Hybrid Surface Mesh Adaptation for Climate Modeling

Solution-driven mesh adaptation is becoming quite popular for spatial error control in the numerical simulation of complex computational physics applications,such as climate modeling.Typically,spatial adaptation is achieved by element subdivision (h adaptation) with a primary goal of resolving the local length scales of interest.A sec- ond,less-popular method of spatial adaptivity is called'mesh motion'(r adaptation); the smooth repositioning of mesh node points aimed at resizing existing elements to capture the local length scales.This paper proposes an adaptation method based on a combination of both element subdivision and node point repositioning (rh adaptation). By combining these two methods using the notion of a mobility function,the proposed approach seeks to increase the flexibility and extensibility of mesh motion algorithms while providing a somewhat smoother transition between refined regions than is pro- duced by element subdivision alone.Further,in an attempt to support the requirements of a very general class of climate simulation applications,the proposed method is de- signed to accommodate unstructured,polygonal mesh topologies in addition to the most popular mesh types.

An Evaluation of RegCM3_CERES for Regional Climate Modeling in China

A 20-year simulation of regional climate over East Asia by the regional climate model RegCM3_CERES （Regional Climate Model version 3 coupled with the Crop Estimation through Resource and Environment Synthesis） was carried out and compared with observations and the original RegCM3 model to compre- hensively evaluate its performance in simulating the regional climate over continental China. The results showed that RegCM3_CERES reproduced the regional climate at a resolution of 60 km over China by using ERA40 data as the boundary conditions, albeit with some limitations. The model captured the basic char- acteristics of the East Asian circulation, the spatial distribution of mean precipitation and temperature, and the daily characteristics of precipitation and temperature. However, it underestimated both the intensity of the monsoon in the monsoonal area and precipitation in southern China, overestimated precipitation in northern China, and produced a systematic cold temperature bias over most of continental China. Despite these limitations, it was concluded that the RegCM3_CERES model is able to simulate the regional climate over continental China reasonably well.

ADVANCES IN REGIONAL CLIMATE MODELING SINCE 1990

Due to the close relationship between regional climate anomalies and social-economy and society development,climatologists worldwide paid great attention to the regional climate anomalies over a long period of time and the corresponding investigation of regional climate modeling has made great progresses.Since 1990 the regional climate simulations have made a more substantial achievement.This paper will focus on the reliability and uncertainties of regional climate modeling by global climate models,the advances on regional climate modeling in the world and the outlook of regional climate modeling.

Litterfall production modeling based on climatic variables and nutrient return from stands of Eucalyptus grandis Hill ex Maiden and Pinus taeda L.

Native grasslands in the Pampas of South America are increasingly being replaced by Eucalyptus and Pinus stands.The short rotation regimes used for the stands require high nutrient levels,with litterfall being a major source of nutrient return.To model the litterfall production using climatic variables and assess the nutrient return in 14-year-old Eucalyptus grandis and Pinus taeda stands,we measured litter production over 2 years,using conical litter traps,and monitored climatic variables.Mean temperature,accumulated precipitation,and mean maximum vapor pres-sure deficit at the seasonal level influenced litterfall produc-tion by E.grandis;seasonal accumulated precipitation and mean maximum temperature affected litterfall by P.taeda.The regression tree modeling based on these climatic vari-ables had great accuracy and predictive power for E.grandis(N=33;MAE(mean absolute error)=0.65;RMSE(root mean square error)=0.91;R^(2)=0.71)and P.taeda(N=108;MAE=1.50;RMSE=1.59;R^(2)=0.72).The nutrient return followed a similar pattern to litterfall deposition,as well as the order of importance of macronutrients(E.grandis:Ca>N>K>Mg>P;P.taeda:N>Ca>K>Mg>P)and micronutrients(E.grandis and P.taeda:Mn>Fe>Zn>Cu)in both species.This study constitutes a first approximation of factors that affect litterfall and nutrient return in these systems.

Modeling Surgery: A New Way Toward Understanding Earth Climate Variability

A new modeling concept, referred to as Modeling Surgery, has been recently developed at University of Wisconsin-Madison. It is specifically designed to diagnose coupled feedbacks between different climate components as well as climatic teleconnections within a specific component through systematically modifying the coupling configurations and teleconnective pathways. It thus provides a powerful means for identifying the causes and mechanisms of low-frequency variability in the Earth's climate system. In this paper, we will give a short review of our recent progress in this new area.

