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Michael B. Natoli and Eric D. Maloney

through a weighted linear interpolation. As a result, infrared information is only used to track systems identified by microwave estimates rather than adding additional calibrated precipitation estimates. Estimates are then bias corrected using gauge data over land and the Global Precipitation Climatology Project over ocean ( Xie et al. 2017 ). While such bias correction improves the accuracy of satellite precipitation estimates over complex terrain, there are still quantitative weaknesses in products

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Emily M. Riley Dellaripa, Eric D. Maloney, Benjamin A. Toms, Stephen M. Saleeby, and Susan C. van den Heever

. Other studies have focused on the changes in amplitude and phase of the DCP over the MC through different MJO large-scale conditions. Using TRMM observations, Peatman et al. (2014) found that the DCP amplitude over MC land peaks just prior to the arrival of large-scale active MJO convection. Birch et al. (2016) reached a similar conclusion with TRMM observations and regional climate model simulations, but focused on the DCP over Sumatra during different large-scale MJO conditions. Cloud

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Benjamin A. Toms, Susan C. van den Heever, Emily M. Riley Dellaripa, Stephen M. Saleeby, and Eric D. Maloney

important for understanding the role of moist convection in climate in general, and particularly as it relates to the MJO. Fig . 1. Pentad OLR anomalies for the simulated MJO event based on OMI, reconstructed using the OMI principal components for each pentad. The anomalies shown are only for the 20–96-day anomalies represented by OMI and therefore do not directly consider the mesoscale convective structure of the MJO. Positive (negative) OLR anomalies correspond to suppressed (enhanced) convection

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