Assessment on Temporal and Spatial Variation Analysis of Extreme Temperature Indices: A Case Study of the Yangtze River Basin
Abstract
:1. Introduction
2. Study Area, Data, and Methods
2.1. Study Area
2.2. Data
2.3. Methods
2.3.1. Extreme Temperature Indices
2.3.2. Mann–Kendall (M–K) Trend and Abrupt Changes Analysis
2.3.3. R/S Analysis
2.3.4. The Sliding t-Test
3. Results
3.1. Temporal and Spatial Variations of Extreme Temperatures
3.1.1. Temporal Variation of Relative Indices
3.1.2. Spatial Variation of Relative Indices
3.2. Temporal and Spatial Variations of Absolute Indices
3.2.1. Temporal Variation of Absolute Indices
3.2.2. Spatial Variation of Absolute Indices
3.3. Temporal and Spatial Variations of the Extremal Indices
3.3.1. Temporal Variation of the Extremal Indices
3.3.2. Spatial Variation of Extremal Indices
3.4. Analysis of Abrupt Changes of Extreme Temperature Indices
3.4.1. Relative Indices
3.4.2. Absolute Indices
3.4.3. Extremal Indices
3.5. The Prediction of Extreme Temperature Indices
3.6. Possible Causes of Observed Changes in Temperature Extremes
4. Discussions
4.1. Comparison with Previous Studies
4.2. The Effects of Extreme Temperature Indices
5. Conclusions
- (1)
- The trend of cold days, cold nights, ice days, and frost days decreased by −2.2, −3.6, −0.66, and −2.5 d/10a, respectively, while the trend of TX90, TN90, SU, TXx, and TR shows trends of 4.73, 3.82, 2.2, 0.27, and 2.8 d/10a, respectively. The tendency rates of TXn, TNn, TNx, and DTR range is 0.39, 0.5, 0.24, and −0.003 °C/10a, respectively. Spatially, the main extremely warm indices of meteorological stations were increasing, while the extremely cold indices were decreasing in the Yangtze River Basin.
- (2)
- Except for DTR and TN90, there were no abrupt changes; the other 11 extreme temperature indicators all had abrupt changes. TX10 changed abruptly in 1987 and TN10 changed abruptly in 2003; ID changed abruptly in 1982 and FD changed abruptly in 1988; SU had an abrupt change point in 1988 and TR had an abrupt change point in 1985; the occurrences of abrupt changes of TXn and TNx were in 2001 and 1998, respectively. The main cold indices changed abruptly in the 1980s and the main warm indices changed abruptly in the late 1990s and early 2000s.
- (3)
- The extreme temperature indices are affected by the atmospheric circulation and urban heat island effect in the Yangtze River Basin. Relative indices and absolute indices will continue to maintain the present trend in the future, which has a certain guiding significance for agricultural and social economic development.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Category (1) 1 | Indices | Descriptive Name | Definitions | Units |
---|---|---|---|---|
Relative indices | TX10 | Cold days | Number of days with Tmax < 10th percentile | days |
TN10 | Cold nights | Number of days with Tmin < 10th percentile | days | |
TX90 | Warm days | Number of days with Tmax > 90th percentile | days | |
TN90 | Warm nights | Number of days with Tmin > 90th percentile | days | |
Absolute indices | ID | Ice days | Annual count when TX (daily minimum temperature) < 0 °C | days |
FD | Frost days | Annual count when TN (daily maximum temperature) < 0 °C | days | |
SU | Summer days | Annual count when TX > 25 °C | days | |
TR | Tropical nights | Annual count when TN > 20 °C | days | |
Extremal indices | TXn | Coldest day | Annual lowest TX | °C |
TNn | Coldest night | Annual lowest TN | °C | |
TXx | Warmest day | Annual highest TX | °C | |
TNx | Warmest night | Annual highest TN | °C | |
DTR | Diurnal temperature range | Monthly mean difference between TX and TN | °C |
Extreme Temperature Indices | H | R2 |
---|---|---|
FD | 0.7974 | 0.9196 |
SU | 0.7823 | 0.8656 |
TR | 0.9424 | 0.8834 |
TX10 | 0.8380 | 0.8841 |
TX90 | 0.8604 | 0.7859 |
TN90 | 0.8385 | 0.8521 |
TN10 | 0.7258 | 0.8690 |
Extreme Temperature Indices | Historical Change Tendency | H | Future Change Tendency |
---|---|---|---|
FD | decrease | 0.7974 | decrease |
SU | increase | 0.7823 | increase |
TR | increase | 0.9424 | increase |
TX10 | decrease | 0.8380 | decrease |
TX90 | increase | 0.8604 | increase |
TN90 | increase | 0.8385 | increase |
TN10 | decrease | 0.7258 | decrease |
Indices | 1970–1992 | 1993–2014 |
---|---|---|
FD | −3.13 d/10a | −0.098 d/10a |
ID | −0.729 d/10a | −0.27 d/10a |
SU | −1 d/10a | 2.74 d/10a |
TR | 1 d/10a | 0.4 d/10a |
TNX | 0.62 °C/10a | −0.16 °C/10a |
TXX | 0.092 °C/10a | 0.62 °C/10a |
TXn | 0.19 °C/10a | 0.443 °C/10a |
TNn | 0.789 °C/10a | −0.092 °C/10a |
DTR | −0.129 °C/10a | 0.066 °C/10a |
TX10 | −0.989 d/10a | 0.865 d/10a |
TX90 | −0.788 d/10a | 8.479 d/10a |
TN10 | −4.51 d/10a | 0.375 d/10a |
TN90 | 1.49 d/10a | 7.837 d/10a |
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Shi, G.; Ye, P. Assessment on Temporal and Spatial Variation Analysis of Extreme Temperature Indices: A Case Study of the Yangtze River Basin. Int. J. Environ. Res. Public Health 2021, 18, 10936. https://doi.org/10.3390/ijerph182010936
Shi G, Ye P. Assessment on Temporal and Spatial Variation Analysis of Extreme Temperature Indices: A Case Study of the Yangtze River Basin. International Journal of Environmental Research and Public Health. 2021; 18(20):10936. https://doi.org/10.3390/ijerph182010936
Chicago/Turabian StyleShi, Guangxun, and Peng Ye. 2021. "Assessment on Temporal and Spatial Variation Analysis of Extreme Temperature Indices: A Case Study of the Yangtze River Basin" International Journal of Environmental Research and Public Health 18, no. 20: 10936. https://doi.org/10.3390/ijerph182010936