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Land snow is considered one of the important Earth system elements altering sub-seasonal to seasonal (S2S) atmospheric variability and predictability. However, the causal relationship in the snow–atmosphere interaction and its impact on S2S predictability are still not clearly understood. In this study, we investigated the sub-monthly causal relationship between observed snow cover (SC) and surface air temperature (SAT) in the Northern Hemisphere. We used Liang–Kleeman information flow analysis to scrutinise the direction of causation and identify "cold spots" where SC conditions actively influence SAT on a sub-monthly timescale. The cold spots were identified by geographical location and season: North Eurasia in September and October; East Siberia in October and May; Canada in November; East Asia in November and March; Central Asia in October and November; and East Europe in March. Results based on snow water equivalent instead of SC also confirmed the cold spots identified in SC. Furthermore, we evaluated the SC–SAT causal relation in operational S2S prediction models. The results indicated that the S2S models underestimate the SC influence on SAT to greater or lesser degrees, implying the deficiencies in the models. This study emphasises the importance of faithfully reproducing the SC effect on SAT in S2S models for further possible improvements in sub-seasonal prediction skill. The findings renew a fundamental understanding of the snow–atmosphere interaction and sub-seasonal predictability arising from land snow conditions. [ABSTRACT FROM AUTHOR]

Results from eight regional climate models (RCMs) participating in the Impact of Initialized Land Temperature and Snowpack on Sub-seasonal to Seasonal Prediction (LS4P) initiative of the Global Energy and Water Exchanges (GEWEX) are examined and compared with observations over the Tibetan Plateau (TP). The RCM common domain covers most areas of East Asia with a horizontal resolution of 20–30 km. The model simulation covers a period from April to September in each year between 1991 and 2015. This study explores the RCMs' ability for seasonal climate simulation over the TP, focusing on the summer monsoon climate as part of the LS4P initiative. An intercomparison is made among eight RCMs for precipitation, surface air temperature, mid-troposphere atmospheric circulation, moisture conditions, and surface energy fluxes. It shows that the downscaling characteristics differ significantly between two major RCM types. The RegCM4 models show positive precipitation biases over the entire TP, especially over the south and southeast TP, while the WRF models mostly show both positive and negative precipitation biases over the TP with relatively high spatial correlation between simulated and observed precipitation. The multi-model ensemble mean produces overall smaller precipitation biases than most individual RCMs, with the largest biases over the southeastern TP, and smaller surface air temperature biases over most areas of the TP, especially over the central and southwestern TP. Moreover, the ensemble mean can better reproduce the inter-annual variation of precipitation and surface air temperature than most RCMs with proper magnitude. Sensitivity analyses using RegCM4 with different physics parameterizations show that varying land and cumulus schemes may induce large precipitation differences over the TP by affecting moisture and atmospheric circulation conditions in the lower and upper troposphere, respectively. Moreover, turbulent heat and radiation fluxes differences are associated with the temperature differences between different RegCM4 models. [ABSTRACT FROM AUTHOR]

The slowly varying soil temperature can exert local and nonlocal influences on regional climate system, and may thus provide a critical source of subseasonal-to-seasonal climate prediction. In this study, we identify that soil temperature in May over the key region of Central Asia (42 °N–50 °N, 62 °E–80°E, KRCA) from Noah, Mosaic, CLM and ERA-interim datasets is closely linked to variations of the surface air temperature, daily maximum temperature and hot days over Northeastern China in summer (June–July–August), with correlation coefficients of regional average detrended time series ranging from 0.42 to 0.54, and all significant at the 99% confidence level for the period of 1979–2018. The possible physical mechanism behind the substantial downstream impacts of soil temperature over Central Asia are explored via diagnostical analysis combined with regional climate model experiments. Warmer soil temperature in May over the KRCA can keep to the summer and cause positive anomalies of geopotential height in summer over Northeastern China through the Rossby wave propagation, and associated stronger subsidence warming, less cloud cover, more solar radiation reaching the surface, higher planetary boundary layer, and stronger thermal advection at 850 hPa, which provide favorable conditions for warmer surface air temperature particularly in the daytime as well as more hot days. This study further reveals that soil temperature over Central Asia in May makes important contribution to prediction of summer surface air temperature, daily maximum temperature and hot days over Northeastern China in terms of regional average time series and spatial patterns. Our findings highlight the previously-unknown substantial role of antecedent soil temperature condition over Central Asia for summer surface air temperature variation and prediction over Northeastern China. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau, as a major elevated heat source, plays a critical role in the Asian monsoon and global climate. Observational data revealed significant correlations between spring surface air temperature in the Tibetan Plateau and downstream summer precipitation interannual variations. Sensitivity experiments using the regional Climate-Weather Research and Forecasting model (CWRF) were conducted to understand the physical processes and mechanisms underlying such delayed teleconnections. A positive temperature forcing was imposed over the plateau on the surface and subsurface soil layers only at the initial conditions around May 1st, 2003. This regional forcing quickly induces positive perturbations in local air temperature and, more importantly, maintains its signal in local soil, especially deep layers, for several months. Consequently, the soil temperature serves as a charged capacitor to modulate the planetary atmospheric circulation and through Rossby wave chains to cause significant summer precipitation anomalies over broad regions. This relayed teleconnection pattern is consistent with that identified from observational data records and CWRF climate simulations during 1980–2015. Diagnostic analyses of observations and simulations suggest that the Tibetan Plateau heating significantly impacts summer East Asian monsoon climate through influencing the South Asian High and shifting the East Asian jet. [ABSTRACT FROM AUTHOR]

This study applies three widely used land models (SSiB, CLM, and Noah-MP) coupled in a regional climate model to quantitatively assess their skill in preserving the imposed ± 5 °C anomalies on the initial land surface and subsurface temperature (LST/SUBT) and generating the 2-m air temperature (T2m) anomalies over Tibetan Plateau (TP) during May–August. The memory of the LST/SUBT initial anomalies (surface/soil memory) is defined as the first time when time series of the differences in daily LST/SUBT cross the zero line during the simulation, with the unit of days. The memory of the T2m anomalies (T2m memory) is defined in the same way. The ensemble results indicate that the simulated soil memory generally increases with soil depth, which is consistent with the results based on the observations with statistic methods. And the soil memory is found to change rapidly with depth above ~ 0.6–0.7 m and vary slowly below it. The land models have fairly long soil memories, with the regional mean 1.0-m soil memory generally longer than 60 days. However, they have short T2m memory, with the regional means generally below 20 days. This may bring a big challenge to use the LST/SUBT approach on the sub-seasonal to seasonal (S2S) prediction. Comparison between the three land models shows that CLM and Noah-MP have longer soil memory at the deeper layers (> ~ 0.05 m) while SSiB has longer T2m/surface memories and near-surface (≤ ~ 0.05 m) soil memory. As a result, it is difficult to say which land model is optimal for the application of the LST/SUBT approach on the S2S prediction. The T2m/surface/soil memories are various over TP, distinct among the land models, and different between the + 5 °C and − 5 °C experiment, which can be explained by both changes in the surface heat fluxes and variances in the hydrological processes over the plateau. [ABSTRACT FROM AUTHOR]

This study aims to examine the intraseasonal variation of PM2.5 concentration in North China and explore the potential influence of the Eurasian mid-high-latitude intraseasonal oscillation (ISO) on this variation. A statistically significant period of 10–30 days is observed for PM2.5 concentration anomalies in North China. Further study suggests that circulation patterns and associated meteorological factors play a crucial role in pollution events in North China. These factors influence local accumulation of pollutants and hygroscopic growth conditions. Based on the ISO phases, it is found that, at the earliest, the circulation in phase 2 provides favorable conditions for pollution. The circulation involved phase 2 leads to a strong increase in surface air temperature, a decrease in sea level pressure, and an increase in humidity in the low layers. These conditions provide favorable meteorological conditions for the accumulation of PM2.5 in North China. The interannual variability of ISO intensity and its impact on PM2.5 concentration in North China has also been analyzed. The results show that the circulation is stronger and propagates more southeastward during strong ISO years. Under the influence of the anticyclonic circulation in Mongolia during strong ISO years, favorable moisture conditions and atmospheric stability contribute to an increase in pollution. [ABSTRACT FROM AUTHOR]

