drag forces are caused by changes in the external and internal friction in the atmosphere. Changes in surface friction are mainly caused by changes in the surface roughness due to land use and cover change (LUCC), including urbanization, and changes in internal friction are mainly induced by changes in the boundary layer characteristics. Future studies should compare the spatio-temporal differences in SWS between high and low altitudes and quantify the effects of different factors on the SWS. Additionally, in-depth analysis of extreme SWS events and prediction of future mean and extreme SWS values at global and regional scales are also necessary. Abstract Changes in terrestrial near-surface wind speed (SWS) are induced by a combination of anthropogenic activities and natural climate changes. Thus, the study of the long-term changes of SWS and their causes is very important for recognizing the effects of these processes. Although the slowdown in SWS has been analyzed in previous studies, to the best of knowledge, no overall comparison or detailed examination of this research has been performed. Similarly, the causes of the decreases in SWS and the best directions of future research have not been discussed in depth. Therefore, we analyzed a series of studies reporting SWS trends spanning the last 30 years from around the world. The changes in SWS differ among different regions. The most significant decreases have occurred in Central Asia and North America, with mean linear trends of − 0.11 m s −1 decade −1 ; the second most significant decreases have occurred in Europe, East Asia, and South Asia, with mean linear trends of − 0.08 m s −1 decade −1 ; and the weakest decrease has occurred in Australia. Although the SWS in Africa has decreased, this region lacks long-term observational data. Therefore, the uncertainties in the long-term SWS trend are higher in this region than in other regions. The changes in SWS, caused by a mixture of global-, regional-, and localscale factors, are mainly due to changes in driving forces and drag forces. The changes in the driving forces are caused by changes in atmospheric circulation, and the changes in the Keywords

Probabilistic tropical cyclone (TC) occurrence, at lead times of week 1–4, in the Subseasonal to Seasonal (S2S) dataset are examined here. Forecasts are defined over 15° in latitude × 20° in longitude regions, and the prediction skill is measured using the Brier skill score with reference to climatological reference forecasts. Two types of reference forecasts are used: a seasonally constant one and a seasonally varying one, with the latter used for forecasts of anomalies from the seasonal climatology. Models from the European Centre for Medium-Range Weather Forecasts (ECMWF), Australian Bureau of Meteorology, and Météo-France/Centre National de Recherche Météorologiques have skill in predicting TC occurrence four weeks in advance. In contrast, only the ECMWF model is skillful in predicting the anomaly of TC occurrence beyond one week. Errors in genesis prediction largely limit models’ skill in predicting TC occurrence. Three calibration techniques, removing the mean genesis and occurrence forecast biases, and a linear regression method, are explored here. The linear regression method performs the best and guarantees a higher skill score when applied to the in-sample dataset. However, when applied to the out-of-sample data, especially in areas where the TC sample size is small, it may reduce the models’ prediction skill. Generally speaking, the S2S models are more skillful in predicting TC occurrence during favorable Madden–Julian oscillation phases. Last, we also report accumulated cyclone energy predictions skill using the ranked probability skill score.

The eastward-propagating Madden–Julian oscillation (MJO) typically exhibits complex behavior during its passage over the Maritime Continent, sometimes slowly propagating eastward and other times stalling and even terminating there with large amounts of rainfall. This is a huge challenge for present-day numerical models to simulate. One possible reason is the inadequate treatment of the diurnal cycle and its scale interaction with the MJO. Here these two components are incorporated into a simple self-consistent multiscale model that includes one model for the intraseasonal impact of the diurnal cycle and another one for the planetary/intraseasonal circulation. The latter model is forced self-consistently by eddy flux divergences of momentum and temperature from a model for the diurnal cycle with two baroclinic modes, which capture the intraseasonal impact of the diurnal cycle. The MJO is modeled as the planetary-scale circulation response to a moving heat source on the synoptic and planetary scales. The results show that the intraseasonal impact of the diurnal cycle during boreal winter tends to strengthen the westerlies (easterlies) in the lower (upper) troposphere in agreement with the observations. In addition, the temperature anomaly induced by the intraseasonal impact of the diurnal cycle can cancel that from the symmetric–asymmetric MJO with convective momentum transfer, yielding stalled or suppressed propagation of the MJO across the Maritime Continent. The simple multiscale model should be useful for the MJO in observations or more complex numerical models.