Atmospheric Circulation Model Research Articles

Southern Ocean drives multidecadal atmospheric CO2 rise during Heinrich Stadials

The last glacial period was punctuated by cold intervals in the North Atlantic region that culminated in extensive iceberg discharge events. These cold intervals, known as Heinrich Stadials, are associated with abrupt climate shifts worldwide. Here, we present CO2 measurements from the West Antarctic Ice Sheet Divide ice core across Heinrich Stadials 2 to 5 at decadal-scale resolution. Our results reveal multi-decadal-scale jumps in atmospheric CO2 concentrations within each Heinrich Stadial. The largest magnitude of change (14.0 ± 0.8 ppm within 55 ± 10 y) occurred during Heinrich Stadial 4. Abrupt rises in atmospheric CO2 are concurrent with jumps in atmospheric CH4 and abrupt changes in the water isotopologs in multiple Antarctic ice cores, the latter of which suggest rapid warming of both Antarctica and Southern Ocean vapor source regions. The synchroneity of these rapid shifts points to wind-driven upwelling of relatively warm, carbon-rich waters in the Southern Ocean, likely linked to a poleward intensification of the Southern Hemisphere westerly winds. Using an isotope-enabled atmospheric circulation model, we show that observed changes in Antarctic water isotopologs can be explained by abrupt and widespread Southern Ocean warming. Our work presents evidence for a multi-decadal- to century-scale response of the Southern Ocean to changes in atmospheric circulation, demonstrating the potential for dynamic changes in Southern Ocean biogeochemistry and circulation on human timescales. Furthermore, it suggests that anthropogenic CO2 uptake in the Southern Ocean may weaken with poleward strengthening westerlies today and into the future.

Leaf functional traits and ecological niche of Fagus grandifolia and Oreomunnea mexicana in natural forests and plantings as a proxy of climate change.

Functional traits reflect species' responses to environmental variation and the breadth of their ecological niches. Fagus grandifolia and Oreomunnea mexicana have restricted distribution in upper montane cloud forests (1700-2000 m a.s.l.) in Mexico. These species were introduced into plantings at lower elevations (1200-1600 m a.s.l.) that have climates predicted for montane forests in 2050 and 2070. The aim was to relate morphological leaf traits to the ecological niche structure of each species. Leaf functional traits (leaf area, specific leaf area [SLA], thickness, and toughness) were analyzed in forests and plantings. Atmospheric circulation models and representative concentration pathways (RCPs: 2.6, 4.5, 8.5) were used to assess future climate conditions. Trait-niche relationships were analyzed by measuring the Mahalanobis distance (MD) from the forests and the plantings to the ecological niche centroid (ENC). For both species, leaf area and SLA were higher and toughness lower in plantings at lower elevation relative to those in higher-elevation forests, and thickness was similar. Leaf traits varied with distance from sites to the ENC. Forests and plantings have different environmental locations regarding the ENC, but forests are closer (MD 0.34-0.58) than plantings (MD 0.50-0.70) for both species. Elevation as a proxy for expected future climate conditions influenced the functional traits of both species, and trait patterns related to the structure of their ecological niches were consistent. The use of distances to the ENC is a promising approach to explore variability in species' functional traits and phenotypic responses in optimal versus marginal environmental conditions.

Distribution and protection of Thesium chinense Turcz. under climate and land use change.

Wild medicinal plants are prominent in the field of Traditional Chinese Medicine (TCM), but their availability is being impacted by human activities and ecological degradation in China. To ensure sustainable use of these resources, it is crucial to scientifically plan areas for wild plant cultivation. Thesium chinense, a known plant antibiotic, has been overharvested in recent years, resulting in a sharp reduction in its wild resources. In this study, we employed three atmospheric circulation models and four socio-economic approaches (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) to investigate the primary environmental factors influencing the distribution of T. chinense. We also examined changes in its suitable area using the Biomod2 package. Additionally, we utilized the PLUS model to project and analyze future land use changes in climate-stable regions for T. chinense. Our planning for wild tending areas of T. chinense was facilitated by the ZONATION software. Over the next century, the climate-stable regions for T. chinense in China is approximately 383.05 × 104 km2, while the natural habitat in this region will progressively decline. Under the current climate conditions, about 65.06% of the habitats in the high suitable areas of T. chinense are not affected by future land use changes in China. Through hotspot analysis, we identified 17 hotspot cities as ideal areas for the wild tending of T. chinense, including 6 core hotspot cities, 6 sub-hotspot cities, and 5 fringe hotspot cities. These findings contribute to a comprehensive research framework for the cultivation planning of T. chinense and other medicinal plants.