This study focuses on the analysis of the simulation of the main climatological features of the Orinoco low-level jet (OLLJ) by a set of models included in the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6) and their projected changes under three Shared Socioeconomic Pathways (SSPs): SSP2-4.5, SSP3-7.0, and SSP5-8.5. We consider the 1979–2014 period to evaluate the historical simulations using the ERA5 reanalysis as the reference dataset. In general, CMIP6 models are able to capture the activation of the OLLJ during December-January–February (DJF) in the Orinoco basin, as well as the main links between this circulation and low-level moisture transport patterns in northern South America. Regarding the analysis of projections, CMIP6 models suggest a weakening and shrinking of the OLLJ, especially in its exit region, by the end of the twenty-first century, which in turn induces changes in atmospheric moisture transport patterns in the region during DJF. The projected changes of the OLLJ are associated with variations in the regional gradients of mean sea level pressure, near-surface air temperature, and surface sensible heat flux in association with drier conditions in the Orinoco basin. These projections are consistent with previous studies suggesting a drier Orinoco river basin throughout the twenty-first century. Assessing the projected changes of this low-level jet in northern South America improves our understanding of the different phenomena that modulate atmospheric moisture transport in the region, which is particularly important given its high vulnerability to climate change. [ABSTRACT FROM AUTHOR]

Based on the multi-model ensemble mean of CMIP6 simulations, the future changes in frequency, intensity and duration of Compound (both daytime and nighttime) heatwaves (HWs) in summer over China at various global warming levels (GWLs) under the SSP3-7.0 and SSP5-8.5 are assessed. HWs over China become more frequent and hotter, and the duration of HWs becomes longer compared to those in the recent climate. The magnitudes of these changes are primarily dependent on GWLs, but they are not very sensitive to the scenarios. At 4 ℃ GWL, the frequency of HWs increases by more than fivefold under both scenarios, and the intensity (duration) of HWs averaged under the two scenarios is 2.28 ℃ hotter (3.59 days longer) than the one in the recent climate over the entire China. Meanwhile, the maximum duration of HW events can reach more than 25 days in summer in comparison with 8 days in the recent climate. The changes in HW properties are regionally dependent at the four GWLs. For example, the largest increase in HW frequency is over the Northwest China, the largest increase in intensity in HWs is seen over the Northeast and Northwest, and the largest increase in HW duration is over the Southwest China. The extreme rare events (50-year and 100-year events) in the recent climate would become the norm over China and four sub-regions at 4 ℃ GWL. Overall, seasonal mean warming dominates the changes in HW properties over China at the different GWLs. The seasonal mean warming in summer across China is related to the increases of longwave radiation, partly due to increase in greenhouse gas forcing and partly resulted from increased water vapor and the increase of shortwave radiation (under the SSP5-8.5) over eastern China related to decreases in aerosols and total cloud cover. Furthermore, the regional variations in the water vapor over China are consistent with atmospheric circulation changes. The seasonal mean surface warming results in enhanced upward sensible and latent heat fluxes, leading to increased summer mean daily maximum and minimum of near-surface air temperature and the enhancement of HWs properties over the entire China. Changes of shortwave radiation tend to play a weaker role for surface warming under the SSP3-7.0 than those under the SSP5-8.5, which is related to increased aerosol changes under the SSP3-7.0. [ABSTRACT FROM AUTHOR]

Although the influences of El Niño–Southern Oscillation (ENSO) and boreal summer intraseasonal oscillation (ISO) on basin-wide tropical cyclone (TC) activity over the western North Pacific (WNP) have been widely recognized, how the seasonal and subseasonal anomalies of sea surface temperature and atmospheric ISO variations modulate different types of WNP TCs needed further examination, as addressed in this study. Using a fuzzy c-means clustering method, we objectively classified the WNP TCs into seven distinct clusters with different genesis locations and trajectories. The genesis numbers of all seven TC clusters revealed significant spectral variance at the intraseasonal timescale in the bands of 10–30 and 30–90 days. Based on the diagnosis of scale-decomposed genesis potential index, we found that the increase in ISO-related mid-tropospheric moistening plays the most important role in TC genesis for all seven clusters, while anomalous circulations (low-level vorticity and mid-level vertical motion) are secondary. The trajectories associated with straight-moving and recurving TC clusters are modulated by ISO-related steering flows. These modulations of TC activities by ISO vary with the phase of ENSO. The modulations of ISO are significantly greater for TCs generated in the southeast quadrant of the WNP in El Niño years than in La Niña years, while ISO imposes a larger impact on landfalling TCs occurring in La Niña years, which are changed by the low-level winds associated with ENSO conditions. The compound effects of ENSO and ISO on TC clusters provide useful sources of subseasonal TC predictability. Our statistical model using the information of ENSO and ISO shows skillful predictions of WNP TC genesis numbers and track distributions at the lead time up to 30 days. [ABSTRACT FROM AUTHOR]

Air temperature variability and prediction are important considering the potential implications on human health, water resource management, agriculture and land-atmosphere interaction. In this paper, we investigate the delayed influence of El Niño on spring Surface Air Temperature (SAT) variability over India using observations and assess its predictability in coupled climate models. Analysis suggests that El Niño, at its decaying phase, exerts a strong influence on the spring SAT over Southern Peninsular India (SPI). This warming is mainly induced by an anomalous anticyclone, which extends from the Western North Pacific (WNP) region to the SPI. The anomalous anticyclone-induced downdraft reduces the cloud cover and increases incoming shortwave radiation at surface, which in turn causes a dry atmospheric column and dry soil moisture over this region. As a result of this decreased soil moisture, latent heat flux into atmosphere reduces and enhances sensible heat transfer, further contributing to dry soil moisture. Both dry soil moisture and anomalous anticyclone contributes to enhanced SAT over SPI region. It is found that 6 years out of the top 10 warmest years over the SPI region correspond to the decaying phase of El Niño, suggesting the importance of the present study. It is also found that the intense SAT warming over SPI aids in increasing frequencies of Discomfort Index hours (exceeding 28 and 30 °C in a day) and the Universal Thermal Climate Index during El Niño decaying spring years. Further, we have examined the predictability of the spring SAT during decaying El Niño years based on the Asia-Pacific Economic Cooperation Climate Center (APCC) models. It is noted that most of the APCC models reasonably predicted the spatial distribution of warm SAT over India during the El Niño decaying spring season at 1 and 3 month lead. This study highlights the predictability of spring SAT a season in advance over India, which would help in planning better adaptation and mitigation strategies. [ABSTRACT FROM AUTHOR]

The effects of initial errors in the subseasonal prediction are investigated using the Korea Meteorological Administration (KMA) Global Seasonal Forecasting System version 5 (GloSea5). Two experiments are designed that utilized (1) analysis data from weather prediction and (2) reanalysis data as the atmospheric initial conditions, which are considered processes of the current operational system. A comparison of these two experiments reveals the effect of the atmospheric initial conditions on subseasonal prediction. Additionally, the effects of different initial prescriptions on the hindcasts and forecasts are investigated. GloSea5 generally represents the observed temperature patterns well; however, cold biases are distinct over continents in the Northern Hemisphere, including the East Asia region in the hindcast results. However, the forecast results simulate anomalously high temperatures in most regions, except for parts of the polar and Australian regions. In this study, it is clear that improved atmospheric initial conditions lead to changes in the prediction skills of variables related to seasonal climate variability in mid-latitude regions. In addition, the biases of the surface temperature are reduced in most regions when the atmospheric initial condition are made consistent between the hindcast and forecast. Notably, increased initial errors in real-time forecasts, compared to hindcasts, can cause more biases in surface temperature and atmospheric circulation fields on a subseasonal time scale. [ABSTRACT FROM AUTHOR]

This study investigates the coupled variability of temperature and precipitation in eastern China during summer using empirical orthogonal function (EOF) analysis to better understand and mitigate simultaneous occurrences of extreme events, such as compound droughts and heat waves. Two dominant modes are identified: the first exhibits a strong warming and drying trend in the region north of the Yangtze River, with the opposite occurring in the south; the second illustrates decadal oscillations in temperature and precipitation, alternating between cool-wet conditions and warm-dry conditions in southern China. The underlying mechanisms for these leading modes are revealed through correlation, composite analysis, and model simulations. The first mode is associated with a negative Pacific-Japan teleconnection in the lower atmosphere and a stationary Rossby wave train across Eurasia in the upper troposphere, which are influenced by global warming and sea surface temperature anomalies in the western North Atlantic. The second mode is linked to alternating active periods of the North Atlantic Oscillation (NAO) and Pacific Decadal Oscillation (PDO). The NAO exerts a significant influence on the summer climate in eastern China during its active phases, while the PDO shows an opposite effect when the NAO is less active. These findings provide valuable implications for long-term planning and adaptation strategies to better cope with compound extreme events in eastern China. [ABSTRACT FROM AUTHOR]

