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With the development of refined numerical forecasts, problems such as score distortion due to the division of precipitation thresholds in both traditional and improved scoring methods for precipitation forecasts and the increasing subjective risk arising from the scale setting of the neighborhood spatial verification method have become increasingly prominent. To address these issues, a general comprehensive evaluation method (GCEM) is developed for cross-scale precipitation forecasts by directly analyzing the proximity of precipitation forecasts and observations in this study. In addition to the core indicator of the precipitation accuracy score (PAS), the GCEM system also includes score indices for insufficient precipitation forecasts, excessive precipitation forecasts, precipitation forecast biases, and clear/rainy forecasts. The PAS does not distinguish the magnitude of precipitation and does not delimit the area of influence; it constitutes a fair scoring formula with objective performance and can be suitable for evaluating rainfall events such as general and extreme precipitation. The PAS can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts, enabling the quantitative evaluation of the comprehensive capability of various refined precipitation forecasting products. Based on the GCEM, comparative experiments between the PAS and threat score (TS) are conducted for two typical precipitation weather processes. The results show that relative to the TS, the PAS better aligns with subjective expectations, indicating that the PAS is more reasonable than the TS. In the case of an extreme-precipitation event in Henan, China, two high-resolution models were evaluated using the PAS, TS, and fraction skill score (FSS), verifying the evaluation ability of PAS scoring for predicting extreme-precipitation events. In addition, other indices of the GCEM are utilized to analyze the range and extent of both insufficient and excessive forecasts of precipitation, as well as the precipitation forecasting ability for different weather processes. These indices not only provide overall scores similar to those of the TS for individual cases but also support two-dimensional score distribution plots which can comprehensively reflect the performance and characteristics of precipitation forecasts. Both theoretical and practical applications demonstrate that the GCEM exhibits distinct advantages and potential promotion and application value compared to the various mainstream precipitation forecast verification methods. [ABSTRACT FROM AUTHOR]

The surface solar irradiance (SSI) is crucial for the land‐atmosphere processes and remarkably affected by the topography over the rugged areas. However, the Coupled Model Intercomparison Project Phase 6 (CMIP6) HighResMIP models adopting the parallel‐plane radiative scheme without considering the sub‐grid terrain solar radiative effects (3DSTSRE) overestimate the SSI in the rugged areas and the overestimation increases with the sub‐grid terrain complexity. To reduce the biases of the SSI simulations, this study offline corrects the SSI simulations of CMIP6 HighResMIP models by a 3DSTSRE scheme. Results show that the SSI biases produced by the HighResMIP models in the rugged regions can be significantly reduced by adopting the 3DSTSRE offline correction, and the improvements increase with the sub‐grid terrain complexity, indicating that considering the 3DSTSRE in the climate models to improve the SSI simulations over rugged areas is necessary. Plain Language Summary: The surface incident solar radiation greatly affected by terrains plays important roles in various processes between the land and atmosphere. However, the Coupled Model Intercomparison Project Phase 6 (CMIP6) HighResMIP models without considering the 3D sub‐grid terrain solar radiative effect (3DSTSRE) largely overestimate the surface incident solar radiation over the rugged areas. In this study, adopting a 3DSTSRE scheme to offline correct the surface incident solar radiation simulations from the CMIP6 HighResMIP models can clearly reduce the biases over the rugged areas, and the improvements increase with the sub‐grid terrain complexity, implying that the 3DSTSRE should be considered in the climate models to improve the surface incident solar radiation simulation over the rugged areas. Key Points: The biases of surface solar irradiance (SSI) simulated by the CMIP6 HighResMIP models increase with the sub‐grid terrain complexityThe biases of simulated SSI over rugged areas can be clearly reduced by the 3DSTSRE offline correctionThe 3DSTSRE should be considered in the climate models to improve the SSI simulation over rugged areas [ABSTRACT FROM AUTHOR]

