No abstract

The influence of El Niño Southern Oscillation (ENSO) on the north Indian temperature, precipitation, and potential evapotranspiration (PET) change patterns were evaluated during the monsoon season across the last century. Trends and shifts in 146 districts were assessed using nonparametric statistical tests. To quantify their temporal variation, the concept of apportionment entropy was applied to both the annual and seasonal scales. Results suggest that the El Niño years played a greater role in causing hydro-climatological changes compared to the La Niña or neutral years. El Niño was more influential in causing shifts compared to trends. For certain districts, a phase change in ENSO reversed the trend/shift direction. The century-wide analysis suggested that the vast majority of the districts experienced significant decreasing trends/shifts in temperature and PET. However, precipitation experienced both increasing and decreasing trends/shifts based on the location of the districts. Entropy results suggested a lower apportionment of precipitation compared to the other variables, indicating an intermittent deviation of precipitation pattern from the generic trend. The findings may help understand the effects of ENSO on the hydro-climatological variables during the monsoon season. Practitioners may find the results useful as monsoon is the most important season for India causing climate extremes.

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The trend and shift in the seasonal temperature, precipitation and streamflow time series across the Midwest have been analyzed, for the period 1960-2013, using the statistical analyses (Mann-Kendall test with and without considering short term persistence (MK2 and MK1, respectively) and Pettitt test). The paper also utilizes a relatively new approach, wavelet analysis, for testing the existence of trend and shift in the time series. The method has the ability to decompose a time series in to lower (trend) and higher frequency components (noise). Discrete wavelet transform (DWT) has been employed in the present study with an aim to find which periodicities are mainly responsible for trend in the original data. The combination of MK1, MK2 and DWT along with Pettitt test hasn't been extensively used up to this time, especially in detecting trend and shift in the Midwest. The analysis of climate division temperature and precipitation data and USGS naturalized streamflow data revealed the presence of periodicity in the time series data. All the incorporated time series data were seasonal to analyze the trends and shifts for four seasons-winter, spring, summer and fall independently. D3 component of DWT were observed to be influential in detecting real trend in Temperature, precipitation and streamflow data, however unlike temperature, precipitation and streamflow showed decreasing trend as well. Shift was relatively observed more than trend in the region with dominance of D3 component in the data. The result indicate the significant warming trend which agrees with the "increasing temperature" observations in the past two decades, however a clear explanation for precipitation and streamflow is not obvious.

Understanding what controls vertical motion profile shape is fundamental to understanding tropical precipitation patterns.There are two controls that have been studied previously: the thermodynamic profiles of the environment and the dynamics imposed by sea surface temperature (SST) patterns. To fit these two perspectives together, we focus on two regions with distinctly top and bottom-heavy vertical motion: The Western Pacific and the Central Eastern Pacific. These regions have roughly the same column-integrated water, precipitation, and column-integrated horizontal moisture advection, however the shape in the West is top-heavy while the East is bottom-heavy. The top-heaviness angle is introduced to describe this difference.To study thermodynamic controls on vertical motion profile shape, we use weak temperature gradient (WTG) simulations. We are able to simulate the shape differences between our two regions from the thermodynamics. We then show that the dry static stability and the underlying SST are the most important for the vertical motion shape differences between our two regions. We then show that the qualitative shape differences can be explained using a simple entraining plume model. The entraining plume model accepts the temperature and moisture profiles as inputs and outputs the plumeâ\euros buoyancy, which is directly related to the vertical motion profile shape. We find that increasing the dry static stability leads to bottom-heaviness. We hypothesize that the SST gradients lead to an equilibrium temperature that is cooler than an identical atmosphere with no gradient. The cooler boundary layer leads to a thermodynamic environment that is more conducive to bottom-heaviness.