Previous assessments on climate effects of land use and land cover changes (LUCC) mostly focused on the altered surface upward shortwave radiation flux due to changes in surface albedo. However, the explorer on the physical mechanism using the Weather Research and Forecasting model with subgrid scale process precisely described here revealed that the LUCC impacts could not be directly interpreted by surface albedo changes only. The land use-cloud-radiation feedback, within which cloud amount and cloud ceiling, large-scale circulation related moisture flux and local evaporation were altered, played an essential role in affecting surface energy and water budgets between land surface and the atmosphere, especially for the impacted downward shortwave radiation flux. With subgrid scale process considered in describing LUCC and the land use-cloud-radiation feedback emphasized, LUCC impacts on surface air temperature (SAT), precipitation and near-surface wind speed (NSWS) were explored, which displayed marked temporal and spatial characteristics. The LUCC climate effects for both the influenced terrestrial subregions and the intensity were larger over summertime, expressing marked affection on the East Asian Summer Monsoon system. The LUCC impacts on SAT and NSWS mainly presented as changes in mean state, whereas the influences on the precipitation principally displayed as changes in the variability. LUCC induced changes in the averaged SAT, precipitation and NSWS were small, whereas the nearly symmetric distributions between positive and negative changes, which contributed to total changes, were much larger and might have a considerable impact on local and regional climate, especially on extreme climate events. [ABSTRACT FROM AUTHOR]

Topographically channeled winds such as gap winds can be key drivers of freezing rain and ice accretion. Understanding the effect of these winds on the response of freezing rain and ice accretion to global warming is challenging because the spatial resolution of global, and most regional, climate models is too coarse to accurately simulate these winds. To examine the effect of global warming in a region influenced by strong gap winds (the northern Willamette Basin, Oregon, United States), we used 13 year retrospective and pseudo-global warming simulations from a high-resolution, convection-permitting climate model capable of reproducing the easterly gap winds through the Columbia River Gorge. We compared results from the high-resolution model to those from a large ensemble of simulations generated with a coarser-resolution climate model without a well-defined Gorge. Generally, the future projected occurrence of freezing rain decreased at lower elevations and increased at higher elevations. Easterly, low-level winds that bring cold air into the basin were stronger during projected future freezing rain because in a warmer climate, weaker easterly winds were less likely to decrease the basin's near-surface air temperatures to sub-freezing. Because of the stronger gap winds, more of the projected ice events had longer durations and accreted more ice, even at low elevations downwind of the Gorge. The coarser resolution model also projected stronger easterly winds during freezing rain, which implies that the necessity for stronger easterly winds during future freezing rain is not limited to the gap winds but is a regional, if not more widespread. [ABSTRACT FROM AUTHOR]

We investigate the interannual variability of surface air temperature in the twenty-first century using the Coupled Model Intercomparison Project Phase 6 (CMIP6) model data under three shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5). Relative to 1961−2014, the interannual variability of annual temperature is projected to increase by 6%, 6%, and 12% globally in the 2051–2100 period under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios, respectively, with an average increase of 10–22% in low latitudes and decrease of 3–28% in high-latitude oceans. The spatial pattern of wintertime variability changes is mainly determined by variations in the meridional temperature gradient. Sea ice losses and variations in snow extent in the mid to high latitudes are both related with large variability decreases according to analysis of the underlying surface. In South America and South Africa, the variability enhancement is related to the adjustment of the wet–dry status, while that in South Asia and central Africa depends more on the positive longwave radiative effect due to the increase in clouds. In tropical oceans, the increases in sea surface temperature variabilities and air–sea interactions dominate the enhanced surface air temperature variability. [ABSTRACT FROM AUTHOR]

The relationship between Arctic Oscillation (AO) and surface air temperature (SAT) over the Tibetan Plateau (TP) has been long debated, particularly in boreal summer. Based on the statistical analysis, this study reveals a significant interdecadal shift in the relationship between summer AO and the first mode of the summer SAT (SAT_EOF1) over the eastern TP in recent decades. Specifically, during 1979–1998, the correlation between summer AO and SAT_EOF1 was weak and insignificant, but during 1999–2018, it was strong and significant. Changes in the AO-related regional atmospheric circulations are responsible for this enhanced AO-SAT_EOF1 connection. During the latter period, the anomalous anticyclone related to AO has extended further westward from eastern China to the eastern TP, leading to the increased water vapor transport and prevalent descending over the eastern TP. As a result, there has been a decrease in cloud cover over the eastern TP, allowing more solar radiation to reach the ground surface and thus contributing to the enhanced AO-SAT_EOF1 linkage. Further analysis indicates that the phase transition of the Pacific decadal oscillation (PDO) is a crucial factor in regulating the AO-SAT_EOF1 linkage. Since the late 1990s, the PDO has transitioned from a positive to a negative phase, playing a role in the westward extension of the AO-related anomalous anticyclone over the eastern side of the TP through the Pacific-East Asian (PEA) teleconnection. Finally, the model simulation results provide conclusive evidence that the phase transition of the PDO contributes to the unstable AO-SAT_EOF1 connection. [ABSTRACT FROM AUTHOR]

Previous studies have reported significant uncertainty in the relationship between El Niño-Southern Oscillation (ENSO) and the winter surface air temperature (SAT) over central North America (NA). This paper uses reanalysis data and statistical methods to investigate the possible modulation effect of the Victoria mode (VM) during the preceding spring on the winter ENSO–SAT relationship. The correlation between ENSO and the winter SAT over central NA was found to be significantly positive during the positive VM phase. However, this significant correlation is almost absent during the negative VM phase. Further analysis revealed that the zonal location of the sea surface temperature anomalies (SSTA) over the tropical Pacific is an essential aspect of this VM modulation. During the positive VM phase, the dominant positive SSTA in the central-eastern tropical Pacific contribute to the formation of the negative phase of the North Pacific Oscillation (NPO)-like teleconnection, which further enhances the anomalous southerly winds and SAT over central NA. In contrast, during the negative VM phase, the Aleutian low-like atmospheric response induced by the central tropical Pacific SSTA is limited to the central North Pacific, which has a limited effect on the variation of the central NA SAT. The VM modulation mechanism is shown to be well reproduced by historical simulations of the Coupled Model Intercomparison Project Phase 6. Our results suggest that, despite the uncertainty associated with the ENSO–SAT connection, ENSO may provide prediction skills for the winter SAT over central NA during the positive VM phase. [ABSTRACT FROM AUTHOR]

This document discusses the importance of subseasonal-to-seasonal (S2S) prediction of extreme precipitation and land forcing in mitigating the impacts of climate change. The World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP) have launched a joint S2S Prediction Project to improve S2S precipitation prediction over land. The document highlights the role of sea surface temperature (SST) and land-induced forcing in S2S predictability, and emphasizes the need for further research on atmosphere-land interactions. The special issue includes research on the role of land-induced forcing in S2S variability, mechanisms of dynamic and physical processes, and evaluation of regional climate models. The document concludes by stating that while progress has been made, there are still many challenging issues to be addressed in order to achieve a comprehensive understanding of land-induced forcing and S2S predictability. [Extracted from the article]

Continued Amazonian deforestation perturbs the surface turbulent fluxes which are important for building the conditions for the wet season onset in the southern Amazon. This work evaluates the impacts of tropical deforestation on the onset and development of the Amazonian rainy season using a weather typing approach. We use 19-year simulations (2001–2019) with the Regional Earth System Model from the Institute Pierre Simone Laplace (RegIPSL) with twin control/deforestation experiments. RegIPSL represents the dominant modes or the atmospheric circulation patterns (CPs) of the daily-to-decadal circulation variability in tropical South America, and the evolution of atmospheric and surface conditions along the dry-to-wet transition period. According to RegIPSL, forests and crops contribute differently to the onset. During the dry-to-wet transition period, croplands/grasslands present a stronger shallow convection driven by a higher atmospheric temperature. Large-scale subsidence suppresses low-level convection in the region and deep convection only persists over forests where the atmosphere presents more convective potential energy. After the onset and the establishment of large-scale rainfall structures, both land covers behave similarly in terms of surface fluxes. Deforestation decreases the frequency of the CP typically linked to the onset. Changes in the spatial structure and frequency of the wet season CPs reinforce the hypothesis of a deforestation-induced dry season lengthening. Variations in the CP frequency and characteristic rainfall have opposite effects on accumulated rainfall during the dry-to-wet transition period. Whereas alterations in frequency are associated with a regional circulation response, changes in the CP characteristic rainfall correspond to a local response to deforestation. [ABSTRACT FROM AUTHOR]

