| 1. |
-
- 2019
-
Tidskriftsartikel (refereegranskat)
|
|
| 2. |
- An, Dong, et al.
(författare)
-
Evidence of climate shift for temperature and precipitation extremes across Gansu Province in China
- 2020
-
Ingår i: Theoretical and Applied Climatology. - : Springer Science and Business Media LLC. - 1434-4483 .- 0177-798X. ; 139:3-4, s. 1137-1149
-
Tidskriftsartikel (refereegranskat)abstract
- Temperature and precipitation extremes are the dominant causes of natural disasters. In this study, seven indices of extreme temperature and precipitation events in Gansu Province, China, were analysed for the period 1961–2017. An abrupt climate shift was recorded during 1980–1981. Thus, the study period was divided into a preshift (before the climate shift) period 1961–1980 and an aftshift (after the climate shift) period 1981–2017. Comparison of mean extreme indices for preshift and aftshift periods was performed for the purpose of exploring possible increasing/decreasing patterns. Generalized extreme value (GEV) distribution was applied spatially to fit the extreme indices with return periods up to 100 years for preshift/aftshift periods. Singular value decomposition (SVD) was adopted to investigate possible correlation between the extreme climate events and indices of large-scale atmospheric circulation. The results indicate that changes in mean and return levels between the preshift and aftshift periods vary significantly in time and space for different extreme indices. Increase in extreme temperature regarding magnitude and frequency for the aftshift period as compared with the preshift period suggests a change to a warmer and more extreme climate during recent years. Changes in precipitation extremes were different in southern and northern parts of Gansu. The precipitation extremes in the north have increased that can result in more serious floods and droughts in the future. SVD analyses revealed a complex pattern of correlation between climate extremes and indices of large-scale atmospheric circulation. Strengthening of westerlies and weakening of the south summer monsoon contribute to the complex changing patterns of precipitation extremes. Results in this study will contribute to disaster risk prevention and better water management in this area.
|
|
| 3. |
- Cao, Qing, et al.
(författare)
-
ENSO influence on rainy season precipitation over the Yangtze River Basin
- 2017
-
Ingår i: Water. - : MDPI AG. - 2073-4441. ; 9:7
-
Tidskriftsartikel (refereegranskat)abstract
- The paper explores the impact of El Niño-Southern Oscillation (ENSO) on rainy season precipitation properties over the Yangtze River Basin. The multi-scale moving t-test was used to determine the onset and withdrawal of the rainy season. Results showed the following: (1) Onset and withdrawal of the averaged rainy season over the Yangtze River Basin showed a similar distribution and both progressed northwards and westwards. There is a trend for delayed onset of rainy season precipitation over the Yangtze River Basin. A similar trend in the withdrawal of rainy season precipitation was not found. (2) The decaying Central and Eastern PacificWarming are indicative of wet signals in the Yangtze River Basin, with precipitation anomalies up to 25% above normal. The decaying Eastern Pacific Cooling and developing Eastern PacificWarming are indicative of dry signals over the Yangtze River Basin, with 5-20% lower than average precipitation (3) ENSO Modoki in the developing phase is more important than the developing ENSO when it comes to present wetter or drier signals. Conversely, the decaying ENSO shows more prominent wet or dry signals than the decaying ENSO Modoki.
|
|
| 4. |
- Cao, Qing, et al.
(författare)
-
Impact of ENSO regimes on developing- and decaying-phase precipitation during rainy season in China
- 2017
-
Ingår i: Hydrology and Earth System Sciences. - : Copernicus GmbH. - 1027-5606 .- 1607-7938. ; 21:11, s. 5415-5426
-
Tidskriftsartikel (refereegranskat)abstract
- This study investigated the influence of five El Niño-Southern Oscillation (ENSO) types on rainy-season precipitation in China: central Pacific warming (CPW), eastern Pacific cooling (EPC), eastern Pacific warming (EPW), conventional ENSO and ENSO Modoki. The multi-scale moving t test was applied to determine the onset and withdrawal of rainy season. Results showed that the precipitation anomaly can reach up to 30 % above average precipitation during decaying CPW and EPW phases. Developing EPW could cause decreasing precipitation over large areas in China with 10-30 % lower than average precipitation in most areas. Conventional El Niño in the developing phase had the largest influence on ENSO-related precipitation among developing ENSO and ENSO Modoki regimes. Decaying ENSO also showed a larger effect on precipitation anomalies, compared to decaying ENSO Modoki. The difference between rainy-season precipitation under various ENSO regimes may be attributed to the combined influence of anti-cyclone in the western North Pacific and the Indian monsoon. Stronger monsoon and anti-cyclone are associated with enhanced rainy-season precipitation. The results suggest a certain predictability of rainy-season precipitation related to ENSO regimes.
|
|
| 5. |
- Cao, Qing, et al.
