Institute of Atmospheric Physics

Abstract Canonical El Niño (EN) events typically peak in boreal winter and then rapidly decay in the ensuing months, transitioning to a La Niña (LN) event or a neutral condition by the following winter. Strikingly, an EN event that peaked in the 1986/87 boreal winter unexpectedly persisted into the following year, generating a rare 2-yr consecutive EN event. However, the 1986/87–1987/88 2-yr EN event receives little attention. This study reveals that this 2-yr EN event encompasses some critical yet commonly overlooked processes for the formation and development of an EN event. Specifically, the high-frequency (HF) westerly wind anomalies, induced by the tropical cyclones (TCs) and Madden–Julian oscillation (MJO) events, were the pivotal drivers of the unexpected reignition in the second year. During the 1986/87 winter, the unexpected emergence of four TCs induced vigorous westerly wind anomalies over the western equatorial Pacific (WEP), disrupting the anomalous anticyclone circulation over the western North Pacific anticyclone (WNPAC) and the associated easterly wind anomalies over the WEP that were anticipated during the 1986/87 winter. Such unexpected westerly wind anomalies helped maintain the EN warming through December 1986–February 1987. Subsequently, a series of HF westerly wind anomalies, induced by TCs and MJO events in April, May, and July 1987, reinvigorated the waning warming, pulling it back into a fledged EN event by the end of 1987. Gaining insights into the formation mechanism behind this unique 2-yr EN event can deepen our understanding of El Niño–Southern Oscillation (ENSO) dynamics and provide implications for enhancing the accuracy of EN prediction. Significance Statement Considering the critical impacts of multiyear El Niño–Southern Oscillation (ENSO) events on global weather and climate, understanding the formation dynamics of multiyear ENSO events is vital for improving the accuracy of ENSO prediction. Canonical El Niño (EN) events typically peak in boreal winter and then decay rapidly; however, the 1986/87 EN event persisted unexpectedly for two consecutive years, unlike typical single-year EN events. A revisit of 1986/87–1987/88 2-yr EN event reveals critical yet commonly overlooked processes in EN formation and development. Observational analyses reveal that the high-frequency westerly wind anomalies induced by the TCs and MJOs are crucial to the formation of this 2-yr consecutive EN event. Understanding the mechanism of this unique 2-yr EN event can enhance our knowledge of ENSO dynamics.

Abstract Prolonged compound hot–dry events (CHDEs) have been linked to surging emergency medical demand, especially among vulnerable populations, making them a growing public health concern in a warming climate. However, the seasonal and regional drivers of high health-risk CHDEs (HHR–CHDEs) remain unclear, limiting effective public health responses. Here, we integrate a temperature–humidity-based health-risk index, ambulance dispatch records, and distributed lag nonlinear models to obtain high health-risk temperature–humidity thresholds. During HHR–CHDEs exposure, particularly higher emergency dispatch demands are observed among males, the elderly, and individuals suffering from trauma or alcohol poisoning. We further use ERA5 reanalysis data to examine the dominant modes and physical mechanisms of HHR–CHDEs across China during the early and late warm seasons. In the early warm season, HHR–CHDEs are concentrated in northwest China and are jointly driven by enhanced surface heating (51% contribution) and intensified moisture loss (37%), underpinned by the synergistic effect of an upstream Rossby wave source over eastern Europe and anomalous northwest Pacific sea surface temperature (SST) warming. This coupling promotes a quasi-stationary high pressure anomaly that blocks synoptic disturbances and reinforces regional heat–dryness feedbacks. By contrast, in the late warm season, HHR–CHDEs are centered over the middle–lower Yangtze River region and are dominated by persistent heat accumulation (65%) with a secondary drought contribution (25%). These events are driven by large-scale circulation anomalies resulting from upstream Rossby wave energy originating in the North Atlantic and enhanced by downstream SST warming over the subtropical northwest Pacific. This Atlantic–Pacific coupling induces pronounced adjustments in the Walker and Hadley circulations, promoting subsidence and suppressed monsoonal moisture transport, and sustaining a health-threatening hot–dry atmosphere over densely populated regions. These findings reveal seasonally distinct remote forcing pathways and highlight the value of integrating large-scale diagnostics into climate–health early warning systems. Significance Statement High health-risk compound hot–dry events (HHR–CHDEs) are a growing climate–health threat, yet their physical drivers remain poorly understood. This study identifies seasonally distinct large-scale atmospheric and oceanic precursors of HHR–CHDEs across China, revealing key Rossby wave pathways and land–atmosphere feedbacks that amplify these events. By integrating climate diagnostics with health-relevant thresholds, our findings bridge the gap between meteorological extremes and public health outcomes, offering a foundation for targeted early warning systems under climate change.