Prolonged low temperature significantly threatens transportation and planting in populous areas and is closely linked to slowly varying forcing such as sea surface temperature (SST). In this study, we reveal the impact of the north–south dipole pattern in extra-tropical North Atlantic SST (DNA) anomaly on surface air temperature (SAT) over southern China in February. The positive phase of the DNA is favorable for a positive North Atlantic Oscillation-like pattern at the troposphere via synoptic eddy vorticity forcing and triggers a southeastward-propagating Rossby wave train associated with the deepened East Asian trough and the strengthened Siberian high, which are conducive to enhancement of the East Asian winter monsoon. A stronger monsoon leads to lower-than-normal SAT over southern China by intensifying southward cold air outbreaks. Considerably, the extremely low temperature over southern China in February 2022 is explainable by this physical mechanism. Furthermore, experiments with a linear baroclinic model verify that the proposed downstream propagating Rossby wave train is mainly associated with the midlatitude North Atlantic SST anomaly. These results emphasize that the extra-tropical North Atlantic SST anomaly should be focused when interpreting and predicting the late winter SAT over southern China. [ABSTRACT FROM AUTHOR]

This paper investigates the process behind climate model biases, especially in rainfall, during the southwest (June to August; JJA) and northeast monsoon (December to February; DJF) seasons over the Philippines using the downscaled Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment-Southeast Asia (SEACLID/CORDEX-SEA). Biases in the surface and near-surface climate are assessed over land in eastern (EastPH) and western (WestPH) Philippines using observation and reanalysis datasets. Results show that models with well-represented sea surface temperature (SST) provided better added values after downscaling. Although the CMIP5-driven models tend to overestimate both surface energy and water partitioning, simulations with well-represented SST have better surface energy partitions. In contrast to the reference simulation driven by ERA-Interim reanalysis, the CMIP5-driven simulations tend to underestimate (overestimate) moisture flux convergence during the DJF (JJA) season, which might have contributed to the overall underestimation (overestimation) of rainfall in this season. Further investigation along a vertical transect shows the differences in governing mechanisms for each season. During DJF (JJA) season, the simulation with underestimated (overestimated) SST, near-surface air temperature, and mixing ratio results in underestimated (overestimated) rainfall over EastPH (WestPH). In addition, the CMIP5-driven models were found to overestimate low-level winds, which may have induced the deep convection regardless of season, suggesting the role of low-level winds in the convection scheme used in RegCM4 aside from topography and land cover. [ABSTRACT FROM AUTHOR]

During the second half of the twentieth century, the Antarctic Surface Air Temperature (SAT) trends are characterized by fast warming over West Antarctica but mild cooling over East Antarctica. However, after 2000, the warming over several stations in the Antarctic Peninsula slowed down, whereas the South Pole experienced fast warming. These reversed SAT trends show strong regionality and seasonality, together with large uncertainty and disagreement among different observational and reanalysis datasets, which makes it difficult to achieve a comprehensive understanding of the multi-decadal Antarctic SAT trend and its reversal. In this study, we use the Combined Maximum Covariance Analysis (CMCA) method to extract the most coherent modes of the Antarctic SAT trends among six reanalysis datasets and 26 station-based observations. Further analysis shows that the reversals of the SAT trends before and after 2000, especially for austral spring and summer, are mainly attributed to the reversed trends of the leading CMCA modes and their related atmospheric circulation and thermal advection patterns over Antarctica. For austral spring, the reversal of the west-warming-east-cooling pattern over Antarctica is closely related to the changes of thermal advection induced by the anomalous circulation center over the Antarctic Peninsula–Weddell Sea region. For summer, the post-2000 reversal of the Antarctic Peninsula-warming-East Antarctic-cooling is attributed to the stratospheric ozone recovery over the Antarctic, and the associated adjustment of the southern annular mode. The CMCA decomposition better combines the information from different measurements, clarifying the long-term SAT trend and its reversal for different seasons. [ABSTRACT FROM AUTHOR]

The East Asian winter monsoon (EAWM) intensifies in the early twenty-first century and links with frequent impacts of large-scale persistent extreme cold events in winter in East Asia in recent years. We found that there has been a significant positive correlation between the EAWM and Interhemispheric Oscillation (IHO). However, conspicuous interdecadal variations have occurred in the relationship between the EAWM and IHO. The relationship between the IHO and EAWM was most significant during 1979–2020, but this relationship was weak and insignificant during 1962–1978. During 1979–2020, the atmospheric mass (surface pressure) difference between the Northern Hemisphere (NH) and Southern Hemisphere (SH) during 1979–2020 was significantly reduced by 7.85% (0.75 × 1015 kg) compared with that during 1962–1978. Such interhemispheric redistribution of atmospheric mass (AM) has had a distinct impact on the land-sea pressure contrast in East Asia and has intensified the connection between the EAWM and IHO. A strengthened EAWM has resulted in notable cooling and more severe winters in China. The apparent exportation of AM in the Antarctic region is an important driving factor for this interhemispheric change. The accompanying anomalous accumulation of AM in the NH is linked with an increase in the pressure difference between land and sea in East Asia, resulting in intensifying correlation between IHO and the EAWM. The decadal enhancement of the IHO during 1979–2020 was closely connected with conspicuous warming in the tropical troposphere/lower stratosphere (UTLS). A seesaw pattern of anomalous air temperature and ozone between tropical and Antarctic UTLS has induced a decrease in Antarctic ozone masses and air temperature and has strengthened the polar vortex, corresponding to a decadal enhancement of interhemispheric AM imbalance. [ABSTRACT FROM AUTHOR]

Extreme heat events happen frequently in East Asia, and may cause great damage to the ecosystem and society. The synergistic effect of the summer positive North Atlantic Oscillation (pNAO) and positive northwest Pacific (pNWP) sea surface temperature anomaly (SSTA) on the interannual variability of the extreme heat events in the central–eastern China (CEC) is investigated in this study. The two factors act synergistically in strengthening the extreme heat events in the CEC via a series of atmospheric bridges, and the CEC is likely to experience a hotter summer when both the summer pNAO and pNWP SSTA occur. The pNWP SSTA increases the strength of pNAO via the eastward propagating Rossby wave from the western Pacific. The enhanced pNAO induces a stronger eastward Rossby wave propagation across the Eurasian continent, and leads to a strong anomalous anticyclone over the CEC. The significantly increased atmosphere thickness increases the air temperature of the layer, and favors the extreme heat events in the CEC. Besides, the pNWP SSTA also has adjacent effect on the atmospheric circulation over the CEC, which could lead to a positive geopotential height anomaly. Therefore, the summer pNAO and pNWP SSTA act synergistically in influencing the atmospheric circulation over the CEC, and thereby significantly increase the extreme heat events in the CEC. [ABSTRACT FROM AUTHOR]

The temperature rise during the growing season on the Tibetan Plateau (TP) is crucial for the local vegetation phenology and atmospheric circulation. In this study, we investigated the possible effects of soil moisture (SM) anomalies associated with the freeze–thaw process on the surface air temperature (SAT) rise during the growing season using observations and reanalysis data from 1979 to 2014. Results demonstrate that winter SM anomalies associated with the freeze–thaw process can persist until July, significantly modulating SAT rise intensity from May to July on the TP. Positive winter SM anomalies can lead to decreased in SAT in May but increased in SAT in July, thus strengthening the SAT rise from May to July. Further analysis of physical mechanisms suggest the positive winter SM anomaly leads to the increase of surface latent heat flux but the decrease of surface sensible heat flux in May, thus cooling the SAT. As July approaches, significantly increased atmospheric water vapor caused by the positive winter SM anomaly leads to the enhancement of surface downward longwave radiation, which exceeds the cooling effect of decreased sensible heat, resulting in a warmer SAT. Previous studies mainly revealed the "drier SM—higher SAT" feedback. Here we highlight that the thermal variations caused by SM anomalies related with the freeze–thaw process are complicated in the TP, with completely opposite climatic effects during different months. [ABSTRACT FROM AUTHOR]

Future changes in interannual variability (IAV) of Arctic climate indicators such as sea ice and precipitation are still fairly uncertain. Alongside global warming-induced changes in means, a thorough understanding of IAV is needed to more accurately predict sea ice variability, distinguish trends and natural variability, as well as to reduce uncertainty around the likelihood of extreme events. In this study we rank and select CMIP6 models based on their ability to replicate observations, and quantify simulated IAV trends (1981–2100) of Arctic surface air temperature, evaporation, precipitation, and sea ice concentration under continued global warming. We argue that calculating IAV on grid points before area-averaging allows for a more realistic picture of Arctic-wide changes. Large model ensembles suggest that on shorter time scales (30 years), IAV of all variables is strongly dominated by natural variability (e.g. 93% for sea ice area in March). Long-term trends of IAV are more robust, and reveal strong seasonal and regional differences in their magnitude or even sign. For example, IAV of surface temperature increases in the Central Arctic, but decreases in lower latitudes. Arctic precipitation variability increases more in summer than in winter; especially over land, where in the future it will dominantly fall as rain. Our results emphasize the need to address such seasonal and regional differences when portraying future trends of Arctic climate variability. [ABSTRACT FROM AUTHOR]

