Panmao Zhai’s research while affiliated with Chinese Academy of Meteorological Sciences and other places

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Publications (100)


The flow chart of data production from emissions to human-induced warming, the remaining carbon budget and changes to climatic impact drivers, illustrating both the rationale and workflow within the paper production.
Annual global anthropogenic GHG emissions by source, 1970–2023. Refer to Sect. 2.1 and Table S1 for a list of datasets. Datasets with an asterisk (*) indicate the sources used to compile global total greenhouse gas emissions following the WGIII assessment in (a). CO2-equivalent emissions in (a) and (f) are calculated using GWP100 from the AR6 WGI Chap. 7 (Forster et al., 2021). F-gas emissions in (a) comprise only UNFCCC F-gas emissions (see Sect. 2.1 for a list of species). F-gas emissions in (f) refer to UNFCCC F-gases, except for “CIP v2024.04 [ODS F-gases]”. Some of the major depicted differences between datasets (e.g. between GCB v2024 and Grassi NGHGI v2024 in panel c) are due to varying system boundaries, rather than underlying uncertainties in activity levels or emissions factors.
Annual global anthropogenic greenhouse gas emissions by assessment convention in 2023. Refer to Table 1 for a list of underlying datasets. Differences between conventions are primarily due to differences in system boundaries (Lamb et al., 2025). Uncertainties are ±8 % for CO2-FFI, ±70 % for CO2-LULUCF, ±30 % for CH4 and F-gases, and ±60 % for N2O, corresponding to a 90 % confidence interval.
Atmospheric concentrations of a set of well-mixed greenhouse gases over 2000–2024. The grey shaded region represents continuing changes since AR6. Note the different vertical scales.
Effective radiative forcing (ERF) from 1750–2024. (a) 1750–2024 change in ERF, showing best estimates (bars) and 5 %–95 % uncertainty ranges (lines) from major anthropogenic components to ERF, total anthropogenic ERF and solar forcing. Note that solar forcing in 2024 is a single-year estimate and hence differs from Table 3. (b) Time evolution of ERF from 1750 to 2024. Best estimates from major anthropogenic categories are shown along with solar and volcanic forcing (thin coloured lines), total (thin black line), and anthropogenic total (thick black line). The 5 %–95 % uncertainty in the anthropogenic forcing is shown by grey shading.

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Indicators of Global Climate Change 2024: annual update of key indicators of the state of the climate system and human influence
  • Article
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June 2025

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Chris Smith

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Tristram Walsh

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Panmao Zhai

In a rapidly changing climate, evidence-based decision-making benefits from up-to-date and timely information. Here we compile monitoring datasets (published at 10.5281/zenodo.15639576; Smith et al., 2025a) to produce updated estimates for key indicators of the state of the climate system: net emissions of greenhouse gases and short-lived climate forcers, greenhouse gas concentrations, radiative forcing, the Earth's energy imbalance, surface temperature changes, warming attributed to human activities, the remaining carbon budget, and estimates of global temperature extremes. This year, we additionally include indicators for sea-level rise and land precipitation change. We follow methods as closely as possible to those used in the IPCC Sixth Assessment Report (AR6) Working Group One report. The indicators show that human activities are increasing the Earth's energy imbalance and driving faster sea-level rise compared to the AR6 assessment. For the 2015–2024 decade average, observed warming relative to 1850–1900 was 1.24 [1.11 to 1.35] °C, of which 1.22 [1.0 to 1.5] °C was human-induced. The 2024-observed best estimate of global surface temperature (1.52 °C) is well above the best estimate of human-caused warming (1.36 °C). However, the 2024 observed warming can still be regarded as a typical year, considering the human-induced warming level and the state of internal variability associated with the phase of El Niño and Atlantic variability. Human-induced warming has been increasing at a rate that is unprecedented in the instrumental record, reaching 0.27 [0.2–0.4] °C per decade over 2015–2024. This high rate of warming is caused by a combination of greenhouse gas emissions being at an all-time high of 53.6±5.2 Gt CO2e yr⁻¹ over the last decade (2014–2023), as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that the rate of increase in CO2 emissions over the last decade has slowed compared to the 2000s, and depending on societal choices, a continued series of these annual updates over the critical 2020s decade could track decreases or increases in the rate of the climatic changes presented here.

