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Ellen Dyer and Richard Washington

Abstract

The interannual variability, trends, and the mean climatology of East African long rains are difficult for models to simulate. This is in part because long rains do not respond in a simple way to large-scale modes of variability such as ENSO and because of interactions with complex topography. Here we focus on the Kenyan regional climate in the ERA-Interim dataset during the long rains to create a set of atmospheric diagnostics that can be applied to the evaluation of climate models. Subseasonal observed rainfall and reanalysis reveal that very wet seasons and very dry seasons develop differently at the beginning of the season. Subseasonal aggregation periods (days 60–80, 80–100, 90–120, 120–150) highlight local (e.g., midtropospheric ascent, moisture flux convergence in the lower to midtroposphere, and midtropospheric moisture) and large-scale (e.g., midtropospheric zonal winds over central Africa, upper-tropospheric velocity potential) diagnostics that are useful to evaluate model atmospheric circulation affecting Kenyan rainfall in mean and wet or dry extremes.

Open access
Shusaku Sugimoto, Bo Qiu, and Niklas Schneider

Abstract

The Kanto district in Japan, including Tokyo, has 40 million inhabitants and its summer climate is characterized by high temperature and humidity. The Kuroshio that flows off the southern coast of the Kanto district has taken a large meander (LM) path since the summer of 2017 for the first time since the 2004–05 event. Recently developed satellite observations detected marked coastal warming off the Kanto–Tokai district during the LM path period. By conducting regional atmospheric model experiments, it is found that summertime coastal warming increases water vapor in the low-level atmosphere through enhanced evaporation from the ocean and influences near-surface winds via the vertical mixing effect over the warming area. These two changes induce an increase in water vapor in Kanto district, leading to an increase in downward longwave radiation at the surface and then surface warming through a local greenhouse effect. As a result, summer in Kanto district becomes increasingly hot and humid in LM years, with double the number of discomfort days compared with non-LM years. Our simulations and supplementary observational studies reveal the significant impacts of the LM-induced coastal warming on the summertime climate in Japan, which can exceed previously identified atmospheric teleconnections and climate patterns. Our results could improve weather and seasonal climate forecasts in this region.

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Marius Årthun, Robert C. J. Wills, Helen L. Johnson, Léon Chafik, and Helene R. Langehaug

Abstract

Decadal sea surface temperature (SST) fluctuations in the North Atlantic Ocean influence climate over adjacent land areas and are a major source of skill in climate predictions. However, the mechanisms underlying decadal SST variability remain to be fully understood. This study isolates the mechanisms driving North Atlantic SST variability on decadal time scales using low-frequency component analysis, which identifies the spatial and temporal structure of low-frequency variability. Based on observations, large ensemble historical simulations, and preindustrial control simulations, we identify a decadal mode of atmosphere–ocean variability in the North Atlantic with a dominant time scale of 13–18 years. Large-scale atmospheric circulation anomalies drive SST anomalies both through contemporaneous air–sea heat fluxes and through delayed ocean circulation changes, the latter involving both the meridional overturning circulation and the horizontal gyre circulation. The decadal SST anomalies alter the atmospheric meridional temperature gradient, leading to a reversal of the initial atmospheric circulation anomaly. The time scale of variability is consistent with westward propagation of baroclinic Rossby waves across the subtropical North Atlantic. The temporal development and spatial pattern of observed decadal SST variability are consistent with the recent observed cooling in the subpolar North Atlantic. This suggests that the recent cold anomaly in the subpolar North Atlantic is, in part, a result of decadal SST variability.

Open access
Irina Rudeva and Ian Simmonds

Abstract

For the last few decades the Northern Hemisphere midlatitudes have seen an increasing number of temperature extreme events. It has been suggested that some of these extremes are related to planetary wave activity. In this study we identify wave propagation regions at 300 hPa using the ERA-Interim dataset from 1980 to 2017 and link them to temperature extremes in densely populated regions of the Northern Hemisphere. Most studies have used background flow fields at monthly or seasonal scale to investigate wave propagation. For a phenomenon that is influenced by threshold incidents and nonlinear processes, this can distort the net Rossby wave signal. A novel aspect of our investigation lies in the use of daily data to study wave propagation allowing it to be diagnosed for limited but important periods across a wider range of latitudes, including the polar region. We show that winter temperature extremes in the midlatitudes can be associated with circulation anomalies in both the Arctic and the tropics, while the relative importance of these areas differs according to the specific midlatitude region. In particular, wave trains connecting the tropical Pacific and Atlantic may be associated with temperature anomalies in North America and Siberia. Arctic seas are markedly important for Eurasian regions. Analysis of synoptic temperature extremes suggests that pre-existing local temperature anomalies play a key role in the development of those extremes, as well as amplification of large-scale wave trains. We also demonstrate that warm Arctic regions can create cold outbreaks in both Siberia and North America.

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Taylor B. Aydell and Craig B. Clements

ABSTRACT

Remote sensing techniques have been used to study and track wildfire smoke plume structure and evolution; however, knowledge gaps remain because of the limited availability of observational datasets aimed at understanding fine-scale fire–atmosphere interactions and plume microphysics. Meteorological radars have been used to investigate the evolution of plume rise in time and space, but highly resolved plume observations are limited. In this study, we present a new mobile millimeter-wave (Ka band) Doppler radar system acquired to sample the fine-scale kinematics and microphysical properties of active wildfire smoke plumes from both wildfires and large prescribed fires. Four field deployments were conducted in autumn of 2019 during two wildfires in California and one prescribed burn in Utah. Radar parameters investigated in this study include reflectivity, radial velocity, Doppler spectrum width, differential reflectivity Z DR, and copolarized correlation coefficient ρ HV. Observed radar reflectivity ranged between −15 and 20 dBZ in plume, and radial velocity ranged from 0 to 16 m s−1. Dual-polarimetric observations revealed that scattering sources within wildfire plumes are primarily nonspherical and oblate-shaped targets as indicated by Z DR values measuring above 0 and ρ HV values below 0.8 within the plume. Doppler spectrum width maxima were located near the updraft core region and were associated with radar reflectivity maxima.

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Gregory L. Wagner, Gregory P. Chini, Ali Ramadhan, Basile Gallet, and Raffaele Ferrari

Abstract

Between 5% and 25% of the total momentum transferred between the atmosphere and ocean is transmitted via the growth of long surface gravity waves called “swell.” In this paper, we use large-eddy simulations to show that swell-transmitted momentum excites near-inertial waves and drives turbulent mixing that deepens a rotating, stratified, turbulent ocean surface boundary layer. We find that swell-transmitted currents are less effective at producing turbulence and mixing the boundary layer than currents driven by an effective surface stress. Overall, however, the differences between swell-driven and surface-stress-driven boundary layers are relatively minor. In consequence, our results corroborate assumptions made in Earth system models that neglect the vertical structure of swell-transmitted momentum fluxes and instead parameterize all air–sea momentum transfer processes with an effective surface stress.

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Xiangzhou Song, Chunlin Ning, Yongliang Duan, Huiwu Wang, Chao Li, Yang Yang, Jianjun Liu, and Weidong Yu

Abstract

Six-month buoy-based heat flux observations from the poorly sampled tropical southeastern Indian Ocean are examined to document the extremes during three tropical cyclones (TCs) from December 2018 to May 2019. The most striking feature at the mooring site (16.9°S, 115.2°E) during the TCs is the extensively suppressed diurnal cycle of the net surface flux (Qnet), with a mean daytime (nighttime) reduction of 470 (131) W m−2, a peak decrease at approximately noon of 695 W m−2 and an extreme drop during TC Riley of 800 W m−2. The mean surface cooling in the daytime is primarily contributed by the 370 W m−2 decrease in shortwave radiation associated with the increased cloudiness. The air–sea turbulent heat fluxes increase by approximately 151 W m−2 in response to the enhanced wind speed under near-neutral boundary conditions. The daily mean rainfall-induced cooling is 8 W m−2, with a maximum magnitude of 90 W m−2. The mean values, seasonal variation, and synoptic variability of the characteristic heat fluxes are used to assess the new reanalysis data from ERA5 and MERRA2 and the analyzed OAFlux. The overall performance of the high-frequency net heat flux estimates at the synoptic scale is satisfactory, but the four flux components exhibit different quality levels. A serious error is that ERA5 and MERRA2 poorly represent TCs, and they show significant daily mean Qnet biases with opposite directions, −59 W m−2 (largely due to the overestimated latent heat with a bias of −76 W m−2) and 50 W m−2 (largely due to the overestimated shortwave radiation with a bias of 41 W m−2), respectively.

