summer light precipitation frequency pattern rather well. For the magnitude, WRF model generally simulates the observed summer light precipitation frequency well over most areas of East Asia except for some areas of the Northwest, where summer light precipitation frequency is overestimated.

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Figure 1. Observed (left) and modeled (right) summer mean light precipitation frequency (days per year) for the period 1980–1999: (a, b) ≤2 mm day−1, (c, d) ≤5 mm day−1 and (e, f) ≤10 mm day−1

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Figure 2 compares geographic distributions of interannual variability of summer light precipitation frequency expressed by its standard deviation over East Asia during 1980–1999 between the observations and WRF model simulations. The observed light precipitation variability with p≤2 mm day−1 shows a clear southeast to northwest gradient, with maximum value appearing over the tropics and southern China, and minimum value over the Northwest. A similar pattern is seen for interannual variability of summer light precipitation with p≤5 mm day−1 and p≤10 mm day−1. The WRF model captures the features very well. The model biases mainly occur over some areas of the Northwest and the tropics, where interannual variability of summer light precipitation frequency is underestimated.

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Figure 2. Observed (left) and modeled (right) standard deviation of summer light precipitation frequency (days per year) for the period 1980–1999: (a, b) ≤2 mm day−1, (c, d) ≤5 mm day−1 and (e, f) ≤10 mm day−1

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To examine the changes induced by soil moisture–atmosphere coupling, we compute the differences in standard deviation of summer light precipitation frequency between CTL and SoilM because soil moisture interactions are disabled in SoilM. Figure 3 presents that the differences in standard deviation for summer light precipitation frequency with p≤2 mm day−1, p≤5 mm day−1 and p≤10 mm day−1 show a similar pattern. The soil moisture–atmosphere coupling generally exerts amplifying effects on interannual variability of summer light precipitation frequency over East Asia. Meanwhile, we note that the amplifying effects depend on climate regimes. The significantly amplifying effects mainly appear over the climatic and ecological transition zones of the southern Siberia–northern Mongolia region and northern China with the magnitude on the order of 0.5–1.5 days per year. The most significantly amplifying effects are found for the light precipitation events with p≤2 mm day−1, which have more grid cells passing the 90% confidence level. The amplifying effects are also seen over many areas of western China, and a portion of southern China. In contrast, significantly damping effects are limited to small areas, mainly appearing over some areas of the Yangtze-Huai River Valley. The damping effects may be caused by negative soil moisture feedbacks or large-scale processes (e.g. Giorgi et al., 1996; Findell and Eltahir, 2003; Cook et al., 2006). Generally speaking, soil moisture has much less significant effects on summer light precipitation frequency over humid and arid regions than those over the climatic and ecological transition zones.

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Figure 3. Differences in standard deviation of summer light precipitation frequency (days per year) between CTL and SoilM: (a) ≤2 mm day−1, (b) ≤5 mm day−1 and (c) ≤10 mm day−1. The solid circles represent that the values are significant at the 90% level by F test

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We further calculate the ratio of the difference in interannual variance between CTL and SoilM to the variance in CTL, which reflects percent contribution of soil moisture–atmosphere coupling to the variance of interannual summer light precipitation frequency (Figure 4). Again, the light precipitation events with p≤2 mm day−1, p≤5 mm day−1 and p≤10 mm day−1 exhibit a similar pattern. Over the regions, where significant changes occur, soil moisture–atmosphere coupling makes a large contribution to interannual variability of summer light precipitation, accounting for 30–60% of the total variance.

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Figure 4. Percent contribution of soil moisture–atmosphere coupling to the variance of interannual summer light precipitation frequency: (a) ≤2 mm day−1, (b) ≤5 mm day−1 and (c) ≤10 mm day−1. The percentage is calculated as the ratio of the difference in interannual variance between CTL and SoilM (CTL minus SoilM) to the variance in CTL

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In this study, we also analyze the role of soil moisture–atmosphere coupling in summer moderate (10–20 mm day−1) and heavy precipitation (≥20 mm day−1) (not shown). The results show that the role of soil moisture–atmosphere coupling in moderate and heavy precipitation is much lesser than that of light precipitation. This is consistent with the result that precipitation extremes are not significantly affected by soil moisture variability over the Europe found by Jaeger and Seneviratne (2011).

