The atmospheric motion is inherently nonlinear.The high-impact weather events that people concern are generally determined by small-and medium-scale systems overlaid on the large-scale circulation.The accumulation of ...The atmospheric motion is inherently nonlinear.The high-impact weather events that people concern are generally determined by small-and medium-scale systems overlaid on the large-scale circulation.The accumulation of seemingly minor computational errors can significantly impact the model’s predictive capabilities.When solving these equations,the flow field is commonly separated into basic flow and perturbation flow through the introduction of a reference state.This approach solves the problem of“small differences between large numbers”in terms such as the pressure gradient force(PGF)and improves the spatial discretization accuracy of the model.This paper first reviews the development of zero-dimensional(0D),one-dimensional(1D),two-dimensional(2D),three-dimensional(3D),and four-dimensional(4D)reference state deduction methods.Then,it details the implementation of these different dimensional reference state deduction methods within the context of the Global Regional Assimilation and Prediction System Global Forecast System(GRAPESGFS)model of China Meteorological Administration(CMA).Furthermore,the accuracy of the different dimensional reference states is tested through multiple benchmark tests.The results demonstrate that the high-dimensional reference state provides a closer approximation to the real atmosphere across various altitudes and latitudes,resulting in a more comprehensive and effective improvement in discretization accuracy.Finally,the paper offers suggestions on issues related to reference state deduction.展开更多
The definition of a reference state close to the realistic atmosphere in an atmospheric model is essential for deriving prognostic deviations and improving numerical accuracy.In this study,a new dynamical framework al...The definition of a reference state close to the realistic atmosphere in an atmospheric model is essential for deriving prognostic deviations and improving numerical accuracy.In this study,a new dynamical framework allowing easy switching between a one-dimensional(1D)and a three-dimensional(3D)time-independent reference state is developed for the semi-implicit semi-Lagrangian solver in a global non-hydrostatic atmospheric model on Yin–Yang grids.The 3D reference state is introduced with consideration of additional horizontal gradient terms of referencestate terms,which is different from the 1D reference state.It is characterized by reduced magnitude of deviations,more accurate pressure gradient force,as well as alleviated numerical noise.Four idealized benchmark tests and multiple full-physics real-case forecasts are carried out to assess the impact of the 3D and 1D reference states.The 3D reference state shows significant advantages in the simulation of atmospheric transport and wave propagation in the idealized experiments.In the real-case forecasts,batched forecasts from June to August 2021 show a comprehensive improvement in medium-range prediction by using the 3D reference state.The new scheme achieves an enhanced prediction skill for large-scale circulation and extends the effective forecast period by 0.8 days in the Northern Hemisphere.展开更多
In this paper, an analogue correction method of errors （ACE） based on a complicated atmospheric model is further developed and applied to numerical weather prediction （NWP）. The analysis shows that the ACE can eff...In this paper, an analogue correction method of errors （ACE） based on a complicated atmospheric model is further developed and applied to numerical weather prediction （NWP）. The analysis shows that the ACE can effectively reduce model errors by combining the statistical analogue method with the dynamical model together in order that the information of plenty of historical data is utilized in the current complicated NWP model, Furthermore, in the ACE, the differences of the similarities between different historical analogues and the current initial state are considered as the weights for estimating model errors. The results of daily, decad and monthly prediction experiments on a complicated T63 atmospheric model show that the performance of the ACE by correcting model errors based on the estimation of the errors of 4 historical analogue predictions is not only better than that of the scheme of only introducing the correction of the errors of every single analogue prediction, but is also better than that of the T63 model.展开更多