In this study, a process‐based lake model is used to investigate the influence of climate change on the thermodynamics of 30 large lakes over Tibetan Plateau (TP). The lake model was driven by the atmospheric forcing derived from the bias‐corrected projections of three global climate models in the twenty‐first century under three Shared Socioeconomic Pathways (SSPs). The hindcasts during 2000–2014 can reasonably capture the seasonality and magnitude of satellite retrieved lake surface temperature (LST). Future projections during 2015–2100 suggest a widespread increased LST, declined ice cover, and prolonged stratification, with the severity of changes in line with the climate driver shifts under different SSPs. Under the scenario with the highest level of anthropogenic radiative forcing (SSP5‐8.5), the end‐of‐century (2086–2100) changes of LST, ice thickness, and stratification duration averaged across all studied lakes reach 4.90°C, −0.43 m, and 65.46 days, respectively. Note that the positive ice‐albedo feedback can cause excess lake warming by accelerating ice break‐up (30.07 days earlier) and stratification onset (46.83 days earlier). By the end of this century, more frequent, multi‐seasonal thermal extremes are anticipated to push nearly half of the studied lakes into a permanent heatwave state. Together with the remarkable LST increase and winter ice loss, the lakes will mix less frequently and may shift from a dimictic to warm monomict mixing regime. Hopefully, the irreversible thermal changes can be avoided if the anthropogenic radiative forcing is controlled within the envelope outlined by the stringent climate mitigation scenario SSP1‐2.6. Plain Language Summary: Lake thermodynamics play a fundamental role in controlling a wide range of physical and biogeochemical processes within lakes, for example, evaporation, nutrients and dissolved gases cycling, zooplankton and phytoplankton proliferation. This study uses lake numerical modeling to understand how climate change will affect the thermodynamics of 30 large lakes over TP, examining simulations throughout the twenty‐first century under three SSPs. From 2000 to 2014 to 2086–2100, LST increase, ice loss, and stratification prolongation are anticipated across all studied lakes. These changes are more severe under the scenario with higher levels of climate driver shifts. Under the worst scenario SSP5‐8.5, the above end‐of‐century changes reach 4.90°C, −0.43 m, and 65.46 days, respectively. Additionally, by 2100, nearly half of the studied lakes will be in a constant state of "heatwave", meaning the water will be unusually warm all the time. The substantial lake warming and ice loss further cause the lakes to mix less frequently and risk shifts from a dimictic to warm monomict mixing regime. On a hopeful note, the thermal changes can possibly be controlled within the natural envelope if we adhere to the stringent climate mitigation scenario SSP1‐2.6. Key Points: Lake numerical modeling gains insights on the large‐lake thermal response to a changing climate over TP during the twenty‐first centuryResults from the worst scenario project substantial end‐of‐century changes of LST, thermal extreme, ice, stratification, and mixing regimeOut‐of‐control thermal response can be avoided by adhering to the stringent climate mitigation scenario [ABSTRACT FROM AUTHOR]

Rugged topography considerably regulates the surface downwelling long‐wave radiation (SDLR) flux and further affects the surface radiation and energy balances. The three dimensional sub‐grid terrain long‐wave radiative effect (3DSTLRE) is absent in most current numerical models, which usually adopt plane‐parallel schemes to simulate the SDLR flux. This study has developed a clear‐sky 3DSTLRE parameterization scheme based on the isotropic assumption of SDLR at rugged terrains and systematically evaluated its ability over the Tibetan Plateau (TP). Results show that the 3DSTLRE scheme achieves good and stable performance regardless of the horizontal resolution, time of the year, and sub‐grid terrain complexity. At different model horizontal resolutions ranging from 0.025° to 0.8°, the normalized mean absolute errors (NMAE) of the daily SDLR flux simulated by the clear‐sky 3DSTLRE scheme over most of TP are less than 0.9%, and the NMAE of the daily SDLR flux produced by the clear‐sky 3DSTLRE scheme regionally averaged over the grids with different sub‐grid terrain complexity are less than 0.25% in different months. Neglecting the 3DSTLRE in the plane‐parallel schemes may lead to clearly underestimated SDLR flux over the rugged areas, and the underestimation increases with the horizontal resolution and sub‐grid terrain complexity. At different model horizontal resolutions, the mean underestimation of the clear‐sky daily SDLR flux simulated by the plane‐parallel scheme over most of TP ranges from 5 to 20 W · m−2 with a relative underestimation of 4∼10%. The 3DSTLRE scheme can clearly reduce the biases of plane‐parallel scheme and exhibits wide application prospects in various numerical models. Plain Language Summary: Terrain greatly affects the surface downwelling long‐wave radiation (SDLR) flux and further modulates the surface radiation and energy balance and thereafter weather and climate at local to regional scales. But most current numerical models do not consider the 3‐dimensional sub‐grid terrain long‐wave radiative effect (3DSTLRE). This study has developed a clear‐sky 3DSTLRE parameterization scheme to describe the 3DSTLRE in the numerical models. Several experiments have been conducted to test the accuracy of the 3DSTLRE parameterization scheme in Tibetan Plateau and to indicate the necessity of considering the 3DSTLRE over the areas with rugged sub‐grid terrains in numerical models. Results show that the clear‐sky 3DSTLRE scheme can accurately calculate the SDLR flux at the model grids with different horizontal resolutions. The plane‐parallel schemes without considering the 3DSTLRE tend to clearly underestimate the SDLR flux over the rugged areas. The 3DSTLRE parameterization scheme can obviously reduce the biases of the SDLR flux simulated by the plane‐parallel scheme over the regions with complex terrain. Due to the advantages of a solid physical foundation, high accuracy, and strong flexibility, the 3DSTLRE scheme developed in this study exhibits wide application prospects in various numerical models. Key Points: A clear‐sky three‐dimensional sub‐grid terrain long‐wave radiative effect (3DSTLRE) parameterization scheme has been developedThe 3DSTLRE scheme shows high accuracy and is portable to the models with different horizontal resolutionsWithout considering the 3DSTLRE, the surface downwelling long‐wave radiation over the rugged terrain areas is underestimated [ABSTRACT FROM AUTHOR]