Taking the semiannual cycle of surface air temperature (SAT) into account in fitting the finer structure of the seasonal cycle, this study reveals the specific role of the semiannual cycle in modulating variations of the season onsets and lengths for the first time. The time-varying amplitudes and phases of the annual and semiannual SAT cycle for the period 1964 to 2017 in China are extracted from daily observations based on harmonic analysis. The results show that the phase differences between the two harmonics remain essentially unchanged, while the amplitude ratio of the semiannual to annual harmonics tends to increase after 1988. This enhanced semiannual cycle together with the global warming and annual cycle changes jointly led to a much longer summer with an average speed of 7.45 days/10 years and shorter spring, autumn, and winter with speeds of − 2.43, − 1.63, and − 4.26 days/10 years, respectively. Such obvious asymmetry cannot be found in fitting seasonal cycles by only annual harmonics. The average absolute percentages of the linear trends of season onsets and lengths caused by the intensification of the semiannual cycle are 52.63% and 78.66%. It indicates that season onsets and length not only depend on the phase of annual and semiannual harmonic, but also highly related to the strength of semiannual cycle. The time evolutions of semiannual cycle strength in China are found to be significantly correlated to the meridional temperature advection. The anomalous stronger southward wind in December can result in colder temperature and hence intensify the semiannual component. [ABSTRACT FROM AUTHOR]

The diurnal cycle is a prominent feature of Earth's weather and climate. Partly due to lack of sub-daily data, our understanding of the diurnal cycle is incomplete. This study analyzes 3-hourly surface observations and ERA5 hourly data to evaluate ERA5's performance in simulating the diurnal cycle and to quantify the diurnal variations in common meteorological and climate fields over the globe. The goal is to provide a standard reference for the diurnal cycle in various surface and atmospheric fields. Here I focus on surface pressure (Ps), air temperature (Tas), relative (RH) and specific humidity (q), and winds. Results show that ERA5 captures well the observed diurnal variations in Ps, Tas and RH, showing the dominant westward-propagating wavenumber-2 pattern in Ps and wavenumber-1 pattern in Tas and RH. Over many land areas, Ps 24 h cycle (S1) can reach an amplitude of 1.0–1.5 hPa, comparable to its semidiurnal cycle (S2), and the S1 enhances the 1st peak around 1000 local solar time (LST) but suppresses the 2nd peak around 2200 LST in Ps. Diurnal variations in Tas and RH are out-of-phase and dominated by S1, with a mean amplitude of 3–4 °C for Tas and 10–15% for RH over land (but with considerable variations) and a maximum for Tas (a minimum for RH) around 1500 LST. Tas and RH diurnal variations are much weaker over ocean, with an amplitude of ~ 0.7–0.8 °C for Tas and 1–2% for RH. Surface q is slightly higher during the day than at night with a dip in middle afternoon in the tropics and warm-season extratropics. Surface wind speed shows a diurnal amplitude of 0.5–1.0 m/s over land and about half of that over ocean and a peak in the early-middle afternoon. ERA5 data suggests that the surface Tas and RH diurnal cycle extends to the middle-upper troposphere with similar phases but reduced amplitudes. Sea surface temperatures in ERA5 lack any diurnal variations, which dampens diurnal variations in its marine Tas and RH and causes incorrect diurnal cycle in marine q. [ABSTRACT FROM AUTHOR]

The northernmost margin of the East Asian summer monsoon (NMEASM) is the northernmost position that the East Asia summer monsoon (EASM) can reach. NMEASM has obvious multi-scale variability, and well reflects the wet/dry climate variability in northern China. Predicting the location change of the NMEASM is important for understanding future East Asian climate change. However, the variability of the NMEASM has not been studied extensively, and its underlying mechanisms have not been clarified. To explore the movement of the NMEASM and its causes, we use reanalysis datasets to evaluate the NMEASM index from 1979 to 2018. The NMEASM indicates a decreasing trend over 40 years and a significant abrupt point in 2000, which is positively correlated with the Tibetan Plateau snow cover before 2000 and the Siberian snow cover after 2000 in spring. The decreased Siberian snow cover increases the soil temperature and decreases the atmospheric baroclinicity over Mongolia and northern China after 2000. The decreased atmospheric baroclinicity induces the dipole mode of anticyclonic anomaly over Mongolia and northern China and the cyclonic anomaly over the Sea of Japan by modulating the wave activity flux (WAF). The WAF's southeastward propagation strengthens the anticyclonic anomaly over Mongolia and northern China and the cyclonic anomaly over the Sea of Japan, which weakens the upward movement and water vapor transport, respectively. Hence, the decreased Siberian snow cover in spring modulates the precipitation over Mongolia and northern China and the southward movement of NMEASM by turbulent westerly circulation. [ABSTRACT FROM AUTHOR]

In the late twentieth century, global mean surface air temperature especially on land is continuously warming. Our analyses show that the global mean of dust increased since 1980, using the Modern-Era Retrospective Analysis version 2 for Research and Applications (MERRA-2) reanalysis data. This variation of global dust is mainly contributed by the dust increase outside of dust core areas (i.e. high dust mass concentration region). The causes to result in global dust variations are explored. In dust core areas, surface wind is the primary driving factor for surface dust, both of which show no remarkable trends of increase or decrease since 1980. In areas outside of the core areas, especially in arid and semi-arid areas in North and Middle Asia, surface air temperature warming is the primary impact factor causing the dust increase. An increase in surface air temperature is accompanied by enhancement of atmospheric instability which can trigger more upward motion and bring more dust. All 9 Earth System Models (ESMs) for the Aerosol Chemistry Model Intercomparison Project (AerChemMIP) reproduce the reasonable spatial distribution and seasonal cycle of dust in the present day. But only a few models such as BCC-ESM1 and GFDL-ESM4 simulate the increasing trend of dust similar to MERRA-2. While the primary impact of wind in dust core areas, and surface temperature outside of the core areas, especially in middle to high latitudes in Eurasian continent, are presented in most ESMs. [ABSTRACT FROM AUTHOR]

Being strongly influenced by internal climate variability, the atmospheric circulation response to greenhouse gas forcing in the future climate is uncertain. This study addresses atmospheric circulation through representative circulation types (CTs) and investigates the CTs' changes with respect to frequency and effect on surface temperature and precipitation over a pan-Scandinavian domain. The analysis is based on the Swedish Meteorological and Hydrological Institute Large Ensemble performed with EC-Earth3: 50-member ensembles from one historical and six scenario simulations for the twenty-first century are used to assess internal variability and significance of changes. Although the results show no strong future changes in the CTs' sea level pressure patterns, CT frequency changes suggest a future extension of summer conditions towards spring and autumn and point towards a clearer distinction between summer and winter. The present-climate CT effect on surface temperature is found to generally weaken which is consistent with a general decrease in temperature variability. Largest-scale and strongest temperature effect changes are projected between March and May for CT3, a cyclone towards the east of the domain associated with a domain-wide cooling effect that will likely be decreased towards the end of the twenty-first century. Similarly but of opposite sign, the CT effect on precipitation is strengthening as a result of the increased precipitation variability. Here, largest-scale and strongest effect enhancement is found for CT6, thus increasing its wetting effect over southern Scandinavia and drying effect west of the Scandes. Changes are generally largest towards the end of the twenty-first century and tend to increase with the forcing strength, thus maximizing for SSP585. [ABSTRACT FROM AUTHOR]

During the austral winter (June–August) of 2021, the meteorological services of Brazil, Argentina, Peru, Paraguay, Bolivia, and Chile all issued forecasts for unusually cold conditions. Record-low minimum temperatures and cold spells were documented, including one strong cold wave episode that affected 5 countries. In this study, we define a cold wave as a period in which daily maximum and minimum air temperatures are below the corresponding climatological 10th percentile for three or more consecutive days. The intense cold wave event in the last week of June, 2021, resulted in record-breaking minimum daily temperatures in several places in central South America and Chile. Several locations had temperatures about 10 °C below average, central South America had freezing conditions, and southern Brazil even saw snow. The cold air surge was characterized by an intense upper-air trough located close to 35° S and 70° W. The southerly flow to the west of this trough brought very cold air northward into subtropical and tropical South America. A northward flow between the lower-level cyclonic and anticyclonic perturbations caused the intense southerly flow between the upper-level ridge and trough. This condition facilitated the inflow of near-surface cold air from southern Argentina into southeastern Brazil and tropical South America east of the Andes. In the city of São Paulo, the cold wave caused the death of 13 homeless people from hypothermia. Frost and snow across southern and southeastern Brazil caused significant damage to coffee, sugarcane, oranges, grapes, and other fruit and vegetable crops. Wine and coffee production fell, the latter by 30%, and prices of food and commodities in the region rose. [ABSTRACT FROM AUTHOR]