Machine Learning Emulation of Subgrid‐Scale Orographic Gravity Wave Drag in a General Circulation Model With Middle Atmosphere Extension

AbstractGravity wave parameterizations contribute to uncertainties in middle atmosphere modeling. To investigate the potential for using machine learning to represent atmospheric gravity waves and the impact of implementing such schemes in a general circulation model (GCM), we train a random forest (RF) emulator on outputs from an existing complex parameterization scheme for orographic gravity wave drag (GWD). The performance of the RF emulator is then evaluated with a focus on stratospheric climatology and variability in climate simulations from the middle atmosphere resolving Beijing Climate Center Atmospheric Circulation Model. In offline tests, the predicted orographic GWD by the RF agrees remarkably well with the target GWD throughout the troposphere and the middle atmosphere. The RF emulator can reproduce the observed climatology of zonal‐mean wind and air temperature in the GCM simulation, as well as its target scheme. Compared to the target orographic GWD parameterization scheme, the RF emulator can reproduce the breakdown of the polar vortex in the Southern Hemisphere stratosphere. This study demonstrates the feasibility of using machine learning to emulate parameterized orographic GWD for modeling the stratosphere with a GCM.

The Study of Internal Gravity Waves in the Earth’s Atmosphere by Radio Occultations: A Review

Internal gravity waves (IGWs) in the middle atmosphere are the main source of mesoscale fluctuations of wind and temperature. The parameterization of IGWs and study of their climatology is necessary for the development of global atmospheric circulation models. In this review, we focus on the application of Radio Occultation (RO) observations for the retrieval of IGW parameters. (1) The simplest approach employs the retrieved temperature profiles. It is based on the fact that IGWs are highly anisotropic structures and can be accurately retrieved by RO. The basic assumption is that all the temperature fluctuations are caused by IGWs. The smoothed background temperature profile defines the the Brunt–Väisälä frequency, which, together with the temperature fluctuations, defines the IGW specific potential energy. Many studies have derived the distribution and climatology of potential energy, which is one of the most important characteristics of IGWs. (2) More detailed analysis of the temperature profiles is based on the derivation of the temperature fluctuation spectra. For saturated IGWs, the spectra must obey the power law with an exponent of −3. Such spectra are obtained by using Wave Optical (WO) processing. (3) More advanced analysis employs space–frequency analysis. It is based on phase-sensitive techniques like cross S- or wavelet transforms in order to identify propagating IGWs. (4) Another direction is the IGW parameter estimate from separate temperature profiles applying the stability condition in terms of the Richardson number. In this framework, a necessary condition is formulated that defines whether or not the temperature fluctuations can be related to IGW events. The temperature profile retrieval involves integral transforms and filtering that constitute the observation filter. (5) A simpler filter is implemented by the analysis of the RO amplitude fluctuation spectra, based on the diffraction theory in the framework of the phase screen and weak fluctuation approximations. The two spectral parameters, the external scale and the structural characteristic, define the specific potential energy. This approach allows the derivation of the spacial and seasonal distributions of IGW activity. We conclude that the success of IGW study by RO is stimulated by a large number of RO observations and advanced techniques based on Fourier and space–time analysis, physical equations describing IGWs, and diffraction theory.

An improved version of the piecewise parabolic method advection scheme: description and performance assessment in a bidimensional test case with stiff chemistry in toyCTM v1.0.1

Abstract. This study presents a novel method to estimate the performance of advection schemes in numerical experiments along with a semi-realistic, non-linear, stiff chemical system. This method is based on the examination of the “signature function”, an invariant of the advection equation. Apart from exposing this concept in a particular numerical test case, we show that a new numerical scheme based on a combination of the piecewise parabolic method (PPM) with the flux adjustments of Walcek outperforms both the PPM and the Walcek schemes for inert tracer advection as well as for advection of chemically active species. From a fundamental point of view, we think that our evaluation method, based on the invariance of the signature function under the effect of advection, offers a new way to evaluate objectively the performance of advection schemes in the presence of active chemistry. More immediately, we show that the new PPM + W (“piecewise parabolic method + Walcek”) advection scheme offers chemistry-transport modellers an alternative, high-performance scheme designed for Cartesian-grid Eulerian chemistry-transport models, with improved performance over the classical PPM scheme. The computational cost of PPM + W is not higher than that of PPM. With improved accuracy and controlled computational cost, this new scheme may find applications in other fields such as ocean models or atmospheric circulation models.