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Contribution of the Northeast China Cold Vortex to the Persistent Extreme Precipitation Events over the Yangtze–Huaihe River Basin

Persistent extreme precipitation events (PEPEs) have dramatic socioeconomic impacts in the Yangtze–Huaihe River basin (YHRB). However, the possible role of the Northeast China cold vortex (NEC-CV) in modulating the PEPEs over the YHRB remains unresolved. In this study, the contribution of NEC-CVs to summer precipitation is first examined over central-eastern China, which is characterized by a local and long-distance effect, along with distinct geographic variability. Limited influence is found for the areas outside a threshold of 4× radius of NEC-CV. The YHRB is one of the regions significantly affected by the NEC-CVs, which accounts for about 35%–40% of the total extreme precipitation. During 1961–2022, about 27.7% of the total PEPEs are found to be closely related to the NEC-CVs. In addition, two types of PEPEs (type W/type E) are identified based on the position of corresponding NEC-CV tracks. Significant impacts are found for the opportune configurations of NEC-CVs. The PEPEs are found to be located more westward/eastward for type W/type E, with the anomalous moisture mainly coming from the western North Pacific/South China Sea. The two PEPEs exhibit the anomalous eastward/westward extension of the South Asian high/western North Pacific subtropical high and anomalous southward shift of the upper-level jet with respect to the climatology. Meanwhile, the lower troposphere is dominated by a large-scale low pressure, strong wind shear, and intense moisture transport in the YHRB. The concurrent combinations of the upstream Ural blocking and the downstream Okhotsk blocking are favorable for the development and southward intrusion of NEC-CVs to the YHRB in type W. However, the counterparts in type E are closely associated with the upstream Baikal blocking. The precursor signals of the NEC-CVs can be detected 12/8 days prior to the peak PEPE occurrence at 500 hPa for type W/type E. Significance Statement Persistent extreme precipitation events (PEPEs) can cause catastrophic flooding. This study demonstrates the role of the Northeast China cold vortex (NEC-CV) in influencing such high-impact weather events in the Yangtze–Huaihe River basin (YHRB). Using the latest reanalysis datasets and neural network technology, we quantitatively conclude that the NEC-CVs have contributed to about 35%–40% of the total extreme precipitation and 27.7% of the total PEPEs in the YHRB over the past 60 years. The relevant PEPEs are dominated by the NEC-CVs, with the opportune configuration of the upper and lower circulation systems. These key findings present a new perspective on the meteorology of the PEPEs with implications for the medium-range weather forecasts.


Indicators of Global Climate Change 2024: annual update of key indicators of the state of the climate system and human influence

May 2025

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617 Reads

In a rapidly changing climate, evidence-based decision-making benefits from up-to-date and timely information. Here we compile monitoring datasets (published here https://doi.org/10.5281/zenodo.15327155 Smith et al., 2025a) to produce updated estimates for key indicators of the state of the climate system: net emissions of greenhouse gases and short-lived climate forcers, greenhouse gas concentrations, radiative forcing, the Earth's energy imbalance, surface temperature changes, warming attributed to human activities, the remaining carbon budget, and estimates of global temperature extremes. This year, we additionally include indicators for sea-level rise and land precipitation change. We follow methods as closely as possible to those used in the IPCC Sixth Assessment Report (AR6) Working Group One (WGI) report. The indicators show that human activities are increasing the Earth’s energy imbalance and driving faster sea-level rise compared to the AR6 assessment. For the 2015–2024 decade average, observed warming relative to 1850–1900 was 1.24 [1.11 to 1.35] °C, of which 1.23 [1.0 to 1.5] °C was human-induced. The 2024 observed record in global surface temperature (1.52°C best estimate) is well above the best estimate of human-caused warming (1.36°C). However, the 2024 observed warming can still be regarded as a typical year, considering the human induced warming level and the state of internal variability associated with the phase of El Niño and Atlantic variability. Human-induced warming has been increasing at a rate that is unprecedented in the instrumental record, reaching 0.27 [0.2–0.4] °C per decade over 2015–2024. This high rate of warming is caused by a combination of greenhouse gas emissions being at an all-time high of 53.6 ± 5.2 GtCO2e per year over the last decade (2014–2023), as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that the rate of increase in CO2 emissions over the last decade has slowed compared to the 2000s, and depending on societal choices, a continued series of these annual updates over the critical 2020s decade could track decreases or increases in the rate of the climatic changes presented here.



