Atmospheric Science Letters最新文献

This study investigates the impact of the Madden–Julian Oscillation (MJO) on the extreme rainfall events across 11 eastern coastal stations during the northeast monsoon season (November to March) over the Philippines from 1979 to 2019. The contribution of synoptic systems to these extreme rainfall events such as tropical cyclones (TCs), low-pressure systems (LPS), cold surges (CS), and other disturbances as they coincide with a strong and active MJO were quantified. The results show that the probability of extreme rainfall occurrence increases first to as much as 20% in the southernmost stations in Phase 4. Then, it increases to more than 60% in central-eastern stations in Phase 6. The extreme rainfall events were then classified into: MJO-only, TC-MJO, TC-nonMJO, LPS-MJO, LPS-nonMJO, CS-MJO, CS-nonMJO, and others. The percentage contribution of MJO only, TC-MJO, LPS-MJO, and CS-MJO to the total extreme rainfall events ranges from 9% to 16%, 0% to 3%, 2% to 4%, 1% to 9%, respectively. The relationship between MJO and flooding events in the Philippines was also examined. About 28 flood events or 266 flooding days were identified during the analysis period, wherein 50% of these events coincidentally occurred during strong and active phases of MJO.

High levels of particulate matter (PM) are relevant to severe air pollution and can adversely impact human health. Maintaining healthy air quality for the residents of the Arctic region is essential to satisfy the no-one-left-behind policy of the Sustainable Development Goals (SDGs) by the United Nations. In this study, we installed a PM_2.5 measurement system in Qaanaaq, Greenland, and obtained the first continuous PM_2.5 measurements from July 20, 2022 to August 13, 2022. We observed several increased PM_2.5 events; relatively high PM_2.5 levels persisted from August 8, 2022. On the same day, visible black smoke emitted from the Qaanaaq dump site originated from open waste burning. By confirming less transboundary air pollution contributions from remote aerosol source regions to Qaanaaq during the measurement period using NOAA's HYSPLIT backward trajectory analysis and NASA's MERRA-2 aerosol re-analysis, we confirmed that the increased PM_2.5 was primarily due to local open waste burning with less contributions from transboundary air pollution. However, small contributions from biomass burning outside Greenland were plausible during the early measurement period. Additionally, NOAA's HYSPLIT dispersion calculations suggested possible aerosol depositions from local open waste burning to nearby sea areas, such as Baffin Bay. Although the hourly mean PM_2.5 mass concentration was not alarmingly high during the measurement period, future studies should incorporate longer-term continuous PM_2.5 measurements along with other atmospheric chemical analyses to identify possible local air pollution sources in detail to ensure clean ambient air for the future in the Arctic. Our study provides quantitative evidence of the impact of open waste burning on air quality at a study site in Greenland, which could be crucial in developing air quality policies for this region in the Arctic.

This study investigates the influence of the Northeast China cold vortex (NCCV) on the northward-moving typhoons (NTCs) over the western North Pacific (WNP). There is a significant inverse relationship between the NCCV during June–September and simultaneous NTCs during 1981–2021. Fewer (more) NTCs are observed during NCCV active (inactive) year a combination of less (more) NTC genesis, particularly over the central Pacific region of 10°–30° N and 130°–150° E, and fewer (more) NTCs moving northwestward and making landfall in coastal regions of the Yellow Sea and Bohai Sea. These regions are characterized by significantly decreased low-level vorticity and mid-level humidity, which impedes NTC genesis and notably enhances the deep-layer subtropical straight westerly steering flow, thus blocking the northward movement of NTCs. These remarkable environmental changes during different NCCV years are clearly linked with the changes of an anomalous anticyclone in the subtropics (20°–30° N, 120°–160° E). In short, more (less) NCCV activity strengthens (weakens) the anomalous anticyclone, resulting in fewer (more) NTCs.

Using a reanalysis dataset and large-ensemble simulation results, this study examines a possible factor of increasing trend in early winter precipitation in recent decades in the Hokuriku region of Japan. Monthly precipitation in December has a significant increasing trend after the early 1990s, which is different from those in January and February. The increasing precipitation in December is related to that in the sea surface upward latent heat flux due to intensified winter monsoon circulation and warming sea surface temperatures (SSTs) over the Sea of Japan. December averaged SSTs show a trend pattern in recent decades that is similar to the negative phase of the interdecadal Pacific oscillation (IPO), accompanied by positive trends from the eastern Indian Ocean to the western tropical Pacific. The enhanced trend of convection over the Bay of Bengal is seen; suggesting a combined effect of climatologically high SSTs and IPO-related warmed SSTs over the region. Trends in recent decades of an upper-level wavy pattern from South Asia to near Japan along the subtropical jet associated with enhanced convection near the Bay of Bengal and the related pressure drop from Japan to the north are seen, which contribute to intensified winter monsoon circulation.