Оценка точности воспроизведения метеорологических характеристик по модели WRF для акватории Каспийского моря

The paper presents the accuracy estimates for the simulation of meteorological characteristics obtained from the WRF model with a spatial resolution of 6 km adapted for the Caspian Sea. It was used to simulate meteorological characteristics using various parameterizations of physical processes available in the WRF model. The model was verified using data from coastal weather stations for 2021. It was found that the best results in reproducing meteorological characteristics are achieved using the Thompson graupel scheme as a parameterization of physical processes, the Tiedtke scheme as a parameterization of convection, the RRTMG scheme as a parameterization of long-wave and short-wave radiation, the MYJ scheme as a boundary layer parameterization, and the Noah Land-Surface Model as a surface layer parameterization. An analysis of the simulation results versus observational data from weather stations showed that the model correctly reproduces the modulus and direction of wind speed, air temperature, and sea-level pressure. It was found that the model correctly reproduces not only the average characteristics of wind speed, but also its extreme values, which is especially important when modeling storm surges in the Caspian Sea. Keywords: Caspian Sea, regional nonhydrostatic atmosphere circulation model, numerical methods

Diversity of Lagged Relationships in Global Means of Surface Temperatures and Radiative Budgets for CMIP6 piControl Simulations

Abstract Radiative feedbacks over interannual time scales can be potentially useful for global warming estimation. However, the diversity of the lead–lag relationships in global mean surface temperature (GMST) and net radiation flux at the top of the atmosphere (GMTOA) create uncertainty during the estimation of radiative feedbacks. In this study, key physical processes controlling lead–lag relationships were elucidated by categorizing preindustrial control simulations of CMIP6 into three groups based on cross correlation values of GMTOA against GMST at lag 0 and lag +1 year. The diversity in the lead–lag relationships was primarily caused by the climatological state difference of the atmosphere over the equatorial Pacific, which modulated the strength of convective activity and sensitivity of low-level clouds. Diminished atmospheric stability caused enhanced convective activity, more efficient energy release, and smaller lags. In addition, enhanced stability in the lower atmosphere rendered the low-level clouds more sensitive to sea surface temperature changes and considerably delayed the radiative response. The climatological state difference of the atmosphere resulted from model-inherent atmospheric conditions. These findings suggest that the diversity of lead–lag relationships of GMST and GMTOA over interannual time scales could represent the characteristics of general atmospheric circulation models and possible solutions of the actual atmosphere, which could also affect long-term feedback features.

Extreme temperature fluctuations in laboratory models of the mid-latitude atmospheric circulation.

Using two laboratory-scale conceptual fluid dynamic models of the mid-latitude atmospheric circulation we investigate the statistical properties of pointwise temperature signals obtained in long experiment runs. We explore how the average "equator-to-pole" temperature contrast influences the range and the jump distribution of extreme temperature fluctuations, the ratio of the frequencies of rapid cooling and warming events, and the persistence of "weather" in the set-ups. We find simple combinations of the control parameters-temperature gradient, rotation rate and geometric dimensions-which appear to determine certain scaling properties of these statistics, shedding light on the underlying dynamics of the Rossby wave-related elements of the mid-latitude weather variability.

Mineral magnetic proxies for evaluation of anthropogenic pollution at children's playgrounds – a case study from Sofia city

Quality of the urban environment where children play is of great concern for protecting their health. Thus, fast and economically feasible proxy methods for assessment of urban environment are increasingly applied. In this study, settled dust from 13 playgrounds from Sofia city (Bulgaria), was investigated by mineral magnetism, portable X-ray fluorescence measurements, and scanning electron microscopy. The aim of the study was to evaluate the degree of anthropogenic pollution of playgrounds during winter and summer seasons and to identify pollution sources. Magnetic susceptibility (χ) was measured for two dust fractions - very coarse (grain sizes between 1 and 2 mm) and size fraction of d < 1 mm. In spite of this rough separation, systematic seasonal difference in χ of the two fractions is observed. Winter dust, containing larger amount of finer fraction shows lower χ. Regardless of lower relative content of d < 1 mm fraction, summer playground dusts are more strongly magnetic. Complex Pollution Load Index (PLI), calculated using contents of Cu, Zn, S, Pb (Potentially Toxic Elements (PTE)), shows higher contamination in summer dust, compared to winter. Anhysteretic and isothermal remanences of dust d < 1 mm demonstrate prevailing magnetically stable grains at playgrounds located at greater distance from major boulevards. Thermomagnetic analyses of magnetic susceptibility identified magnetite as the main magnetic mineral, although metallic iron was also evident in summer dust. Based on the meteorological models of atmospheric circulation over Sofia, the pollution sources suggested in a previous research, on one hand, and the carried out Factor Analysis, on the other hand, the results point out that in spite of higher PM10 dust load in winter, summer dust pollution causes stronger PTEs contamination. Factor analysis revealed four factors, explaining most of variability in the data. These factors were identified as: 1) re-suspension of soil and road dust; 2) fine particles magnetite of stable single domain grain size, originating probably from traffic exhaust and non-exhaust emissions; 3) emissions from installations burning waste materials; 4) coal burning.

