Skip to content
akaturk Academic measurement

Article detail · 2013

The Optimality of Potential Rescaling Approaches in Land Data Assimilation

Journal

Journal of Hydrometeorology

ISSN 1525-755X

YÖKSİS OpenAlex Open access · bronze SJR Q1 JCR Q1 Citations 144 Top 10% Percentile 98.3% FWCI 8.63
Year
2013
Type
article

Data source split

  • YÖKSİS YÖKSİS article record
  • YÖKSİS venue Journal of Hydrometeorology
  • Catalog match (ISSN) Journal of Hydrometeorology
  • OpenAlex OpenAlex enrichment (abstract, citations, topics)

Abstract

OpenAlex · English

Abstract It is well known that systematic differences exist between modeled and observed realizations of hydrological variables like soil moisture. Prior to data assimilation, these differences must be removed in order to obtain an optimal analysis. A number of rescaling approaches have been proposed for this purpose. These methods include rescaling techniques based on matching sampled temporal statistics, minimizing the least squares distance between observations and models, and the application of triple collocation. Here, the authors evaluate the optimality and relative performances of these rescaling methods both analytically and numerically and find that a triple collocation–based rescaling method results in an optimal solution, whereas variance matching and linear least squares regression approaches result in only approximations to this optimal solution.

Topics

Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

144 citations

OpenAlex cited_by_count (cache / database)

Authors

  1. MUSTAFA TUĞRUL YILMAZ ORTA DOĞU TEKNİK ÜNİVERSİTESİ
  2. Crow Wade T
  3. tuğçe olgun