Atmospheric rivers (ARs) play important roles in various extreme weather events across the US. While AR features in western US have been extensively studied, there remains limited understanding of their variability in the eastern US (EUS). Using both observations and a state-of-the-art climate model, we find a significant increase (~10% dec−1) in winter AR frequency in the EUS during the past four decades. This trend is closely linked to recent changes in the Pacific/North America (PNA) teleconnection pattern, accompanied by a poleward shift of the mid-latitude jet stream. We further reveal a strong correlation (R = 0.8; P < 0.001) between interannual variations in AR occurrence and the PNA index. This linkage has been verified in various model simulations. A statistical model, built on this linkage, has proven effective in predicting the AR frequency using the PNA index at both monthly and seasonal scales. These promising results have important implications for addressing concerns related to AR-associated extreme precipitation and flooding in this region.
Gentile, Emanuele S., Ming Zhao, Vincent E Larson, Colin M Zarzycki, and Zhihong Tan, May 2024: The effect of coupling between CLUBB turbulence scheme and surface momentum flux on global wind simulations. Journal of Advances in Modeling Earth Systems, 16(5), DOI:10.1029/2024MS004295. Abstract
The higher-order turbulence scheme, Cloud Layers Unified by Binormals (CLUBB), is known for effectively simulating the transition from cumulus to stratocumulus clouds within leading atmospheric climate models. This study investigates an underexplored aspect of CLUBB: its capacity to simulate near-surface winds and the Planetary Boundary Layer (PBL), with a particular focus on its coupling with surface momentum flux. Using the GFDL atmospheric climate model (AM4), we examine two distinct coupling strategies, distinguished by their handling of surface momentum flux during the CLUBB's stability-driven substepping performed at each atmospheric time step. The static coupling maintains a constant surface momentum flux, while the dynamic coupling adjusts the surface momentum flux at each CLUBB substep based on the CLUBB-computed zonal and meridional wind speed tendencies. Our 30-year present-day climate simulations (1980–2010) show that static coupling overestimates 10-m wind speeds compared to both control AM4 simulations and reanalysis, particularly over the Southern Ocean (SO) and other midlatitude ocean regions. Conversely, dynamic coupling corrects the static coupling 10-m winds biases in the midlatitude regions, resulting in CLUBB simulations achieving there an excellent agreement with AM4 simulations. Furthermore, analysis of PBL vertical profiles over the SO reveals that dynamic coupling reduces downward momentum transport, consistent with the found wind-speed reductions. Instead, near the tropics, dynamic coupling results in minimal changes in near-surface wind speeds and associated turbulent momentum transport structure. Notably, the wind turning angle serves as a valuable qualitative metric for assessing the impact of changes in surface momentum flux representation on global circulation patterns.
This study examines the potential impacts of large-scale atmospheric circulations that are forced by sea surface temperatures (SST) on global tropical cyclone (TC) formation. Using the Geophysical Fluid Dynamics Laboratory (GFDL) global atmosphere and land surface model, version 4 (AM4), under different SST distributions, it is found that the east–west clustering of global TC formation is mainly governed by large-scale circulations in response to given SSTs, instead of direct ocean surface fluxes associated with zonal SST anomalies. Our zonally homogeneous SST simulations in the presence of realistic surface coverage show that TC clusters still emerge as a result of the breakdown of zonal circulations related to land–sea distribution, which produce specific “hotspots” for global TC formation. Sensitivity experiments with different climate warming scenarios and model physics confirm the persistence of these TC clusters in the absence of all zonal SST variations. These robust results offer new insights into the effects of large-scale circulation and terrain forcing on TC clusters beyond the traditional view of direct SST impacts, which are based on the direct alignment of the warmest SST regions and TC clusters. In addition, our experiments also capture internal variability of the global TC frequency, with an average fluctuation of 6–8 TCs at several dominant frequencies of ∼3, 6, and 9 years, even in the absence of all SST interannual variability and ocean coupling. This finding reveals an intrinsic “noise” level of the global TC frequency that one has to take into account when examining the past and future trends in TC activity and their related significance or detectability.
Global climate models (GCMs) struggle to simulate polar clouds, especially low-level clouds that contain supercooled liquid and closely interact with both the underlying surface and large-scale atmosphere. Here we focus on GFDL's latest coupled GCM–CM4–and find that polar low-level clouds are biased high compared to observations. The CM4 bias is largely due to moisture fluxes that occur within partially ice-covered grid cells, which enhance low cloud formation in non-summer seasons. In simulations where these fluxes are suppressed, it is found that open water with an areal fraction less than 5% dominates the formation of low-level clouds and contributes to more than 50% of the total low-level cloud response to open water within sea ice. These findings emphasize the importance of accurately modeling open water processes (e.g., sea ice lead-atmosphere interactions) in the polar regions in GCMs.
Liu, Jiachen, Jun Yang, Yixiao Zhang, and Zhihong Tan, February 2023: Convection and clouds under different planetary gravities simulated by a small-domain cloud-resolving model. The Astrophysical Journal, 944(1), DOI:10.3847/1538-4357/aca965. Abstract
In this study, we employ a cloud-resolving model to investigate how gravity influences convection and clouds in a small-domain (96 × 96 km) radiative–convective equilibrium. Our experiments are performed with a horizontal grid spacing of 1 km, which can resolve large (>1 km2) convective cells. We find that under a given stellar flux, sea surface temperature increases with decreasing gravity. This is because a lower-gravity planet has larger water vapor content and more clouds, resulting in a larger clear-sky greenhouse effect and a stronger cloud warming effect in the small domain. By increasing stellar flux under different gravity values, we find that the convection shifts from a quasi-steady state to an oscillatory state. In the oscillatory state, there are convection cycles with a period of several days, comprised of a short wet phase with intense surface precipitation and a dry phase with no surface precipitation. When convection shifts to the oscillatory state, the water vapor content and high-level cloud fraction increase substantially, resulting in rapid warming. After the transition to the oscillatory state, the cloud net positive radiative effect decreases with increasing stellar flux, which indicates a stabilizing climate effect. In the quasi-steady state, the atmospheric absorption features of CO2 are more detectable on lower-gravity planets because of their larger atmospheric heights. While in the oscillatory state, the high-level clouds mute almost all of the absorption features, making the atmospheric components hard to characterize.