Abstract Oceanic meridional heat transport (MHT), a key component of Earth's energy flow, fundamentally shapes climate variability by redistributing heat between hemispheres and across latitudes, thereby regulating surface energy exchange, atmospheric circulation, and hydrological patterns. However, accurate quantification of the global MHT remains challenging. Here, we use the energy budget approach to derive MHT from 1985 to 2023 based on sea surface heat fluxes (Fs), ocean heat content tendency (OHCT), and heat changes related to sea ice melt/formation (Q ice ), with objective adjustment applied to these components under an ocean energy budget constraint. This approach enables an improved estimate of the MHT climatology, variability, and trend for the global, Indo-Pacific and Atlantic oceans. With good agreement with RAPID and OSNAP mooring array observation time series, our estimates indicate realistic northward MHT at all latitudes in the North Atlantic with a peak of 1.22 ± 0.07 PW at 24.5°N. In contrast, the Indo-Pacific MHT is poleward with a peak of −1.67 ± 0.06 PW at 13.5°S. Regional energy budgets reveal that Fs dominates the mean state of MHT, while OHCT controls its interannual variability. After 2000, when the data quality of both OHC and Fs improved a lot, the Indo-Pacific Ocean exhibited a statistically significant increase in MHT, whereas the Atlantic Ocean showed a basin-wide weakening of MHT, particularly between 25°S and 18°N. The derived ocean MHT data in this study provide a basis to evaluate model and reanalysis data, and support a better understanding of the Earth’s energy flow.

Abstract. Extended-range prediction during the transitional seasons remains particularly challenging due to the volatile large-scale circulation background. This study investigates the dynamical linkages, Rossby wave characteristics, and subseasonal predictability of three successive atmospheric blocking events in May–June 2023, which contributed to severe Canadian wildfires, anomalous East Asian precipitation, and European heatwaves. The results indicate that the three blocking episodes are not independent but interconnected through downstream propagation of quasi-stationary Rossby wave energy. Spatiotemporal local diagnostics of phase speed, amplitude, and zonal wavenumber further reveal that all episodes are dominated by slowly propagating, large-amplitude planetary-scale Rossby waves in the troposphere, with zonal wavenumbers typically below the climatological zonal wavenumber. Day-to-day evolution shows abrupt transitions during blocking onset from an eastward-propagating synoptic-scale small-amplitude regime to a quasi-stationary or westward-propagating planetary-scale large-amplitude regime, with the reverse during blocking’s decaying stage. ECMWF ensemble forecasts exhibit high predictability of 500 hPa geopotential height at 15–19-day lead times, with the best performance for the Ural blocking, where skillful members capture both the amplification of wave amplitude and spatial scale. In contrast, forecasts for the Canadian and European blocking show limited growth in wave parameters and associated geopotential height. For all episodes, skillful subseasonal predictions depend on capturing upstream quasi-stationary troughs over the North Pacific or North Atlantic, potentially influenced by exceptionally high sea surface temperatures in these basins during May–June 2023. These findings underscore that the growth in both amplitude and scale contributes to forecast errors in blocking circulation, while upstream wave precursors and external boundary forcing provide key sources of subseasonal predictability for persistent blocking circulation.

