Uncertainty in the specification of surface characteristics, part II: Hierarchy of interaction-explicit statistical analysis

被引:53
|
作者
Niyogi, DS [1 ]
Raman, S [1 ]
Alapaty, K [1 ]
机构
[1] N Carolina State Univ, State Climate Off N Carolina, Raleigh, NC 27695 USA
基金
美国国家科学基金会;
关键词
planetary boundary layer; SVAT; factorial analysis; atmospheric interactions; uncertainty analysis; sensitivity analysis;
D O I
10.1023/A:1002023724201
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The uncertainty in the specification of surface characteristics in soil-vegetation-atmosphere-transfer (SVAT) schemes within planetary boundary-layer (PBL) or mesoscale models is addressed. The hypothesis to be tested is whether the errors in the specification of the individual parameters are accumulative or whether they tend to balance each other in the overall sense for the system. A hierarchy of statistical applications is developed: classical one-at-a-time (OAT) approach, level 1; linear analysis of variance (ANOVA), level 1.5; fractional factorial (FF), or level 2; two-factor interaction (TFI) technique, or level 2.5; and a non-linear response surface methodology (RSM), or level 3. Using the First ISLSCP Field Experiment (FIFE) observations for June 6, 1987 as the initial condition for a SVAT scheme dynamically coupled to a PBL model, the interactions between uncertainty errors are analyzed. A secondary objective addresses the temporal changes in the uncertainty pattern using data for morning, afternoon, and evening conditions. It is found that the outcome from the level 1 OAT-like studies can be considered as the limiting uncertainty values for the majority of mesoscale cases. From the higher-level analyses, it is concluded that for most of the moderate surface scenarios, the effective uncertainty from the individual parameters is balanced and thus lowered. However, for the extreme cases, such as near wilting or saturation soil moisture, the uncertainties add up synergistically and these effects can be even greater than those from the outcomes of the OAT-like studies. Thus, parameter uncertainty cannot be simply related to its deviation alone, but is also dependent on other parameter settings. Also, from the temporal changes in the interaction pattern studies, it is found that, for the morning case soil texture is the important parameter, for afternoon vegetation parameters are crucial, while for the evening case soil moisture is capable of propagating maximum uncertainty in the SVAT processes. Finally, a generic hypothesis is presented that an appropriate question for analysis has to be rephrased from the previous 'which parameters are significant?' to 'what scenarios make a particular parameter significant?'
引用
收藏
页码:341 / 366
页数:26
相关论文
共 50 条
  • [1] Uncertainty in the Specification of Surface Characteristics, Part ii: Hierarchy of Interaction-Explicit Statistical Analysis
    Devdutta S. Niyogi
    Sethu Raman
    Kiran Alapaty
    Boundary-Layer Meteorology, 1999, 91 : 341 - 366
  • [2] PART II. STATISTICAL ANALYSIS
    Mahalanobis, P. C.
    Rao, C. Radhakrishna
    SANKHYA, 1949, 9 : 111 - 180
  • [3] UNCERTAINTY IN THE SPECIFICATION OF SURFACE CHARACTERISTICS: A STUDY OF PREDICTION ERRORS IN THE BOUNDARY LAYER
    Kiran Alapaty
    Sethu Raman
    Devdutta S. Niyogi
    Boundary-Layer Meteorology, 1997, 82 : 475 - 502
  • [4] Uncertainty in the specification of surface characteristics: A study of prediction errors in the boundary layer
    Alapaty, K
    Raman, S
    Niyogi, DS
    BOUNDARY-LAYER METEOROLOGY, 1997, 82 (03) : 473 - 500
  • [5] Multivariate Analysis in Surface Analysis - Part II
    Gilmore, I. S.
    Wagner, M. S.
    SURFACE AND INTERFACE ANALYSIS, 2009, 41 (08) : 633 - 633
  • [6] Statistical analysis of medical data. Part II
    Shufelt, C
    Hachamovitch, R
    JOURNAL OF NUCLEAR CARDIOLOGY, 2000, 7 (03) : 263 - 266
  • [7] Statistical analysis of medical data. Part II
    Chrisandra Shufelt
    Rory Hachamovitch
    Journal of Nuclear Cardiology, 2000, 7 : 263 - 266
  • [8] Statistical Analysis of Surface Texture Performance With Provisions With Uncertainty in Texture Dimension
    Mo, Fan
    Shen, Cong
    Zhou, Jia
    Khonsari, Michael M.
    IEEE ACCESS, 2017, 5 : 5388 - 5398
  • [9] Application of statistical uncertainty and sensitivity evaluations to a PWR LBLOCA analysis calculated with the code ATHLET. Part 1: uncertainty analysis
    Kozmenkov, Y.
    Rohde, U.
    KERNTECHNIK, 2013, 78 (04) : 354 - 361
  • [10] Parameter uncertainty and statistical analysis of tyre-pavement interaction under braking
    da Silva, Debora Cardoso
    Ravahatra, Ndrianary Rakotovao
    Picoux, Benoit
    Reynaud, Philippe
    Yotte, Sylvie
    Petit, Christophe
    ROAD MATERIALS AND PAVEMENT DESIGN, 2025,