Yang, Jun, Yixiao Zhang, Zuntao Fu, Mingyu Yan, Xinyi Song, Mengyu Wei, Jiachen Liu, Feng Ding, and Zhihong Tan, June 2023: Cloud behaviour on tidally locked rocky planets from global high-resolution modelling. Nature Astronomy, DOI:10.1038/s41550-023-02015-8. Abstract
Determining the behaviour of convection and clouds is one of the biggest challenges in our understanding of exoplanetary climates. Given the lack of in situ observations, one of the most preferable approaches is to use cloud-resolving or cloud-permitting models (CPM). Here we present CPM simulations in a quasi-global domain with high spatial resolution (4 × 4 km2 grid) and explicit convection to study the cloud regime of 1:1 tidally locked rocky planets orbiting around low-mass stars. We show that the substellar region is covered by deep convective clouds and cloud albedo increases with increasing stellar flux. The CPM produces relatively lower cloud liquid water concentration, smaller cloud coverage, lower cloud albedo and deeper H2O spectral features than previous general circulation model simulations using empirical convection and cloud parameterizations. Furthermore, cloud streets—long bands of low-level clouds oriented nearly parallel to the direction of the mean boundary-layer winds—appear in the CPM and substantially affect energy balance and surface precipitation at a local level.
Land–atmosphere (L–A) interactions encompass the co-evolution of the land surface and overlying planetary boundary layer, primarily during daylight hours. However, many studies have been conducted using monthly or entire-day mean time series due to the lack of subdaily data. It is unclear whether the inclusion of nighttime data alters the assessment of L–A coupling or obscures L–A interactive processes. To address this question, we generate monthly (M), entire-day mean (E), and daytime-only mean (D) data based on the ERA5 (5th European Centre for Medium-Range Weather Forecasts reanalysis) product and evaluate the strength of L–A coupling through two-legged metrics, which partition the impact of the land states on surface fluxes (the land leg) from the impact of surface fluxes on the atmospheric states (the atmospheric leg). Here we show that the spatial patterns of strong L–A coupling regions among the M-, D-, and E-based diagnoses can differ by more than 80 %. The signal loss from E- to M-based diagnoses is determined by the memory of local L–A states. The differences between E- and D-based diagnoses can be driven by physical mechanisms or averaging algorithms. To improve understanding of L–A interactions, we call attention to the urgent need for more high-frequency data from both simulations and observations for relevant diagnoses. Regarding model outputs, two approaches are proposed to resolve the storage dilemma for high-frequency data: (1) integration of L–A metrics within Earth system models, and (2) producing alternative daily datasets based on different averaging algorithms.
Zhang, Bosong, Ming Zhao, and Zhihong Tan, February 2023: Using a Green’s Function approach to diagnose the pattern effect in GFDL AM4 and CM4. Journal of Climate, 36(4), DOI:10.1175/JCLI-D-22-0024.11105–1124. Abstract
Global radiative feedbacks exhibit large dependence on the spatial structure of sea surface temperature (SST) changes, which is referred to as the “pattern effect.” A Green’s function (GF) approach has been demonstrated to be useful in identifying and understanding contributions of regional SST changes to global radiative feedbacks. Here, we explore the ability of the GF approach in quantifying the pattern effect in an atmospheric model (AM4) and a coupled model (CM4) recently developed at NOAA’s Geophysical Fluid Dynamics Laboratory (GFDL), including the impact of SST changes on global-mean and local responses of key variables important to climate. Given historical SST patterns, the GF derived from idealized experiments with SST warming patches can largely reproduce AM4 simulated global-mean and regional responses. When AM4 is forced by SST patterns retrieved from the CM4 abrupt quadrupling of carbon dioxide experiment, the same GF captures interannual variations of AM4 simulated global-mean responses but falls short of reproducing the magnitude of the responses. A decomposition of such SST patterns into global-mean values plus remaining anomalies helps reduce biases. Additional idealized experiments are conducted to examine the sensitivity of the GF to the amplitude and sign of SST perturbations and to the integration time and the confidence level of the significance test. Impacts of these factors on the performance of the GF are discussed.
This study investigates how climate sensitivity depends upon the spatial pattern of radiative forcing. Sensitivity experiments using a coupled ocean-atmosphere model were conducted by adding anomalous incoming solar radiation over the entire globe, Northern Hemisphere mid-latitudes, Southern Ocean, and tropics. The varied forcing patterns led to highly divergent climate sensitivities. Specifically, the climate is nearly twice as sensitive to Southern Ocean forcing as tropical forcing. Strong coupling between the surface and free troposphere in the tropics increases the inversion strength, leading to smaller cloud feedback in the tropical forcing experiments. In contrast, the extratropics exhibit weaker coupling, a decrease or near-zero change in the inversion strength, and strong positive cloud feedback. These results contrast with the conventional SST-pattern effect in which tropical surface temperature changes regulate climate sensitivity. They also have important implications for other potentially asymmetric forcings, such as those from geoengineering, volcanic eruptions, and paleoclimatic changes.