Abstract. The Lightning Mapping Imager (LMI) aboard the Fengyun-4A (FY-4A) satellite, once one of the only two geostationary lightning detection payloads operating in space, has accumulated a substantial volume of observational data. Extensive efforts have been made to correct lightning geolocation deviations, including payload misalignment correction, cloud-top height parallax correction, and thermal deformation correction. These measures have substantially improved the geolocation accuracy of LMI observations. However, individual correction schemes are not necessarily applicable across the entire LMI field of view; furthermore, a comprehensive, unified correction dataset has yet to be established, which has limited the wider utilization of LMI data. To address the remaining systematic geolocation deviations in current LMI lightning products, we propose a new correction method based on reference data from the World Wide Lightning Location Network (WWLLN). Using ground-based lightning observations as a benchmark, the LMI field of view is subdivided into 400 subregions arranged in a 20 × 20 grid. Within each subregion, sensitivity experiments are conducted to match spaceborne LMI detections with ground-based lightning events, thereby quantifying the systematic deviation for each subregion. A weighted curve-fitting approach is then applied to the coordinate deviations derived from the matched events to obtain a correction curve for each subregion. These subregional correction curves are subsequently mapped back to the image coordinates, enabling an analysis of the spatiotemporal variability of lightning geolocation deviations across the full LMI coverage. Finally, the fitted curve values are applied as correction terms to the original data, resulting in the construction of a new, refined correction dataset. Building upon the existing Level-2 lightning products, this method significantly enhances the geolocation accuracy of LMI observations. The coordinate deviations between LMI detections and ground-based lightning network observations exhibit pronounced convergence in both the zonal and meridional components, indicating a substantial improvement in geolocation performance. In addition, a domain-wide assessment of geolocation accuracy reveals that, except for regions such as Xinjiang and Mongolia where lightning occurrence is too sparse to support robust curve fitting, the geolocation accuracy across most of the LMI field of view is relatively stable, with an average error of approximately 15 km (about 1.5 pixels), achieving high practical accuracy. The corrected dataset is publicly available at https://doi.org/10.11888/Atmos.tpdc.303312 (Zhang et al., 2026).

Global storm-resolving simulations at kilometer scales (1–5 km) provide new opportunities to represent convective processes, yet they remain in the gray zone of deep convection, where cumulus parameterization choices can strongly affect model performance. Using global kilometer-scale simulations from the Digital Earth Global Hackathon 2025, this study applies a new vortex–mesoscale convective system (MCS) tracking and matching algorithm to examine how two convection parameterization configurations—turning off deep convection (IFS-deepoff) and deep convection with reduced cloud-base mass flux (IFS-rcbmf)—influence the simulation of MCSs, vortices, and precipitation during the 2020 Meiyu season over East Asia. Results show that IFS-deepoff outperforms IFS-rcbmf in reproducing the total amount and spatial distribution of precipitation, although both schemes overestimate MCS frequency and their contribution to rainfall over the Sichuan Basin and the middle–lower Yangtze River. Importantly, precipitation biases are not governed by MCS frequency alone, but depend strongly on the coupling between MCSs and vortices. Precipitation in both schemes is highly sensitive to vortex simulation, with IFS-deepoff producing stronger extremes due to enhanced moisture convergence associated with boundary-layer vortices and increased convective available potential energy (CAPE). These findings highlight vortex–MCS coupling as a critical control on precipitation in the kilometer-scale gray zone, demonstrating that convection parameterization influences rainfall primarily through its modulation of multiscale dynamical interactions. This study provides new insight for improving convection treatment in next-generation global storm-resolving models.

Projections of the Asian–Australian, African, and American monsoons are currently challenged by considerable levels of uncertainty, which influences the effectiveness of climate change adaptation strategies. Clarifying the uncertainty sources is essential to reduce this uncertainty. Most previous studies have addressed this issue based on limited members in individual models, which cannot strictly isolate the forced model response from the internal variability. Here, we first employ the latest multi-model large ensemble (MMLE), with a total of 550 members from eight models, under very-high emission scenarios. The results show that model uncertainty (internal variability) increases (decreases) with time for all monsoon regions, but with notably regional disparities in their relative contributions. On the grid scale, internal variability dominates the total uncertainty of summer precipitation changes during the near-term (2020–2039) and mid-term (2040–2059) periods in most monsoon regions. For monsoon circulation, internal variability exerts an even greater influence over the Asian–Australian monsoon region. Compared with the MMLE results, a conventional approach to isolate the forced signal based on polynomial fitting tends to underestimate the fraction of internal variability, particularly when and where that fraction is large. Consequently, the conventional approach overestimates the forced signal of monsoon precipitation relative to internal noise, leading to an earlier time of emergence by about 10 years compared with that derived from the MMLE, which is before 2050 for most monsoon regions. The results highlight the necessity of using MMLEs to quantify sources of uncertainty in climate projections, providing important implications for improving the robustness of future climate assessments.