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Influence of snowmelt on soil moisture and on near surface air temperature during winter–spring transition season

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Abstract

This study examines relationships between snowmelt and soil moisture (SM), in particular, the influence of snowmelt on soil moisture memory (SMM) and on near surface air temperature (T2M) over the extra-tropical northern hemisphere (ENH) using four state-of-the-art reanalysis products: ERA-Interim, ERA-Interim Land, MERRA-Land, and GLDAS, as well as using Canadian Seasonal and Interannual Prediction System (CanSIPS) seasonal hindcast data, over a 20 year period (1986–2005). We use correlation-based metrics along with a simple classification-based on when the top layer soil temperature (\(T_g\)) rises above freezing point during the annual freeze–thaw season, to evaluate the influence of snowmelt on SM. Our results show considerable differences across reanalyses as well as CanSIPS hindcasts regarding timing of maximum SWE (\({\rm{SWE}}_{\rm{max}}\)) occurrences as well as the onset of thawing of the frozen soil. Correlation statistics indicate that \({\rm{SWE}}_{\rm{max}}\) strongly influences SM. As a measure of the persistence of this relationship, a decay time is defined by lag in days over which the correlation of SM with lagged \({\rm{SWE}}_{\rm{max}}\) decays to 1/e of its peak value. For a majority of grid cells over ENH this decay time is less than 45 days, which suggests \({\rm{SWE}}_{\rm{max}}\) does not strongly influence the SM beyond subseasonal time scales. The interannual autocorrelation of SM indicates strong persistence over subseasonal time scales, consistently across reanalyses as well as CanSIPS hindcasts. However, intra-seasonal autocorrelations of ERA-Interim and MERRA-Land SM over North America show anomalous sudden decline of SMM compared to the other products, likely due to the offline forcing of atmospheric variables which blocks the atmosphere’s response to land feedbacks. One of the models used in CanSIPS, the Canadian Climate Model version 4 (CanCM4), also shows a sudden decline of intra-seasonal autocorrelation over Central Asia which is most likely due to weak land–atmosphere coupling over the region. Lag–lead correlation statistics between SM and T2M during the soil thaw period suggests that SM anomalies have measurable lagged influence on T2M with varying decay time over different regions and across different datasets.

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Notes

  1. Negative correlations between \({\rm{SWE}}_{\rm{max}}\) and SM are considered as noise, and the decay time is calculated only for positive correlations which are statistically significant.

References

  • Ambadan JT, Berg A, Merryfield W (2015) Influence of snow and soil moisture initialization on sub-seasonal predictability and forecast skill in boreal spring. Clim Dyn. doi:10.1007/s00382-015-2821-9

    Google Scholar 

  • Balsamo G, Albergel C, Beljaars A, Boussetta S, Brun E, Cloke H, Dee D, Dutra E, Muñoz-Sabater J, Pappenberger F, de Rosnay P, Stockdale T, Vitart F (2015) ERA-Interim/Land: a global land surface reanalysis data set. Hydrol Earth Syst Sci 19(1):389–407. doi:10.5194/hess-19-389-2015

    Article  Google Scholar 

  • Berg A, Lintner BR, Findell K, Seneviratne SI, van den Hurk B, Ducharne A, Chéruy F, Hagemann S, Lawrence DM, Malyshev S, Meier A, Gentine P (2015) Interannual coupling between summertime surface temperature and precipitation over land: processes and implications for climate change. J Clim 28(3):1308–1328. doi:10.1175/JCLI-D-14-00324.1

    Article  Google Scholar 

  • Chen F, Mitchell K, Schaake J, Xue Y, Pan HL, Koren V, Duan QY, Ek M, Betts A (1996) Modeling of land surface evaporation by four schemes and comparison with FIFE observations. J Geophys Res 101(D3):7251–7268. doi:10.1029/95JD02165

    Article  Google Scholar 

  • Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda MA, Balsamo G, Bauer P et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137(656):553–597

    Article  Google Scholar 

  • Delworth TL, Manabe S (1988) The influence of potential evaporation on the variabilities of simulated soil wetness and climate. J Clim 1(5):523–547. doi:10.1175/1520-0442(1988)001\(<\)0523:TIOPEO\(>\)2.0.CO;2

  • Douville H, Royer JF (1996) Sensitivity of the Asian summer monsoon to an anomalous Eurasian snow cover within the Meteo-France GCM. Clim Dyn 12(7):449–466. doi:10.1007/BF02346818

    Article  Google Scholar 

  • Douville H, Royer JF, Mahfouf JF (1995) A new snow parameterization for the Météo-France climate model. Clim Dyn 12(1):21–35. doi:10.1007/BF00208760

