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1. Arctic Sea Ice Volume Variability over 1901–2010: A Model-Based Reconstruction

   https://doi.org/10.1175/jcli-d-19-0008.1  

   Schweiger, Axel J.; Wood, Kevin R.; Zhang, Jinlun (August 2019, Journal of Climate)

   Abstract PIOMAS-20C, an Arctic sea ice reconstruction for 1901–2010, is produced by forcing the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) with ERA-20C atmospheric data. ERA-20C performance over Arctic sea ice is assessed by comparisons with measurements and data from other reanalyses. ERA-20C performs similarly with respect to the annual cycle of downwelling radiation, air temperature, and wind speed compared to reanalyses with more extensive data assimilation such as ERA-Interim and MERRA. PIOMAS-20C sea ice thickness and volume are then compared with in situ and aircraft remote sensing observations for the period of ~1950–2010. Error statistics are similar to those for PIOMAS. We compare the magnitude and patterns of sea ice variability between the first half of the twentieth century (1901–40) and the more recent period (1980–2010), both marked by sea ice decline in the Arctic. The first period contains the so-called early-twentieth-century warming (ETCW; ~1920–40) during which the Atlantic sector saw a significant decline in sea ice volume, but the Pacific sector did not. The sea ice decline over the 1979–2010 period is pan-Arctic and 6 times larger than the net decline during the 1901–40 period. Sea ice volume trends reconstructed solely from surface temperature anomalies are smaller than PIOMAS-20C, suggesting that mechanisms other than warming, such as changes in ice motion and deformation, played a significant role in determining sea ice volume trends during both periods. 

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2. Declining tropical cyclone frequency under global warming

   https://doi.org/10.1038/s41558-022-01388-4  

   Chand, Savin S.; Walsh, Kevin J.; Camargo, Suzana J.; Kossin, James P.; Tory, Kevin J.; Wehner, Michael F.; Chan, Johnny C.; Klotzbach, Philip J.; Dowdy, Andrew J.; Bell, Samuel S.; et al (July 2022, Nature Climate Change)

   Abstract Assessing the role of anthropogenic warming from temporally inhomogeneous historical data in the presence of large natural variability is difficult and has caused conflicting conclusions on detection and attribution of tropical cyclone (TC) trends. Here, using a reconstructed long-term proxy of annual TC numbers together with high-resolution climate model experiments, we show robust declining trends in the annual number of TCs at global and regional scales during the twentieth century. The Twentieth Century Reanalysis (20CR) dataset is used for reconstruction because, compared with other reanalyses, it assimilates only sea-level pressure fields rather than utilize all available observations in the troposphere, making it less sensitive to temporal inhomogeneities in the observations. It can also capture TC signatures from the pre-satellite era reasonably well. The declining trends found are consistent with the twentieth century weakening of the Hadley and Walker circulations, which make conditions for TC formation less favourable. 

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3. Factors Affecting the Weakening Rate of Tropical Cyclones over the Western North Pacific

   https://doi.org/10.1175/MWR-D-19-0356.1  

   Fei, Rong; Xu, Jing; Wang, Yuqing; Yang, Chi (September 2020, Monthly Weather Review)

   null (Ed.)

   Abstract In this study, based on the 6-hourly tropical cyclone (TC) best track data and the ERA-Interim reanalysis data, statistical analyses as well as a machine learning approach, XGBoost, are used to identify and quantify factors that affect the overwater weakening rate (WR) of TCs over the western North Pacific (WNP) during 1980–2017. Statistical analyses show that the TC rapid weakening events usually occur when intense TCs cross regions with a sharp decrease in sea surface temperature (DSST) with relatively faster eastward or northward translational speeds, and move into regions with large environmental vertical wind shear (VWS) and dry conditions in the upshear-left quadrant. Results from XGBoost indicate that the relative intensity of TC (TC intensity normalized by its maximum potential intensity), DSST, and VWS are dominant factors determining TC WR, contributing 26.0%, 18.3%, and 14.9% to TC WR, and 9, 5, and 5 m s−1 day−1 to the variability of TC WR, respectively. Relative humidity in the upshear-left quadrant of VWS, zonal translational speed, divergence at 200 hPa, and meridional translational speed contribute 12.1%, 11.8%, 8.8%, and 8.1% to TC WR, respectively, but only contribute 2–3 m s−1 day−1 to the variability of TC WR individually. These findings suggest that the improved accurate analysis and prediction of the dominant factors may lead to substantial improvements in the prediction of TC WR. 

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4. Subseasonal Tropical Cyclone Prediction and Modulations by MJO and ENSO in CESM2

   https://doi.org/10.1029/2022JD036986  

   Li, Hui; Richter, Jadwiga H.; Lee, Chia‐Ying; Kim, Hyemi (November 2022, Journal of Geophysical Research: Atmospheres)

   Abstract Subseasonal tropical cyclone (TC) reforecasts from the Community Earth System Model version 2 (CAM6) subseasonal prediction system are examined in this study. We evaluate the modeled TC climatology and the probabilistic forecast skill of basin‐wide TC genesis at weekly temporal resolution. Prediction skill is calculated using the Brier skill score relative to a constant annual mean climatology and to a monthly varying seasonal climatology during TC season. The model captures the observed basin‐wide climatological TC seasonality and spatial distributions at weeks 1–6, but TC genesis is largely underestimated from Week 2 onward. For some basins and lead times, the predicted TC genesis is primarily controlled by the number of TC “seeds” and the mean‐state climate condition. The model has good prediction skill relative to the constant climatology across all the basins and lead times, but is only skillful in the eastern Pacific, North Indian Ocean, and Southern Hemisphere at Week 1 when compared to the seasonal climatology, indicating limited skill in predicting deviations from the seasonal cycle. We find strong modulations of the predicted TC genesis at up to 3 weeks of forecast lead time by the Madden‐Julian Oscillation. The interannual variability of predicted TC genesis and accumulated cyclone energy are skillfully predicted in the North Atlantic and the Northwestern Pacific, with a strong modulation by the El Nino‐Southern Oscillation. 

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5. How Frequently Does Rapid Intensification Occur after Rapid Contraction of the Radius of Maximum Wind in Tropical Cyclones over the North Atlantic and Eastern North Pacific?

   https://doi.org/10.1175/MWR-D-21-0322.1  

   Li, Yuanlong; Wang, Yuqing; Tan, Zhe-Min (July 2022, Monthly Weather Review)

   Abstract The phenomenon that rapid contraction (RC) of the radius of maximum wind (RMW) could precede rapid intensification (RI) in tropical cyclones (TCs) has been found in several previous studies, but it is still unclear how frequently and to what extent RC precedes RI in rapidly intensifying and contracting TCs in observations. In this study, the statistical relationship between RMW RC and TC RI is examined based on the extended best track dataset for the North Atlantic and eastern North Pacific during 1999–2019. Results show that for more than ∼65% of available TCs, the time of the peak contraction rate precedes the time of the peak intensification rate, on average, by ∼10–15 h. With the quantitatively defined RC and RI, results show that ∼50% TCs with RC experience RI, and TCs with larger intensity and smaller RMW and embedded in more favorable environmental conditions tend to experience RI more readily following an RC. Among those TCs with RC and RI, more than ∼65% involve the onset of RC preceding the onset of RI, on average, by ∼15–25 h. The preceding time tends to be longer with lower TC intensity and larger RMW and shows weak correlations with environmental conditions. The qualitative results are insensitive to the time interval for the calculation of intensification/contraction rates and the definition of RI. The results from this study can improve our understanding of TC structure and intensity changes. 

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