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Time series analysis and lag-based multiple regression analysis (MRA) were applied to the observed water levels from July 1st 1998 to December 31st 2013 to update knowledge concerning the interaction among the water level fluctuations in the Mekong River (MR), the Tonle Sap River (TSR) and Tonle Sap Lake (TSL) and to interpolate water levels using the flood pulse system, where continuous hydrological measurements have not been developed. The reverse flow from the TSR to TSL occurs mainly from May to October and its duration differs yearly ranging from 80 to 150 days. Periodic components (annual and semi-annual) and short-term variations (< 174 days including non-periodic components) of water level in the MR highly correlated to those in the TSL and TSR through the flood pulse, but the signal of the short-term flood weakened in the TSL. The lag-based MRA model well reproduced the observed water levels (both R2 and NSE > 0.99), indicating that the water level in the MR propagates and affects water levels in the TSL and TSR and this process is more influential than the other inputs from tributaries and rainfall to the lake. In addition, the regression model implied that the incoming water of TSL might be almost provided by the flow from the MR via TSR in 2011, while the other sources (i.e., tributaries and rainfall) contributed to the rising water level of TSL in 2012 and 2013. The presented approach and model can be applied to areas where the flood pulse is regularly observed and can support to evaluate roles of river–lake interaction, and the model can also support interpolating missing water level data simply and robustly. [ABSTRACT FROM AUTHOR]

Statistically significant time‐lagged relationship of pre‐monsoon precipitation in Indochina Peninsula (ICP) with large‐scale feature over the Pacific and Indian Oceans, which was recently found in observational datasets by the authors, is investigated with a large‐ensemble (100 ensembles) simulation database called "Database for Policy Decision‐Making for Future Climate Change" (d4PDF). Two different strategies were taken to perform Empirical Orthogonal Function (EOF) analysis on the large‐ensemble dataset, namely statistics of the analysis results for each ensemble member separately and analysis on the 6,000‐year data (100 times 60 years). d4PDF can reproduce well the climatological characteristics of the observed pre‐monsoon precipitation. Significant time‐lagged correlations of several climate indices related to sea surface temperature (SST) with the pre‐monsoon precipitation in ICP as obtained in the observation are confirmed in d4PDF for both strategies of EOF analyses on each ensemble member and on 6,000‐year data. The climate simulation in d4PDF can capture the lag‐to‐lag variations of the time‐lagged correlation patterns very well, though it is weaker. The time‐lagged regressions of SST and zonal wind at 850 hPa upon the first principal component (PC1) time‐series of the EOF analysis of the pre‐monsoon precipitation over ICP are investigated in low latitudes over the Pacific and Indian Oceans. The observed time‐lagged regression features are also confirmed in d4PDF dataset; the significant regression areas expand larger and significant time lags become longer than the observation, especially in the case of 6,000‐year data, due to enough number of samples. Cluster analysis on the regression maps shows that the obtained groups with larger numbers of ensemble members are closer to the observation than the other groups. The randomness of time‐lagged regression feature among the 100 ensemble members is not directly related to the randomness of the SST perturbation introduced in the lower boundary condition for the ensemble simulation of d4PDF. [ABSTRACT FROM AUTHOR]

Statistically significant time-lagged relationship of pre-monsoon precipitation in Indochina Peninsula (ICP) with large-scale feature over the Pacific and Indian Oceans, which was recently found in observational datasets by the authors, is investigated with a large-ensemble (100 ensembles) simulation database called "Database for Policy Decision-Making for Future Climate Change" (d4PDF). Two different strategies were taken to perform Empirical Orthogonal Function (EOF) analysis on the large-ensemble dataset, namely statistics of the analysis results for each ensemble member separately and analysis on the 6,000-year data (100 times 60 years). d4PDF can reproduce well the climatological characteristics of the observed pre-monsoon precipitation. Significant time-lagged correlations of several climate indices related to sea surface temperature (SST) with the pre-monsoon precipitation in ICP as obtained in the observation are confirmed in d4PDF for both strategies of EOF analyses on each ensemble member and on 6,000-year data. The climate simulation in d4PDF can capture the lag-to-lag variations of the time-lagged correlation patterns very well, though it is weaker. The time-lagged regressions of SST and zonal wind at 850 hPa upon the first principal component (PC1) time-series of the EOF analysis of the pre-monsoon precipitation over ICP are investigated in low latitudes over the Pacific and Indian Oceans. The observed time-lagged regression features are also confirmed in d4PDF dataset; the significant regression areas expand larger and significant time lags become longer than the observation, especially in the case of 6,000-year data, due to enough number of samples. Cluster analysis on the regression maps shows that the obtained groups with larger numbers of ensemble members are closer to the observation than the other groups. The randomness of time-lagged regression feature among the 100 ensemble members is not directly related to the randomness of the SST perturbation introduced in the lower boundary condition for the ensemble simulation of d4PDF. [ABSTRACT FROM AUTHOR]