The role of temperature advection in the Arctic lower troposphere under changing level of global warming is investigated using a large-ensemble climate simulation dataset. Taking the 30-year climatology of the non-warming simulation (HPB-NAT) as a reference, we examined the difference in temperature advection under changing basic states of the historical experiment (HPB) and 2 K and 4 K warming experiments (HFB-2K and HFB-4K) and decomposed them into terms related to dynamical changes, thermodynamical changes and the eddy term which is a covariance term related to the effect of sub-monthly transient eddies. Under the HPB experiment, it was found that the total change in advection hangs in a balance between the positive signal located along the sea-ice boundary in the North Atlantic and along the Eurasian continent driven by a stronger dynamical term and a negative signal in the thermodynamical term and eddy term. It is found that with the progression of global warming the dynamical term of advection increases due to changes in the large-scale atmospheric circulation, but the thermodynamical term and eddy term decrease due to weaker temperature gradient and increased sensible heat flux from the newly opened ice-free ocean, respectively. Atmospheric temperature advection terms related to large-scale atmospheric circulation partially cancels one another, and the relative importance of the eddy term diverging locally induced sensible heat from the newly opened ice-free ocean dominates as global warming progresses. [ABSTRACT FROM AUTHOR]

Southern China is prone to floods during the wet season, and regional extreme precipitation is expected to become more frequent given the context of climate change. However, the prediction skills and predictability of the spatial distribution of extreme precipitation days (EPDs) over southern China remain unclear. To address this issue, through observational diagnosis and numerical experiment, the present study revealed the formation mechanisms of the two leading modes of pre-summer (May and June) EPDs in southern China, and established a physical-based empirical model (P-E model) to predict the distribution of EPDs in the region. The results revealed the following: (1) the first mode of pre-summer EPDs in southern China displayed a uniform pattern, while the second mode presented a meridional dipole pattern. The uniform pattern of the first mode is associated with the tropical western North Pacific anomalous anticyclone (TWPAC), whereas the meridional dipole pattern of the second mode is related to the subtropical western North Pacific anomalous anticyclone (SWPAC); (2) the spring North Atlantic tripole sea surface temperature (SST) pattern, the northern North America surface air temperature, and the snow cover depth over central Siberia contribute to the variation of the first mode and TWPAC, whereas the spring extratropical North Atlantic dipole SST pattern and the spring change of sea ice concentration over the Barents and Kara seas are physically linked with the variation of the second mode and SWPAC; (3) based on these predictors, the established P-E model demonstrated predictive skill with regard to the principal components of the first two modes, and the spatial distribution of EPDs in southern China was reconstructed. The areal mean temporal correlation coefficient skill for the independent prediction period (2011–2021) was 0.34, while for the pattern correlation coefficient skill averaged over the entire period was 0.28. In comparison with the maximum attainable skills, both metrics indicate potential for improvement. The findings of this study represent a reference for the prediction and predictability of the spatial distribution of pre-summer EPDs in southern China. [ABSTRACT FROM AUTHOR]

Excessive heat can cause discomfort, stress even mortality to humans. We investigate the multifaceted characteristics of summer heat and the affected population across China using a composite heat index (HI) based on meteorological observations and the Coupled Model Intercomparison Project Phase 6 climate models. We highlight that HI is only applicable when maximum air temperature is above 26.7 ℃. From 1961 to 2014, China has experienced increasing heat days (1.05 day/10a) and severity (0.15 ℃/10a) with more population influenced by expanding heat extent. Simultaneously, increases in the frequency (7.58–14.80 times), duration (0.46–1.23 days) and intensity (1.00–1.42 ℃/day) of heat events are detected with increased population exposure (9.33 × 105–5.59 × 106 times·persons). In the future, increases in heat severity, spatial extent, and the affected population would be aggravated from 1.5 to 2 to 3 ℃ warming. Dangerous heat events would experience increases in frequency (12.67–70.81 times), duration (0.85–7.21 days), intensity (1.78–8.57 ℃/day), and population exposure (2.06 × 106–3.18 × 107 times·persons) under a warming climate. Some regions over the Tibetan Plateau and southwest China would be affected by expanding cautionary and extremely cautionary heat. Northwest China would experience intensified dangerous heat events whereas southeastern China would face longer-lasting heat events with stronger intensity. Precautionary strategies are essential for these regions under risk. [ABSTRACT FROM AUTHOR]

The increasing intensity and frequency of high-temperature events in response to climate change can potentially impact the aviation industry, since aircraft takeoff and landing performances depend on near-surface air temperature. Previous studies have combined climate data with aircraft technical data to estimate the future impact of rising high temperatures on aircraft takeoff. They found a decrease of maximum takeoff weights and the lengthening of takeoff distances. The Mediterranean region is a climate change "hot spot" area, specially concerned by extreme high-temperatures increase. In this study, the magnitude and trends of the daily maximum near-surface temperature extremes in summer were analysed over major airports in Southwestern Europe. Trends in the period 1961–2014 were analysed from observations and reanalysis. Future changes by 2021–2050 and 2071–2100, with respect to 1961–2005, were analysed from simulations performed with Regional and Global Climate Models (RCMs and GCMs). Before assessing future climate projections, climate models were evaluated in present climate, and the RCM and GCM ensembles were compared to each other. No clear added value was found for RCMs over GCMs in present climate at the airport scale in these terms. GCMs project larger temperature changes than RCMs over the same locations. Multi-model ensemble mean projected changes under the RCP8.5 scenario range between + 1.7 and + 3.2 ∘ C by the near term, and between + 4.9 and + 8.5 ∘ C by the long term, across the airports and the RCM and GCM ensembles. This increase of high-temperature extremes would impact airport operations. Adaptation or mitigation policies would become necessary. [ABSTRACT FROM AUTHOR]

More than 85% of the Ethiopian population's livelihood depends on rain-fed agriculture. Therefore, accurate climate estimation is quite useful to improve food security. However, the poor spatial resolution of satellite open access Outgoing Long-wave Radiation (OLR) data and the complicated relationship with the temperature and precipitation over variable topography features, the climate estimation is below the satisfactory level. Hence, to address this problem, this paper aimed to model OLR based on moisture parameters related to the air temperature in Ethiopia. European Center for Medium-Range Weather Forecast (ECMWF) and satellite data from 1981 to 2020 has been used to develop a new OLR model. The atmospheric moisture budget equation was applied for the new OLR mode development. The results indicated that the seasonal variation moisture coefficient (α) for winter, spring, summer, and autumn is found 0.99, − 0.29, 0.91, and 0.98 m3w−1 which is satisfied the model requirement. During winter, spring, summer, and autumn, the average value of OLR are found 269.60, 246.10, 247.90, and 255.60 Wm−2 from satellite direct observation respectively; while from the developed model is found at 268.79, 244.01, 248.97 and 254.93 Wm−2 respectively. Based on error matrices the developed mode is well agreed with satellite direct observation at a specific point and it is helpful to estimate OLR in the required spatial resolution. Generally the increment of the local moisture which is decreased OLR and increases the air temperature. Hence, stakeholders must pay high attention to the new OLR model adaptations for flood prevention and drought monitoring in Ethiopia. [ABSTRACT FROM AUTHOR]

Several of the best track datasets reveal the earlier end of the tropical cyclone (TC) season over the main WNP (the east of the Philippine Islands) from 1980 to 2019, especially by the date of the upper decile of the storm days (constructed by adding one to each date if any TC exists). The enhanced vertical wind shear (VWS) during the late season (October and November) is consistent with this earlier end of the TC season. In October, the enhanced VWS is the result of the increased zonal and meridional shears, which are affected by the earlier circulation transition of the East Asian summer monsoon recessed and winter monsoon onset during late October. During November, the zonal wind shear dominates the enhanced VWS, which vertically is the opposite trend of air temperature below and above the tropopause and the meridionally opposite trend of air temperature in the north and south of 30°N. The opposite air temperature trends induce the thermal wind balance, which causes enhanced westerlies in the mid-latitudes and strong zonal shear. Three pathways increase VWS in the late season over the WNP, leading to the earlier end of the TC season. The strong impact of VWS limits TC formation, although the ambient warming underlying the surface (supports a broader and stronger potential intensity). The effect of the thermodynamical parameter, depending on relative humidity at the low and middle troposphere, is uncertain because of the inconsistent and weak trends in October between ERA5 and MERRA-2, but they both become unfavorable to TC genesis during November. The practically important meaning of the VWS for the TC season provides a possibility for future projections of the TC season. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) is an important component of the global climate system, while the characteristics of its climate are poorly represented in most regional climate models at coarse resolutions. In this study, a 20-year (2000–2019) dynamical downscaling simulation at the gray-zone resolution (9 km) using the WRF model driven by the ERA5 reanalysis is conducted over the TP. Based on comparisons against in-situ observations and the Integrated Multi-satellite Retrievals for GPM (IMERG) version 6 satellite precipitation product, the assessment of basic climate variables, such as near-surface air temperature (T2m) and precipitation, is performed to evaluate the model's performance and understand its added value better. Results show that both WRF and ERA5 can successfully reproduce the spatial patterns of annual mean and seasonal mean surface air temperature. However, significant cold and wet biases are found especially over the southeastern TP in ERA5, which are greatly improved in WRF with reduced RMSEs. Not only the climatological characteristics, but also the inter-annual variability and seasonal variation of T2m and precipitation are well captured by WRF which reduces the cold and wet biases especially in winter and summer compared to ERA5, respectively. Besides, at daily scale, the overestimation of precipitation in WRF and ERA5 is mainly caused by the overestimated precipitation frequency when precipitation intensity changed slightly. Furthermore, WRF outperforms ERA5 in capturing the diurnal variation of precipitation with more realistic peak time in all sub-regions over the TP. Further investigation into the mechanism of model bias reveals that less simulated snow cover fraction plays a crucial role in increasing the surface net energy by affecting surface albedo over the southeastern TP in WRF, leading to higher T2m. In addition, less water vapor transport from the southern boundary of TP leads to reduced wet bias in WRF, indicating that the added value in dynamical downscaling at gray-zone resolution is obtained by representing water vapor transport more realistically. [ABSTRACT FROM AUTHOR]

