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
  • [1] Warm Season Evaluation of Soil Moisture Prediction in the Soil, Vegetation, and Snow (SVS) Scheme
    Alavi, Nasim
    Belair, Stephane
    Fortin, Vincent
    Zhang, Shunli
    Husain, Syed Z.
    Carrera, Marco L.
    Abrahamowicz, Maria
    [J]. JOURNAL OF HYDROMETEOROLOGY, 2016, 17 (08) : 2315 - 2332
  • [2] Assimilating remotely sensed snow observations into a macroscale hydrology model
    Andreadis, Konstantinos M.
    Lettenmaier, Dennis P.
    [J]. ADVANCES IN WATER RESOURCES, 2006, 29 (06) : 872 - 886
  • [3] Impacts of snow cover fraction data assimilation on modeled energy and moisture budgets
    Arsenault, Kristi R.
    Houser, Paul R.
    De Lannoy, Gabrielle J. M.
    Dirmeyer, Paul A.
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2013, 118 (14) : 7489 - 7504
  • [4] Near-Surface and Land Surface Forecast System of the Vancouver 2010 Winter Olympic and Paralympic Games
    Bernier, Natacha B.
    Belair, Stephane
    Bilodeau, Bernard
    Tong, Linying
    [J]. JOURNAL OF HYDROMETEOROLOGY, 2011, 12 (04) : 508 - 530
  • [5] Brasnett B, 1999, J APPL METEOROL, V38, P726, DOI 10.1175/1520-0450(1999)038<0726:AGAOSD>2.0.CO
  • [6] 2
  • [7] Assimilation of Passive L-band Microwave Brightness Temperatures in the Canadian Land Data Assimilation System: Impacts on Short-Range Warm Season Numerical Weather Prediction
    Carrera, Marco L.
    Bilodeau, Bernard
    Belair, Stephane
    Abrahamowicz, Maria
    Russell, Albert
    Wang, Xihong
    [J]. JOURNAL OF HYDROMETEOROLOGY, 2019, 20 (06) : 1053 - 1079
  • [8] The Canadian Land Data Assimilation System (CaLDAS): Description and Synthetic Evaluation Study
    Carrera, Marco L.
    Belair, Stephane
    Bilodeau, Bernard
    [J]. JOURNAL OF HYDROMETEOROLOGY, 2015, 16 (03) : 1293 - 1314
  • [9] de Rosnay P., 2015, Meteorology, V143, DOI [https://doi.org/10.21957/lkpxq6x5, DOI 10.21957/LKPXQ6X5]
  • [10] SMOS brightness temperature forward modelling and long term monitoring at ECMWF
    de Rosnay, Patricia
    Munoz-Sabater, Joaquin
    Albergel, Clement
    Isaksen, Lars
    English, Stephen
    Drusch, Matthias
    Wigneron, Jean-Pierre
    [J]. REMOTE SENSING OF ENVIRONMENT, 2020, 237