Rainbelt Properties of Persistent Heavy Precipitation over the Yangtze River Basin and Associated Three-Dimensional Circulations

In this study, we objectively identified rain belts of persistent precipitation processes over the Yangtze River basin during 1961–2021 based on an improved rotating calipers algorithm. Considering the accumulated precipitation volume as the flood-inducing indicator, persistent heavy precipitation events were identified and categorized into three types—along, north, and south of the Yangtze River—by applying k-means clustering for spatial similarity. Results showed that events along and in the south of Yangtze are more persistent and more flood inducing than events in the north of Yangtze. Composite analysis revealed the relevant three-dimensional stable circulation patterns and indicated that the location of their rain belts is determined by circulation configurations. For events along the Yangtze, an eastward-propagating wave train facilitates a single-blocking high and deepens the East Asian trough. A southeastward-positioned South Asian high (SAH) and intensified westerly jet support a strong divergence in the Yangtze River basin at 200 hPa. The western Pacific subtropical high (WPSH) stretches southwestward with a strong low-level jet, inducing warm and humid air to converge with cold air along the Yangtze. For events in the south of the Yangtze, a relatively southeastward wave train maintains under double-blocking highs. The northeast sector of the SAH, the westerly jet, WPSH, and low-level jet are located more to the south. Last, events in the north of the Yangtze are associated with the development of a blocking high and a dominant belt of low pressure to the south. The unfavorable circulation pattern inhibits cold air invasion, resulting in relatively weaker precipitation with shorter duration. Significance Statement Considering the location, spatial coverage, and intensity of persistent precipitation processes in the Yangtze River basin, this study objectively classified rain belts of persistent heavy precipitation (PHP) events, investigated the corresponding stable circulation patterns, and constructed three-dimensional conceptual models for three types of PHP events. This study may help to better understand the formation mechanisms of PHP events and serve as a reference for improving the forecasting of such events operationally.


Evaluation of High‐Resolution Downscaling Predictions for the July 2023 Extreme Rainstorm in the Beijing‐Tianjin‐Hebei Region Based on CMA‐CPSv3

The integration of weather and climate prediction represents the current frontier in the development of numerical modeling in China. Dynamic downscaling serves as a pivotal approach, improving the performance and resolution of global climate models to the weather scale. Focusing on the ‘23.7’ extreme rainstorm (July 29, 00:00–August 2, 00:00 UTC) in the Beijing‐Tianjin‐Hebei region, this study assesses predictions from the China Meteorological Administration Climate Prediction System version 3 (CMA‐CPSv3, 45 km resolution) and 9‐km dynamic downscaling hindcasts from the Weather Research and Forecasting model (WRF‐9 km). In contrast to the conventional climate anomaly approaches, direct outputs are used for evaluation, similar to weather forecasting tests. By examining, both the CMA‐CPSv3 predictions and the WRF‐9 km hindcasts provide a 5‐day prediction window for this rainstorm. They successfully predict the rainstorms and related atmospheric circulations from July 24th onward, aligning with observed and reanalyzed data. WRF‐9 km, with the higher resolution and optimised physical processes, outperforms CMA‐CPSv3, especially in precipitation spatial distribution and center intensity. The WRF‐9 km 7/24 hindcast demonstrates the most significant enhancement compared to the corresponding CMA‐CPSv3 prediction. This improvement is notably reflected in the substantial increase in spatial correlation, from 0.68 to 0.79, as well as a reduction in the difference of center values, decreasing from −51% to −20%. Furthermore, the WRF‐9 km 7/24 hindcast improves the Critical Success Index by 0.08, the Success Rate by 0.08, and the Probability of Detection by 0.29 for heavy rainfall (over 25.0 mm/d). However, improvements in large‐scale circulations with WRF‐9 km are limited, which may restrict advancements in predictability. In conclusion, the WRF‐9 km enhances the performance and resolution of CMA‐CPSv3 predictions, which can be regarded as a viable pathway for CMA‐CPSv3 to achieve weather‐climate integration.


