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Anantha Aiyyer, Ademe Mekonnen, and Carl J. Schreck III


The impact of localized convection associated with tropical cyclones (TCs) on activity ascribed to equatorial waves is estimated. An algorithm is used to remove outgoing longwave radiation (OLR) signal in the vicinity of observed tropical cyclones, and equatorial wave modes are extracted using the standard wavenumber–frequency decomposition method. The results suggest that climatological activity of convection-coupled equatorial waves is overestimated where TC tracks are densest. The greatest impact is found for equatorial Rossby (ER)- and tropical depression (TD)-type waves followed by the Madden–Julian oscillation (MJO). The basins most affected are the eastern and western North Pacific Ocean where, on average, TCs may contribute up to 10%–15% of the climatological wave amplitude variance in these modes. In contrast, Kelvin waves are least impacted by the projection of TCs. The results are likely relevant for studies on the climatology of equatorial waves in observations and global climate model simulations and for those examining individual cases of TC genesis modulated by equatorial wave activity.

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Carl J. Schreck III, Lei Shi, James P. Kossin, and John J. Bates


The Madden–Julian oscillation (MJO) and convectively coupled equatorial waves are the dominant modes of synoptic-to-subseasonal variability in the tropics. These systems have frequently been examined with proxies for convection such as outgoing longwave radiation (OLR). However, upper-tropospheric water vapor (UTWV) gives a more complete picture of tropical circulations because it is more sensitive to the drying and warming associated with subsidence. Previous studies examined tropical variability using relatively short (3–7 yr) UTWV datasets. Intersatellite calibration of data from the High Resolution Infrared Radiation Sounder (HIRS) has recently produced a homogeneous 32-yr climate data record of UTWV for 200–500 hPa. This study explores the utility of HIRS UTWV for identifying the MJO and equatorial waves.

Spectral analysis shows that the MJO and equatorial waves stand out above the low-frequency background in UTWV, similar to previous findings with OLR. The fraction of variance associated with the MJO and equatorial Rossby waves is actually greater in UTWV than in OLR. Kelvin waves, on the other hand, are overshadowed in UTWV by horizontal advection from extratropical Rossby waves.

For the MJO, UTWV identifies subsidence drying in the subtropics, poleward of the convection. These dry anomalies are associated with the MJO’s subtropical Rossby gyres. MJO events with dry anomalies over the central North Pacific Ocean also amplify the 200-hPa flow pattern over North America 7 days later. These events cannot be identified using equatorial OLR alone, which demonstrates that UTWV is a useful supplement for identifying the MJO, equatorial waves.

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Boyin Huang, Matthew J. Menne, Tim Boyer, Eric Freeman, Byron E. Gleason, Jay H. Lawrimore, Chunying Liu, J. Jared Rennie, Carl J. Schreck III, Fengying Sun, Russell Vose, Claude N. Williams, Xungang Yin, and Huai-Min Zhang


This analysis estimates uncertainty in the NOAA global surface temperature (GST) version 5 (NOAAGlobalTemp v5) product, which consists of sea surface temperature (SST) from the Extended Reconstructed SST version 5 (ERSSTv5) and land surface air temperature (LSAT) from the Global Historical Climatology Network monthly version 4 (GHCNm v4). Total uncertainty in SST and LSAT consists of parametric and reconstruction uncertainties. The parametric uncertainty represents the dependence of SST/LSAT reconstructions on selecting 28 (6) internal parameters of SST (LSAT), and is estimated by a 1000-member ensemble from 1854 to 2016. The reconstruction uncertainty represents the residual error of using a limited number of 140 (65) modes for SST (LSAT). Uncertainty is quantified at the global scale as well as the local grid scale. Uncertainties in SST and LSAT at the local grid scale are larger in the earlier period (1880s–1910s) and during the two world wars due to sparse observations, then decrease in the modern period (1950s–2010s) due to increased data coverage. Uncertainties in SST and LSAT at the global scale are much smaller than those at the local grid scale due to error cancellations by averaging. Uncertainties are smaller in SST than in LSAT due to smaller SST variabilities. Comparisons show that GST and its uncertainty in NOAAGlobalTemp v5 are comparable to those in other internationally recognized GST products. The differences between NOAAGlobalTemp v5 and other GST products are within their uncertainties at the 95% confidence level.

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