Recent studies demonstrated that summer light precipitation frequency experienced remarkable interannual variations over East Asia (e.g. Yan and Yang, 2000; Gong et al., 2004; Qian et al., 2007, 2009, 2010; Ren et al., 2010; Liu et al., 2011). Our results indicate that soil moisture feedbacks contribute much to the observed interannual variability over many areas of East Asia, in particular the climatic and ecological transition zones. In addition, summer light precipitation frequency has been found to have apparently decreasing trends over East Asia in the last several decades (Qian et al., 2009, 2010). The role of soil moisture–atmosphere coupling in the decreasing trends of light precipitation frequency is subject to further investigation.

Soil moisture affects precipitation mainly through its effects on evapotranspiration or latent heat flux. Over the areas where soil moisture has significantly amplifying effects on summer light precipitation frequency variability, soil moisture generally shows strong effects on interannual variability of latent heat flux (Figure 5(a)), and latent heat flux has close linkages with summer light precipitation frequency for p≤2 mm day−1 (Figure 5(b)). Over most of other areas, either soil moisture has small effects on latent heat flux or connections between summer latent heat flux and light precipitation frequency are weak. Similar results are seen for p≤5 mm day−1 and p≤10 mm day−1 (not shown). Correlations of latent heat flux with moderate and heavy precipitation frequency are generally much less significant than those with light precipitation frequency. This may explain why soil moisture has much smaller effects on the moderate and heavy precipitation than those on light precipitation. We also calculate correlations of summer evaporative fraction (calculated as the ratio of latent heat flux to the sum of latent and sensible heat fluxes) and summer light, moderate and heavy precipitation frequency, and find that the results are generally consistent with those of latent heat flux.

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Figure 5. (a) Differences in standard deviation of summer latent heat flux w m2 between CTL and SoilM and (b) correlations between summer latent heat flux and light precipitation frequency (p≤2 mm day−1)

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Changes in convective light precipitation frequency variability resemble those of total light precipitation frequency variability (Figure 6(a)). In contrast, changes in large-scale light precipitation frequency variability are much less significant (Figure 6(b)). Also, latent heat flux is much more closely linked to convective light precipitation frequency than large-scale light precipitation frequency (Figure 6(c) and (d)). The results indicate that soil moisture feedbacks on summer light precipitation frequency variability mainly depend not only on the ability of soil moisture to affect latent heat flux, but also on the ability of latent heat flux to affect convection.

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Figure 6. (a) Differences in standard deviation of summer convective light precipitation frequency (days per year) (p≤2 mm day−1) between CTL and soilM, (b) same as (a) but for summer large-scale light precipitation frequency, (c) correlations between summer latent heat flux and convective light precipitation frequency (p≤2 mm day−1), and (d) same as (c) but for summer large-scale light precipitation frequency

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4. Conclusions

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Approach
  5. 3. Results
  6. 4. Conclusions
  7. Acknowledgements
  8. References

In this study, we have analyzed two long-term WRF experiments with coupled and uncoupled soil moisture evolution to investigate the contribution of soil moisture–atmosphere coupling to the interannual variability of summer light precipitation frequency over East Asia. The WRF model is able to simulate climate mean and interannual variability of summer light precipitation frequency over East Asia well both in spatial pattern and magnitude; therefore, it can be used to explore the role of soil moisture feedbacks in the light precipitation frequency variability. The soil moisture–atmosphere coupling significantly amplifies interannual variability of summer light precipitation frequency over the climatic and ecological transition zones of the southern Siberia–northern Mongolia region and northern China, many areas of western China, and portion of southern China, accounting for 30–60% of the variance. The results help identify that soil moisture–atmosphere coupling is an important cause responsible for summer light precipitation variations and would contribute the skill to summer light precipitation prediction.

