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Abstract Compound heat anomalies associated with humidity, such as compound hot-dry events and hot-wet events, pose greater health risks than single heat anomalies. Here, we utilize ambulance dispatch data along with air temperature and relative humidity to study human impacts on these events in China. We show that relying solely on temperature without considering humidity may underestimate the health risks of these events on populations. Over the past 40 years, anthropogenic activities have increased hot-dry events by 2.34 times and decreased hot-wet events by 0.63 times, especially in the Yangtze River region, compared to natural forcing. We also speculate that, in the future up to 2060, under the carbon-neutral scenario, the frequencies of high health-risk hot-dry events and hot-wet events caused by human activities can be reduced by one-half and over one-fifth, respectively, compared to the high-emissions scenario. These findings provide guidance for assessing health risks under global warming.

Abstract Capabilities of 43 models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) to simulate the Madden‐Julian Oscillation (MJO) were compared in this study. Models with higher MJO simulation skills reproduce organized large‐scale convection more frequently over the equatorial western Pacific (EWP), suggesting that MJO simulations are tightly connected to organization of large‐scale precipitation over the EWP. MJO simulation skills are not significantly correlated with the mean sea surface temperature (SST) over the EWP, but tightly connected to SST threshold for convection there. The top simulations exhibit lower SST threshold and more realistic SST‐precipitation relationship over the EWP, suggesting that convection can be organized more efficiently and intensified more rapidly with the increasing SST in these simulations. Our results emphasize that reproducing the relationship between SST and large‐scale precipitation over the EWP is critical to MJO simulations.

The impacts of solar activity on the tropical Pacific climate have been widely reported. However, few studies focus on the effects of solar activity on the tropical cyclone (TC). Based on the observational and reanalysis data for 1979–2020, this study investigated the solar modulation of TC frequency over the western North Pacific in different solar cycle phases. Results suggest that the regressions of TC frequency to solar activity are asymmetric in the high- and low-solar activity years (HS and LS). Specifically, the intensified solar activity could markedly induce more TCs in HS; however, no significant modulation can be found in LS. Further exploration reveals a possible air–sea coupled mechanism for this interesting phenomenon. The relatively cloud-free area in the western North Pacific could receive more incoming solar radiation at the surface in HS than in LS. This increased regional surface net solar radiation in HS could produce a stronger surface upward latent heat flux and, thus, greater evaporation. Along with that, the local upward motion is dramatically enhanced over the TC source. Then, for compensation, the regional sea level pressure is reduced, and the low-level winds become cyclonic over the TC origin. All of these solar-caused regional atmospheric anomalies in HS contribute to more TC generations. The key to this possible mechanism is the increased regional solar forcing at the ocean surface that is amplified by regionally enhanced upward latent heat flux and evaporation.

The Sun has an obvious quasi-11-year cycle and numerous short-term eruptive activities. There are four processes of energy transmission in the effectuation chain of solar forcing to the climate system: solar energy input into the atmosphere, atmospheric absorption of the input energy, transformation of the absorbed energy into dynamic and thermodynamic responses in the atmosphere, and coupling among all the layers affected by solar forcings. However, the four processes have not been discussed in their entirety. This present paper reviews studies over the last decade on how solar radiation varies during the solar cycle and solar eruptions, and, correspondingly, how the terrestrial atmosphere absorbs the input solar energy.

The Huaihe River Basin (HRB) is one of the most severely affected regions by torrential rain disasters in China. However, with climate warming, it is unclear what new features torrential rain exhibits and how the main modes of torrential rain change in this region. This study analyzes the first two modes of torrential rain in the HRB from 1961 to 2020 and their driving factors. Results show that in the last 30 years, the frequency of torrential rain events in the HRB has clearly increased, especially in southern HRB region during the flood season. The first mode of torrential rain is an entire basin-wide mode, with a period of 2–3 years. The mode is primarily influenced by the low-level westerly jet stream and Jianghuai cyclones, which are closely linked to the stratospheric Quasi-Biennial Oscillation (QBO) through influencing planetary wave propagation and convective activity under different phases of QBO. The second mode is a north-south distribution mode, with a period of 4–6 years. The leading circulation system is the frontal systems. Both the East Asia/Pacific (EAP) teleconnection wave train and ENSO drive the second torrential rain mode. During El Niño years, anomalous subsidence and anticyclone in the western tropical Pacific, induced by sea surface temperature warming in the eastern tropical Pacific through the East Asia/Pacific teleconnection, can trigger the EAP wave train poleward in the East Asian region. This wave train leads to the cold-warm confrontation conducive to the second torrential rain mode.

