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SCIENCE CHINA Earth Sciences, Volume 60, Issue 9: 1707-1718(2017) https://doi.org/10.1007/s11430-016-9059-0

From solar terms to medical terms (Part I): A first step with big data

Ge CHEN1,2,*, Jie SHI3,†
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  • ReceivedMar 1, 2017
  • AcceptedMay 22, 2017
  • PublishedJul 18, 2017

Abstract

The story of the Twenty-four Solar Terms (24-STs) is one of the most popular elements in Chinese culture, which has a profound influence on agriculture production, health care, and even daily life in both ancient and modern China. This traditional calendric system was invented by the Chinese ancestors through combining fundamental astronomical knowledge with climatic and phenological conditions in the Yellow River Basin some 2000 years ago. Although the basic philosophy of the 24-STs remains valid for the country as a whole to date, their regional robustness has been increasingly challenged by accumulating observational data in terms of temporal shift and spatial inhomogeneity. To tackle these issues, we propose to recalibrate the medically related critical timings of Great Heat and Great Cold in the classic ST system by using big meteorological data, and adjust them by introducing geographically correlated analytical models. As a result, a novel calendric system, called the Twenty-four Medical Terms (24-MTs), has been developed as an upgraded version of the traditional 24-STs. The proposed 24-MTs are characterized by two striking features with respect to the 24-STs: A varying duration of each MT instead of a fixed one for the ST, and a geographically dependent timing for each MT instead of a unified one for the entire nation. As such, the updated 24-MTs are expected to provide a more realistic estimate of these critical timings around the year, and hence, a more precise guidance to agronomic planning and health care activity in China.


Funded by

Natural Science Foundation of China(61361136001)


Acknowledgment

The authors would like to thank Wang Xuan, Ren Yibin and Liu Yingjie for their assistances in figure plotting and literature survey. This research was partially supported by the National Natural Science Foundation of China (Grant No. 61361136001).


Contributions statement

Corresponding author (email: jieshiqd68@163.com)


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  • Figure 1

    Map of mainland China with administrative boundaries. Also overlaid are the regions of YRB (yellow), CRB (blue), and ZRB (red), as well as the locations of the 24, 34, and 9 Chinese meteorological stations within the three basins.

  • Figure 2

    Geographical distributions of SAT related properties over mainland China derived from the BEST dataset of 1960–2015 using Fast Fourier Transform (FFT). (a) Amplitude of annual SAT harmonic; (b) amplitude of semiannual SAT harmonic; (c) percentage of variance explained by annual SAT harmonic; (d) percentage of variance explained by semiannual SAT harmonic. Also overlaid is the boundary of the YRB.

  • Figure 3

    Geographical distributions of the timing (in sequential day) of annual maximum ((a), (c), (e)) and minimum ((b), (d), (f)) SAT ((a) and (b)), precipitation ((c) and (d)), and humidity ((e) and (f)) deriving from the BEST, GPCP, and NCEP datasets using FFT, respectively. Also overlaid is the boundary of the YRB.

  • Figure 4

    Annual variations of SAT over mainland China derived from the CMA (red) and BEST (blue) datasets using EEMD, respectively. (a) Overall average; (b) the YRB; (c) the CRB; (d) the ZRB.

  • Figure 5

    Time shifts of the twenty STs (excluding the SE, SS, AE, and WS) for the YRB (red), CRB (green), and ZRB (blue) derived from the BEST SAT dataset using EEMD.

  • Figure 6

    Geographical distributions of the time shift of annual maximum ((a), (c), (e)) and minimum ((b), (d), (f)) SAT derived from the BEST ((a) and (b)) and CMA ((c) and (d)) datasets using EEMD. (e) and (f) are the differences of (a) and (c), and (b) and (d), respectively.

  • Figure 7

    The main menu (a) and search result (b) of the ST/MT-geographical information system for estimating the timing of calibrated Solar Terms for Chinese cities over the mainland.

  • Figure 8

    Geographical distributions of the time shift of the STs corresponding to the warming period derived from the BEST dataset using EEMD. (a) BS1; (b) RW; (c) WI; (d) PB; (e) GR; (f) BS2; (g) GF; (h) GE; (i) SH.