(författare)
-
On the predictability of daily rainfall during rainy season over the Huaihe River Basin
- 2019
-
Ingår i: Water. - : MDPI AG. - 2073-4441. ; 11:5
-
Tidskriftsartikel (refereegranskat)abstract
- In terms of climate change and precipitation, there is large interest in how large-scale climatic features affect regional rainfall amount and rainfall occurrence. Large-scale climate elements need to be downscaled to the regional level for hydrologic applications. Here, a new Nonhomogeneous Hidden Markov Model (NHMM) called the Bayesian-NHMM is presented for downscaling and predicting of multisite daily rainfall during rainy season over the Huaihe River Basin (HRB). The Bayesian-NHMM provides a Bayesian method for parameters estimation. The model avoids the risk to have no solutions for parameter estimation, which often occurs in the traditional NHMM that uses point estimates of parameters. The Bayesian-NHMM accurately captures seasonality and interannual variability of rainfall amount and wet days during the rainy season. The model establishes a link between large-scale meteorological characteristics and local precipitation patterns. It also provides a more stable and efficient method to estimate parameters in the model. These results suggest that prediction of daily precipitation could be improved by the suggested new Bayesian-NHMM method, which can be helpful for water resources management and research on climate change.
|
|
| 6. |
- Chen, Sichun, et al.
(författare)
-
Spatiotemporal Changes in Precipitation and Temperature in the Huaibei Plain and the Relation between Local Precipitation and Global Teleconnection Patterns
- 2019
-
Ingår i: Journal of Hydrologic Engineering. - 1084-0699. ; 24:8
-
Tidskriftsartikel (refereegranskat)abstract
- The Huaibei Plain is one of the most severe water scarcity areas in China. Understanding of hydroclimatic variation in this area at different timescales and its relationship with global teleconnection patterns are important for assessment of water resources utilization. In this study, spatiotemporal changes of seasonal and annual precipitation and temperature, including trend, abrupt change, variability, and periodicity were examined to recognize the potential remarkable changes during the last 41 years. The relationship between precipitation in the Huaibei Plain and teleconnection patterns using climate indexes was revealed by applying singular value decomposition. Results showed a nonsignificant annual precipitation increase about 2.4 mm/year. The annual average temperature increased about 1.2°C during 1970-2010. The abrupt change of annual precipitation mainly occurred during the 1970s and 1980s, while the primary mutation points for temperature were detected in 1990s, especially in 1997. The mean areal precipitation is characterized by a statistically significant 2- to 4-year periodicity at different phases, and the 2- to 5-year band is the major cycle for annual average temperature in this region. A statistically strong 5- to 8-year periodicity for precipitation could be detected from the middle of the 1980s to the end of the 1990s. Precipitation has positive correlation with the West Pacific Pattern and El Nino Southern Oscillation. The investigated results might have considerable implications for managing water resources in the Huaibei Plain.
|
|
| 7. |
- Du, Yiheng, et al.
(författare)
-
Hydrologic response of climate change in the source region of the Yangtze River, based on water balance analysis
- 2017
-
Ingår i: Water. - : MDPI AG. - 2073-4441. ; 9:2
-
Tidskriftsartikel (refereegranskat)abstract
- Due to the large amount of water resources stored in glaciers, permafrost, and lakes, the source region of the Yangtze River (SRYR) is of great importance for the overall basin water flow. For this purpose, a state of art review and calculations were made for the period 1957-2013 using observed hydrological and meteorological data with a water balance approach. Actual evapotranspiration was calculated and validated by empirical formulas. Water storage change analysis was conducted with uncertainty boundaries using a 10-year moving window. Results show that temperature, precipitation, and actual evapotranspiration in the SRYR increased by 0.34°C, 11.4 mm, and 7.6 mm per decade, respectively (significant at 0.05 probability level). Runoffappears to have increased at a rate of 3.3 mm per decade. The SRYR water storage in total has not changed significantly during the period, although the moving average is mostly below zero. Based on the water balance equation, the increase in calculated evapotranspiration is mainly due to the significantly increasing temperature. This in combination with increasing precipitation leads to a relatively stable water storage during the study period. Correlation analyses show that precipitation dominates runoffduring the warm season (May to October), while temperature anomalies dominate the runoffduring the cold season (November to April). The influence of temperature on runoffseems to enhance during the winter period.
|
|
| 8. |
- du, Yiheng, et al.
