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Assessment of IMERG-V06, TRMM-3B42V7, SM2RAIN-ASCAT, and PERSIANN-CDR Precipitation Products over the Hindu Kush Mountains of Pakistan, South Asia
by
Hamza, Ali
, Chen, Xi
, Afzal, Arslan
, Gulakhmadov, Aminjon
, Azam, Muhammad
, Kamran Shafi, Muhammad
, Anjum, Muhammad Naveed
, Masud Cheema, Muhammad Jehanzeb
in
Accuracy
/ Algorithms
/ Bias
/ correlation
/ Correlation coefficient
/ Correlation coefficients
/ detection
/ Estimates
/ False alarms
/ Gauges
/ Hindu Kush Mountains
/ Hydrometeorology
/ IMERG-V06
/ light
/ Mountains
/ Pakistan
/ PERSIANN-CDR
/ Precipitation
/ probability
/ Remote sensing
/ Root-mean-square errors
/ satellite precipitation
/ satellites
/ seasons
/ SM2Rain-ASCAT
/ Temporal variability
/ TRMM satellite
/ TRMM-3B42V7
2020
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Assessment of IMERG-V06, TRMM-3B42V7, SM2RAIN-ASCAT, and PERSIANN-CDR Precipitation Products over the Hindu Kush Mountains of Pakistan, South Asia
by
Hamza, Ali
, Chen, Xi
, Afzal, Arslan
, Gulakhmadov, Aminjon
, Azam, Muhammad
, Kamran Shafi, Muhammad
, Anjum, Muhammad Naveed
, Masud Cheema, Muhammad Jehanzeb
in
Accuracy
/ Algorithms
/ Bias
/ correlation
/ Correlation coefficient
/ Correlation coefficients
/ detection
/ Estimates
/ False alarms
/ Gauges
/ Hindu Kush Mountains
/ Hydrometeorology
/ IMERG-V06
/ light
/ Mountains
/ Pakistan
/ PERSIANN-CDR
/ Precipitation
/ probability
/ Remote sensing
/ Root-mean-square errors
/ satellite precipitation
/ satellites
/ seasons
/ SM2Rain-ASCAT
/ Temporal variability
/ TRMM satellite
/ TRMM-3B42V7
2020
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Assessment of IMERG-V06, TRMM-3B42V7, SM2RAIN-ASCAT, and PERSIANN-CDR Precipitation Products over the Hindu Kush Mountains of Pakistan, South Asia
by
Hamza, Ali
, Chen, Xi
, Afzal, Arslan
, Gulakhmadov, Aminjon
, Azam, Muhammad
, Kamran Shafi, Muhammad
, Anjum, Muhammad Naveed
, Masud Cheema, Muhammad Jehanzeb
in
Accuracy
/ Algorithms
/ Bias
/ correlation
/ Correlation coefficient
/ Correlation coefficients
/ detection
/ Estimates
/ False alarms
/ Gauges
/ Hindu Kush Mountains
/ Hydrometeorology
/ IMERG-V06
/ light
/ Mountains
/ Pakistan
/ PERSIANN-CDR
/ Precipitation
/ probability
/ Remote sensing
/ Root-mean-square errors
/ satellite precipitation
/ satellites
/ seasons
/ SM2Rain-ASCAT
/ Temporal variability
/ TRMM satellite
/ TRMM-3B42V7
2020
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Assessment of IMERG-V06, TRMM-3B42V7, SM2RAIN-ASCAT, and PERSIANN-CDR Precipitation Products over the Hindu Kush Mountains of Pakistan, South Asia
Journal Article
Assessment of IMERG-V06, TRMM-3B42V7, SM2RAIN-ASCAT, and PERSIANN-CDR Precipitation Products over the Hindu Kush Mountains of Pakistan, South Asia
2020
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Overview
In this study, the performances of four satellite-based precipitation products (IMERG-V06 Final-Run, TRMM-3B42V7, SM2Rain-ASCAT, and PERSIANN-CDR) were assessed with reference to the measurements of in-situ gauges at daily, monthly, seasonal, and annual scales from 2010 to 2017, over the Hindu Kush Mountains of Pakistan. The products were evaluated over the entire domain and at point-to-pixel scales. Different evaluation indices (Correlation Coefficient (CC), Root Mean Square Error (RMSE), Bias, and relative Bias (rBias)) and categorical indices (False Alarm Ration (FAR), Critical Success Index (CSI), Success Ratio (SR), and Probability of Detection (POD)) were used to assess the performances of the products considered in this study. Our results indicated the following. (1) IMERG-V06 and PERSIANN capably tracked the spatio-temporal variation of precipitation over the studied region. (2) All satellite-based products were in better agreement with the reference data on the monthly scales than on daily time scales. (3) On seasonal scale, the precipitation detection skills of IMERG-V06 and PERSIANN-CDR were better than those of SM2Rain-ASCAT and TRMM-3B42V7. In all seasons, overall performance of IMERG-V06 and PERSIANN-CDR was better than TRMM-3B42V7 and SM2Rain-ASCAT. (4) However, all products were uncertain in detecting light and moderate precipitation events. Consequently, we recommend the use of IMERG-V06 and PERSIANN-CDR products for subsequent hydro-meteorological studies in the Hindu Kush range.
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