    Article  Google Scholar 

  • Giorgi F, Jones C, Asrar GR (2009) Addressing climate information needs at the regional level: the CORDEX framework. WMO Bull 58(3):175–183

    Google Scholar 

  • Gouttevin I, Menegoz M, Dominé F, Krinner G, Koven C, Ciais P, Tarnocai C, Boike J (2012) How the insulating properties of snow affect soil carbon distribution in the continental pan-Arctic area. J Geophys Res Biogeosci. doi:10.1029/2011JG001916

    Google Scholar 

  • Hohenegger C, Brockhaus P, Bretherton CS, Schär C (2009) The soil moisture-precipitation feedback in simulations with explicit and parameterized convection. J Clim 22(19):5003–5020. doi:10.1175/2009JCLI2604.1

    Article  Google Scholar 

  • Jeong JH, Linderholm HW, Woo SH, Folland C, Kim BM, Kim SJ, Chen D (2013) Impacts of snow initialization on subseasonal forecasts of surface air temperature for the cold season. J Clim 26(6):1956–1972. doi:10.1175/JCLI-D-12-00159.1

    Article  Google Scholar 

  • Koren V, Schaake J, Mitchell K, Duan QY, Chen F, Baker JM (1999) A parameterization of snowpack and frozen ground intended for NCEP weather and climate models. J Geophys Res D104(16):19,569–19,585. doi:10.1029/1999JD900232

    Article  Google Scholar 

  • Koster RD, Suarez MJ (2001) Soil moisture memory in climate models. J Hydrometeorol 2(6):558–570

    Article  Google Scholar 

  • Koster RD, Dirmeyer PA, Guo Z, Bonan G, Chan E, Cox P, Gordon C, Kanae S, Kowalczyk E, Lawrence D et al (2004) Regions of strong coupling between soil moisture and precipitation. Science 305(5687):1138–1140. doi:10.1126/science.1100217

    Article  Google Scholar 

  • Koster RD, Sud YC, Guo Z, Dirmeyer PA, Bonan G, Oleson KW, Chan E, Verseghy D, Cox P, Davies H et al (2006) GLACE: the global land-atmosphere coupling experiment. Part I: Overview. J Hydrometeorol 7(4):590–610

    Article  Google Scholar 

  • Koster RD, Mahanama SPP, Yamada TJ, Balsamo G, Berg AA, Boisserie M, Dirmeyer PA, Doblas-Reyes FJ, Drewitt G, Gordon CT et al (2011) The second phase of the global land–atmosphere coupling experiment: soil moisture contributions to subseasonal forecast skill. J Hydrometeorol 12(5):805–822. doi:10.1175/2011JHM1365.1

    Article  Google Scholar 

  • Koven CD, Riley WJ, Stern A (2013) Analysis of permafrost thermal dynamics and response to climate change in the CMIP5 earth system models. J Clim 26(6):1877–1900. doi:10.1175/JCLI-D-12-00228.1

    Article  Google Scholar 

  • Lorenz R, Argüeso D, Donat MG, Pitman AJ, van den Hurk B, Berg A, Lawrence DM, Chéruy F, Ducharne A, Hagemann S, Meier A, Milly PCD, Seneviratne SI (2015) Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble. J Geophys Res. doi:10.1002/2015JD024053

    Google Scholar 

  • Medler MJ, Montesano P, Robinson D (2002) Examining the Relationship Between Snowfall and Wildfire Patterns in the Western United States. Phys Geogr 23(4):335–342. doi:10.2747/0272-3646.23.4.335

    Article  Google Scholar 

  • Merryfield WJ, Lee WS, Boer GJ, Kharin VV, Scinocca JF, Flato GM, Ajayamohan R, Fyfe JC, Tang Y, Polavarapu S (2013) The Canadian seasonal to interannual prediction system. Part I: Models and initialization. Mon Weather Rev 141(8):2910–2945. doi:10.1175/MWR-D-12-00216.1

    Article  Google Scholar 

  • Mudryk LR, Derksen C, Kushner PJ, Brown R (2015) Characterization of Northern Hemisphere Snow Water Equivalent Datasets, 1981–2010. J Clim 28(20):8037–8051. doi:10.1175/JCLI-D-15-0229.1

    Article  Google Scholar 

  • Orsolini YJ, Senan R, Balsamo G, Doblas-Reyes FJ, Vitart F, Weisheimer A, Carrasco A, Benestad RE (2013) Impact of snow initialization on sub-seasonal forecasts. Clim Dyn 41(7–8):1969–1982. doi:10.1007/s00382-013-1782-0

    Article  Google Scholar 

  • Pal JS, Eltahir EAB (2003) A feedback mechanism between soil-moisture distribution and storm tracks. Q J R Meteorol Soc 129(592):2279–2297. doi:10.1256/qj.01.201