Influence of contemporary warming on landscape-zonal systems of the East-European sub-continent: Predictive empirical-statistical modeling

Presented in the given article regional geo-ecological prognoses are based on the construction of discrete empirical-statistical models of zonal and regional ecosystems. The analysis was carried out on the examples of the flat territories of the Volga River basin, as well as the northern macro-slope of the Main Caucasian ridge. Regional landscape-ecological calculations and mapping were carried out according to the global climatic models GISS-1988 and E GISS-2007 belong­ing to the family of models of general atmospheric circulation. The strategy of geo-ecological prognosis was as follows: first to identify the selected ecosystem objects (either zonal type of plant formations and regional kinds of landscape) to certain values of contemporary climatic conditions and then to estimate the most probable transformation of the revealed ecological niches of the given objects according to the expected climatic changes for the given prognostic date. The geo-ecological analysis has been performed using mainly two types of empirical models: (a) informational, describing the geo-component interrelations, serving as a basis for the regional bank of their ecological niches that characterizes their parametric space; (b) “fuzzy” set-theoretical models, describing the polysystem units of landscape-zonal organization by operations with the ecological niches as descriptive vectors. Predictions of ecosystem transformations include two stages of analysis: (1) evaluation of the probabilities of changes in the functional states of ecosystems and (2) calculations of the rates of ecosystem transformations. Quantitative predictive analysis is carried out by means of operations with the hydro-thermal niches of zonal-regional ecosystems. The ecological estimates of forthcoming global warming refer first of all to the functional but not structural-morphological prediction. The most probable directions and degree of conversion of the ecosystem are estimated by the maximum values of transformation. The algorithms of predictive calculations are described in detail for both stages of analysis. The results of the zonal-regional prognostic analysis are presented in both graphic-analytical models and small-scale maps.

Future Climate Prediction Based on Support Vector Machine Optimization in Tianjin, China

Climate is closely related to human life, food security and ecosystems. Forecasting future climate provides important information for agricultural production, water resources management and so on. In this paper, historical climate data from 1962–2001 was used at three sites in Tianjin Baodi, Tianjin and Tanggu districts as baseline and the model parameters were calibrated by the Long Ashton Research Station Weather Generator (LARS-WG). 2m-temperatures in 2011–2020 were verified under two scenarios, representative concentration pathway (RCP) 4.5 and RCP8.5 in different atmospheric circulation models with optimal minimum 2m-temperatures at the three sites. From 2031–2050, Tianjin will be using more moderate minimum 2m-temperatures in future simulations. Support vector machines (SVM) were used to optimize the simulated data to obtain more accurate future maximum and minimum 2m-temperatures for the three sites. The results showed that the determinant coefficient of LARS-WG simulation was 0.8 and SVM optimized determinant coefficient was 0.9 which greatly improved the prediction accuracy. The minimum and maximum future 2m-temperatures optimized under European Community Earth System Model (EC-EARTH) were relatively low and the same future 2m-temperatures optimized under Hadley Centre Global Environment Model Earth System (Had-GEM2-ES4) were high especially in the RCP8.5 scenario which simulated 2051–2070 climate. The SVM optimization showed that the maximum and minimum 2m-temperatures were in general agreement with the original simulation values.