Schematic diagram of recovery time estimation. Green bars indicate the detrended and deseasonalized monthly NDVI series. Dashed black line indicates pre-drought vegetation condition, which is represented by the mean detrended and deseasonalized monthly NDVI across the same number of months as the relevant drought event. In this case, the drought event lasts three months, therefore the pre-drought vegetation condition is estimated as the mean detrended and deseasonalized monthly NDVI during the three months preceding drought. Red solid line indicates the monthly SPEI-06 series, and dashed red line indicates the SPEI-06 threshold (−1) for drought detection.
Global distribution of vegetation recovery post general drought and CDHE. (a), (b) Total number of general drought and CDHE events during 1982–2016. (c), (d) recovery time post general drought and CDHE averaged over the period of 1982–2016. For panel (c) and (d), a pie chart of recovery time shown in the spatial patterns is shown in the inset at bottom-left. Only vegetated regions (defined following IGBP) with drought occurrence are shown here.
Recovery time post general drought and CDHE for different vegetation types. ENF, evergreen needle-leaved forest; EBF, evergreen broad-leaved forest; DNF, deciduous needle-leaved forest; DBF, deciduous broadleaved forest; MF, mixed forest; Shrub, closed and open shrublands. Each bar graph, i.e. panels (a)–(f), (h)–(m), refers to a vegetation type defined based on IGBP, with the global distribution shown in panel (g). For each bar graph, left shown is the frequency distribution of recovery time post general drought, while right shown for recovery time post CDHE events. Numbers on the top refer to the mean recovery time post general drought (left) or post CDHE events (right). Letters indicate statistically significance regarding difference between drought types at p < 0.05 based on analysis of variance (ANOVA).
Relative contribution of potential driving factors on the drought recovery time for different vegetation types. Vegetation types defined here include: evergreen needle-leaved forest (ENF), evergreen broad-leaved forest (EBF), deciduous needle-leaved forest (DNF), deciduous broadleaved forest (DBF), mixed forest (MF), temperate shrubland (Shr(t)), boreal and arctic shrubland (Shr(b)), savannas, temperate grassland (Grass(t)), boreal and arctic tundra (Tund(b)), tundra over the Tibetan Plateau (Tund(T)), and cropland. Preciprecovery, total precipitation during post-drought recovery period; MAP, mean annual precipitation; SMrecovery, mean soil moisture during post-drought recovery period; VPDrecovery, mean vapor pressure deficit during post-drought recovery period; Tmprecovery, mean temperature during post-drought recovery period; SMdrought, mean soil moisture during drought; VPDdrought, mean vapor pressure deficit during drought; Tmpdrought, mean temperature during drought; MAT, mean annual temperature; aridity index, mean annual aridity index; CV of precip, coefficient of variation (CV) of annual precipitation; CV of Tmp, coefficient of variation of annual temperature; duration, drought duration; intensity, drought intensity indicated by SPEI values; sand fraction, topsoil sand fraction; biodiversity, plant species richness; Veg loss, vegetation loss during drought. The z-score was calculated for Preciprecovery, VPDrecovery, VPDdrought, and SMdrought before the boosted regression tree (BRT) analysis to make the magnitudes of the values comparable across variables.
Protracted vegetation recovery after compound drought and hot extreme compared to general drought

January 2025

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131 Reads

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2 Citations

Recovery time is critical for accurate assessment of drought impacts on vegetation growth and terrestrial carbon dynamics. However, the dominant factors driving the spatiotemporal variation of recovery time are still poorly understood; hardly any research has focused on the comparison of recovery time between general drought and compound dry-hot events. This study examined recovery time of vegetation greenness post different drought types during 1982–2016 and attempted to identify the predominant factors determining vegetation recovery time over the globe. Our findings demonstrated protracted recovery of vegetation greenness after compound drought and hot extreme (CDHE) event compared to general drought in 68% of global vegetated area. Deciduous broadleaved forest exhibited the most remarkable difference between recovery time post CDHE (13.8 ± 5.6 months) and post general drought (9.3 ± 4.7 months). We also revealed that post-event moisture condition and long-term precipitation were the chief impact factors of drought recovery time.