MODELING THE EFFECTS OF ANTHROPOGENIC SULFATE IN CLIMATE CHANGE BY USING A REGIONAL CLIMATE MODEL

Effects of aerosol with focus on the direct climate effect of anthropogenic sulfate aerosol under 2×CO2 condition were investigated by introducing aerosol distribution into the latest version of RegCM2. Two experiments, first run (2×CO2 + 0 aerosol concentration) and second run (2×CO2 + aerosol distribution), were made for 5 years respectively. Preliminary analysis shows that the direct climate effect of aerosol might cause a decrease of surface air temperature. The decrease might be larger in winter and in South China. The regional-averaged monthly precipitation might also decrease in most of the months due to the effect. The annual mean change of precipitation might be a decrease in East and an increase in West China. But the changes of both temperature and precipitation simulated were much smaller as compared to the greenhouse effect.

Toward a Learnable Climate Model in the Artificial Intelligence Era

Artificial intelligence(AI)models have significantly impacted various areas of the atmospheric sciences,reshaping our approach to climate-related challenges.Amid this AI-driven transformation,the foundational role of physics in climate science has occasionally been overlooked.Our perspective suggests that the future of climate modeling involves a synergistic partnership between AI and physics,rather than an“either/or”scenario.Scrutinizing controversies around current physical inconsistencies in large AI models,we stress the critical need for detailed dynamic diagnostics and physical constraints.Furthermore,we provide illustrative examples to guide future assessments and constraints for AI models.Regarding AI integration with numerical models,we argue that offline AI parameterization schemes may fall short of achieving global optimality,emphasizing the importance of constructing online schemes.Additionally,we highlight the significance of fostering a community culture and propose the OCR(Open,Comparable,Reproducible)principles.Through a better community culture and a deep integration of physics and AI,we contend that developing a learnable climate model,balancing AI and physics,is an achievable goal.

Numerical Experiments on the Spin-up Time for Seasonal-Scale Regional Climate Modeling

In this paper, the numerical experiments on the issue of spin-up time for seasonal-scale regional climate modeling were conducted with the newly Regional Climate Model （RegCM3）, in the case of the abnormal climate event during the summer of 1998 in China. To test the effect of spin-up time on the regional climate simulation results for such abnormal climate event, a total of 11 experiments were performed with different spin-up time from 10 days to 6 months, respectively. The simulation results show that, for the meteorological variables in the atmosphere, the model would be running in “climate mode” after 4-8-day spin-up time, then, it is independent of the spin-up time basically, and the simulation errors are mainly caused by the model＇ s failure in describing the atmospheric processes over the model domain. This verifies again that the regional climate modeling is indeed a lateral boundary condition problem as demonstrated by earlier research work. The simulated mean precipitation rate over each subregion is not sensitive to the spin-up time, but the precipitation scenario is somewhat different for the experiment with different spin-up time, which shows that there exists the uncertainty in the simulation to precipitation scenario, and such a uncertainty exhibits more over the areas where heavy rainfall happened. Generally, for monthly-scale precipitation simulation, a soin-uo time of 1 month is enough, whereas a spin-up time of 2 months is better for seasonal-scale one. Furthermore, the relationship between the precipitation simulation error and the advancement/withdrawal of East Asian summer monsoon was analyzed. It is found that the variability of correlation coefficient for precipitation is more significant over the areas where the summer monsoon is predominant. Therefore, the model＇s capability in reproducing precipitation features is related to the heavy rainfall processes associated with the advancement/withdrawal of East Asian summer monsoon, which suggests that it is necessary to develop a more reliable parameterization scheme to capture the convective precipitation of heavy rainfall pro- cesses associated with the activities of East Asian summer monsoon, so as to improve the climate modeling over China.

Modeling Aerosol Climate Effects over Monsoon Asia:A Collaborative Research Program

This paper describes the latest progress of a collaborative research program entitled ＂Modeling Aerosol Climate Effects over Monsoon Asia＂, under the Climate Sciences agreement between the U.S. Department of Energy and the Chinese Academy of Sciences（in the early 1980 s, Professor Duzheng YE played a critical role in leading and formalizing the agreement）. Here, the rationale and approach for pursuing the program, the participants, and research activities of recent years are first described, and then the highlights of the program＇s key findings and relevant scientific issues, as well as follow-up studies, are presented and discussed.