(författare)
-
Integrated large‐scale circulation impact on rainy season precipitation in the source region of the Yangtze River
- 2020
-
Ingår i: International Journal of Climatology. - : Wiley. - 1097-0088 .- 0899-8418. ; 40:4, s. 2285-2295
-
Tidskriftsartikel (refereegranskat)abstract
- Monthly precipitation data at regular grids of 0.5° × 0.5° derived from observations during June–August 1961–2016 were used to reveal characteristics of large‐scale circulations associated with rainy season precipitation over the source region of the Yangtze River (SRYR). The integrated impact of major influencing circulation patterns was examined by principal component analysis and composites. Results showed that the first rainy season precipitation mode associates with the Southern Oscillation Index (SOI) and the Pacific Decadal Oscillation (PDO), explaining 64% of spatial and temporal rainy season precipitation variance in the region. Composites of precipitation pattern under different phases of SOI and PDO revealed that the effect of PDO on precipitation varies with the SOI phase. When out of phase with the SOI, PDO‐induced precipitation anomalies are magnified. When they are in phase, anomalies weaken or even disappear. Composites of moisture flux patterns show that large‐scale atmospheric circulation affects the strength of westerlies that transport moisture to the study area and formation of convergence. In coming decades, the PDO is likely to continue in a negative phase with La Niña (positive SOI) events, implying more precipitation during the rainy season. Consequently, this knowledge can be used to improve decision making regarding water supply and flood risk management in the SRYR.
|
|
| 9. |
- du, Yiheng, et al.
(författare)
-
Multi-Space Seasonal Precipitation Prediction Model Applied to the Source Region of the Yangtze River, China
- 2019
-
Ingår i: Water. - 2073-4441. ; 11:12
-
Tidskriftsartikel (refereegranskat)abstract
- This paper developed a multi-space prediction model for seasonal precipitation using a high-resolution grid dataset (0.5° × 0.5°) together with climate indices. The model is based on principal component analyses (PCA) and artificial neural networks (ANN). Trend analyses show that mean annual and seasonal precipitation in the area is increasing depending on spatial location. For this reason, a multi-space model is especially suited for prediction purposes. The PCA-ANN model was examined using a 64-grid mesh over the source region of the Yangtze River (SRYR) and was compared to a traditional multiple regression model with a three-fold cross-validation method. Seasonal precipitation anomalies (1961–2015) were converted using PCA into principal components. Hierarchical lag relationships between principal components and each potential predictor were identified by Spearman rank correlation analyses. The performance was compared to observed precipitation and evaluated using mean absolute error, root mean squared error, and correlation coefficient. The proposed PCA-ANN model provides accurate seasonal precipitation prediction that is better than traditional regression techniques. The prediction results displayed good agreement with observations for all seasons with correlation coefficients in excess of 0.6 for all spatial locations.
|
|
| 10. |
- Jiang, Peng, et al.
(författare)
-
Changes of storm properties in the United States : Observations and multimodel ensemble projections
- 2016
-
Ingår i: Global and Planetary Change. - : Elsevier BV. - 0921-8181. ; 142, s. 41-52
-
Tidskriftsartikel (refereegranskat)abstract
- Changes in climate are likely to induce changes in precipitation characteristics including intensity, frequency, duration and patterns of events. In this paper, we evaluate the performance of multiple regional climate models (RCMs) in the North American Regional Climate Change Assessment Program (NARCCAP) to simulate storm properties including storm duration, inter-storm period, storm intensity, and within-storm patterns at eight locations in the continental US. We also investigate the future projections of them based on precipitation from NARCCAP historic runs and future runs. Results illustrate that NARCCAP RCMs are consistent with observed precipitation in the seasonal variation of storm duration and inter-storm period, but fail to simulate the magnitude. The ability to simulate the seasonal trend of average storm intensity varies among locations. Within-storm patterns from RCMs exhibit greater variability than from observed records. Comparisons between RCM-historic simulations and RCM projections indicate that there is a large variation in the future changes in storm properties. However, multi-model ensembles of the storm properties suggest that most regions of the United States will experience future changes in storm properties that includes shorter storm duration, longer inter-storm period, and larger average storm intensity.
|
|
