Responses of tropical cyclones (TCs) to CO2 doubling are explored using coupled global climate models (GCMs) with increasingly refined atmospheric/land horizontal grids (~ 200 km, ~ 50 km and ~ 25 km). The three models exhibit similar changes in background climate fields thought to regulate TC activity, such as relative sea surface temperature (SST), potential intensity, and wind shear. However, global TC frequency decreases substantially in the 50 km model, while the 25 km model shows no significant change. The ~ 25 km model also has a substantial and spatially-ubiquitous increase of Category 3–4–5 hurricanes. Idealized perturbation experiments are performed to understand the TC response. Each model’s transient fully-coupled 2 × CO2 TC activity response is largely recovered by “time-slice” experiments using time-invariant SST perturbations added to each model’s own SST climatology. The TC response to SST forcing depends on each model’s background climatological SST biases: removing these biases leads to a global TC intensity increase in the ~ 50 km model, and a global TC frequency increase in the ~ 25 km model, in response to CO2-induced warming patterns and CO2 doubling. Isolated CO2 doubling leads to a significant TC frequency decrease, while isolated uniform SST warming leads to a significant global TC frequency increase; the ~ 25 km model has a greater tendency for frequency increase. Global TC frequency responds to both (1) changes in TC “seeds”, which increase due to warming (more so in the ~ 25 km model) and decrease due to higher CO2 concentrations, and (2) less efficient development of these“seeds” into TCs, largely due to the nonlinear relation between temperature and saturation specific humidity.
Liao, Weilin, Xiaoping Liu, Dan Li, M Luo, D Wang, S Wang, and Jane Baldwin, et al., October 2018: Stronger Contributions of Urbanization to Heat Wave Trends in Wet Climates. Geophysical Research Letters, 45(20), DOI:10.1029/2018GL079679. Abstract
It is well‐known that urban areas are typically hotter than the surrounding (vegetated) rural areas. However, the contribution of urbanization to the trends of extreme temperature events such as heat waves (HWs) is less understood. Using a homogenized meteorological dataset drawn from nearly 2,000 stations in China, we find that urban and rural areas have different HW trends and the urban‐rural contrast of HW trends varies across climate regimes. In wet climates, the increasing trends of HWs in urban areas are greater than those in rural areas, suggesting a positive contribution of urbanization to HW trends. In arid regions, the urbanization contribution to HW trends is smaller and even negative. The stronger urbanization contribution to HW trends in wet climates is linked to the smaller variability of urban heat island intensity. This study highlights the important role of local hydroclimate in modulating the urbanization contribution to extreme temperatures.
Zhao, L, M Oppenheimer, Q Zhu, and Jane Baldwin, et al., March 2018: Interactions between urban heat islands and heat waves. Environmental Research Letters, 13(3), DOI:10.1088/1748-9326/aa9f73. Abstract
Heat waves (HWs) are among the most damaging climate extremes to human society. Climate models consistently project that HW frequency, severity, and duration will increase markedly over this century. For urban residents, the urban heat island (UHI) effect further exacerbates the heat stress resulting from HWs. Here we use a climate model to investigate the interactions between the UHI and HWs in 50 cities in the United States under current climate and future warming scenarios. We examine UHI2m (defined as urban-rural difference in 2m-height air temperature) and UHIs (defined as urban-rural difference in radiative surface temperature). Our results show significant sensitivity of the interaction between UHI and HWs to local background climate and warming scenarios. Sensitivity also differs between daytime and nighttime. During daytime, cities in the temperate climate region show significant synergistic effects between UHI and HWs in current climate, with an average of 0.4 K higher UHI2m or 2.8 K higher UHIs during HWs than during normal days. These synergistic effects, however, diminish in future warmer climates. In contrast, the daytime synergistic effects for cities in dry regions are insignificant in the current climate, but emerge in future climates. At night, the synergistic effects are similar across climate regions in the current climate, and are stronger in future climate scenarios. We use a biophysical factorization method to disentangle the mechanisms behind the interactions between UHI and HWs that explain the spatial-temporal patterns of the interactions. Results show that the difference in the increase of urban versus rural evaporation and enhanced anthropogenic heat emissions (air conditioning energy use) during HWs are key contributors to the synergistic effects during daytime. The contrast in water availability between urban and rural land plays an important role in determining the contribution of evaporation. At night, the enhanced release of stored and anthropogenic heat during HWs are the primary contributors to the synergistic effects.
Arid Extratropical Asia (AEA) is bisected at the wetter Tianshan Mountains (a northern offshoot of the Tibetan Plateau) into East and West Deserts, each with unique climatological characteristics. The East Deserts (~ 75 – 115°E, ~ 35 – 55°N) have a summer precipitation maximum, and the West Deserts (~ 45 – 75°E, ~ 35 – 55°N) have a winter-spring precipitation maximum. A new high-resolution (50 km atmosphere/land) global coupled climate model is run with the Tianshan Mountains removed to determine whether these mountains are responsible for the climatological East-West differentiation of AEA. Multi-centennial simulations for the Control and NoTianshan runs highlight statistically significant effects of the Tianshan. Overall, the Tianshan are found to enhance the precipitation seasonality gradient across AEA, mostly through altering the East Deserts. The Tianshan dramatically change the precipitation seasonality of the Taklimakan Desert directly to its east (the driest part of AEA), by blocking West winter precipitation, enhancing subsidence over this region, and increasing East summer precipitation. The Tianshan increase East summer precipitation through two mechanisms: 1) orographic precipitation which is greatest on the eastern edge of the Tianshan in summer, and 2) remote enhancement of the East Asian Summer Monsoon through alteration of the larger-scale seasonal mean atmospheric circulation. The decrease in East winter precipitation also generates remote warming of the Altai and Kunlun Mountains, northeast and southeast of the Tianshan respectively, due to reduction of snow cover and corresponding albedo decrease.