Institute Of Atmospheric Physics Research Articles

The North Pacific Meridional Mode and Its Impact on ENSO in the Second Version of the Chinese Academy of Sciences Earth System Model

AbstractThe North Pacific Meridional Mode (PMM) is the strongest interannual air‐sea coupled system in the subtropical northeastern Pacific, which can significantly impact the development of El Niño and Southern Oscillation (ENSO). This study examines performance of the second version of the Chinese Academy of Sciences Earth System Model (CAS‐ESM2), developed primarily at the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP/CAS), in simulating the PMM, ENSO, and their relationship. It reveals that CAS‐ESM2 can well reproduce the tropical climate mean states, including sea surface temperature (SST), surface winds, and precipitation. Furthermore, the model shows a good ability in reproducing the seasonal evolutions of the PMM and ENSO. Moreover, CAS‐ESM2 effectively simulates the influence of the PMM on subsequent ENSO and the underlying physical mechanisms, including the wind‐evaporation‐SST feedback process, the trade wind charging mechanism and summer deep convection mechanism. However, some improvements are still needed, particularly in representing the periodicity of the PMM, an overestimation of the ENSO intensity and westward extension of ENSO‐related SST anomalies in the tropical Pacific. The results obtained from the CAS‐ESM2 showcase significant progress in understanding the interaction between air‐sea interaction systems over the tropics and subtropics.

Evaluation of in situ observations on Marine Weather Observer during Typhoon Sinlaku

Abstract. The mobile ocean weather observation system, named Marine Weather Observer (MWO), developed by the Institute of Atmospheric Physics (IAP), consists of a fully solar-powered, unoccupied vehicle and meteorological and hydrological instruments. One of the MWOs completed a long-term continuous observation, actively approaching the center of Typhoon Sinlaku from 24 July to 2 August 2020, over the South China Sea. The in situ and high-temporal-resolution (1 min) observations obtained from MWO were analyzed and evaluated through comparison with the observations made by two types of buoys during the evolution of Typhoon Sinlaku. First, the air pressure and wind speed measured by MWO are in good agreement with those measured by the buoys before the typhoon, reflecting the equivalent measurement capabilities of the two methods under normal sea conditions. The sea surface temperature (SST) between MWO and the mooring buoys is highly consistent throughout the observation period, indicating the high stability and accuracy of SST measurements from MWO during the typhoon evolution. The air temperature and relative humidity measured by MWO have significant diurnal variations, generally lower than those measured by the buoys, which may be related to the mounting height and sensitivity of sensors. When actively approaching the typhoon center, the air pressure from MWO can reflect some drastic and subtle changes, such as a sudden drop to 980 hPa, which is difficult to obtain by other observation methods. As a mobile meteorological and oceanographic observation station, MWO has shown its unique advantages over traditional observation methods, and the results preliminarily demonstrate the reliable observation capability of MWO in this paper.

Atmospheric CH4 and Its Isotopic Composition (δ13C) in Urban Environment in the Example of Moscow, Russia

Measurements of near-surface methane (CH4) mixing ratio and its stable isotope 13C were carried out from January 2018 to December 2020 at the A.M. Obukhov Institute of Atmospheric Physics (IAP) research site in the center of Moscow city. The data show moderate interannual variations in monthly mean CH4 with maximum values being observed predominantly in winter (2.05–2.10 ppmv on average). The most δ13C depleted CH4 (up to −56‰) is observed in summer and autumn following seasonal decrease in traffic load in the city. The highest CH4 concentrations (>2.2 ppmv) were likely to be caused by air transport from the E–SE sector where potentially large microbial CH4 sources are located (landfills and water treatment plants, Moscow River). Keeling plots of these episodes in different seasons of 2018–2020 showed δ13C isotopic signatures of about −58–−59‰ for the spring–autumn period and −67‰ for winter. A good correlation was observed between CH4 and other pollutants: CO2, CO, and benzene in daytime (10:00–19:00) hours (R > 0.7). Contribution of urban methane emissions due to vehicle exhausts (∆[CH4]auto) and microbial activity (∆[CH4]micro+) along with regional baseline mixing ratios of CH4 ([CH4]base) and CO ([CO]base) were estimated from the linear orthogonal regression analyses of the measured daytime mixing ratios. A significant role of microbial methane in the formation of CH4 maximums in Moscow was revealed. Contributions of the upwind continental CH4 and CO sources to the measured species levels were estimated through comparison with the Mace Head site data representative for the Northern Hemisphere baseline air. The study provides, for the first time, important insights into the long- and short-term variations of CH4 levels in Moscow in connection to the local (urban) emissions and long-range transport from upwind continental sources. The results will contribute to elaboration of a default emission inventory in air quality modeling and help to identify the areas for targeted mitigation efforts.

Retrievals of precipitable water vapor and aerosol optical depth from direct sun measurements with EKO MS711 and MS712 spectroradiometers

Abstract. Based on the strict radiative transfer algorithm, a new method is developed to derive the precipitable water vapor (PWV) and aerosol optical depth (AOD) from the ground-based direct sun irradiance measurements. The attenuated direct irradiance from 300 to 1700 nm was measured by a pair of grating spectroradiometers, MS711 and MS712 produced by EKO Instruments, located at the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS), Beijing (39.98∘ N, 116.38∘ E), from June 2020 to March 2021. Compared with regular sun photometers such as CE-318 and POM, EKO instruments can measure a wider range of continuous spectra, but their field of view (FOV) is also relatively large. In the PWV inversion of this work, a strong water vapor absorption band around 1370 nm is introduced to retrieve PWV in a relatively dry atmosphere. The circumsolar radiation (CSR) of the EKO instruments is corrected to reduce the influence of scattering from a relatively larger FOV on the AOD inversion. The PWV and AOD inversion results obtained by MS711 and MS712 are compared with the synchronous data of the CE-318 sun photometer. The two retrieval results are highly consistent. The correlation coefficient, mean bias, and standard deviation of PWVEKO and PWVCIMEL are 0.999, −0.027 cm (−2.42 %), and 0.054 cm (3.93 %), respectively, and the relative deviations of the differences between the two are slightly larger for drier air (PWV < 0.5 cm) and lower solar elevation angle. The correlation coefficients of AODEKO and AODCIMEL at 380, 440, 500, 675, 870, and 1020 nm are greater than 0.99, and the relative deviations vary between −6.59 % and 4.27 %.