Headwater streams play a major role for provision of ecosystem services,e.g.drinking water.We investigated a high-altitude headwater catchment of the Kharaa River(including 411st-order rivers)to understand the impact ...Headwater streams play a major role for provision of ecosystem services,e.g.drinking water.We investigated a high-altitude headwater catchment of the Kharaa River(including 411st-order rivers)to understand the impact of land cover(especially forest cover),environment and human usage on runoff,chemical water quality and macroinvertebrate fauna in a river basin under discontinuous permafrost conditions in an arid,sparsely populated region of Mongolia.To verify our hypotheses that different landuses and environmental impacts in permafrost headwaters influence water quality,we investigated 105 sampling sites,37 of them at intermittent stream sections without water flow.Discharge was positively impacted by land cover types steppe,grassland and forest and negatively by shrubland,forest burnt by wild fires(indicating a reduction of permafrost)and slope.Water quality was affected by altitude,longitude and latitude,shrub growth and water temperature.Shannon diversity of macroinvertebrates was driven by water temperature,iron content of the water,flow velocity,and subbasin size(adjusted R^(2)=0.54).Sample plots clustered in three groups that differed in water chemistry,macroinvertebrate diversity,species composition and bio-indicators.Our study confirms that steppes and grasslands have a higher contribution to runoff than forests,forest cover has a positive impact on water quality,and diversity of macroinvertebrates is higher in sites with less nutrients and pollutants.The excellent ecological status of the upper reaches of the Kharaa is severely threatened by forest fires and human-induced climate change and urgently needs to be conserved.展开更多
Statistical energy functions are general models about atomic or residue-level interactions in biomolecules, derived from existing experimental data. They provide quantitative foundations for structural modeling as wel...Statistical energy functions are general models about atomic or residue-level interactions in biomolecules, derived from existing experimental data. They provide quantitative foundations for structural modeling as well as for structure-based protein sequence design. Statistical energy functions can be derived computationally either based on statistical distributions or based on variational assumptions. We present overviews on the theoretical assumptions underlying the various types of approaches. Theoretical considerations underlying important pragmatic choices are discussed.展开更多
基金Supported by the National Natural Science Foundation of China(42090032 and 42275168).
文摘The atmospheric motion is inherently nonlinear.The high-impact weather events that people concern are generally determined by small-and medium-scale systems overlaid on the large-scale circulation.The accumulation of seemingly minor computational errors can significantly impact the model’s predictive capabilities.When solving these equations,the flow field is commonly separated into basic flow and perturbation flow through the introduction of a reference state.This approach solves the problem of“small differences between large numbers”in terms such as the pressure gradient force(PGF)and improves the spatial discretization accuracy of the model.This paper first reviews the development of zero-dimensional(0D),one-dimensional(1D),two-dimensional(2D),three-dimensional(3D),and four-dimensional(4D)reference state deduction methods.Then,it details the implementation of these different dimensional reference state deduction methods within the context of the Global Regional Assimilation and Prediction System Global Forecast System(GRAPESGFS)model of China Meteorological Administration(CMA).Furthermore,the accuracy of the different dimensional reference states is tested through multiple benchmark tests.The results demonstrate that the high-dimensional reference state provides a closer approximation to the real atmosphere across various altitudes and latitudes,resulting in a more comprehensive and effective improvement in discretization accuracy.Finally,the paper offers suggestions on issues related to reference state deduction.
基金Supported by the National Natural Science Foundation of China(42375153,42075151,and 42205157).
文摘The definition of a reference state close to the realistic atmosphere in an atmospheric model is essential for deriving prognostic deviations and improving numerical accuracy.In this study,a new dynamical framework allowing easy switching between a one-dimensional(1D)and a three-dimensional(3D)time-independent reference state is developed for the semi-implicit semi-Lagrangian solver in a global non-hydrostatic atmospheric model on Yin–Yang grids.The 3D reference state is introduced with consideration of additional horizontal gradient terms of referencestate terms,which is different from the 1D reference state.It is characterized by reduced magnitude of deviations,more accurate pressure gradient force,as well as alleviated numerical noise.Four idealized benchmark tests and multiple full-physics real-case forecasts are carried out to assess the impact of the 3D and 1D reference states.The 3D reference state shows significant advantages in the simulation of atmospheric transport and wave propagation in the idealized experiments.In the real-case forecasts,batched forecasts from June to August 2021 show a comprehensive improvement in medium-range prediction by using the 3D reference state.The new scheme achieves an enhanced prediction skill for large-scale circulation and extends the effective forecast period by 0.8 days in the Northern Hemisphere.