Previous regional climate model studies over the Europe demonstrated that soil moisture–atmosphere coupling can make a large contribution to summer total precipitation variability over particular areas (Seneviratne et al., 2006; Jerez et al., 2012), but generally play a relatively small role in influencing extreme precipitation (e.g. Jaeger and Seneviratne, 2011). Similar results are seen in WRF model simulations over East Asia according to Zhang et al. (2011) and this study. This study represents the first demonstration that soil moisture feedbacks can make an important contribution to summer light precipitation variations over East Asia. Meanwhile, we should mention that the results need to be confirmed further with other regional climate models in order to evaluate their model dependency, and also the role of soil moisture–atmosphere coupling in light precipitation frequency should be investigated by observational data in the future.

Acknowledgements

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Approach
  5. 3. Results
  6. 4. Conclusions
  7. Acknowledgements
  8. References

We thank Pingping Xie for providing the East Asia gauge-based precipitation analysis. We would also like to thank two anonymous reviewers for their helpful comments on this manuscript. This work was supported by the National Basic Research Program of China (2012CB955604 and 2009CB421405), and ‘100-talent program’ of the Chinese Academy of Sciences, and special fund for President's Prize of the Chinese Academy of Sciences.

References

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Approach
  5. 3. Results
  6. 4. Conclusions
  7. Acknowledgements
  8. References
  • Cook BI, Bonan G, Levis S. 2006. Soil moisture feedbacks to precipitation in southern Africa. Journal of Climate 19: 41984206, DOI: 10.1175/JCL13856.1.
  • Easterling DR, Evans JL, Groisman PY, Karl TR, Kunkel KE, Ambenje P. 2000. Observed variability and trends in extreme climate events: a brief review. Bulletin of the American Meteorological Society 81: 417425.
  • Findell KL, Eltahir EAB. 2003. Atmospheric controls on soil moisture-boudary layer interactions. Part II: feedbacks within the continental United States. Journal of Hydrometeorlogy 4: 570583.
  • Giorgi F, Mearns LO, Shields C, Mayer L. 1996. A regional model study of the importance of local versus remote controls of the 1988 drought and the 1993 flood over the central United States. Journal of Climate 9: 11501162.
  • Gong D, Wang S. 2000. Severe summer rainfall in China associated with enhanced global warming. Climate Research 16: 5159.
  • Gong D, Shi P, Wang J. 2004. Daily precipitation changes in semiarid region over northern China. Journal of Arid Environment 59: 771784, DOI: 10.1016/j.jaridenv.2004.02.006.
  • Jaeger EB, Seneviratne SI. 2011. Impact of soil moisture-atmosphere coupling on European climate extremes and trends in a regional climate model. Climate Dynamics 36: 19191939.
  • Jerez S, Montavez JP, Gomez-Navarro JJ, Jimenez PA, Jimenez-Guerrero P, Lorente R, Gonzalez-Rouco JF. 2012. The role of the land-surface model for climate change projections over the Iberian Peninsula. Journal of Geophysical Research 117: D01109, DOI: 10.1029/2011JD016576.
  • Koster RD, Dirmeyer PA, Guo Z, Bonan G, Chan E, Cox P, Gordon CT, Kanae S, Kowalczyk E, Lawrence D, Liu P, Lu C-H, Malyshev S, McAvaney B, Mitchell K, Mocko D, Oki T, Oleson K, Pitman A, Sud YC, Taylor CM, Verseghy D, Vasic R, Xue Y, Yamada T. 2004. Regions of strong coupling between soil moisture and precipitation. Science 305: 11381140.
  • Lei Y, Duan A. 2011. Prolonged dry episodes and drought over China. International Journal of Climatology 31: 18311840.