The Baltic Sea is among the fastest-warming seas globally in recent decades affecting biogeochemical conditions such as euxinic areas but also pelagic and benthic marine ecosystems. It is therefore crucial to understand how this heat gain is distributed vertically. We used reconstructed atmospheric forcing fields for 1850–2008 to perform an ocean climate simulation that adequately captures climatogical temperature and salinity profiles. Then, a water mass classification distinguishes three water masses corresponding to the classical view, warm and fresh surface waters, cold and fresh intermediate waters, and cold and salty bottom waters, and two transition water masses. The temperature trends show a similar three layers pattern with fast warming at the surface (~ 0.06 K decade− 1) and bottom (> 0.04 K decade− 1) and slow in the intermediate layers (< 0.04 K decade− 1). The slow warming in the intermediate layer is explained by both weakly warmed water winter convection and the summer surface thermocline isolating the intermediate layers. The warming in the deep layers is related to warm surface inflow from the North Sea and Baltic proper in the southern and northern Baltic Sea respectively. Furthermore, sensitivity experiments show that the warming magnitude is controlled by rising air temperature while the vertical distribution of heat gain is related to surface wind conditions. Finally, the North Atlantic Oscillation and Atlantic Multidecadal Oscillation are well correlated with the temperature minimum and thus modulate the magnitude of warming in the intermediate layers on shorter time scales. This study provides a new picture of the Baltic Sea's warming and suggests that this complexity is essential for understanding the influence of climate change on marine ecosystems. [ABSTRACT FROM AUTHOR]

As one of the most significant circulation systems over the Northern Hemisphere in the cold season, the East Asian winter monsoon (EAWM) has been broadly investigated from the seasonal-mean perspective, while subseasonal variations in the EAWM still remain ambiguous. Based on Season-reliant Empirical Orthogonal Function (S-EOF) analysis, this study shows that the subseasonal strength reversal of the EAWM (SR-EAWM), featuring a weaker (or stronger) EAWM in early winter (December) and a stronger (or weaker) EAWM in late winter (January–February), is a distinct leading mode of the month-to-month variation of the EAWM. The weak-to-strong SR-EAWM is characterized by an anomalous low over Eurasia and a weakened East Asian major trough (EAT) in early winter, with an intensified Siberian High and a deepened EAT in late winter. The SR-EAWM is preceded by surface air temperature anomalies over Davis Strait (DST) and those over central-eastern North America (CENAT) in September–October. The DST mainly influences the SR-EAWM in early winter through a "sea ice bridge" of the November Baffin Bay sea ice concentration anomaly (BBSIC). The BBSIC could intensify the DST in December by altering surface heat flux, thus exciting a downstream atmospheric response and modulating the strength of the EAT in early winter. The CENAT affects the SR-EAWM in late winter by inducing an "ocean bridge" of the western North Atlantic sea surface temperature anomaly (WNASST). The WNASST can persist into late winter and then significantly affects the SR-EAWM by regulating Eurasian circulation anomalies and the downstream EAT. The bridge roles of the BBSIC and WNASST can be further verified by a linear baroclinic model. Finally, two physical-empirical models are established using the DST/BBSIC and the CENAT indices, respectively. Both exhibit promising prediction skills. The results highlight that the DST, BBSIC, and CENAT are crucial predictability sources for the SR-EAWM. [ABSTRACT FROM AUTHOR]

Cloud-radiation process has a strong impact on surface air temperature (SAT). Using the Weather Research and Forecasting (WRF) model, this study investigates the effects of cumulus and radiation parameterization on SAT simulation over Eastern China (EC) during the summer season from 2001 to 2020. Four experiments are performed at a 30 km resolution using the combination of two cumulus schemes (KF and KF-CUP) and two radiation schemes (CAM and RRTMG). The results indicate that the KF and RRTMG scheme can produce warmer SAT than KF-CUP and CAM, respectively. By decomposing the differences in SAT simulation, it is found that KF and RRTMG have greater surface downward shortwave radiation (DSR), and the DSR shows a significant positive correlation with SAT in most parts of EC. Further analysis reveals that low-level cloud (LC) can strongly reflect the DSR, and the LC fraction (LCF) of KF and RRTMG is less than that of KF-CUP and CAM, respectively. The reason for this phenomenon is that the sub-grid cumulus heating rate is higher in KF and RRTMG, resulting in their higher air temperature (T) and greater differences between T and dew point (Td), which is not conducive to the formation of large-scale stratiform cloud and the increase of LCF. As a result, KF and RRTMG have more DSR and higher SAT than KF-CUP and CAM, respectively. The same mechanism can also explain the differences in the sub-seasonal cycle simulations between the four experiments. By comparing the SAT error in each subregion, this study can also provide a reference for future dynamic downscaling over the EC region. [ABSTRACT FROM AUTHOR]

Exploring the predictability sources of Northeast Asian spring surface air temperature (NEAST) is of great socioeconomic importance. In the present study, three factors that alternately take control of NEAST during different epochs in the past 60 years are identified. Specifically, NEAST was found to be closely associated with the Arctic Oscillation (AO) in 1961–1994 (E1), the rainfall over the tropical Indian Ocean (RIO) in 1995–2004 (E2), and the tripole pattern of North Atlantic sea surface temperature (NAT) in 2005–2020 (E3). During E1, zonally elongated barotropic cyclonic anomalies associated with the negative phase of the AO led to negative NEAST. During E2, negative diabatic heating related to suppressed RIO stimulated a Rossby wave train propagating from the Arabian Sea to Northeast Asia, resulting in barotropic cyclonic anomalies in the region and negative NEAST. During E3, positive diabatic heating anomalies in the extratropical North Atlantic induced by NAT caused two quasi-barotropic Rossby wave trains over the mid-to-high latitudes of continental Eurasia. The Rossby wave trains both ended with a barotropic cyclonic anomaly over Northeast Asia, leading to negative NEAST. Further analyses show that the rapid decline in Arctic sea-ice cover in the Sea of Okhotsk and Bering Sea in the mid-1990s, weakening of the central Asian westerly jet, and enhancement of NAT-related rainfall anomalies around the mid-2000s, were responsible for the changes in the factors controlling NEAST. A physical-based empirical model constructed using the three identified factors and their precursors nicely reproduced and forecasted the variation in NEAST, outperforming the hindcast of the coupled dynamical models. [ABSTRACT FROM AUTHOR]

To get a better overview of atmosphere-driven mass changes at Urumqi Glacier No.1, Chinese Tien Shan, the surface energy budget and mass balance is modeled by linking the COupled Snowpack and Ice surface energy and MAss balance model (COSIMA) with in-situ measured meteorological records for the ablation period in 2018. The COSIMA is calibrated by manual optimization and the modeled results agree well with the in-situ surface temperature, snow height and seasonal mass balance. Our results reveal that Urumqi Glacier No.1 experienced a significant mass loss, with an average value of − 0.77 m w.e. over the ablation period 2018. The surface energy budget components can be classified into two categories: radiation (shortwave and longwave) and turbulent fluxes. Surface melt and solid precipitation were dominated components of mass balance. The COSIMA can reproduce the glaciological mass balance compared with other models. Sensitivity analysis showed that the mass balance was more sensitive to the temperature than precipitation, and mass loss caused by temperature increase of 1 K needed to be compensated by at least 40% precipitation increase. Air temperature during the ablation period was more important than annual precipitation in controlling mass balance changes on Urumqi Glacier No. 1. These findings will enhance our understanding of the mechanisms underlying mass balance processes of ablation period and their contribution to the acceleration of glacier retreat in Tien Shan. [ABSTRACT FROM AUTHOR]

