Advanced search
1 file | 8.25 MB Add to list

Evaluation of PERSIANN-CDR for meteorological drought monitoring over China

(2016) REMOTE SENSING. 8(5).
Author
Organization
Abstract
In this paper, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) is analyzed for the assessment of meteorological drought. The evaluation is conducted over China at 0.5 degrees spatial resolution against a ground-based gridded China monthly Precipitation Analysis Product (CPAP) from 1983 to 2014 (32 years). The Standardized Precipitation Index (SPI) at various time scales (1 month to 12 months) is calculated for detecting drought events. The results show that PERSIANN-CDR depicts similar drought behavior as the ground-based CPAP in terms of capturing the spatial and temporal patterns of drought events over eastern China, where the intensity of gauge networks and the frequency of droughts are high. 6-month SPI shows the best agreement with CPAP in identifying drought months. However, large differences between PERSIANN-CDR and CPAP in depicting drought patterns and identifying specific drought events are found over northwestern China, particularly in Xinjiang and Qinghai-Tibet Plateau region. Factors behind this may be due to the relatively sparse gauge networks, the complicated terrain and the performance of PERSIANN algorithm.
Keywords
MULTISATELLITE PRECIPITATION ANALYSIS, GLOBAL PRECIPITATION, WATER-RESOURCES, ANALYSIS TMPA, SUMMER PRECIPITATION, GAUGE, OBSERVATIONS, TROPICAL RAINFALL, PASSIVE MICROWAVE, TIBETAN PLATEAU, CLIMATE-CHANGE, drought monitoring, meteorological drought, PERSIANN-CDR precipitation, SPI

Downloads

  • Guo et al Remote Sensing.pdf
    • full text
    • |
    • open access
    • |
    • PDF
    • |
    • 8.25 MB

Citation

Please use this url to cite or link to this publication:

MLA
Guo, Hao, Anming Bao, Tie Liu, et al. “Evaluation of PERSIANN-CDR for Meteorological Drought Monitoring over China.” REMOTE SENSING 8.5 (2016): n. pag. Print.
APA
Guo, H., Bao, A., Liu, T., Chen, S., & Ndayisaba, F. (2016). Evaluation of PERSIANN-CDR for meteorological drought monitoring over China. REMOTE SENSING, 8(5).
Chicago author-date
Guo, Hao, Anming Bao, Tie Liu, Sheng Chen, and Felix Ndayisaba. 2016. “Evaluation of PERSIANN-CDR for Meteorological Drought Monitoring over China.” Remote Sensing 8 (5).
Chicago author-date (all authors)
Guo, Hao, Anming Bao, Tie Liu, Sheng Chen, and Felix Ndayisaba. 2016. “Evaluation of PERSIANN-CDR for Meteorological Drought Monitoring over China.” Remote Sensing 8 (5).
Vancouver
1.
Guo H, Bao A, Liu T, Chen S, Ndayisaba F. Evaluation of PERSIANN-CDR for meteorological drought monitoring over China. REMOTE SENSING. 2016;8(5).
IEEE
[1]
H. Guo, A. Bao, T. Liu, S. Chen, and F. Ndayisaba, “Evaluation of PERSIANN-CDR for meteorological drought monitoring over China,” REMOTE SENSING, vol. 8, no. 5, 2016.
@article{8576778,
  abstract     = {In this paper, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) is analyzed for the assessment of meteorological drought. The evaluation is conducted over China at 0.5 degrees spatial resolution against a ground-based gridded China monthly Precipitation Analysis Product (CPAP) from 1983 to 2014 (32 years). The Standardized Precipitation Index (SPI) at various time scales (1 month to 12 months) is calculated for detecting drought events. The results show that PERSIANN-CDR depicts similar drought behavior as the ground-based CPAP in terms of capturing the spatial and temporal patterns of drought events over eastern China, where the intensity of gauge networks and the frequency of droughts are high. 6-month SPI shows the best agreement with CPAP in identifying drought months. However, large differences between PERSIANN-CDR and CPAP in depicting drought patterns and identifying specific drought events are found over northwestern China, particularly in Xinjiang and Qinghai-Tibet Plateau region. Factors behind this may be due to the relatively sparse gauge networks, the complicated terrain and the performance of PERSIANN algorithm.},
  articleno    = {379},
  author       = {Guo, Hao and Bao, Anming and Liu, Tie and Chen, Sheng and Ndayisaba, Felix},
  issn         = {2072-4292},
  journal      = {REMOTE SENSING},
  keywords     = {MULTISATELLITE PRECIPITATION ANALYSIS,GLOBAL PRECIPITATION,WATER-RESOURCES,ANALYSIS TMPA,SUMMER PRECIPITATION,GAUGE,OBSERVATIONS,TROPICAL RAINFALL,PASSIVE MICROWAVE,TIBETAN PLATEAU,CLIMATE-CHANGE,drought monitoring,meteorological drought,PERSIANN-CDR precipitation,SPI},
  language     = {eng},
  number       = {5},
  pages        = {17},
  title        = {Evaluation of PERSIANN-CDR for meteorological drought monitoring over China},
  url          = {http://dx.doi.org/10.3390/rs8050379},
  volume       = {8},
  year         = {2016},
}

Altmetric
View in Altmetric
Web of Science
Times cited: