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Pure and Applied Geophysics

, Volume 176, Issue 4, pp 1807–1826 | Cite as

Evaluation of WRF-simulated multilevel soil moisture, 2-m air temperature, and 2-m relative humidity against in situ observations in India

  • B. Kantha RaoEmail author
  • V. Rakesh
Article
  • 86 Downloads

Abstract

The ability of the Weather Research and Forecasting (WRF) model to simulate multilevel soil moisture (SM), 2-m air temperature (T2m), and 2-m relative humidity (RH2m) was evaluated for five different locations in India. WRF model simulations were carried out for 30 cases during different seasons with two different land surface schemes, viz. Noah and Rapid Update Cycle (RUC). The simulations were compared with in situ observations taken routinely at 30-min time intervals at the five selected locations. Statistical evaluation showed that, although the model could simulate SM reasonably well [with the majority of cases falling in the < 25% relative error (RE) category] at different depths for Delhi (DLH) and Gulbarga (GLB), the model errors were high (with most cases falling in the > 50% RE category) for Almora (ALR), Hyderabad (HYD), and Cochin (CHN). In case of T2m, model errors were high (RE > 15%) over hilly terrain, e.g., at ALR, while errors were relatively lower (RE < 10%) for plane areas such as HYD, GLB, DLH, and CHN. In general, the diurnal variation showed that the model underestimated (overestimated) afternoon temperatures during nonrainy (rainy) days. RH2m was also well simulated by the model at the locations HYD, GLB, and CHN, although it underestimated RH2m during morning hours at the locations ALR and DLH. Overall, the comparison showed that the WRF model could reproduce the near-surface temperature and humidity for plane areas such as HYD, GLB, and CHN reasonably well, but has limitations for complex terrains, e.g., at ALR, and highly polluted cities such as DLH.

Keywords

Soil moisture 2-m air temperature 2-m relative humidity WRF Land surface models 

Notes

Acknowledgements

The authors are grateful to the CSIR for making available the meteorological observation data. The authors acknowledge the National Center for Atmospheric Research (NCAR) for its support for the WRF modeling system (www.mmm.ucar.edu/wrf) and the National Centers for Environmental Prediction (NCEP) for making available the analysis data (http://ncep.noaa.gov/pub/data/nccf/com/gfs/prod). The CSIR 4PI high-performance computing (HPC) facility used for computing is gratefully acknowledged. The authors also acknowledge support and encouragement from the Head CSIR 4PI.

Supplementary material

24_2018_2022_MOESM1_ESM.docx (3.2 mb)
Supplementary material 1 (DOCX 3323 kb)

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.CSIR Fourth Paradigm Institute (CSIR-4PI)BangaloreIndia

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