The Radon and Hilbert transform and their applications to convectively coupled waves (CCWs) are reviewed. The Hilbert Transform is used to compute the wave envelope, whereas the Radon transform is used to estimate the phase and group velocities of CCWs. Together, they provide an objective method to understand CCW propagation. Results reveal phase speeds and group velocities for fast waves (mixed Rossby-gravity, westward and eastward inertio-gravity, and Kelvin) that are consistent with previous studies and with Matsuno's equatorial wave dispersion curves. However, slowly-propagating tropical depression-like systems and equatorial Rossby waves exhibit wave envelopes that propagate faster than the individual wave crests, which is not predicted by dry shallow water theory.

Operational Meteorologists (OMs) in the Met Office have a perception that elevated convection is not well represented in kilometre-scale models, which are generally associated with an improved representation of convection. Here, we consider why there may be a problem with representing elevated convection and consider how OMs judge the model to be poor so often. Three OMs have subjectively scored and classified observed elevated convection cases over the UK from 2017 to 2020. Continental plumes (warm, moist, air coming from the near continent or Africa) account for 73% of the cases. The most frequent errors are associated with (i) location, (ii) organisation, (iii) timing and (iv) intensity of the convection. Thus, OMs perceive that the biggest problem with predicting elevated convection is constraining the location of the convective events. The location errors are particularly prevalent for events coming to the UK from the near continent. The location errors are most frequently identified for flow regimes coming from the near continent in weakly forced synoptic conditions. The identification of this problem enables the specific targeting of research into continental plumes (for UK elevated convection) but also raises questions around the role of lateral boundary conditions in the forecasts of elevated convection.

The changes in the East Asian polar-front jet (EAPJ) and the East Asian subtropical jet (EASJ) profoundly impact the weather and climate in East Asia. However, the link between aerosols and the jet streams is still unclear. Here, we investigated the decadal co-variation of aerosols and the East Asian jet streams in the boreal winter during the period of 1980–2019. In synch with a positive change in aerosol optical depth over East Asia, 300-hPa winds show an equatorward shift of the land branch of the EASJ, and weakened EAPJ and oceanic branch of the EASJ. This can be linked to the enhanced meridional temperature gradient along 30°–50° N but weakened in northern regions and the decreasing synoptic-scale transient eddy kinetic energy over subtropical Pacific. Relative importance estimation of aerosols and ocean signals emphasized the contributions of aerosols in jet variations. In turn, meteorological conditions related to jet streams also contribute to variations in aerosols, the decadal co-variations are a result of their interactions, particularly for the oceanic branch of EASJ. The findings would be helpful in providing potential indicators of climate change.

We describe a method for quantifying the contribution of climate change to local monthly, seasonal, and annual mean temperatures for locations where long observational temperature records are available. The method is based on estimating the change in the monthly mean temperature distribution due to climate change using CMIP6 (Coupled Model Intercomparison Project Phase 6) model data. As a case study, we apply the method to the record-warm September 2023 in Helsinki, and then briefly examine all record-warm months of the 21st century. Our results suggest that climate change made the record-warm September in Helsinki 9.4 times more likely and 1.4°C warmer. Thus, the new monthly mean record in September 2023 would probably not have been set without the observed global warming. The presented and provided tool allows operational meteorologists and climatologists to monitor and report the impact of climate change on local temperatures in near real time.

Ensemble forecasts have been shown to better predict observed Atlantic climate variability than that of their own ensemble members. This phenomenon—termed the signal-to-noise paradox—is found to be widespread across models, timescales, and climate variables, and has wide implications. The signal-to-noise paradox can be interpreted as forecasts underestimating the amplitude of predictable signals on seasonal-to-decadal timescales. The cause of this remains unknown. Here, we examine sea level pressure variability from a very large multi-model ensemble of uninitialized atmosphere-only simulations, focusing on boreal winter. To assess signal-to-noise errors, the ratio of predictable components (RPC) is examined globally, as well as for regional climate indices: the North Atlantic Oscillation, Arctic Oscillation, Southern Annular Mode, and an Arctic index. Our analyses reveal significant correlations between the multi-model ensemble-mean and observations over large portions of the globe, particularly the tropics, North Atlantic, and North Pacific. However, RPC values greater than one are apparent over many extratropical regions and in all four climate indices. Higher-resolution models produce greater observation-model correlations and greater RPC values than lower-resolution models in all four climate indices. We find that signal-to-noise errors emerge more clearly at higher resolution, but the amplitudes of predictable signals do not increase with resolution, at least across the range of resolutions considered here. Our results suggest that free-running atmospheric models underestimate predictable signals in the absence of sea surface temperature biases, implying that signal-to-noise errors originate in the atmosphere or in ocean–atmosphere coupling.