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Ricardo Domingues, Matthieu Le Hénaff, George Halliwell, Jun A. Zhang, Francis Bringas, Patricia Chardon, Hyun-Sook Kim, Julio Morell, and Gustavo Goni

Abstract

Major Atlantic hurricanes Irma, Jose, and Maria of 2017 reached their peak intensity in September while traveling over the tropical North Atlantic Ocean and Caribbean Sea, where both atmospheric and ocean conditions were favorable for intensification. In situ and satellite ocean observations revealed that conditions in these areas exhibited (i) sea surface temperatures above 28°C, (ii) upper-ocean heat content above 60 kJ cm−2, and (iii) the presence of low-salinity barrier layers associated with a larger-than-usual extension of the Amazon and Orinoco riverine plumes. Proof-of-concept coupled ocean–hurricane numerical model experiments demonstrated that the accurate representation of such ocean conditions led to an improvement in the simulated intensity of Hurricane Maria for the 3 days preceding landfall in Puerto Rico, when compared to an experiment without the assimilation of ocean observations. Without the assimilation of ocean observations, upper-ocean thermal conditions were generally colder than observations, resulting in reduced air–sea enthalpy fluxes—enthalpy fluxes are more realistically simulated when the upper-ocean temperature and salinity structure is better represented in the model. Our results further showed that different components of the ocean observing system provide valuable information in support of improved TC simulations, and that assimilation of underwater glider observations alone enabled the largest improvement over the 24 h time frame before landfall. Our results, therefore, indicated that ocean conditions were relevant for more realistically simulating Hurricane Maria’s intensity. However, further research based on a comprehensive set of hurricane cases is required to confirm robust improvements to forecast systems.

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Ji-Won Kim, Ting-Huai Chang, Ching-Teng Lee, and Jin-Yi Yu

Abstract

Using observational data and model hindcasts produced by a coupled climate model, we examine the response of the East Asian winter monsoon (EAWM) to three types of El Niño: eastern Pacific (EP) and central Pacific I (CP-I) and II (CP-II) El Niños. The observational analysis shows that all three El Niño types weaken the EAWM with varying degrees of impact. The EP El Niño has the largest weakening effect, while the CP-II El Niño has the second largest, and the CP-I El Niño has the smallest. We find that diverse El Niño types impact the EAWM by altering the responses of two anomalous anticyclones during El Niño mature winter: the western North Pacific anticyclone (WNPAC) and Kuroshio anticyclone (KAC). The WNPAC responses are controlled by the Gill response and Indian Ocean warming processes that both respond to the eastern-to-central tropical Pacific precipitation anomalies. The KAC responses are controlled by a poleward wave propagation responding to the northwestern tropical Pacific precipitation anomalies. We find that the model hindcasts significantly underestimate the weakening effect during the EP and CP-II El Niños. These underestimations are related to a model deficiency in which it produces a too-weak WNPAC response during the EP El Niño and completely misses the KAC response during both types of El Niño. The too-weak WNPAC response is caused by the model deficiency of simulating too-weak eastern-to-central tropical Pacific precipitation anomalies. The lack of KAC response arises from the unrealistic response of the model’s extratropical atmosphere to the northwestern tropical Pacific precipitation anomalies.

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Xiaojing Li and Youmin Tang

Abstract

This work uses a 19-yr ensemble hindcast of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the average predictable time (APT) method to detect the most predictable tropical intraseasonal variability (ISV) mode. The first and most predictable mode (APT1) of tropical ISV is similar to a joint merger of the two Madden–Julian oscillation (MJO) modes with more weight on the second mode and is characterized by a tripole pattern with two positive centers in the equatorial western Indian Ocean and central Pacific Ocean and a negative center over the Maritime Continent. The APT1 doubles the skillful prediction period made by the MJO defined by a correlation skill of 0.5 (approximately 25 days in the ECMWF model), demonstrating its potential to become a skillful prediction target and to offer powerful subseasonal prediction sources. The underlying physical process and predictability source of the APT1 are further analyzed. The APT1 is very similar to the pattern triggered by the most predictable tropical intraseasonal sea surface temperature (SST) anomalies mode, suggesting its oceanic origin. Tropical ocean–atmosphere interaction plays a critical role in the APT1 by enhancing the evolution of tropical convection cells under WES (wind–evaporation–SST) and Bjerknes feedbacks. The internal atmospheric processes also have an important impact on the formation and maintenance of the APT1.

Open access