The extreme heat wave in China in August 2022 related to extreme northward movement of the eastern center of SAH

This study reveals the causes of extreme high temperatures in China in August 2022 and the role of South Asian high (SAH) anomaly. The 2022 extreme heat events in the Tibetan Plateau (TP) and Yangtze River basin (YRB) are the strongest since 1979, accompanied by an anticyclonic anomaly in the northeastern part of the SAH. Six displacement indices of the SAH are defined by taking advantage of the stream function R of horizontal circulation in the three-pattern decomposition of the global atmospheric circulation (3P-DGAC) model, which can effectively remove the systematic errors in geopotential high caused by global warming. The results show an extreme northward shift of the eastern center of SAH occur in August 2022, with correlation coefficients 0.85 and 0.69 with the temperature anomaly indices of TP and YRB regions, respectively, for 1979–2022. In addition to the La Niña event, we find evidence that the soil moisture in the Indo-China Peninsula (ICP) region from January to August 2022 is extremely wet, linked to significant impacts on the northward movement of the eastern center of SAH response to land-air interactions. Further, the 3P-DGAC model helps us to reveal that the extreme northward shift of the eastern center of SAH brings extensive circulation adjustments, in which the local meridional circulation anomaly intensifies the high temperature in the YRB, while the local zonal circulation in the middle latitudes is the main cause of the high temperature in the TP. Meanwhile, the northward shift of the eastern center of SAH pushes the East Asian subtropical westerly jet (EAJ) northeastward, and the convergent downdraft to the right of EAJ exit also further aggravates the summer hot extremes in China in 2022.

A shallow layer laboratory model of large-scale atmospheric circulation

A new shallow layer laboratory model of global atmospheric circulation is realised and studied by experiments and numerical simulations. A shallow rotating cylindrical fluid layer of 30 mm thickness and 690 mm diameter, with a localised heater at the bottom periphery and localised cooler in the central part of the upper boundary is considered. The rim heater imitates the equator heating and disc cooler – the North pole cooling. The flow transforms from the Hadley-like regime to the baroclinic wave regime through transitional states. The decrease in the thermal Rossby number for the fixed value of Taylor number results in the regularisation of the baroclinic waves. All wave regimes, even with regular wave structures, are characterised by strong non-periodic fluctuations. The observed baroclinic wave structures are a combination of temporarily evolving different baroclinic modes. The important outcome of the shallow layer model is a realisation of the Earth-like meridional three-cell structure. It is shown that the three-cell structure with analogs of polar, Ferrel and Hadley cells exist only in a limited range of parameters. A comparison of the results for the water and silicon oil demonstrated that the physical properties of the fluid can have a strong impact on the baroclinic wave structure.

A Hybrid Atmospheric Model Incorporating Machine Learning Can Capture Dynamical Processes Not Captured by Its Physics‐Based Component

AbstractIt is shown that a recently developed hybrid modeling approach that combines machine learning (ML) with an atmospheric global circulation model (AGCM) can serve as a basis for capturing atmospheric processes not captured by the AGCM. This power of the approach is illustrated by three examples from a decades‐long climate simulation experiment. The first example demonstrates that the hybrid model can produce sudden stratospheric warming, a dynamical process of nature not resolved by the low resolution AGCM component of the hybrid model. The second and third example show that introducing 6‐hr cumulative precipitation and sea surface temperature (SST) as ML‐based prognostic variables improves the precipitation climatology and leads to a realistic ENSO signal in the SST and atmospheric surface pressure.

POLIPHON conversion factors for retrieving dust-related cloud condensation nuclei and ice-nucleating particle concentration profiles at oceanic sites

Abstract. Aerosol–cloud interactions (ACIs) are the largest contributor to the uncertainty in the global radiation budget. To improve the current consideration of ACIs in global circulation models, it is necessary to characterize the 3-D distribution of dust-related cloud condensation nuclei concentration (CCNC) and ice-nucleating particle concentration (INPC) globally. This can potentially be realized using the POlarization LIdar PHOtometer Networking (POLIPHON) method together with spaceborne lidar observations. However, dust-related conversion factors that convert bulk aerosol optical properties from lidar measurements to aerosol microphysical properties are still less constrained in many regions, which limits the applications of the POLIPHON method. Here we retrieve the essential dust-related conversion factors at remote oceanic and coastal sites using the historical AErosol RObotic NETwork (AERONET) database. Depolarization-ratio-based dust ratios Rd at 1020 nm are applied to identify the dust-occurring cases, thus enabling us to contain fine-mode dust-dominated cases (after the preferential removal of large-sized dust particles during transport), study the evolution of dust microphysical properties along the transoceanic pathway, and mitigate occasional interference of large-sized marine aerosols. The newly proposed scheme is proven to be valid and feasible by intercomparisons with previous studies at nine sites in/near deserts. The dust-related conversion factors are calculated at 20 oceanic and coastal sites using both pure dust (PD) and PD plus dust-dominated mixture (PD+DDM) datasets. At nearly half of the sites, the conversion factors are solely calculated using the PD datasets, while at the remaining sites, the participation of DDM datasets is required to ensure a sufficient number of data for the calculation. Evident variation trends in conversion factors are found for cv,d (extinction-to-volume concentration, gradually decreasing), c250,d (extinction-to-particle (with a radius &gt; 250 nm) number concentration, gradually increasing), and cs,d (extinction-to-surface-area concentration, gradually decreasing) along both the transpacific and transatlantic dust transport pathways. The retrieved dust-related conversion factors are anticipated to inverse 3-D dust-related CCNC and INPC distributions globally, thereby improving the understanding of ACIs in atmospheric circulation models.

