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akaturk Akademik ölçüm

Makale detayı · 2013

The Optimality of Potential Rescaling Approaches in Land Data Assimilation

Dergi

Journal of Hydrometeorology

ISSN 1525-755X

YÖKSİS OpenAlex Açık erişim · bronze SJR Q1 JCR Q1 Atıf 144 Üst %10 Yüzdelik 98.3% FWCI 8.63
Yıl
2013
Tür
article

Veri kaynağı ayrımı

  • YÖKSİS YÖKSİS makale kaydı
  • YÖKSİS dergi adı Journal of Hydrometeorology
  • Katalog eşleşmesi (ISSN) Journal of Hydrometeorology
  • OpenAlex OpenAlex zenginleştirmesi (özet, atıf, konular)

Özet

OpenAlex · İngilizce

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.

Konular

Atıflar

OpenAlex cited_by_count. WoS veya Scopus atıf sayısı değildir; o kaynaklar için ayrı kolon yoktur.

144 atıf

OpenAlex cited_by_count (önbellek / veritabanı)

Yazarlar

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