  • Lei Y, Hoskins B, Slingo J. 2011. Exploring the interplay between natural variability and anthropogenic climate change in summer rainfall over China. Part I: observational evidence. Journal of Climate 24: 45844599.
  • Liu S, Fu C, Shiu CJ, Chen JP, Wu F. 2009. Temperature dependence of global precipitation extremes. Geophysical Research Letters 36: L17702, DOI: 10.1029/2009GL040218.
  • Liu B, Xu M, Henderson M, Qi Y. 2005. Observed trends of precipitation amount, frequency, and intensity in China, 1960–2000. Journal of Geophysical Research 110: D08103, DOI: 10.1029/2004JD00 4864.
  • Liu B, Xu M, Henderson M. 2011. Where have all the showers gone? Regional declines in light precipitation events in China, 1960–2000. International Journal of Climatology 31: 11771191.
  • Qian W, Fu J, Yan Z. 2007. Decrease of light rain events in summer associated with a warming environment in China during 1961–2005. Geophysical Research Letters 34: L11705, DOI: 10.1029/2007GL029631.
  • Qian Y, Gong D, Fan J, Leung LR, Bennartz R, Chen D, Wang W. 2009. Heavy pollution suppresses light rain in China: observations and modeling. Journal of Geophysical Research 114: D00K02, DOI: 10.1029/2008JD011575.
  • Qian Y, Gong D, Leung R. 2010. Light rain events change over North America, Europe, and Asia for 1973–2009. Atmospheric Science Letters 11: 301306.
  • Ren G, Feng G, Yan Z. 2010. Progresses in observation studies of climate extremes and changes in mainland China (in Chinese). Climatic and Environmental Research 15: 337353.
  • Seneviratne SI, Corti T, Davin EL, Hirschi M, Jaeger EB, Lehner I, Orlowsky B, Teuling AJ. 2010. Investigating soil moisture-climate interactions in a changing climate: a review. Earth-Science Reviews 99: 125161.
  • Seneviratne SI, Lüthi D, Litschi M, Schär C. 2006. Land-atmosphere coupling and climate change in Europe. Nature 443: 205209, DOI: 10.1038/nature05095.
  • Sun Y, Solomon S, Dai A, Portmann RW. 2006. How often does it rain? Journal of Climate 19: 916934, DOI: 10.1175/JCLI3672.1.
  • Trenberth KE. 2011. Changes in precipitation with climate change. Climate Research 47: 123138, DOI: 10.3354/cr00953.
  • Trenberth KE, Dai A, Rasmussen RM, Parsons DB. 2003. The changing character of precipitation. Bulletin of the American Meteorological Society 84: 12051217.
  • Xie P, Yatagai A, Chen MY, Hayasaka T, Fukushima Y, Liu CM, Yang S. 2007. A gauge-based analysis of daily precipitation over East Asia. Journal of Hydrometeorology 8: 607626, DOI: 10.1175/JHM583.1.
  • Yan Z, Yang C. 2000. Geographic patterns of climate extreme changes in China during 1951–1997 (in Chinese). Climatic and Environmental Research 5: 267272.
  • Zhai P, Zhang X, Wan H, Pan X. 2005. Trends in total precipitation and frequency of daily precipitation extremes over China. Journal of Climate 18: 10961108.
  • Zhang J, Wang WC, Wei J. 2008a. Assessing land-atmosphere coupling using soil moisture from the Global Land Data Assimilation System and observational precipitation. Journal of Geophysical Research 113: D17119, DOI: 10.1029/2008JD009807.
  • Zhang J, Wang WC, Leung LR. 2008b. Contribution of land-atmosphere coupling to summer climate variability over the contiguous United States. Journal of Geophysical Research 113: D22109, DOI: 10.1029/2008JD010136.
  • Zhang J, Wu L, Dong W. 2011. Land-atmosphere coupling and summer climate variability over East Asia. Journal of Geophysical Research 116: D05117. DOI: 10.1029/2010JD014714.
  • Zhao C, Tie X, Lin Y. 2006. A possible positive feedback of reduction of precipitation and increase in aerosols over eastern central China. Geophysical Research Letters 33: L11814, DOI: 10.1029/2006GL025959.
  • Zhou T, Yu R. 2005. Atmospheric water vapor transport associated with typical anomalous summer rainfall patterns in China. Journal of Geophysical Research 110: D08104, DOI: 10.1029/2004JD005413.