A High-Resolution Modeling Strategy to Assess Impacts of Climate Change for Mesoamerica and the Caribbean

Mesoamerica and the Caribbean are low-latitude regions at risk for the effects of climate change. Global climate models provide large-scale assessment of climate drivers, but, at a horizontal resolution of 100 km, cannot resolve the effects of topography and land use as they impact the local temperature and precipitation that are keys to climate impacts. We developed a robust dynamical downscaling strategy that used the WRF regional climate model to downscale at 4 - 12 km resolution GCM results. Model verification demonstrates the need for such resolution of topography in order to properly simulate temperatures. Precipitation is more difficult to evaluate, being highly variable in time and space. Overall, a 36 km resolution is inadequate;12 km appears reasonable, especially in regions of low topography, but the 4 km resolution provides the best match with observations. This represents a tradeoff between model resolution and the computational effort needed to make simulations. A key goal is to provide climate change specialists in each country with the information they need to evaluate possible future climate change impacts.

A CMIP6-based assessment of regional climate change in the Chinese Tianshan Mountains

Climate warming profoundly affects hydrological changes,agricultural production,and human society.Arid and semi-arid areas of China are currently displaying a marked trend of warming and wetting.The Chinese Tianshan Mountains(CTM)have a high climate sensitivity,rendering the region particularly vulnerable to the effects of climate warming.In this study,we used monthly average temperature and monthly precipitation data from the CN05.1 gridded dataset(1961-2014)and 24 global climate models(GCMs)of the Coupled Model Intercomparison Project Phase 6(CMIP6)to assess the applicability of the CMIP6 GCMs in the CTM at the regional scale.Based on this,we conducted a systematic review of the interannual trends,dry-wet transitions(based on the standardized precipitation index(SPI)),and spatial distribution patterns of climate change in the CTM during 1961-2014.We further projected future temperature and precipitation changes over three terms(near-term(2021-2040),mid-term(2041-2060),and long-term(2081-2100))relative to the historical period(1961-2014)under four shared socio-economic pathway(SSP)scenarios(i.e.,SSP1-2.6,SSP2-4.5,SSP3-7.0,and SSP5-8.5).It was found that the CTM had experienced significant warming and wetting from 1961 to 2014,and will also experience warming in the future(2021-2100).Substantial warming in 1997 was captured by both the CN05.1 derived from interpolating meteorological station data and the multi-model ensemble(MME)from the CMIP6 GCMs.The MME simulation results indicated an apparent wetting in 2008,which occurred later than the wetting observed from the CN05.1 in 1989.The GCMs generally underestimated spring temperature and overestimated both winter temperature and spring precipitation in the CTM.Warming and wetting are more rapid in the northern part of the CTM.By the end of the 21st century,all the four SSP scenarios project warmer and wetter conditions in the CTM with multiple dry-wet transitions.However,the rise in precipitation fails to counterbalance the drought induced by escalating temperature in the future,so the nature of the drought in the CTM will not change at all.Additionally,the projected summer precipitation shows negative correlation with the radiative forcing.This study holds practical implications for the awareness of climate change and subsequent research in the CTM.

Analysing the Potential Impact of Climate Change on the Hydrological Regime of the Upper Benue River Basin (North Cameroon)

In this study, we analyse the climate variability in the Upper Benue basin and assess its potential impact on the hydrology regime under two different greenhouse gas emission scenarios. The hydrological regime of the basin is more vulnerable to climate variability, especially precipitation and temperature. Observed hydroclimatic data (1950-2015) was analysed using a statistical approach. The potential impact of future climate change on the hydrological regime is quantified using the GR2M model and two climate models: HadGEM2-ES and MIROC5 from CMIP5 under RCP 4.5 and RCP 8.5 greenhouse gas emission scenarios. The main result shows that precipitation varies significantly according to the geographical location and time in the Upper Benue basin. The trend analysis of climatic parameters shows a decrease in annual average precipitation across the study area at a rate of -0.568 mm/year which represents about 37 mm/year over the time 1950-2015 compared to the 1961-1990 reference period. An increase of 0.7°C in mean temperature and 14% of PET are also observed according to the same reference period. The two climate models predict a warming of the basin of about 2°C for both RCP 4.5 and 8.5 scenarios and an increase in precipitation between 1% and 10% between 2015 and 2100. Similarly, the average annual flow is projected to increase by about +2% to +10% in the future for both RCP 4.5 and 8.5 scenarios between 2015 and 2100. Therefore, it is primordial to develop adaptation and mitigation measures to manage efficiently the availability of water resources.

Global Well-Posedness of the Fractional Tropical Climate Model

In this paper, we consider the Cauchy problem of 3-dimensional tropical climate model. This model reflects the interaction and coupling among the barotropic mode u, the first baroclinic mode v of the velocity and the temperature θ. The systems with fractional dissipation studied here may arise in the modeling of geophysical circumstances. Mathematically these systems allow simultaneous examination of a family of systems with various levels of regularization. The aim here is the global strong solution with the least dissipation. By energy estimate and delicate analysis, we prove the existence of global solution under three different cases: first, with the help of damping terms, the global strong solution of the system with Λ2au, Λ2βv and Λ2γ θ for;and second, the global strong solution of the system for with damping terms;finally, the global strong solution of the system for without any damping terms, which improve the known existence theory for this system.

Progress in the Development and Application of Climate Ocean Models and Ocean-Atmosphere Coupled Models in China

A review is presented about the development and application of climate ocean models and oceanatmosphere coupled models developed in China as well as a review of climate variability and climate change studies performed with these models. While the history of model development is briefly reviewed, emphasis has been put on the achievements made in the last five years. Advances in model development are described along with a summary on scientific issues addressed by using these models. The focus of the review is the climate ocean models and the associated coupled models, including both global and regional models, developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences. The progress of either coupled model development made by other institutions or climate modeling using internationally developed models also is reviewed.

Simulating Hydrologic Changes with Climate Change Scenarios in the Haihe River Basin

Climate change scenarios, predicted using the regional climate modeling system of PRECIS (providing regional cli-mates for impacts studies), were used to derive three-layer variable infiltration capacity (VIC-3L) land surface model forthe simulation of hydrologic processes at a spatial resolution of 0.25° × 0.25° in the Haihe River Basin. Three climatescenarios were considered in this study: recent climate (1961-1990), future climate A2 (1991-2100) and future climateB2 (1991-2100) with A2 and B2 being two storylines of future emissions developed with the Intergovernmental Panel onClimate Change (IPCC) special report on emissions scenarios. Overall, under future climate scenarios A2 and B2, theHaihe River Basin would experience warmer climate with increased precipitation, evaporation and runoff production ascompared with recent climate, but would be still likely prone to water shortages in the period of 2031-2070. In addition,under future climate A2 and B2, an increase in runoff during the wet season was noticed, indicating a future rise in theflood occurrence possibility in the Haihe River Basin.

Impacts of Upper Tropospheric Cooling upon the Late Spring Drought in East Asia Simulated by a Regional Climate Model

Responses of late spring （21 April 20 May） rainfall to the upper tropospheric cooling over East Asia are investigated with a regional climate model based on Laboratoire de M6t6orologie Dynamique Zoom （LMDZ4-RCM）. A control experiment is performed with two runs driven by the mean ERA-40 data during 1958-1977 and 1981 2000, respectively. The model reproduces the major decadal-scale circulation changes in late spring over East Asia, including a cooling in the upper troposphere and an anomalous meridional cell. Accordingly, the precipitation decrease is also captured in the southeast of the upper-level cooling region. To quantify the role of the upper-level cooling in the drought mechanism, a sensitivity experiment is further conducted with the cooling imposed in the upper troposphere. It is demonstrated that the upper-level cooling can generate the anomalous meridional cell and consequently the drought to the southeast of the cooling center. Therefore, upper tropospheric cooling should have played a dominant role in the observed late spring drought over Southeast China in recent decades.