基金Project supported by the National Natural Science Foundation of China （Grant Nos 40575036 and 40325015）.Acknowledgement The authors thank Drs Zhang Pei-Qun and Bao Ming very much for their valuable comments on the present paper.
文摘In this paper, an analogue correction method of errors （ACE） based on a complicated atmospheric model is further developed and applied to numerical weather prediction （NWP）. The analysis shows that the ACE can effectively reduce model errors by combining the statistical analogue method with the dynamical model together in order that the information of plenty of historical data is utilized in the current complicated NWP model, Furthermore, in the ACE, the differences of the similarities between different historical analogues and the current initial state are considered as the weights for estimating model errors. The results of daily, decad and monthly prediction experiments on a complicated T63 atmospheric model show that the performance of the ACE by correcting model errors based on the estimation of the errors of 4 historical analogue predictions is not only better than that of the scheme of only introducing the correction of the errors of every single analogue prediction, but is also better than that of the T63 model.
基金This research was financially supported by the German Federal Ministry for Economic Cooperation and Development(grant number:BMZ 81212690)and a‘Forschung vor Ort’grant for G.K.of the Max Weber-Program of the State of Bavaria.Special thanks are due to the Deutsche Gesellschaft für Internationale Zusammenarbeit(GIZ)GmbH,especially Klaus Schmidt-Corsitto,at that time Programme Director for“Biodiversity and Adaptation of Key Forest Ecosystems to Climate Change II Program”of GIZ and many employees of GIZ Mongolia.
文摘Headwater streams play a major role for provision of ecosystem services,e.g.drinking water.We investigated a high-altitude headwater catchment of the Kharaa River(including 411st-order rivers)to understand the impact of land cover(especially forest cover),environment and human usage on runoff,chemical water quality and macroinvertebrate fauna in a river basin under discontinuous permafrost conditions in an arid,sparsely populated region of Mongolia.To verify our hypotheses that different landuses and environmental impacts in permafrost headwaters influence water quality,we investigated 105 sampling sites,37 of them at intermittent stream sections without water flow.Discharge was positively impacted by land cover types steppe,grassland and forest and negatively by shrubland,forest burnt by wild fires(indicating a reduction of permafrost)and slope.Water quality was affected by altitude,longitude and latitude,shrub growth and water temperature.Shannon diversity of macroinvertebrates was driven by water temperature,iron content of the water,flow velocity,and subbasin size(adjusted R^(2)=0.54).Sample plots clustered in three groups that differed in water chemistry,macroinvertebrate diversity,species composition and bio-indicators.Our study confirms that steppes and grasslands have a higher contribution to runoff than forests,forest cover has a positive impact on water quality,and diversity of macroinvertebrates is higher in sites with less nutrients and pollutants.The excellent ecological status of the upper reaches of the Kharaa is severely threatened by forest fires and human-induced climate change and urgently needs to be conserved.
基金This work has been supported by National Natural Science Foundation of China （Grant Nos. 31370755 and 21173203） and the Chinese Ministry of Science and Technology （Grant No. 2012AA02A704）.
文摘Statistical energy functions are general models about atomic or residue-level interactions in biomolecules, derived from existing experimental data. They provide quantitative foundations for structural modeling as well as for structure-based protein sequence design. Statistical energy functions can be derived computationally either based on statistical distributions or based on variational assumptions. We present overviews on the theoretical assumptions underlying the various types of approaches. Theoretical considerations underlying important pragmatic choices are discussed.
