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SCIENCE CHINA Technological Sciences, Volume 63 , Issue 5 : 819-828(2020) https://doi.org/10.1007/s11431-019-1457-3

Satellite precipitation product: Applicability and accuracy evaluation in diverse region

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  • ReceivedJun 28, 2019
  • AcceptedOct 8, 2019
  • PublishedJan 10, 2020

Abstract

Satellite precipitation products, e.g., Tropical Rainfall Measuring Mission version-07 (hereafter TRMM) and its successor Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (hereafter IMERG) are being used at a global scale for rainfall estimation. Recently, SM2RAIN-ASCAT (hereafter SM2RAIN) is a novel addition to satellite-based precipitation products which gives the rainfall estimates from the knowledge of soil moisture state and is based on ‘bottom to top’ approach. A comparative assessment of any newly developed product or a new version of the product is quite vital for algorithm developers and users. Hence, this research work was carried out to evaluate the accuracy and applicability of SM2RAIN, in comparison to in-situ data, TRMM, and IMERG in diverse regions of Pakistan. The comparative analysis was performed on a temporal scale (daily and monthly) and seasonal scale (spring, autumn, summer, and winter) using five performance metrics namely, root mean square error (RMSE), correlation coefficient (CC), false alarm ratio (FAR), the probability of detection (POD), and critical success index (CSI). The results showed that: (1) SM2RAIN is a better rainfall estimation product in the dry region (having avg. CC>0.35), however, less effective in hilly and mountainous terrain having high rainfall intensity; (2) SM2RAIN provides more satisfactory estimates in winter and autumn seasons, while relative poor in the summer season; (3) SM2RAIN performs better in terms of rainfall detection with an average POD of 0.61; (4) the overall performance of SM2RAIN is very convincing and it was concluded that SM2RAIN can be a feasible satellite product for most of the areas of Pakistan. It is noteworthy here to mention that this could be the preliminary assessment of SM2RAIN in diverse climatic zones of Pakistan.


Funded by

the Project(Grant,No.,2018A003)


Acknowledgment

This work was supported by the Project of Hubei Key Laboratory of Regional Development and Environmental Response (Hubei University) (Grant No. 2018A003). The authors would also like to thank the developers of the GPM and TRMM products and specifically Brocca, L., et al. for providing the SM2RAIN data.


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  • Figure 1

    Spatial distribution of 33 selected gauge stations across the whole country in four different climatic zones (Zone 1 to Zone 4).

  • Figure 2

    Spatial distribution of (a) root mean square error, and correlation coefficient, (b) false alarm ratio, the probability of detection and critical success index for SM2RAIN, TRMM and IMERG.

  • Figure 3

    Bar charts of performance metrics obtained by comparing the monthly average rainfall estimates of satellite products with gauge data in all four zones.

  • Figure 4

    Boxplots for the mean square error (a), correlation coefficient (b), probability of detection (c), false alarm ration (d), and critical success index (e) of SM2RAIN, TRMM, and IMERG for different seasons, i.e. winter, spring, summer, and autumn.

  • Table 1   Formulas of performance metrics, their ranges, and ideal values

    Name

    Formula

    Range

    Perfect value

    Root mean square error

    RMSE=[i=1N(RisRio)2N]

    0 to ∞

    0

    Correlation coefficient

    CC=i=1N(RisRavgs)(RioRavgo)i=1N(RisRavgs)2i=1N(RioRavgo)2

    +1 to −1

    1

    False alarm ratio

    FAR=(F.A)/(H+F.A)

    0 to 1

    0

    Probability of detection

    POD=H/(H+M)

    0 to 1

    1

    Critical success index

    CSI=H/T.E

    0 to 1

    1

    N represents the total number of observations, Ris represents daily rainfall estimate from precipitation product for the respective time step in millimetre, Rio shows daily observed rainfall from gauge of respective time step in millimetre, Ravgs indicates average of rainfall estimate from satellite based precipitation product, Ravgo represents average of observed rainfall values, F.A indicates number of false alarms, i.e., when there is no precipitation recorded by gauge but satellite product records rainfall, H shows number of hits, i.e., when rainfall is correctly recorded by satellite product, M represents number of misses, i.e., when the rainfall is not recorded by satellite product, T.E represents total number of events, i.e., F.A+H+M.

  • Table 2   Zonal averages of performance metrics of SM2RAIN, TRMM, and IMERG for 4 zones

    Zone

    RMSE

    CC

    SM2RAIN

    TRMM

    IMERG

    SM2RAIN

    TRMM

    IMERG

    1

    4.52

    5.72

    4.64

    0.18

    0.05

    0.12

    2

    7.18

    7.95

    7.28

    0.28

    0.1

    0.19

    3

    6.33

    8.4

    6.42

    0.22

    0.13

    0.16

    4

    3.94

    5.81

    4.06

    0.2

    0.13

    0.19

    Zone

    FAR

    POD

    SM2RAIN

    TRMM

    IMERG

    SM2RAIN

    TRMM

    IMERG

    1

    0.16

    0.23

    0.34

    0.73

    0.1

    0.21

    2

    0.31

    0.35

    0.42

    0.63

    0.28

    0.33

    3

    0.18

    0.26

    0.32

    0.46

    0.3

    0.29

    4

    0.11

    0.19

    0.24

    0.47

    0.27

    0.31

    Zone

    CSI

     

    SM2RAIN

    TRMM

    IMERG

     

    1

    0.15

    0.07

    0.14

     

    2

    0.28

    0.18

    0.23

     

    3

    0.21

    0.16

    0.18

     

    4

    0.19

    0.13

    0.15

     

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