Precipitation nowcasting is a crucial element in current weather service systems. Data-driven methods have proven highly advantageous, due to their flexibility in utilizing detailed initial hydrometeor observations, and their capability to approximate meteorological dynamics effectively given sufficient training data. However, current data-driven methods often encounter severe approximation/optimization errors, rendering their predictions and associated uncertainty estimates unreliable. Here a probabilistic diffusion model-based precipitation nowcasting methodology is introduced, overcoming the notorious blurriness and mode collapse issues in existing practices. Diffusion models learn a sequential of neural networks to reverse a pre-defined diffusion process that generates the probability distribution of future precipitation fields. The precipitation nowcasting based on diffusion model results in a 3.7% improvement in continuous ranked probability score compared to state-of-the-art generative adversarial model-based method. Critically, diffusion model significantly enhance the reliability of forecast uncertainty estimates, evidenced in a 68% gain of spread-skill ratio skill. As a result, diffusion model provides more reliable probabilistic precipitation nowcasting, showing the potential to better support weather-related decision makings.

The sun plays a crucial role as the primary source of energy for the Earth’s climate system and the issue of the influence of solar activity on the climate has been actively discussed recently. However, the precise impact of solar activity on extreme precipitation on the decadal timescale remains insufficiently confirmed. In this study, we investigate the relationship between summer extreme precipitation events exceeding 20 mm (R20mm) in China and the 11-year sunspot number (SSN) cycle from 1951 to 2018. Results showed that the first mode of June–July R20mm, a “south-drought and north-flooding (SDNF)” distribution, exhibited a significant correlation with the SSN cycle (p = 0.02). The fundamental driver is likely the pronounced periodic response of stratospheric ozone to solar forcing. During summer of the high-solar-activity years (HSY), there is a notable increase in ozone concentration and high temperatures in the stratosphere, particularly in the Southern Hemisphere. This phenomenon leads to a layer of anomalous temperature inversion, suppressing convection at the subtropics. This induced downward anomalous airflow toward the north stimulates convective activity in the equatorial region and generates northward wave activities. These wave activities produce rising and sinking anomalies at different latitudes in the Northern Hemisphere troposphere, finally causing the “SDNF” pattern in China.

Changes in winter snow cover in the Northern Hemisphere (NH) could have a profound impact on mid-latitude weather. Previous studies have focused on the role of regional, e.g. Eurasian or Tibetan, snow cover in summer precipitation anomaly, without considering the synergistic impacts of hemispheric wintertime snow. In this study, we find that the dominant pattern of the NH winter overall snow cover anomaly with a synergistic impact, has a stronger cross-seasonal association with the China’s summer rainfall pattern than regional snow cover anomaly. We summarize three synergistic impact paths of regional snow cover. One is extratropical path, that is the westerlies are affected by less snow in Europe through the snow-soil moisture-atmospheric feedback, and the influence is strengthened by less snow in Mongolia through enhanced temperature anomalies. The second is subtropical path, that is the meridional thermal difference anomaly caused by more snow anomaly on the Tibetan Plateau is strengthened by less Mongolian snow and then impacts the behavior of the upper-tropospheric westerly jet. Third, concurrently, more North American snow enhances the above two synergistic influence paths via the Circumglobal Teleconnection pattern. These three paths can be simultaneously reflected in the associated circulations of the first mode of NH snow cover. Their synergistic impacts eventually influence the meridional East Asia-Pacific pattern circulation anomalies in summer, leading to increased precipitation in the Yangtze River Basin. The cross-seasonal influences of synergistic effects of multiple regional snow anomalies can be identified by CMIP6 multi-model ensembles, particularly the impact of European snow cover.

There is a growing debate regarding the influence of solar activity on climate change as the solar forcing signal on decadal/multidecadal timescales is not robust in long-term reconstructed climate data or numerical simulations. However, solar forcing could be amplified by ocean–atmosphere coupling in sensitive regions, including the North Atlantic Ocean (N.A.). This study assessed the influence of varied total solar irradiance (TSI) due to the effects of solar activity on Atlantic Meridional Overturning Circulation (AMOC) based on an Earth System model with intermediate complexity (PLASIM-GENIE). Three groups of experiments with different TSI series; i.e., constant (NS), decadal varied (DS), and reconstructed whole (AS) for 1610–2000, were conducted and the AMOC response was investigated. The results showed that the internal forcing of the climate system led to quasi-35-year and quasi-65-year AMOC cycles and a significant and stable negative correlation between TSI and AMOC on a multidecadal timescale. The period was significantly extended due to solar forcing. The declining AMOC trend occurred in simulations after 1800. Thus, solar forcing contributed to a weakening AMOC at a rate of 0.41 Sv per century. The decadal variation in TSI was the main contributor to this decline due to solar forcing.

Previous studies indicated that the North Tropical Atlantic (NTA) SST can serve as a precursor for the El Niño–Southern Oscillation (ENSO) predictability and the connection of NTA-ENSO is modulated by the mid-high latitude atmospheric variability. Despite significant solar footprints being found in the North Atlantic and tropical Pacific separately, their role in the two basins’ connection is still missing. In this study, we systematically examined this point by using observational/reanalysis datasets and outputs of a pair of sensitivity experiments with and without solar forcings (SOL and NOSOL). In observations, DJF-mean NAO-like SLP anomalies have a linear covariation with the subsequent JJA-mean El Niño Modoki-like SST anomalies in the tropical Pacific in the following 1 year. This observed SLP-SST covariation shows up in the high solar activity (HS) subset and disappears in the low solar activity (LS) subset. In the HS years, positive NAO-like SLP anomalies are produced by the stronger solar-UV radiation through a “top-down” mechanism. These atmospheric anomalies can enhance the influence of the NTA on the tropical Pacific SST by triggering significant and more persistent subtropical teleconnections. Here we proposed an indirect possible mechanism that the solar-UV forcing can modulate the tropical Pacific SST variability via its impacts on the atmospheric anomalies over the North Atlantic region. However, based on the same analysis method, we found a different coupled mode of the SLP and SST anomalies in the modeling outputs. The SLP anomalies in the North Atlantic, with a triple pattern (negative SLP anomalies in the Pole and the NTA, positive SLP anomalies in the mid-latitude), have “lead-lag” covariations with the Eastern Pacific El Niño-like SST anomalies in both the SOL and NOSOL. Although the impact of the solar activity is found in the North Atlantic and the tropical Pacific respectively in the SOL, no solar effect is involved in the simulated SLP-SST coupled mode.

The effect of solar activity on the regional temperature in winter has been widely discussed. However, whether the summer temperature of land in the northern hemisphere is sensitive to solar activity remains to be further investigated. In this study, the empirical orthogonal function (EOF) analysis, spectrum analysis, and correlation analysis are employed to reveal the possible link between the summer temperature distribution over Eurasian land (0–180°E and 20°N−80°N) and solar activity. The results show that the corresponding time series of the second pattern significantly exhibits an 11-year solar periodicity. Its tripolar temperature distribution is similar to the correlation maps between the temperature and sunspot number (SSN). Particularly, Central Asia (50°E−90°E and 30°N−60°N) is the key response region over Eurasia. The temperature of Central Asia shows a weak but significant negative correlation with SSN. Further analysis of atmospheric circulation indicates that the solar-induced cyclonic and negative geopotential height anomalies in Central Asia weaken the high-pressure ridge on the southwest side and strengthen northwesterly winds. At the same time, with the increase in the cloud cover and the decrease of shortwave radiation, the temperature is lowered. Due to the impact of solar activity, the upper atmosphere over Eurasia forms a wave train-like structure, resulting in a tripolar temperature distribution pattern. On the other hand, the 21-year sliding correlation results suggest that the connection between solar activity and the temperature in Central Asia was strong and decadal stable until 1980. Whereas the temperature and atmospheric circulations in high latitudes become more sensitive to solar activity after 1980. Anyway, solar activity still can be considered a non-negligible factor in the prediction of the summer temperature in Eurasia.

Abstract Wind energy is a fluctuating source for power systems, which poses challenges to grid planning for the wind power industry. To improve the short-term wind forecasts at turbine height, the bias correction approach Kalman filter (KF) is applied to 72-h wind speed forecasts from the WRF model in Zhangbei wind farm for a period over two years. The KF approach shows a remarkable ability in improving the raw forecasts by decreasing the root-mean-square error by 16% from 3.58 to 3.01 m s−1, the mean absolute error by 14% from 2.71 to 2.34 m s−1, the bias from 0.22 to − 0.19 m s−1, and improving the correlation from 0.58 to 0.66. The KF significantly reduces random errors of the model, showing the capability to deal with the forecast errors associated with physical processes which cannot be accurately handled by the numerical model. In addition, the improvement of the bias correction is larger for wind speeds sensitive to wind power generation. So the KF approach is suitable for short-term wind power prediction.

With global warming, the probability of summer compound hot and dry extreme (CHDE) days, which are higher risk compared with single-factor extreme events, increases in some regions. However, there have been few studies on the winter precursor signals of such events. In this study, we found that summer CHDEs have generally increased in the last 20 years, with the increases in the middle and lower reaches of the Yangtze River region and Southwest China being more than double those in other regions of China. The dominant mode of summer CHDEs in China is characterized by more hot–dry days in the Yangtze–Huaihe River Basin (YHRB). Importantly, we found that there is an obvious cross-seasonal relationship between the first mode of winter snow cover in the Northern Hemisphere (NH) and summer CHDEs in China. When the mode of winter snow cover in the NH is in a positive phase with a negative-phase Arctic Oscillation (AO), i.e., more snow cover in Europe, Northeast China, and the northern United States, and less snow cover in central Asia and the midlatitudes in winter, more CHDEs in China in the following summer. Compared with the signals from the AO, these signals from winter snow can be better stored and transmitted into summer through the snow, soil and ocean, inducing a northward shift of the upper-level westerly jet and strengthening of South Asia high. Through the strong dynamic forcing of negative vorticity advection with the change of westerly jet, the subsidence movement in the western Pacific subtropical high (WPSH) region is strengthened, resulting in the stable maintenance of the WPSH in the YHRB. Under the synergy of a remote mid- and high-latitude wave train in summer, which also relates closely to winter snow cover, more CHDEs ultimately occur in the YHRB of China.

The Lancang–Mekong River basin (LMRB) is under increasing threat from global warming. In this paper, the projection of future climate in the LMRB is explored by focusing on the temperature change and extreme temperature events. First, the authors evaluate the bias of temperature simulated by the Weather Research and Forecasting model. Then, correction is made for the simulation by comparing with observation based on the non-parametric quantile mapping using robust empirical quantiles (RQUANT) method. Furthermore, using the corrected model results, the future climate projections of temperature and extreme temperature events in this basin during 2016–35, 2046–65, and 2080–99 are analyzed. The study shows that RQUANT can effectively reduce the bias of simulation results. After correction, the simulation can capture the spatial features and trends of mean temperature over the LMRB, as well as the extreme temperature events. Besides, it can reproduce the spatial and temporal distributions of the major modes. In the future, the temperature will keep increasing, and the warming in the southern basin will be more intense in the wet season than the dry season. The number of extreme high-temperature days exhibits an increasing trend, while the number of extreme low-temperature days shows a decreasing trend. Based on empirical orthogonal function analysis, the dominant feature of temperature over this basin shows a consistent change. The second mode shows a seesaw pattern.

The atmospheric heat source over the Qinghai–Tibetan Plateau (QTP) in spring has an important impact on the climate of the surrounding regions. However, there have been few systematic studies of the dominant mode of the heat source and the cross-seasonal connections with the preceding winter and following summer. Using a distinct empirical orthogonal function (DEOF) decomposition method, we obtained the leading mode of the spring heat source over the QTP and the surrounding regions and analyzed its precursors in the previous winter and lagging effects in the following summer. Our results show that the first mode (DEOF1) was characterized by a warm plateau and cold surrounding regions. The positive phase was significantly associated with the warm Arctic–cold Siberia (WACS) pattern (r = 0.39, p = .01) and the La Niña-like SST anomaly in the Pacific in the preceding winter and the following East Asian subtropical summer monsoon (r = –0.44, p = .01), resulting in a widespread drought in China during the following summer. The cold anomaly in Siberia and the warm anomaly at mid-to low latitudes in winter associated with the WACS pattern coincide with the DEOF1 mode of the heat source over the QTP and its surroundings through change of meridional temperature gradient and wave-flow interactions. A mid-latitude wave train excited by the WACS and the thermal difference in the meridional direction of the spring DEOF1 mode caused high-pressure anomalies over the QTP and the mid-latitude region of East Asia, influencing central and eastern China. This anomaly was not conducive to the northward advancement of the East Asian summer monsoon, resulting in drought in most of China in spring and summer. The cross-seasonal relationship between the main mode of the spring heat source on the QTP and the preceding winter WACS pattern and the following East Asian summer monsoon can be used as a reference in climate prediction studies.