Prediction of Climate Change in the 21^(st) Century in Dalian Area under the Various Emission Scenarios

By using the simulative results of more than 20 climate system models which were provided by the fourth assessment report of the Intergovernmental Panel on Climate Change(IPCC),the climate change in Dalian area in the 21st century under the different scenarios(SRES A2,SRES A1B and SRES B1) were analyzed and predicted with the multi-model's aggregative simulative results via the interpolation downscaling calculation.The results showed that the climate in Dalian would have the obvious warming and wetting tendency in the 21st century as a whole.The annual average warming tendency of air temperature would be 2.45-3.46 ℃/100 years,and the annual precipitation increase trend would be 5.8%-16.3% per 100 years.The warming in winter would be the most obvious,and the precipitation increase would be comparatively obvious in winter and spring.The precipitation decrease would be comparatively obvious in autumn in the previous period of 21st century.In A2,A1B and B1 scenarios,the air temperatures in the late period of 21st century would respectively be 3.46,3.44 and 2.45 ℃ higher than in the ordinary years,and the annual precipitation would respectively be 16.3%,11.8% and 5.79% more than in the ordinary years.

Reducing Uncertainties in Climate Projections with Emergent Constraints:Concepts, Examples and Prospects

Models disagree on a significant number of responses to climate change,such as climate feedback,regional changes,or the strength of equilibrium climate sensitivity.Emergent constraints aim to reduce these uncertainties by finding links between the inter-model spread in an observable predictor and climate projections.In this paper,the concepts underlying this framework are recalled with an emphasis on the statistical inference used for narrowing uncertainties,and a review of emergent constraints found in the last two decades.Potential links between highlighted predictors are explored,especially those targeting uncertainty reductions in climate sensitivity,cloud feedback,and changes of the hydrological cycle.Yet the disagreement across emergent constraints suggests that the spread in climate sensitivity can not be significantly narrowed.This calls for weighting the realism of emergent constraints by quantifying the level of physical understanding explaining the relationship.This would also permit more efficient model evaluation and better targeted model development.In the context of the upcoming CMIP6 model intercomparison a growing number of new predictors and uncertainty reductions is expected,which call for robust statistical inferences that allow cross-validation of more likely estimates.

The Regional Climate Effects of Replacing Farmland and Re-greening the Desertification Lands with Forest or Grass in West China

The West Development Policy being implemented in China causes significant land use and land cover (LULC) changes in West China, of which the two most important types of LULC change are replacing farmland and re-greening the desertification land with forest or grass. This paper modifies the prevailing regional climate model (RCM) by updating its lower boundary conditions with the up-to-date satellite database of the Global Land Cover Characteristics Database (GLCCD) created by the United States Geological Survey and the University of Nebraska-Lincoln. The modified RCM is used to simulate the possible regional climate changes due to the LULC variations. The preliminary results can be summarized as that the two main types of LULC variation, replacing farmland and greening the desertification lands with forest or grass in west China, will affect the regional climate mostly in northwest and north China, where the surface temperature will decrease and the precipitation will increase. The regional climate adjustments in South, Southwest China and on the Tibet Plateau are uncertain.

Characteristics of Anthropogenic Sulfate and Carbonaceous Aerosols over East Asia: Regional Modeling and Observation

The authors present spatial and temporal characteristics of anthropogenic sulfate and carbonaceous aerosols over East Asia using a 3-D coupled regional climate-chemistry-aerosol model, and compare the simulation with the limited aerosol observations over the region. The aerosol module consists of SO2, SO4^2-, hydrophobic and hydrophilic black carbon （BC） and organic carbon compounds （OC）, including emission, advections, dry and wet deposition, and chemical production and conversion. The simulated patterns of SO2 are closely tied to its emission rate, with sharp gradients between the highly polluted regions and more rural areas. Chemical conversion （especially in the aqueous phase） and dry deposition remove 60% and 30% of the total SO2 emission, respectively. The SO4^2- shows less horizontal gradient and seasonality than SO2, with wet deposition （60%） and export （27%） being two major sinks. Carbonaceous aerosols are spatially smoother than sulfur species. The aging process transforms more than 80% of hydrophobic BC and OC to hydrophilic components, which are removed by wet deposition （60%） and export （30%）. The simulated spatial and seasonal SO4^2-, BC and OC aerosol concentrations and total aerosol optical depth are generally consistent with the observations in rural areas over East Asia, with lower bias in simulated OC aerosols, likely due to the underestimation of anthropogenic OC emissions and missing treatment of secondary organic carbon. The results suggest that our model is a useful tool for characterizing the anthropogenic aerosol cycle and for assessing its potential climatic and environmental effects in future studies.