    Article  Google Scholar 

  • Qu X, Hall A (2014) On the persistent spread in snow-albedo feedback. Clim Dyn 42(1):69–81. doi:10.1007/s00382-013-1774-0

    Article  Google Scholar 

  • Reichle RH, Koster RD, Lannoy GJMD, Forman BA, Liu Q, Mahanama SPP, Touré Ally (2011) Assessment and enhancement of MERRA land surface hydrology estimates. J Clim 24(24):6322–6338. doi:10.1175/JCLI-D-10-05033.1

    Article  Google Scholar 

  • Rienecker MM, Suarez MJ, Gelaro R, Todling R, Bacmeister J, Liu E, Bosilovich MG, Schubert SD, Takacs L, Kim GK et al (2011) MERRA: NASA’s modern-era retrospective analysis for research and applications. J Clim 24(14):3624–3648

    Article  Google Scholar 

  • Rodell M, Houser P, Uea Jambor, Gottschalck J, Mitchell K, Meng C, Arsenault K, Cosgrove B, Radakovich J, Bosilovich M et al (2004) The global land data assimilation system. Bull Am Meteorol Soc 85(3):381–394

    Article  Google Scholar 

  • Schär C, Lüthi D, Beyerle U, Heise E (1999) The soil-precipitation feedback: a process study with a regional climate model. J Clim 12(3):722–741. doi:10.1175/1520-0442(1999)012\(<\)0722:TSPFAP\(>\)2.0.CO;2

  • Schlosser CA, Milly PCD (2002) A model-based investigation of soil moisture predictability and associated climate predictability. J Hydrometeorol 3(4):483–501. doi:10.1175/1525-7541(2002)003\(<\)0483:AMBIOS\(>\)2.0.CO;2

  • Scinocca J, McFarlane N, Lazare M, Li J, Plummer D (2008) Technical note: the CCCma third generation AGCM and its extension into the middle atmosphere. Atmos Chem Phys 8(23):7055–7074

    Article  Google Scholar 

  • Seneviratne SI, Koster RD, Guo Z, Dirmeyer PA, Kowalczyk E, Lawrence D, Liu P, Lu CH, Mocko D, Oleson KW, Verseghy D (2006) Soil moisture memory in AGCM simulations: analysis of global land–atmosphere coupling experiment (GLACE) data. J Hydrometeorol 7:1090–1112

    Article  Google Scholar 

  • 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 Sci Rev 99:125–161. doi:10.1016/j.earscirev.2010.02.004

    Article  Google Scholar 

  • Sheffield J, Goteti G, Wood EF (2006) Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling. J Clim 19(13):3088–3111. doi:10.1175/JCLI3790.1

    Article  Google Scholar 

  • Shinoda M (2001) Climate memory of snow mass as soil moisture over central Eurasia. J Geophys Res D106(24):33,393–33,403

    Article  Google Scholar 

  • Sospedra-Alfonso R, Merryfield WJ, Kharin VV (2016a) Representation of snow in the Canadian seasonal to interannual prediction system. Part II: Potential predictability and hindcast skill. J Hydrometeorol 17(9):2511–2535. doi:10.1175/JHM-D-16-0027.1

    Article  Google Scholar 

  • Sospedra-Alfonso R, Mudryk L, Merryfield W, Derksen C (2016b) Representation of snow in the Canadian seasonal to interannual prediction system. Part I: Initialization. J Hydrometeorol 17(5):1467–1488. doi:10.1175/JHM-D-14-0223.1

    Article  Google Scholar 

  • Takala M, Luojus K, Pulliainen J, Derksen C, Lemmetyinen J, Kärnä JP, Koskinen J, Bojkov B (2011) Estimating northern hemisphere snow water equivalent for climate research through assimilation of space-borne radiometer data and ground-based measurements. Remote Sens Environ 115(12):3517–3529. doi:10.1016/j.rse.2011.08.014

    Article  Google Scholar 

  • Teuling AJ, Troch PA (2005) Improved understanding of soil moisture variability dynamics. Geophys Res Lett. doi:10.1029/2004GL021935, l05404

    Google Scholar 

  • Thackeray CW, Fletcher CG, Derksen C (2015) Quantifying the skill of CMIP5 models in simulating seasonal albedo and snow cover evolution. J Geophys Res 120(12):5831–5849. doi:10.1002/2015JD023325

    Google Scholar 

  • Tong J, Déry SJ, Jackson PL, Derksen C (2010) Testing snow water equivalent retrieval algorithms for passive microwave remote sensing in an alpine watershed of western Canada. Can J Remote Sens 36(1):S74–S86. doi:10.5589/m10-009