Solar activity is one of the main external forcing factors driving the Earth’s climate system to change. The snow cover over the Tibetan Plateau is an important physical factor affecting the East Asian climate. At present, insufficient research on the connection between solar activity and snow cover over the Tibetan Plateau has been carried out. Using Solar Radio Flux (SRF), Solar Sunspot Number (SSN), and Total Solar Irradiance (TSI) data, this paper calculated the correlation coefficients with snow indices over the Tibetan Plateau, such as winter and spring snow depth (WSD/SSD) and snow day number (WSDN/SSDN). These snow indices are obtained from the daily gauge snow data in the Tibetan Plateau. Through correlation analyses, it is found that there are significant synchronous or lag correlations between snow indices and solar parameters on multi-time scales. In particular, the Spring Snow Day Number (SSDN) is of significant synchronous or lag correlation with SRF, SSN, and TSI on multi-time scales. It is further found that SSDN over the Tibetan Plateau has more stable positive correlations with SRF by using the 21-year running mean and cross spectrum analyses. Therefore, SSDN can be ascertained to be the most sensitive snow index to the solar activity compared with other snow indices. Moreover, its influence on summer precipitation of China is strongly regulated by solar activity. In high solar activity years (HSAY), the significant correlated area of summer precipitation in China to SSDN is located further north than that in low solar activity years (LSAY). Such impact by solar activity is also remarkable after excluding the impact of ENSO (i.e., El Niño–Southern Oscillation) events. These results provide support for the application of snow indices in summer rainfall prediction in China.

As two important components of the Asian summer monsoon system, the intensities of South Asian High (SAH) and Somali jet (SMJ) in summer exhibit both interannual and decadal variabilities. On the interdecadal timescale, the temporal evolution of the SAH intensity is in phase with that of the SMJ intensity. By comparison, we find that both of them evolve synchronously with the Atlantic Multidecadal Oscillation (AMO), with AMO cold/warm phases corresponding to the weakening/strengthening of SAH and SMJ. Further diagnoses indicate that the interdecadal variabilities of the SAH and SMJ intensities in summer may be modulated by the AMO phase. Mechanistically, this modulation appears to be achieved via an interdecadal Silk Road pattern (SRP)-like wave train along the Asian westerly jet and Matsuno–Gill tropical atmospheric response. The cold SST anomaly over extratropical North Atlantic related to the AMO firstly induces an anomalous high over Western Europe and produces a well-organized wave train between 30°N and 60°N. The anomalous Iranian Plateau low along with the wave train path leads to a weakened SAH. Besides, the AMO-related cold SST anomalies over tropical North Atlantic cool the tropical tropospheric atmosphere through the moist adjustment process and produce a Matsuno–Gill-like atmospheric response covering the tropical Indian Ocean. Due to the Matsuno–Gill response, subsidence motion anomalies over the central tropical Indian Ocean corresponding to a result in increased lower-level divergence and upper-level convergence are excited over the tropical Indian Ocean. Finally, the tropical Indian Ocean divergence in the lower troposphere leads to the weakened summer SMJ, and the tropical Indian Ocean convergence in the upper troposphere results in the decrease and northward displacement of SAH in summer.

