The tropical longwave cloud-radiative feedback is calculated using outgoing longwave radiation (OLR) and precipitation in two versions of Global Precipitation Climatology Project, version 1.3 (GPCPv1.3) and the newer version 3.2 (GPCPv3.2). GPCPv3.2 has less frequent precipitation between 10-40 mm day-1 but more frequent precipitation at other intensities than in GPCPv1.3. The radiative feedback on intraseasonal timescales calculated by GPCPv3.2 is weaker than in GPCPv1.3 by almost half. The radiative feedbacks are also found to have a red-noise like distribution in spatiotemporal spectral space in both precipitation products, but the magnitudes are weaker in GPCPv3.2. OLR lags precipitation by phase angles of up to 40° in eastward-propagating Kelvin and n = 0 inertia-gravity waves in GPCPv3.2, but not in GPCPv1.3. The updated magnitudes and phase shift of the feedback may modify our understanding of tropical disturbances such as the Madden-Julian oscillation.

Recent work using CMIP5 models under RCP8.5 suggests that individual multimodel-mean changes in precipitation and wind variability associated with the Madden-Julian oscillation (MJO) are not detectable until the end of the 21st century. However, a decrease in the ratio of MJO circulation to precipitation anomaly amplitude is detectable as early as 2021-2040, consistent with an increase in dry static stability as predicted by weak-temperature-gradient balance. Here, we examine MJO activity in multiple reanalyses (ERA5,MERRA-2, and ERA-20C) and find that MJO wind and precipitation anomaly amplitudes have a complicated time evolution over the record. However, a decrease in the ratio of MJO circulation to precipitation anomaly amplitude is detected over the observational period, consistent with the change in dry static stability. These results suggest that weak-temperature-gradient theory may be able to help explain changes in MJO activity in recent decades.

Extratropical influences on tropical sea surface temperature (SST) have implications for decadal predictability. We implement a cloud-locking technique to highlight the critical role of clouds in shaping tropical SST response to extratropical thermal forcing. With heating imposed over either extratropical Northern Atlantic or Pacific, Hadley Cells respond similarly that the trades strengthen south of the rainband. The wind-evaporation-SST (WES) feedback leads to cooling over the southern subtropics, which is enhanced in the southeastern Pacific due to the positive feedback between SST and stratiform clouds. This cooling is further extended toward the central Pacific via a WES effect associated with zonally contrasting cloud-radiative-SST feedbacks in the tropics, which is observed in both slab-ocean and dynamical-ocean experiments. We propose that the meridional and zonal SST gradients are tightly linked via WES effects and the cloud-radiative-SST feedbacks, which are largely determined by the climatological rainband position and the spatial distribution of cloud properties.

Boreal-wintertime hindcasts in the Unified Forecast System with the tropics nudged toward reanalysis improve United States (U.S.) West Coast precipitation forecasts at Weeks 3-4 lead times when compared to those without nudging. To diagnose the origin of these improvements, a multivariate k-means clustering method is used to group hindcasts into subsets by their initial conditions. One cluster characterized by an initially strong Aleutian Low demonstrates larger improvements at Weeks 3-4 with nudging compared to others. The greater improvements with nudging for this cluster are related to the model error in simulating the interaction between the Aleutian Low and the teleconnection patterns associated with the Madden-Julian oscillation (MJO) and El Niño-Southern Oscillation (ENSO). Improving forecasts of tropical intraseasonal precipitation, especially during early MJO phases under non-cold ENSO, may be important for producing better Weeks 3-4 precipitation forecasts for the U.S. West Coast.

Due to the coupled nature of the earth system, precipitation forecast errors at S2S lead times are caused by a combination of errors/biases from the atmosphere, ocean, ice and land across a range of spatial and temporal scales. We show that UFS precipitation errors over the U.S. at Weeks 3-4 can be directly related to biases in simulating tropical dynamics. In particular, the inability of the UFS to realistically simulate the Madden-Julian oscillation (MJO) leads to biases in the teleconnection to North America that produces these errors. When the tropics are nudged to produce an accurate representation of the MJO and other tropical disturbances, U.S. West Coast precipitation biases are substantially reduced. A clustering analysis is used to show that the greatest forecast improvements with nudging occur during warm ENSO events when MJO convection is in the Indian Ocean and about to move into the Maritime Continent. Physical mechanisms that explain the improvement in tropical-extratropical teleconnections during certain MJO and ENSO states will be discussed. We will also present future plans to combine state-of-the-art developments in machine learning with process-based diagnostics of the tropical moisture and moist static energy (MSE) budgets to understand and correct precipitation biases in coupled UFS hindcasts. In particular, we will discuss how model biases and errors in tropical variability (e.g. MJO) and associated teleconnections to midlatitudes lead to errors in U.S. precipitation on S2S timescales, and present methods to reduce these errors via post-processing on a forecast-by-forecast basis.