Accumulated occurrence (days) of regional dry (purple) and humid (green) heatwaves in southern China (20°−25°N, 110°−122°E) during each summer (June–August) of 1979–2022. (b) Mean power spectra (black solid line) of standardized 2‐m temperature over the southern China, calculated as the arithmetic average of individual power spectrum for all summers. The Markov red noise spectrum (red dashed line), the priori 99% confidence bound (blue dashed line) and posterior 99% confidence level (green dashed line) are also shown. The blue shading shows the interannual spread. (c) Same as (b), but for relative humidity.
Composites of 10–30‐day filtered (a) 2‐m temperature (color scale, K), (b) 850‐hPa specific humidity (color scale, g kg⁻¹), (c) surface net shortwave (color scale, W m⁻²) and (d) longwave radiation (color scale, W m⁻²) anomalies conditioned on the humid heatwaves in southern China. The radiations are positive downwards. Stippling indicates the region where the anomaly is significant at the 90% confidence level.
Composite of 10–30‐day filtered (a) OLR (W m⁻²), (b) lower‐tropospheric (1,000–700 hPa) integrated specific humidity (color scale, kg m⁻²) and moisture transport (vectors, kg m⁻¹ s⁻¹) conditioned on the humid heatwaves in southern China. Stippling indicates that the OLR or humidity anomaly is statistically significant at the 90% confidence level. The vector is shown only if at least one component is statistically significant at the 90% confidence level. (c) Same as (b), but for 200‐hPa vorticity (color scale, 10⁻⁵ s⁻¹) and wind (vector, m s⁻¹) anomalies.
Barotropic energy conversion (color scale, 10⁻⁴ m² s⁻³) between the 200 hPa summer‐mean flow and 10–30‐day circulation during summers of (a) (c) 2003–2012 and (b) (d) 2013–2022 over the northeastern Atlantic and TP. Also shown are the 200 hPa summer‐mean subtropical westerly jets, denoted as the contour of 20 m s⁻¹. Red rectangles show the origins of the 10–30‐day wave train. Also displayed are standard deviations of the 10–30‐day filtered OLR anomalies (color scale, W m⁻²) during summers of (e) 2003–2012 and (f) 2013–2022. (g) Histogram (bar) and fitted (line) probability density distribution for the frequency occurrences of the circulation configuration of tropical convection mode in Figure 3a and mid−high‐latitude circulation mode in Figure 3c during the summers of (blue) 2003–2012 and (red) 2013−2022.
Combined Influence of 10–30‐Day Tropical and Mid–High‐Latitude Intraseasonal Oscillations on the Rapid Increases of Humid Heatwaves in Southern China

December 2024

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132 Reads

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1 Citation

Plain Language Summary Southern China is a typical hotspot of heatwaves. In the recent decade of 2013–2022, the southern China experienced a marked transition from dry heatwaves to humid ones, with the occurrence frequency of humid heatwaves becoming more than 4 times that of dry counterpart. As the humid heatwaves usually lasting for 3–5 days are more directly associated with the intraseasonal (10–90‐day) variability, we have identified significant 10–30‐day intraseasonal oscillation (ISO) in temperature and humidity in southern China, and found their critical role in inducing the lethal humid heatwaves. This finding provides the scientific clues for extending the forecast lead time of humid heatwaves. The circulation configuration of the 10–30‐day atmospheric ISOs at mid–high latitudes and tropics leads to the concurrence of strong moisture convergence and anomalous descents over southern China. The increased downward longwave radiation in association with moisture enhancement, shortwave radiation and adiabatic heating in association with descents bring about the persisting hot and wet conditions in humid heatwaves. As more barotropic energy are transferred from mean flow to 10–30‐day circulation at mid–high latitudes, and tropical 10–30‐day convection activities get stronger, the occurrence of 10–30‐day circulation configuration induced humid heatwaves have increased from 39% in the period of 2003–2012 to 52.3% in the period of 2013–2022. Therefore, humid heatwaves become the predominant type.