Both the El Niño-Southern Oscillation (ENSO) and the 11-years solar cycle had been identified as important factors that may influence the wintertime southern China precipitation (SCP). However, the interactions between these two factors remain less noticed. In this study, the combined effects of the ENSO and the solar activity on mid-winter (January) SCP are investigated using observational and reanalysis data. Results suggest that both the ENSO and the solar activity are positively correlated with the SCP, although exhibiting distinct spatial patterns. Under different combinations of the ENSO and solar phases, the SCP anomalies show superposition of these two factors to some extent. Generally, the ENSO-related SCP anomalies tend to be enhanced (disturbed) when the ENSO and the solar activity are in-phase (out-of-phase). But this solar modulation effect appears more clear and significant under cold ENSO (cENSO) phase rather than under warm ENSO (wENSO) phase. Further analysis suggests, during the wENSO phase, solar influences on the Northern Hemisphere circulation are generally weak with little significance. In contrast, during the cENSO phase, the solar effect resembles the positive phase of the Arctic Oscillation but with an evident zonal asymmetric component. Its manifestation over the Asia-Pacific domain features by negative geopotential height anomaly over the West Asia and positive geopotential height anomaly over the East Asian coast, a pattern that is favorable for the SCP, thus causing a significant solar modulation on the cENSO-related precipitation anomalies. Further, the potential physical causes of solar effects on circulation are also discussed. Our results highlight the importance of considering solar cycle phase when ENSO is used to predict the East Asian winter climate.

The impacts of the western North Pacific (WNP) tropical cyclone (TC) on East and Southeast Asian inland regions are analyzed. Here, based on a stringent TC selecting criterion, robust increase of TC-related inland impacts between 1979 and 2016 over East and Southeast Asian regions have been detected. The storms sustained for 2–9 h longer and penetrated 30–190 km further inland, as revealed from different best track datasets. The most significant increase of the TC inland impacts occurred over Hanoi and South China. The physical mechanism that affects TC-related inland impacts is shortly discussed. First, the increasing TC inland impacts just occur in the WNP region, but it is not a global effect. Second, besides the significant WNP warming effects on the enhanced TC landfall intensity and TC inland impacts, it is suggested that the weakening of the upper-level Asian Pacific teleconnection pattern since 1970s may also play an important role, which may reduce the climatic 200 hPa anti-cyclonic wind flows over the Asian region, weakening the wind shear near the Philippine Sea, and may eventually intensify the TC intensity when the TCs across the basin. Moreover, the TC inland impacts in the warming future are projected based on a high-resolution (20 km) global model according to the Representative Concentration Pathway 8.5 scenario. By the end of the 21st century, TC mean landfall intensity will increase by 2 m/s (6%). The stronger storms will sustain 4.9 h (56%) longer and penetrate 92.4 km (50%) farther inland, thereby almost doubling the destructive power delivered to Asian inland regions. More inland locations will therefore be exposed to severe storm–related hazards in the future due to warmer climate. Long-term planning to enhance disaster preparedness and resilience in these regions is called for.

Using observational data of soil moisture from the third Tibetan Plateau Experiment for atmospheric science (TIPEX III), the seasonal and diurnal variations characteristics of soil moisture at different depths of 5–160 cm from seven stations were analyzed, with emphasis on the comparative analysis of the differences of soil moisture between different sites and the differences of the synergistic relationship between soil moisture and temperature. The soil moisture was wet in the southeast and dry in the northwest. The studied sites were Lhari, Biru, Nyainrong, Amdo, Nagqu, Baingoin and Seng-ge Kambab in descending order, according to the soil moisture. The seasonal variation of soil moisture at the different sites showed a significant three-peak structure, which was more obvious in the shallow layer than in the deep layer. The first peak occurred from March to May, which was mainly due to the soil thawing in spring. The other two peaks corresponded to the two rainy seasons in the plateau. Soil moisture was the greatest during this rainy period. The diurnal variations of soil moisture and temperature in Amdo, Nagqu, Nyainrong and Baingoin showed a significant positive correlation in the four seasons. The soil moisture and temperature in Lhari and Biru were significantly positively correlated in winter and spring but negatively correlated in summer and autumn. The profiles of the soil moisture with depth varied greatly at different stations in different seasons. The distribution of soil water content at each observational site did not increase or decrease with depth but showed a certain high aquifer, which might be related to the types of the underlying surface and physical properties of soil. During the summer monsoon period, soil moisture in the shallow layer of 5–10 cm was higher at all observational sites. The spatial distribution of soil moisture in the plateau was more heterogeneous than that in the plain area, and only in the central part of the Tibetan Plateau, the soil moisture varied greatly from site to site. This also indicated that it was unreasonable to only use the soil moisture of several stations to represent the overall soil moisture of the region. The results provided a multi-angle observational basis for the validation of satellite data and parameterization of the numerical model of soil moisture over the Tibetan Plateau.