  • Figure 9

    Geographical distributions of the time shift of the STs corresponding to the cooling period derived from the BEST dataset using EEMD. (a) BA; (b) LH; (c) WD; (d) CD; (e) FD; (f) BW; (g) LS; (h) GS; (i) SC.

  • Figure 10

    Time shifts of the twenty STs (excluding the SE, SS, AE, and WS) for Beijing (red) and Shanghai (blue) derived from the BEST SAT dataset using EEMD.

  • Table 1   Timings of the 24-STs and their MT shifts for the YRB, CRB and ZRB derived from the BEST data using EEMD

    No.

    Term title

    Sun’s longitude

    Date (day/month)

    ST (sequential day)

    MT (time shift with respect to ST)

    YRB

    CRB

    ZRB

    1

    SE

    20−21/03

    82.35

    0

    0

    0

    2

    PB

    15°

    04−06/04

    97.57

    ‒7.94

    ‒3.18

    ‒1.27

    3

    GR

    30°

    19−21/04

    112.79

    ‒7.10

    ‒2.07

    ‒0.49

    4

    BS2

    45°

    05−07/05

    128.00

    ‒6.25

    ‒0.95

    0.29

    5

    GF

    60°

    20−22/05

    143.22

    ‒5.41

    0.17

    1.07

    6

    GE

    75°

    05−07/06

    158.44

    ‒4.57

    1.29

    1.84

    7

    SS

    90°

    21−22/06

    173.66

    0

    0

    0

    8

    SH

    105°

    06−08/07

    188.88

    ‒2.89

    3.53

    3.40

    9

    GH

    120°

    22−24/07

    204.10

    ‒2.09

    4.64

    4.18

    10

    BA

    135°

    07−09/08

    220.31

    ‒3.95

    2.50

    2.38

    11

    LH

    150°

    22−24/08

    235.53

    ‒4.81

    1.37

    1.58

    12

    WD

    165°

    07−09/09

    250.75

    ‒5.67

    0.23

    0.78

    13

    AE

    180°

    22−24/09

    265.97

    0

    0

    0

    14

    CD

    195°

    08−09/10

    280.19

    ‒6.39

    ‒1.05

    0.19

    15

    FD

    210°

    23−24/10

    295.41

    ‒7.26

    ‒2.19

    ‒0.61

    16

    BW

    225°

    07−08/11

    310.63

    ‒8.12

    ‒3.33

    ‒1.41

    17

    LS

    240°

    22−23/11

    325.84

    ‒8.98

    ‒4.46

    ‒2.21

    18

    GS

    255°

    06−08/12

    341.06

    ‒9.84

    ‒5.60

    ‒3.01

    19

    WS

    270°

    21−23/12

    356.28

    0

    0

    0

    20

    SC

    285°

    05−07/01

    6.26

    ‒11.32

    ‒7.63

    ‒4.36

    21

    GC

    300°

    20−21/01

    21.47

    ‒12.14

    ‒8.77

    ‒5.16

    22

    BS1

    315°

    03−05/02

    36.69

    ‒11.30

    ‒7.66

    ‒4.38

    23

    RW

    330°

    18−20/02

    51.91

    ‒10.46

    ‒6.54

    ‒3.60

    24

    WI

    345°

    05−07/03

    67.13

    ‒9.62

    ‒5.42

    ‒2.83

  • Table 2   Comparison of the timings of GH and GC for the YRB, CRB and ZRB regions based on BEST and CMA datasets using EEMD

    Region

    SAT

    Timing (sequential day)

    Time shift (day)

    MT (BEST)

    MT (CMA)

    ST

    MT (BEST)

    MT (CMA)

    MT (BEST-CMA)

    YRB

    Max (GH)

    202.04

    200.47

    204.10

    ‒2.09

    ‒3.62

    1.54

    Min (GC)

    9.33

    10.17

    21.47

    ‒12.14

    ‒11.30

    ‒0.84

    CRB

    Max (GH)

    208.74

    208.46

    204.10

    4.64

    4.36

    0.28

    Min (GC)

    12.70

    12.77

    21.47

    ‒8.77

    ‒8.71

    ‒0.07

    ZRB

    Max (GH)

    208.27

    207.27

    204.10

    4.18

    3.18

    1.00

    Min (GC)

    16.31

    15.48

    21.47

    ‒5.16

    ‒5.99

    0.83

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