Improving Snow Analyses for Hydrological Forecasting at ECCC Using Satellite-Derived Data

被引:4
作者
Garnaud, Camille [1 ]
Vionnet, Vincent [1 ]
Gaborit, Etienne [1 ]
Fortin, Vincent [1 ]
Bilodeau, Bernard [1 ]
Carrera, Marco [1 ]
Durnford, Dorothy [2 ]
机构
[1] Environm & Climate Change Canada, Meteorol Res Div, Dorval, PQ H9P 1J3, Canada
[2] Environm & Climate Change Canada, Meteorol Serv Canada, Dorval, PQ H9P 1J3, Canada
关键词
snow analyses; water conservation; streamflow forecasting; assimilation; PRECIPITATION ANALYSIS; COVERED AREA; ASSIMILATION; PERFORMANCE; DEPTH; MODIS; PERTURBATION; SIMULATIONS; IMPROVEMENT; VEGETATION;
D O I
10.3390/rs13245022
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
As part of the National Hydrological Services Transformation Initiative, Environment and Climate Change Canada (ECCC) designed and implemented the National Surface and River Prediction System (NSRPS) in order to provide surface and river flow analysis and forecast products across Canada. Within NSRPS, the Canadian Land Data Assimilation System (CaLDAS) produces snow analyses that are used to initialise the land surface model, which in turn is used to force the river routing component. Originally, CaLDAS was designed to improve atmospheric forecasts with less focus on hydrological processes. When snow data assimilation occurs, the related increments remove/add water from/to the system, which can sometimes be problematic for streamflow forecasting, in particular during the snowmelt period. In this study, a new snow analysis method introduces multiple innovations that respond to the need for higher quality snow analyses for hydrological purposes, including the use of IMS snow cover extent data instead of in situ snow depth observations. The results show that the new snow assimilation methodology brings an overall improvement to snow analyses and substantially enhances water conservation, which is reflected in the generally improved streamflow simulations. This work represents a first step towards a new snow data assimilation process in CaLDAS, with the final objective of producing a reliable snow analysis to initialise and improve NWP as well as environmental predictions, including flood and drought forecasts.
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页数:24
相关论文
共 53 条
  • [41] Improvement of springtime streamflow simulations in a boreal environment by incorporating snow-covered area derived from remote sensing data
    Roy, Alexandre
    Royer, Alain
    Turcotte, Richard
    [J]. JOURNAL OF HYDROLOGY, 2010, 390 (1-2) : 35 - 44
  • [42] Correcting Unintended Perturbation Biases in Hydrologic Data Assimilation
    Ryu, Dongryeol
    Crow, Wade T.
    Zhan, Xiwu
    Jackson, Thomas J.
    [J]. JOURNAL OF HYDROMETEOROLOGY, 2009, 10 (03) : 734 - 750
  • [43] Characteristics of the western United States snowpack from snowpack telemetry (SNOTEL) data
    Serreze, MC
    Clark, MP
    Armstrong, RL
    McGinnis, DA
    Pulwarty, RS
    [J]. WATER RESOURCES RESEARCH, 1999, 35 (07) : 2145 - 2160
  • [44] Assimilation of MODIS Snow Cover Area Data in a Distributed Hydrological Model Using the Particle Filter
    Thirel, Guillaume
    Salamon, Peter
    Burek, Peter
    Kalas, Milan
    [J]. REMOTE SENSING, 2013, 5 (11) : 5825 - 5850
  • [45] Theoretical analysis of errors when estimating snow distribution through point measurements
    Trujillo, E.
    Lehning, M.
    [J]. CRYOSPHERE, 2015, 9 (03) : 1249 - 1264
  • [46] U.S. National Ice Center, 2008, **DATA OBJECT**, DOI 10.7265/N52R3PMC
  • [47] Perturbation of convection-permitting NWP forecasts for flash-flood ensemble forecasting
    Vincendon, B.
    Ducrocq, V.
    Nuissier, O.
    Vie, B.
    [J]. NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2011, 11 (05) : 1529 - 1544
  • [48] Canadian historical Snow Water Equivalent dataset (CanSWE, 1928-2020)
    Vionnet, Vincent
    Mortimer, Colleen
    Brady, Mike
    Arnal, Louise
    Brown, Ross
    [J]. EARTH SYSTEM SCIENCE DATA, 2021, 13 (09) : 4603 - 4619
  • [49] Modelled atmospheric response to changes in Northern Hemisphere snow cover
    Walland, DJ
    Simmonds, I
    [J]. CLIMATE DYNAMICS, 1996, 13 (01) : 25 - 34
  • [50] Further Improvement of the Heavy Orographic Rainfall Retrievals in the GSMaP Algorithm for Microwave Radiometers
    Yamamoto, Munehisa K.
    Shige, Shoichi
    Yu, Cheng-Ku
    Cheng, Lin-Wen
    [J]. JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY, 2017, 56 (09) : 2607 - 2619