Quantifying processes of winter daytime and nighttime warming over the Tibetan Plateau

November 2024

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133 Reads

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3 Citations

Climate Dynamics

The Tibetan Plateau (TP) has experienced accelerated warming in recent decades, especially in winter. However, a comprehensive quantitative study of its long-term warming processes during daytime and nighttime is lacking. This study quantifies the different processes driving the acceleration of winter daytime and nighttime warming over the TP during 1961–2022 using surface energy budget analysis. The results show that the surface warming over the TP is mainly controlled by two processes: (a) a decrease in snow cover leading to a decrease in albedo and an increase in net downward shortwave radiation (snow-albedo feedback), and (b) a warming in tropospheric temperature (850 − 200 hPa) leading to an increase in downward longwave radiation (air warming-longwave radiation effect). The latter has a greater impact on the spatial distribution of warming than the former, and both factors jointly influence the elevation dependent warming pattern. Snow-albedo feedback is the primary factor in daytime warming over the monsoon region, contributing to about 59% of the simulated warming trend. In contrast, nighttime warming over the monsoon region and daytime/nighttime warming in the westerly region are primarily caused by the air warming-longwave radiation effect, contributing up to 67% of the simulated warming trend. The trend in the near-surface temperature mirrors that of the surface temperature, and the same process can explain changes in both. However, there are some differences: an increase in sensible heat flux is driven by a rise in the ground-atmosphere temperature difference. The increase in latent heat flux is associated with enhanced evaporation due to increased soil temperature and is also controlled by soil moisture. Both of these processes regulate the temperature difference between ground and near-surface atmosphere.



Citations (77)


... We used MODIS land cover data based on the International Geosphere-Biosphere Programme (IGBP) classification scheme to statistically analyze the effects of CHEs on different vegetation types. Considering that vegetation of the same type may respond distinctly to extreme events across various climate zones Ren et al., 2023), our study reclassified global vegetation into 13 types based on MODIS IGBP land cover and Köppen-Geiger climate zone data (Huang and Zhai, 2025). Following Huang et al. (2019), the original 17 land cover types were first grouped into 9 major vegetation types: evergreen needleleaf forest (ENF), evergreen broadleaf forest (EBF), deciduous needleleaf forest (DNF), deciduous broadleaf forest (DBF), mixed forest (MF), shrubland (SHR), savanna (SAV), grassland (GRA), and cropland (CRO). ...

Reference:

Differential impacts of compound dry- and humid-hot events on global vegetation productivity
Protracted vegetation recovery after compound drought and hot extreme compared to general drought

... Dry atmospheric conditions over the tropics lead to negative soil moisture anomalies (Fig. 4e), limiting the available moisture for evaporation (Fig. 4f) 54 and subsequently reducing latent heat flux released from the surface 55 . This reduction (i.e., upward heat transport from surface to atmosphere) weakens the cooling effect of evaporation 56 . Additionally, negative anomalies in sensible heat flux in the tropics indicate an increased heat transfer from the surface to the overlaying atmosphere, further warming near-surface air temperatures, and favoring the occurrence of winter warm spells in these areas. ...

Quantifying processes of winter daytime and nighttime warming over the Tibetan Plateau

Climate Dynamics

... On one hand, TCs usually cool the surface ocean and warm the subsurface ocean, leading to a deepened mixed layer (Zhang et al., 2021). On the other hand, mixed layer depth significantly (marginally) affects various TC parameters (e.g., intensity, size and destructiveness) before (after) reaching a depth threshold that is mainly determined by TC intensity (Zhang et al., 2024). Nonetheless, this interaction between TCs and the upper ocean is primarily observed on synoptic or weekly timescales, because TC-induced temperature anomalies in the upper ocean typically disappear over a timescale of a couple of weeks (Dare & McBride, 2011;Ma et al., 2020;Mei & Pasquero, 2013;Price et al., 2008). ...