The Zonal Patterns in Late Quaternary Tropical South American Precipitation

AbstractSpeleothem oxygen isotope records (δ18O) of tropical South American rainfall in the late Quaternary show a zonal “South American Precipitation Dipole” (SAPD). The dipole is characterized by opposing east‐west precipitation anomalies compared to the present—wetter in the east and drier in the west at the mid‐Holocene (∼7 ka), and drier in the east and wetter in the west at the Last Glacial Maximum (∼21 ka). However, the SAPD remains enigmatic because it is expressed differently in western versus eastern δ18O records and isotope‐enabled climate model simulations usually misrepresent the magnitude and/or spatial pattern of δ18O change. Here, we address the SAPD enigma in two parts. First, we re‐interpret the δ18O data to account for upwind rainout effects that are known to be pervasive in tropical South America, but are not always considered in Quaternary paleoclimate studies. Our revised interpretation reconciles the δ18O data with cave infiltration and other proxy records, and indicates that the centroid of tropical South American rainfall has migrated zonally over time. Second, using an energy balance model of tropical atmospheric circulation, we hypothesize that zonal migration of the precipitation centroid can be explained by regional energy budget shifts, such as changing Saharan albedo associated with the African Humid Period, that have not been modeled in previous SAPD studies. This hypothesis of a migrating precipitation centroid presents a new framework for interpreting δ18O records from tropical South America and may help explain the zonal rainfall anomalies that predate the late Quaternary.

Bias Correcting Climate Model Simulations Using Unpaired Image-to-Image Translation Networks

Abstract We assess the suitability of unpaired image-to-image translation networks for bias correcting data simulated by global atmospheric circulation models. We use the Unsupervised Image-to-Image Translation (UNIT) neural network architecture to map between data from the HadGEM3-A-N216 model and ERA5 reanalysis data in a geographical area centered on the South Asian monsoon, which has well-documented serious biases in this model. The UNIT network corrects cross-variable correlations and spatial structures but creates bias corrections with less extreme values than the target distribution. By combining the UNIT neural network with the classical technique of quantile mapping (QM), we can produce bias corrections that are better than either alone. The UNIT+QM scheme is shown to correct cross-variable correlations, spatial patterns, and all marginal distributions of single variables. The careful correction of such joint distributions is of high importance for compound extremes research.

Advances in influencing mechanism and model of total climatic production factors of plant phenology change

<p indent="0mm">Phenology is an important indicator of climate change. It is not only the key to vegetation dynamic simulation, but also directly affects the simulation accuracy of terrestrial carbon cycle and atmospheric general circulation model. This paper summarizes the research status of plant phenology from two aspects: phenological change mechanism and phenological simulation model, and analyzes the research trend of phenology. It points out that most of the current phenological studies only consider the impact of a single climate factor or a few climate factors, and there are still few studies involved in the interaction of multiple climate factors, let alone the interaction of total climate production factors determining plant phenology. Due to the limitation of the understanding of phenological change mechanism and the study of species, the existing phenological models cannot reflect the authenticity of vegetation growth, nor can they effectively simulate the phenological period. The paper points out that it is essential to study the relationship between phenology and total climatic production factors in order to comprehensively understand the mechanism of phenological change. Based on the fact that plant photosynthesis is the most important phenological influencing factor, this paper puts forward the viewpoint of using climate production potential as the driving factor of plant phenological change. Climate production potential not only reflects the comprehensive effect of climate and environmental factors on plant production and their consistency of these factors in the whole process of plant growth, but also includes the interaction between biological factors and environmental factors and the impact of extreme weather and climate events, which is able to realize the accurate simulation of phenology. The future phenological research directions proposed in this paper will help enrich phenological knowledge and improve the simulation accuracy of land carbon cycle model and atmospheric circulation model.

The flow structure in a laboratory model of atmospheric general circulation

The flow structure in a laboratory model of atmospheric general circulation