This study focuses on the strengthening of the maritime influence on the Balkan Peninsula in summer. The study uses mainly statistical methods such as trend analysis, multiple linear regression models, etc. The research period is 1979–2020. The results show that in the beginning of the twenty-first century in southeastern Europe there is a tendency of faster increase in the average August air temperatures compared to the increase in average July air temperatures. Thus, the temperature in August is already higher than that in July. The causes for these changes are changes in atmospheric circulation in summer. Over the last two decades, the transport of air masses from east and southeast has been strengthening, which for the Balkan Peninsula means a transport from water basins toward land. The intra-annual course of air temperature above a water basin, which has a maximum in August, is now becoming typical over land. This feature is not yet present in the entire studied region, but the trends from the measurements in meteorological stations show that very soon the temperatures in August could be higher than that in July over the entire territory of the Balkan Peninsula. On a more global scale, it is still unclear which mechanisms of atmospheric circulation influence the processes in southeastern Europe. Changes in ocean temperatures and atmospheric circulation in the North Atlantic are likely to have an impact. However, other factors (e.g. the increase in global temperatures, the expansion of Hadley cell) may also have an impact. [ABSTRACT FROM AUTHOR]

This study reveals a marked enhancement in the relationship between the variations in location of the winter East Asian Polar Front Jet (EAPJ) and the surface air temperature (SAT) in Eurasia since the mid-1990s. Before the mid-1990s, an evident wave train related to the meridional location of the EAPJ exhibited an anticyclonic anomaly over northern Europe and a cyclonic anomaly in northwestern Asia. With an equatorward shift of the EAPJ after the mid-1990s, the wave train experiences a notable adjustment that is conducive to East Asian cooling, displaying an anticyclonic anomaly around the Kara-Laptev Seas and a cyclonic anomaly near northeastern Asia. Arctic warming anomalies and sea ice loss contributed significantly to these decadal changes. Simulation experiments forced by observed Arctic sea-ice variability further confirm this result. Since the mid-1990s, Arctic sea ice loss (or Arctic warming anomaly) has contributed to a reduction in westerly winds in high latitudes by modulating the meridional temperature gradient. The deaccelerated winds intensify the Arctic cold air propagating to the south, enhancing the atmospheric baroclinicity and the westerly flow in the upper level at the south side of the EAPJ, favoring the southward shift of the EAPJ. With the equatorward shift of the EAPJ, the corresponding SAT anomalies in East Asia are more salient. [ABSTRACT FROM AUTHOR]

The maximum signal-to-noise ratio empirical orthogonal function (MSN-EOF) is used to evaluate the midsummer 2 m temperature over Eastern China using subseasonal forecast data in the ECMWF model. The predictable sources of the most predictable components in the ECMWF model are analyzed, and the improvement of reconstructed predictions with leading predictable components is also investigated. ECMWF has the highest forecast ability among all S2S models but decays significantly after 10 d. The leading predictable mode mainly presents a dipole mode over Eastern China. Both the El Niño-Southern Oscillation and tropical Indian Ocean sea surface temperature anomalies are the main predictable sources of MSN-EOF1. A positive MSN-EOF1 is accompanied by El Niño decay, which can cause the strong and westward West Pacific Subtropical High, accompanied by anomalous southwesterlies over the north of Eastern China. The second predictable mode is the warmer characteristic of the Yangtze-Yellow River Basin, and the sea ice anomalies over the Barents Sea in the previous winter are the main predictable sources. This is accompanied by the wave train propagating from northwestern Russia to northeast Asia. The third predictable mode is mainly the temperature trend item extracted from the ECMWF model. The reconstructed predictions with the leading four MSN-EOF components show higher ability than the model raw predictions, therefore, this method can use the predictable components to filter the model noise and reduce the model error. [ABSTRACT FROM AUTHOR]

Since the 1980s, rapid Arctic sea ice loss has been observed, and its potential influences on the midlatitude weather and climate have been extensively examined, but strongly debated. This study instead investigates influences of Arctic sea ice loss on the Eastern Hemisphere westerly wind on the poleward side of the polar front jet (PFJ), which has significantly weakened in winter but strengthened in summer since 1980s. Observational analyses indicate that the Eastern Hemisphere PFJ anomalies in winter and summer are strongly correlated with Northern Hemisphere (NH) atmospheric circulation, surface air temperature and precipitation changes, and that the winter PFJ variability is significantly correlated to Barents-Kara sea ice anomalies from autumn and winter at interannual time scales. About 58% of the observed winter PFJ weakened trend during 1979–2014 is congruent with the autumn sea ice index over the Barents-Kara Seas. Atmospheric model ensemble simulations from four models show that Arctic sea ice loss contributes to Arctic warming in winter and reduces the northern Eurasia-pole temperature contrast, leading to an significant weakening winter PFJ. Ensemble mean effects of four models and each model due to Arctic sea ice loss explain about 10–20% of the observed winter PFJ weakening trend, because the model simulations underestimate observed impacts of sea ice reduction on Arctic troposphere warming. In summer, the strengthening PFJ is mostly controlled by increasing greenhouse gases and sea surface temperature changes outside the Arctic, but is little affected by Arctic sea ice loss. Our observational and numerical results consistently suggest that a dynamical pathway linking observed Arctic sea ice loss to northern Eurasian winter is through its weakening effect on the westerly wind on the poleward side of the PFJ. [ABSTRACT FROM AUTHOR]

A comprehensive model assessment on a 6-hourly scale from multiple dimensions is critical for model selection of dynamic downscaling to reduce uncertainties. In this study, we evaluated the performance of 13 models involved in the Coupled Model Intercomparison Project-6 (CMIP6) by comparing the simulated meteorological variables at the pressure levels of 850, 500, and 250 hPa, including 6-hourly air temperature, specific humidity, zonal wind, meridional wind, and geopotential height, to those from the ERA5 reanalysis data for the 1979–2014 period. The results indicated that the CMIP6 models could mostly reproduce the spatial pattern of the climatology. Most models underestimated air temperature and geopotential height while overestimating specific humidity and zonal and meridional wind speeds in the upper troposphere. Additionally, the interannual variability of zonal and meridional wind exhibited a relatively better performance but limited ability for specific humidity at 850 hPa. Regarding the annual and diurnal cycles, CMIP6 models reasonably captured the annual cycle shape, while an overestimation was detected in simulating the diurnal amplitude, notably at 250 hPa. Based on a comprehensive rating index and overall rankings, our findings showed that no single model was identified as suitable for the simulation of any variables and regions. The models performed well for five variables, including MPI-ESM1-2-LR, MPI-ESM1-2-HR, TaiESM1, and UKESM1-0-LL, over East Asia. Then, according to the overall performance of the five variables and model accessibility, the optimal model varied by region and shared socioeconomic pathway (SSP) scenario. The multi-model ensemble mean outperformed individual models over almost all regions when it comes to comprehensive performance. The MPI-ESM1-2-LR and MRI-ESM2-0 models were the best two out of 13 models as lateral boundary conditions applied to seven climate scenarios over East Asia. This study provides valuable scientific references for selecting the optimal CMIP6 models for the projection of dynamic downscaling over East Asia and eight subregions. [ABSTRACT FROM AUTHOR]

The present study investigated seasonal and spatial characteristics of the trends in surface air temperature (SAT) over Central Asia during 1979–2018 and the relative contributions of dynamic and thermodynamic effects using a dynamical adjustment methodology. Regional averaged total SAT shows the largest rising rate in spring and its trend is not obvious in winter. The thermodynamically effect induces a widespread warming trend in most of Central Asia in all the four seasons. The dynamically induced SAT trends exhibit obvious seasonal and regional differences. Both dynamic and thermodynamic effects play a crucial role in the total SAT increasing trend in spring, the thermodynamic effect is predominantly responsible for SAT warming and the dynamic effect has a secondary contribution in summer, the rising temperature in autumn is attributed to the thermodynamic effect and the dynamic effect has a negative but insignificant contribution, and the total SAT trend in winter is small due to opposite contributions of thermodynamic and dynamic effects. Further analysis revealed that the changes in the Scandinavia pattern (SCAND) during 1979–2018 are likely the cause of dynamically induced temperature trends in spring, autumn and winter. The dynamical component of summer SAT trends over eastern Central Asia is contributed by the interdecadal transition of the Atlantic multidecadal oscillation (AMO) and Pacific decadal oscillation (PDO). Those climate modes contribute to SAT variations via their effects on wind-induced temperature advection and surface heat fluxes. [ABSTRACT FROM AUTHOR]