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Abstract: In this paper, the variability of daily temperature in the Yangtze River Delta (YRD) for the period 1958–2007 was investigated by selecting three typical temperature variables (daily minimum, mean and maximum temperatures) and the diurnal temperature range (DTR). Three variability patterns of daily mean temperature and two variability patterns of daily minimum and maximum temperatures were first classed, and then statistical properties of three temperature variables in 1958–1985 and 1986–2007 were analyzed. After that, temporal trends of three temperature variables and DTR were detected. Finally, the impacts of urbanization on the variability of daily temperature were investigated. Results indicate that: (1) daily mean temperature shows more complex variability than daily minimum and maximum temperatures; (2) in 1986–2007 three temperature variables have bigger mean values but smaller C v (coefficient of variance) values, and are more close to normal probability distribution; (3) three temperature variables show positive trends in 1986–2007, and the increase of daily mean temperature is more due to the increase of daily minimum temperature in the northern YRD but due to daily maximum temperature in the mid and southern YRD; (4) in the mid and southern YRD, daily maximum temperature has bigger increasing magnitude than daily minimum temperature in 1986–2007, causing positive trend of DTR; and (5) rapid urbanization causes normal distribution of three temperature variables, and notably increasing magnitude of daily temperature and DTR in 1986–2007 at the lower reaches of the Yangtze River and the Hangzhou Bay. [Copyright &y& Elsevier]

This paper explored the projected changes in precipitation, maximum temperature (T max), and minimum temperature (T min) over the Yangtze River Basin (YRB) based on 23 Global climate models (GCMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6). The Empirical Quantile Mapping (EQM) approach was firstly applied to correct the biases in the GCMs. Next, the future changes were investigated by analyzing the multi-model ensemble (MME) of the bias-corrected dataset during 2025–2044 (near-term), 2045–2064 (mid-term), and 2081–2100 (long-term) periods, with reference to the baseline period 1995–2014, under three integrated scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) of the Shared Socioeconomic Pathways (SSPs) and the Representative Concentration Pathways (RCPs). Results show that: (1) the biases in CMIP6 GCMs can be effectively corrected by EQM, and the MME performs better than individual models for each climatic variable. (2) Precipitation over the YRB from 2025 to 2100 is projected to increase at the rate of 9.66 mm/decade, 13.45 mm/decade, and 21.01 mm/decade under SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5, respectively. In the long-term, the annual precipitation is projected to increase by 10.41%, 10.66% and 15.80%, under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5, respectively. (3) T max (T min) over the YRB is projected to increase by 0.09 (0.07) °C/decade, 0.29 (0.27) °C/decade, and 0.66 (0.64) °C/decade under SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5, respectively. In the long-term, T max (T min) averaged over the YRB is projected to increase by 1.75 (1.50) °C, 2.72 (2.54) °C and 5.04 (4.85) °C under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5, respectively. (4) Uncertainties in the projected precipitation and temperature over the YRB were reduced based on MME. But further researches, such as selecting the superior models with respect to the regional climate of the YRB from the CMIP6 and using the ensemble methods that assign weight based on the performance of each model, are still needed to provide more reliable climate projections. • Projected changes were explored by 23 CMIP6 GCMs under the three SSP-RCP scenarios. • Biases in the GCMs were corrected by Empirical Quantile Mapping (EQM) method. • Multi-model ensemble (MME) was used to reduce the uncertainties. [ABSTRACT FROM AUTHOR]