Validation of noah-simulated soil temperature in the north american land data assimilation system phase 2

Youlong Xia, Michael Ek, Justin Sheffield, Ben Livneh, Maoyi Huang, Helin Wei, Song Feng, Lifeng Luo, Jesse Meng, Eric F. Wood

Research output: Contribution to journalArticlepeer-review

51 Scopus citations


Soil temperature can exhibit considerable memory from weather and climate signals and is among the most important initial conditions in numerical weather and climate models. Consequently, a more accurate longterm land surface soil temperature dataset is needed to improve weather and climate simulation and prediction, and is also important for the simulation of agricultural crop yield and ecological processes. The North American Land Data Assimilation phase 2 (NLDAS-2) has generated 31 years (1979-2009) of simulated hourly soil temperature data with a spatial resolution of 1/8° This dataset has not been comprehensively evaluated to date. Thus, the purpose of this paper is to assess Noah-simulated soil temperature for different soil depths and time scales. The authors used long-term (1979-2001) observed monthly mean soil temperatures from 137 cooperative stations over the United States to evaluate simulated soil temperature for three soil layers (0-10, 10-40, and 40-100 cm) for annual and monthly time scales. Short-term (1997-99) observed soil temperatures from 72 Oklahoma Mesonet stations were used to validate simulated soil temperatures for three soil layers and for daily and hourly time scales. The results showed that the Noah land surface model generally matches observed soil temperature well for different soil layers and time scales. At greater depths, the simulation skill (anomaly correlation) decreased for all time scales. The monthly mean diurnal cycle difference between simulated and observed soil temperature revealed large midnight biases in the cold season that are due to small downward longwave radiation and issues related to model parameters.

Original languageEnglish (US)
Pages (from-to)455-471
Number of pages17
JournalJournal of Applied Meteorology and Climatology
Issue number2
StatePublished - Feb 2013

All Science Journal Classification (ASJC) codes

  • Atmospheric Science


  • Agriculture
  • Crop growth
  • Data assimilation
  • Ecological models
  • Land surface model
  • Model evaluation/performance


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