Existing land surface models still have large error in the simulation of surface albedo. At present, introducing the influence of meteorological factors into the albedo parameterization scheme is an effective way to improve the albedo simulation. However, the improvement of the vegetation canopy surface albedo parameterization scheme is still insufficient. Therefore, based on the radiation and meteorological observation data during 1 November 2015–30 April 2018 from a land‐atmosphere interaction observation tower in a typical secondary evergreen broadleaved forest in Southern China, this study firstly analyzed the influencing factors of canopy surface albedo. It was found that the solar elevation angle and air relative humidity are two key factors influencing the canopy surface albedo, and the impact of the solar elevation angle on canopy surface albedo is not exactly the same on diurnal and seasonal scales. Then, two new canopy surface albedo parameterization schemes of additive form and multiplicative form were proposed and introduced into CLM5 model for single point simulation. Results show that the adoption of newly developed canopy surface albedo parameterization schemes can improve the simulation of diurnal and seasonal variations of albedo and reduce the overestimation of the simulation of near‐infrared radiation albedo and visible radiation albedo in the CLM5 model, then significantly reduce the root mean square errors of reflected solar radiation and net radiation simulation. Plain Language Summary: Surface albedo is an important factor affecting the heat exchange between land and atmosphere, and is critical for weather forecasting and regional climate modeling. At present, even in some complex land surface models, the canopy surface albedo parameterization scheme only considers the variation of leaf and stem index and the cosine of the solar zenith angle over time but does not take into account the effect of meteorological factors. In this study, two newly developed canopy albedo schemes that take into account the effects of solar elevation angle and air relative humidity were developed, and then introduced into the CLM5 model for single point simulation. The results show that the new canopy albedo scheme can indeed improve the simulation skills of the reflected solar radiation. The results emphasize the important influence of meteorological factors on the surface albedo, and the findings may provide a base to further develop and improve the CLM5 model. Key Points: Two new canopy surface albedo schemes considering the influence of solar elevation angle and air relative humidity are proposedThe new canopy surface albedo schemes can reduce the canopy surface albedo of evergreen broad‐leaved forest overestimated by CLM5 model [ABSTRACT FROM AUTHOR]

With the development of refined numerical forecasts, the problems such as the score distortion due to the division of precipitation thresholds in both traditional and improved scoring methods for precipitation forecast and the increasing subjective risk arisen from the scale setting of the neighbourhood spatial verification method have become increasingly prominent. To solve this issue, a general comprehensive evaluation method (GCEM) has been developed for cross-scale precipitation forecasts by directly analysing the proximity of precipitation forecasts and observations in this study. In addition to the core element of the precipitation forecast accuracy score (PAS) index, the GCEM system also includes score indices for insufficient precipitation forecasts, excessive precipitation forecasts, precipitation forecast biases and clear/rainy forecasts. The PAS does not distinguish the magnitude of precipitation and delimit the area of influence, it constitutes a fair scoring formula with objective performance and can be suitable for evaluating the rainfall events such as general and extreme precipitation. The PAS can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts, enabling the quantitative evaluation of the comprehensive capability of various refined precipitation forecasting products. Based on the GCEM, comparative experiments between the PAS and TS are conducted for two typical precipitation weather processes. The results show that relative to TS, the PAS aligns with subjective expectations much more, indicating that the PAS is more reasonable than the TS. In addition, other indices of the GCEM are utilized to analyse the range and extent of both insufficient and excessive forecasts of precipitation, as well as the precipitation forecast ability in two weather processes. These indices not only provide overall scores for individual cases similar to the TS but also offer two-dimensional score distribution plots, which can comprehensively reflect the performance and characteristics of precipitation forecasts. Both theoretical and practical applications demonstrate that the GCEM exhibits distinct advantages and potential promotion and application value compared to the various mainstream precipitation forecast verification methods. [ABSTRACT FROM AUTHOR]

Downward solar radiation (DSR) and air temperature (Ta) have significant influences on the thermal state of frozen ground. These parameters are also important forcing terms for physically based land surface models (LSMs). However, the quantitative influences of inaccuracies in DSR and Ta products on simulated frozen ground temperatures remain unclear. In this study, three DSR products (CMFD‐SR, Tang‐SR, and GLDAS‐SR) and two Ta products (CMFD‐Ta and GLDAS‐Ta) were used to force an LSM model in an alpine watershed in Northwest China, to investigate the sensitivity of simulated ground temperatures to different DSR and Ta products. Compared to a control model (CTRL) forced by in situ observed DSR, ground temperatures simulated by the experimental model forced by GLDAS‐SR are obviously decreased because GLDAS‐SR is much lower than in situ observations. Instead, simulation results in models forced by CMFD‐SR and Tang‐SR are much closer to those of CTRL. Ta products led to significant errors in simulated ground temperatures. In conclusion, both CMFD‐SR and Tang‐SR could be used as good alternatives to in situ observed DSR for forcing a model, with acceptable errors in simulation results. However, more care need to be paid for models forced by Ta products instead of Ta observations, and conclusions should be carefully drawn. [ABSTRACT FROM AUTHOR]

We have successfully incorporated a 3‐dimensional sub‐grid terrain solar radiative effect (3D STSRE) parameterization scheme into a convection‐permitting Weather Research and Forecasting model (WRF_CPM) in this study. Impacts of 3D STSRE scheme on the ability of WRF_CPM in forecasting the precipitation in summer over the Tibetan Plateau (TP) and nearby regions with complex terrain have been systematically addressed by conducting experiments without and with the 3D STSRE scheme. Results show that the application of 3D STSRE scheme can obviously mitigate the overestimation of surface solar radiation (SSR) and rainfall over TP and nearby regions, especially over the areas with much more rugged terrain (i.e., southern TP) in the WRF_CPM without 3D STSRE scheme. Further mechanism analyses indicate that the decreased surface heating induced by the reduction of SSR reduces the intensity of the thermal‐low pressure over the TP, which leads to the diminished strength of southwesterly winds and thereafter the weaker convergence of moisture flux over the southern TP. Moreover, the weakened surface thermal forcing makes the local atmosphere more stable, suppressing the vertical water vapor transport and local convection. These effects greatly alleviate the overestimation of precipitation over the southern TP produced by the WRF_CPM without the 3D STSRE scheme. Plain Language Summary: The sub‐grid terrain solar radiative effect (STSRE) is crucial to land‐air interaction, especially over the regions with complicated terrain, such as the Tibetan Plateau (TP). While the plane‐parallel radiative scheme which neglects the STSRE on the surface solar radiation (SSR) is used in most current weather models. Inaccurate depiction of SSR would cause large biases in the surface temperature and precipitation forecast. In this study, a newly developed 3‐dimensional (3D) STSRE scheme with solid physical processes and accurate sub‐grid terrain features is introduced into a convection‐permitting Weather Research and Forecasting (WRF_CPM) model. Results indicate that the adoption of 3D STSRE scheme can reduce the overestimation of the SSR and precipitation over the TP. Findings of this work emphasize the importance of considering the STSRE in high‐resolution weather models and provide an effective way to improve the short‐range precipitation forecast over regions with complex terrain. Key Points: A 3D sub‐grid terrain solar radiative effect scheme has been applied in the Weather Research and Forecasting model and its impact on weather forecast has been studiedThe 3‐dimensional sub‐grid terrain solar radiative effect reduces the overestimation of surface solar radiation, leading to the thermal low over the Tibetan Plateau weakenedThe weakened thermal low together with the more stable atmosphere reduces the overestimation of precipitation forecast over Tibetan Plateau [ABSTRACT FROM AUTHOR]