Using global ocean vertical temperature anomaly data, we identified that a significant response of the sea temperature anomaly (STA) to the solar radio flux (SRF) exists. We found that the STA exhibited a significant correlation with Asian summer and winter precipitation, among which the response from the Qinghai–Tibet Plateau (the QTP) was particularly noticeable. Based on NCEP/NCAR reanalysis data, the latent heat flux (LHF) anomaly, which plays a key role in winter precipitation in China, especially over the QTP, showed a significant response to the SRF in the Pacific. The results demonstrated the bottom-up mechanism of impact of solar activity (SA) on the plateau snow through sea–air interaction. Meanwhile, a top-down mechanism was also present. When the SRF was high, the stratospheric temperature in the low and mid-latitudes increased and the temperature gradient pointed to the pole to strengthen the westerly wind in the mid-latitudes. The EP flux showed that atmospheric long waves in the high altitudes propagated downward from the stratosphere to the troposphere. A westerly (easterly) wind anomaly occurred in the south (north) of the QTP at 500 hPa and the snowfall rate over the QTP tended to increase. When the SRF was low, the situation was the opposite, and the snowfall rate tended to decrease. The model results confirmed that when total solar irradiance (TSI) became stronger (weaker), both of the solar radiation fluxes at the top of the atmosphere and the surface temperature over the QTP increased (decreased), the vertical updraft intensified (weakened), and the snowfall rate tended to increase (decrease) accordingly. These conclusions are helpful to deepen the understanding of SA’s influence on the snow cover over the QTP.

Abstract The Tibetan Plateau is regarded as the Earth's Third Pole, which is the source region of several major rivers that impact more 20% the world population. This high‐altitude region is reported to have been undergoing much greater rate of weather changes under global warming, but the existing reanalysis products are inadequate for depicting the state of the atmosphere, particularly with regard to the amount of precipitation and its diurnal cycle. An ensemble Kalman filter (EnKF) data assimilation system based on the limited‐area Weather Research and Forecasting (WRF) model was evaluated for use in developing a regional reanalysis over the Tibetan Plateau and the surrounding regions. A 3‐month prototype reanalysis over the summer months (June−August) of 2015 using WRF‐EnKF at a 30‐km grid spacing to assimilate nonradiance observations from the Global Telecommunications System was developed and evaluated against independent sounding and satellite observations in comparison to the ERA‐Interim and fifth European Centre for Medium‐Range Weather Forecasts Reanalysis (ERA5) global reanalysis. Results showed that both the posterior analysis and the subsequent 6‐ to 12‐hr WRF forecasts of the prototype regional reanalysis compared favorably with independent sounding observations, satellite‐based precipitation versus those from ERA‐Interim and ERA5 during the same period. In particular, the prototype regional reanalysis had clear advantages over the global reanalyses of ERA‐Interim and ERA5 in the analysis accuracy of atmospheric humidity, as well as in the subsequent downscale‐simulated precipitation intensity, spatial distribution, diurnal evolution, and extreme occurrence.

Extreme precipitation events, which have intensified with global warming, will have a pernicious influence on society. It would be desirable to understand how they will evolve in the future as global warming becomes more serious with time. Thus, the primary objective of this study is to provide a comprehensive understanding of the changing characteristics of the precipitation extremes in the 21st century over Shaanxi Province, a climate-sensitive and environmentally fragile area located in the east of northwestern China, based on a consecutive simulation of the 21st century conducted by the regional climate model RegCM4 forced by the global climate model HadGEM2-ES at high resolution under middle emission scenario of the Representative Concentration Pathway 4.5 (RCP4.5). Basic validation of the model performance was carried out, and six extreme precipitation indices (EPIs) were used to assess the intensity and frequency of the extreme precipitation events over Shaanxi Province. The results show that RegCM4 reproduces the observed characteristics of extreme precipitation events over Shaanxi Province well. Overall for the domain, the EPIs excluding consecutive dry days (CDD) have a growing tendency during 1980–2098 although they exhibit spatial variability over Shaanxi Province. Some areas in the arid northern Shaanxi may have more heavy rainfalls by the middle of the 21st century but less wet extreme events by the end of the 21st century. And the humid central and southern regions would suffer more precipitation-related natural hazards in the future.