    Article  Google Scholar 

  • van den Hurk B, Best M, Dirmeyer P, Pitman A, Polcher J, Santanello J (2011) Acceleration of land surface model development over a decade of glass. Bull Am Meteorol Soc 92(12):1593–1600. doi:10.1175/BAMS-D-11-00007.1

    Article  Google Scholar 

  • van den Hurk B, Kim H, Krinner G, Seneviratne SI, Derksen C, Oki T, Douville H, Colin J, Ducharne A, Cheruy F, Viovy N, Puma M, Wada Y, Li W, Jia B, Alessandri A, Lawrence D, Weedon GP, Ellis R, Hagemann S, Mao J, Flanner MG, Zampieri M, Law R, Sheffield J (2016) The land surface, snow and soil moisture model intercomparison program (LS3MIP): aims, set-up and expected outcome. Geosci Model Dev. doi:10.5194/gmd-2016-72

    Google Scholar 

  • van den Hurk B, Viterbo P, Beljaars A, Betts A (2000) Offline validation of the ERA40 surface scheme. Tech. Rep. 295, European Center for Medium Range Weather Forecast, Shinfield Park, Reading, eCMWF Technical Memorandum

  • Verseghy DL (2000) The Canadian land surface scheme (CLASS): Its history and future. Atmos Ocean 38(1):1–13

    Article  Google Scholar 

  • Viterbo P, Beljaars A, Mahfouf JF, Teixeira J (1999) The representation of soil moisture freezing and its impact on the stable boundary layer. Q J R Meteorol Soc 125(559):2401–2426. doi:10.1002/qj.49712555904

    Article  Google Scholar 

  • Viterbo P, Beljaars ACM (1995) An improved land surface parameterization scheme in the ECMWF model and its validation. J Clim 8(11):2716–2748. doi:10.1175/1520-0442(1995)008\(<\)2716:AILSPS\(>\)2.0.CO;2

  • von Salzen K, Scinocca JF, McFarlane NA, Li J, Cole JNS, Plummer D, Verseghy D, Reader MC, Ma X, Lazare M, Solheim L (2013) The Canadian Fourth Generation Atmospheric Global Climate Model (CanAM4). Part I: Representation of physical processes. Atmos Ocean 51(1):104–125. doi:10.1080/07055900.2012.755610

    Article  Google Scholar 

  • Wang W, Kumar A (1998) A GCM assessment of atmospheric seasonal predictability associated with soil moisture anomalies over North America. J Geophys Res D103(22):28,637–28,646. doi:10.1029/1998JD200010

    Article  Google Scholar 

  • Westerling AL, Hidalgo HG, Cayan DR, Swetnam TW (2006) Warming and earlier spring increase western US Forest Wildfire Activity. Science 313(5789):940–943. doi:10.1126/science.1128834

    Article  Google Scholar 

  • Yeh T, Wetherald R, Manabe S (1983) A model study of the short-term climatic and hydrologic effects of sudden snow-cover removal. Mon Weather Rev 111(5):1013–1024

    Article  Google Scholar 

  • Zhang H, Frederiksen CS (2003) Local and nonlocal impacts of soil moisture initialization on AGCM seasonal forecasts: a model sensitivity study. J Clim 16(13):2117–2137. doi:10.1175/1520-0442(2003)16\(<\)2117:LANIOS\(>\)2.0.CO;2

  • Zveryaev II, Zahn M, Allan RP (2016) Interannual variability in the summertime hydrological cycle over European regions. J Geophys Res. doi:10.1002/2015JD024425

    Google Scholar 

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Acknowledgements

This work was supported by the Canadian Sea Ice and Snow Evolution (CanSISE: http://www.cansise.ca) network, a network project funded under the Climate Change and Atmospheric Research (CCAR) initiative of Natural Science and Engineering Research Council (NSERC) of Canada. The authors would also like to acknowledge and thank Compute Canada. Some of the data analysis used in this study were made possible by the facilities of the Shared Hierarchical Academic Research Computing Network (SHARCNET: http://www.sharcnet.ca) of Compute Canada.

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Authors and Affiliations

  1. Department of Geography, University of Guelph, Guelph, ON, Canada

    Jaison Thomas Ambadan & Aaron A. Berg

  2. Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, University of Victoria, Victoria, BC, Canada

    William J. Merryfield & Woo-Sung Lee

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  1. Jaison Thomas Ambadan
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Ambadan, J.T., Berg, A.A., Merryfield, W.J. et al. Influence of snowmelt on soil moisture and on near surface air temperature during winter–spring transition season. Clim Dyn 51, 1295–1309 (2018). https://doi.org/10.1007/s00382-017-3955-8

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