Development of physically based liquid water schemes for Greenland firn-densification models

被引:30
|
作者
Verjans, Vincent [1 ]
Leeson, Amber A. [2 ]
Stevens, C. Max [3 ]
MacFerrin, Michael [4 ]
Noel, Brice [5 ]
van den Broeke, Michiel R. [5 ]
机构
[1] Univ Lancaster, Lancaster Environm Ctr, Lancaster LA1 4YW, England
[2] Univ Lancaster, Lancaster Environm Ctr, Data Sci Inst, Lancaster LA1 4YW, England
[3] Univ Washington, Dept Earth & Space Sci, Seattle, WA 98195 USA
[4] Univ Colorado, Cooperat Inst Res Environm Sci, Boulder, CO 80309 USA
[5] Univ Utrecht, Inst Marine & Atmospher Res Utrecht, Utrecht, Netherlands
来源
CRYOSPHERE | 2019年 / 13卷 / 07期
关键词
SURFACE MASS-BALANCE; ICE-LAYER FORMATION; MELTWATER STORAGE; PREFERENTIAL FLOW; HYDRAULIC CONDUCTIVITY; POLAR SNOW; GRAIN-SIZE; SHEET; RETENTION; DENSITY;
D O I
10.5194/tc-13-1819-2019
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
As surface melt is increasing on the Greenland Ice Sheet (GrIS), quantifying the retention capacity of the firn layer is critical to linking meltwater production to meltwater runoff. Firn-densification models have so far relied on empirical approaches to account for the percolation-refreezing process, and more physically based representations of liquid water flow might bring improvements to model performance. Here we implement three types of water percolation schemes into the Community Firn Model: the bucket approach, the Richards equation in a single domain and the Richards equation in a dual domain, which accounts for partitioning between matrix and fast preferential flow. We investigate their impact on firn densification at four locations on the GrIS and compare model results with observations. We find that for all of the flow schemes, significant discrepancies remain with respect to observed firn density, particularly the density variability in depth, and that inter-model differences are large (porosity of the upper 15m firn varies by up to 47 %). The simple bucket scheme is as efficient in replicating observed density profiles as the single-domain Richards equation, and the most physically detailed dual-domain scheme does not necessarily reach best agreement with observed data. However, we find that the implementation of preferential flow simulates ice-layer formation more reliably and allows for deeper percolation. We also find that the firn model is more sensitive to the choice of densification scheme than to the choice of water percolation scheme. The disagreements with observations and the spread in model results demonstrate that progress towards an accurate description of water flow in firn is necessary. The numerous uncertainties about firn structure (e.g. grain size and shape, presence of ice layers) and about its hydraulic properties, as well as the one-dimensionality of firn models, render the implementation of physically based percolation schemes difficult. Additionally, the performance of firn models is still affected by the various effects affecting the densification process such as microstructural effects, wet snow metamorphism and temperature sensitivity when meltwater is present.
引用
收藏
页码:1819 / 1842
页数:24
相关论文
共 50 条
  • [1] Evaluating Greenland surface-mass-balance and firn-densification data usingICESat-2 altimetry
    Smith, Benjamin E.
    Medley, Brooke
    Fettweis, Xavier
    Sutterley, Tyler
    Alexander, Patrick
    Porter, David
    Tedesco, Marco
    CRYOSPHERE, 2023, 17 (02): : 789 - 808
  • [2] Explaining the presence of perennial liquid water bodies in the firn of the Greenland Ice Sheet
    Munneke, P. Kuipers
    Ligtenberg, S. R. M.
    van den Broeke, M. R.
    van Angelen, J. H.
    Forster, R. R.
    GEOPHYSICAL RESEARCH LETTERS, 2014, 41 (02) : 476 - 483
  • [3] Multi-technique estimation of ice mass balance in Greenland: impact of the uncertainties on firn densification and GIA models
    Sanchez Lofficial, Ana
    Métivier, Laurent
    Fleitout, Luce
    Chanard, Kristel
    Greff-Lefftz, Marianne
    de La Serve, Maylis
    Gauer, Louis-Marie
    Gourrion, Emma
    Geophysical Journal International, 2025, 240 (03) : 1935 - 1952
  • [4] How well is firn densification represented by a physically based multilayer model? Model evaluation for Devon Ice Cap, Nunavut, Canada
    Gascon, Gabrielle
    Sharp, Martin
    Burgess, David
    Bezeau, Peter
    Bush, Andrew B. G.
    Morin, Samuel
    Lafaysse, Matthieu
    JOURNAL OF GLACIOLOGY, 2014, 60 (222) : 694 - 704
  • [5] Physically based mathematical models of the water vapor sorption by soils
    A. V. Smagin
    Eurasian Soil Science, 2011, 44
  • [6] Physically Based Mathematical Models of the Water Vapor Sorption by Soils
    Smagin, A. V.
    EURASIAN SOIL SCIENCE, 2011, 44 (06) : 659 - 669
  • [7] Development and application of a physically based landscape water balance in the SWAT model
    White, Eric D.
    Easton, Zachary M.
    Fuka, Daniel R.
    Collick, Amy S.
    Adgo, Enyew
    McCartney, Matthew
    Awulachew, Seleshi B.
    Selassie, Yihenew G.
    Steenhuis, Tammo S.
    HYDROLOGICAL PROCESSES, 2011, 25 (06) : 915 - 925
  • [8] River Water Level Prediction Using Physically Based and Data Driven Models
    Shrestha, R. R.
    Nestmann, Franz
    MODSIM 2005: INTERNATIONAL CONGRESS ON MODELLING AND SIMULATION: ADVANCES AND APPLICATIONS FOR MANAGEMENT AND DECISION MAKING: ADVANCES AND APPLICATIONS FOR MANAGEMENT AND DECISION MAKING, 2005, : 1894 - 1900
  • [9] Physically-Based Particle Size Distribution Models of Urban Water Particulate Matter
    Yue Liu
    John J. Sansalone
    Water, Air, & Soil Pollution, 2020, 231
  • [10] Physically-Based Particle Size Distribution Models of Urban Water Particulate Matter
    Liu, Yue
    Sansalone, John J.
    WATER AIR AND SOIL POLLUTION, 2020, 231 (11):