Impact of ocean mixed layer depth on tropical cyclone characteristics: a numerical investigation

... However, it remains a challenge to quantify the dependence of models and to objectively assign weights to ESMs. EC are the most popular method of observational constraint in recent years, which seeks statistical relationships between aspects of future projection change and observable current climate across ESMs (Williamson et al 2021, Shiogama et al 2022, Wang et al 2024. Despite the wide range of applications of EC method, finding the physical mechanisms behind the statistical constraint relationships remains difficult. ...

Constraining future surface air temperature change on the Tibetan Plateau

... The temperature extremes were further exacerbated by enhanced local land-atmosphere feedback under low soil moisture conditions . Similarly, the 2023 HW in North China was also characterized by anomalous anticyclone systems and the land-atmosphere feedback induced by low soil moisture conditions Qian et al. 2024;Wang et al. 2024;Xiao et al. 2024). ...

Record‐breaking heatwave in North China during the midsummer of 2023

... These trends are largely consistent with the findings of previous studies. For example, multiple studies have reported that most areas of the Tibetan Plateau have experienced a significant warmingwetting trend since 1980, while localized warming-drying phenomena have occurred in the eastern high-altitude humid regions (Qian et al. 2012;Wang et al. 2022;Yu et al. 2024). ...

Integrated warm-wet trends over the Tibetan Plateau in recent decades
  • Citing Article
  • July 2024

Journal of Hydrology

... While analytic and radiative transfer calculations demonstrate the feasibility of weakening the CO 2 greenhouse effect 7,8 , such an approach has heretofore never been proposed or tested in coupled ocean-atmosphere or earth system models, and its potential relative to other traditional SAI approaches remains largely unknown. 1 High Meadows Environmental Institute, Princeton University, Princeton, NJ, USA. 2 Admittedly, a few previous studies of SAI using BC aerosols have been performed [9][10][11] ; however, these studies did not consider the above-mentioned impact of BC in modifying the greenhouse effect, by altering the thermal structure of the upper stratosphere, focusing instead on its ability to cool the planet by reducing the solar radiation at the surface, either through radiative forcing at the tropopause or surface level. However, effective radiative forcing (ERF) at the TOA provides a more comprehensive representation of the overall climate impact of a forcing agent, as it accounts for all atmospheric adjustments [12][13][14][15][16][17] . ...

Indicators of Global Climate Change 2023: annual update of key indicators of the state of the climate system and human influence

... 36 Other reports, led independently by researcher groups and academic institutions, have also gained prominence over the years, including the Global Carbon Budget, 37 Net Zero Stocktake, 38 and State of Carbon Dioxide Removal, 39 in addition to several groups of researchers who have endeavored to generate annual overviews of key climate indicators, published in academic journals. [40][41][42] Given the abundance of institutional reports and the numerous academic reviews and syntheses published every year in peer-reviewed journals, what justifies the 10 New Insights in Climate Science initiative? Each report listed above is an important resource for negotiating delegations, but their contribution is to provide updates on key indicators of the state of the climate and of climate action. ...

Indicators of Global Climate Change 2023: annual update of key indicators of the state of the climate system and human influence

... The Qilian Mountains, serving as an ecological corridor between the Loess Plateau and Xizang Plateau and housing the headwaters of major rivers, host a climate-sensitive ecosystem vulnerable to drought-induced ecological disturbances under warming conditions (Nogués-Bravo et al., 2007;Zhang et al., 2021a;Bai et al., 2023). Most previous studies, such as Wang et al. (2021) and Zhou et al. (2024), on flash droughts have focused on the whole of China or Xizang Plateau, while investigations on the influence of atmospheric circulation modes on flash droughts remain lacking. Consequently, research gaps persist regarding localized flash drought dynamics and compound events in the Qilian Mountains. ...

Bivariate attribution of the compound hot and dry summer of 2022 on the Tibetan Plateau
  • Citing Article
  • April 2024

Science China Earth Sciences

... Conversely, GUD of grasslands is dominated by precipitation ( Figure S10 in Supporting Information S1) (C.-P. Wang et al., 2024a;J. Zhao et al., 2020), with the enhanced sensitivity to precipitation along increasing precipitation (Figure 8d). ...

Co-influence of the start of thermal growing season and precipitation on vegetation spring green-up on the Tibetan Plateau
  • Citing Article
  • April 2024

Advances in Climate Change Research