Spatial and temporal variability of snow depth derived from passive microwave remote sensing data in Kazakhstan

Shamshagul Mashtayeva, Liyun Dai, Tao Che, Zhanay Sagintayev, Saltanat Sadvakasova, Marzhan Kussainova, Danara Alimbayeva, Meerzhan Akynbekkyzy

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


Snow cover plays an important role in the hydrological cycle and water management in Kazakhstan. However, traditional observations do not meet current needs. In this study, a snow depth retrieval equation was developed based on passive microwave remote sensing data. The average snow depth in winter (ASDW), snow cover duration (SCD), monthly maximum snow depth (MMSD), and annual average snow depth (AASD) were derived for each year to monitor the spatial and temporal snow distributions. The SCD exhibited significant spatial variations from 30 to 250 days. The longest SCD was found in the mountainous area in eastern Kazakhstan, reaching values between 200 and 250 days in 2005. The AASD increased from the south to the north and maintained latitudinal zonality. The MMSD in most areas ranged from 20 to 30 cm. The ASDW values ranged from 15 to 20 cm in the eastern region and were characterized by spatial regularity of latitudinal zonality. The ASDW in the mountainous area often exceeded 20 cm.

Original languageEnglish
Pages (from-to)1033-1043
Number of pages11
JournalJournal of Meteorological Research
Issue number6
Publication statusPublished - Dec 1 2016


  • Kazakhstan
  • passive microwave
  • remote sensing
  • snow cover
  • snow depth
  • spatial and temporal variations

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Ocean Engineering
  • Hardware and Architecture
  • Computer Science Applications
  • Atmospheric Science

Fingerprint Dive into the research topics of 'Spatial and temporal variability of snow depth derived from passive microwave remote sensing data in Kazakhstan'. Together they form a unique fingerprint.

Cite this