Can Eurasia Experience a Cold Winter under a Third-Year La Niña in 2022/23?

The Northern Hemisphere (NH) often experiences frequent cold air outbreaks and heavy snowfalls during La Niña winters. In 2022, a third-year La Niña event has exceeded both the oceanic and atmospheric thresholds since spring and is predicted to reach its mature phase in December 2022. Under such a significant global climate signal, whether the Eurasian Continent will experience a tough cold winter should not be assumed, despite the direct influence of mid- to high-latitude, large-scale atmospheric circulations upon frequent Eurasian cold extremes, whose teleconnection physically operates by favoring Arctic air invasions into Eurasia as a consequence of the reduction of the meridional background temperature gradient in the NH. In the 2022/23 winter, as indicated by the seasonal predictions from various climate models and statistical approaches developed at the Institute of Atmospheric Physics, abnormal warming will very likely cover most parts of Europe under the control of the North Atlantic Oscillation and the anomalous anticyclone near the Ural Mountains, despite the cooling effects of La Niña. At the same time, the possibility of frequent cold conditions in mid-latitude Asia is also recognized for this upcoming winter, in accordance with the tendency for cold air invasions to be triggered by the synergistic effect of a warm Arctic and a cold tropical Pacific on the hemispheric scale. However, how the future climate will evolve in the 2022/23 winter is still subject to some uncertainty, mostly in terms of unpredictable internal atmospheric variability. Consequently, the status of the mid- to high-latitude atmospheric circulation should be timely updated by medium-term numerical weather forecasts and sub-seasonal-to-seasonal prediction for the necessary date information and early warnings.

The Super-large Ensemble Experiments of CAS FGOALS-g3

A super-large ensemble simulation dataset with 110 members has been produced by the fully coupled model FGOALS-g3 developed by researchers at the Institute of Atmospheric Physics, Chinese Academy of Sciences. This is the first dataset of large ensemble simulations with a climate system model developed by a Chinese modeling center. The simulation has the largest realizations up to now worldwide in terms of single-model initial-condition large ensembles. Each member includes a historical experiment (1850–2014) and an experiment (2015–99) under the very high greenhouse gas emissions Shared Socioeconomic Pathway scenario (SSP5-8.5). The dataset includes monthly and daily temperature, precipitation, and other variables, requiring storage of 275 TB. Additionally, the surface air temperature (SAT) and land precipitation simulated by the FGOALS-g3 super-large ensemble have been validated and projected. The ensemble can capture the response of SAT and land precipitation to external forcings well, and the internal variabilities can be quantified. The availability of more than 100 realizations will help researchers to study rare events and improve the understanding of the impact of internal variability on forced climate changes.

Coral‐Based Sea Surface Salinity Reconstructions and the Role of Observational Uncertainties in Inferred Variability and Trends

AbstractClimate observations in much of the tropical oceans are scarce during most of the 20th century, so paleoclimate proxies are needed to understand the full range of natural climate variability. Past proxy studies have focused primarily on sea surface temperatures, but there are comparatively few salinity reconstructions. Such reconstructions can extend our understanding of hydroclimate across the tropical oceans, including variability in precipitation, evaporation, and ocean circulation. Here we compile a network of salinity‐sensitive coral δ18O records, then apply a reduced‐space method based on empirical orthogonal function analysis to reconstruct annual tropical salinity anomalies over the 20th century. A comparison of surface salinity data sets, including reanalyzes (SODA2/3, Ocean ReAnalysis System 5 (ORAS5), Global Ocean Data Assimilation System) and objective analyses (Institute of Atmospheric Physics (IAP), EN4, Delcroix), show large discrepancies in the spatial structure, temporal evolution, and importance of the leading modes of variability. Two salinity data sets, IAP and ORAS5, are retained for climate reconstruction. Our coral‐based salinity reconstructions reveal significant long‐term trends over the 20th century, which are likely associated with hydrological cycle intensification and possibly a weakening of the Walker Circulation. These reconstructions also capture the spatial and temporal patterns of salinity anomalies associated with the El Niño‐Southern Oscillation, Interdecadal Pacific Oscillation, and Atlantic Multidecadal Oscillation. Ultimately, this approach can enhance our understanding of tropical hydroclimate prior to the observational era.

Long-Term Observations of Stratospheric Species at the A. M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences: Analysis of Trends and Interannual Variations in the Total Contents of O3 and NO2

Long-Term Observations of Stratospheric Species at the A. M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences: Analysis of Trends and Interannual Variations in the Total Contents of O3 and NO2

Specification of the Climate Character in the Study Area of Projected Hydric Reclamation

Hydrical reclamation of the residual pit of Most-Ležáky is part of the comprehensive revitalisation of the land affected in the past bymining activity with an area of 1264 ha. Thus, in terms of remediation and reclamation, the most appropriate way to reclaim theresidual pit, as one of the final stages of the long-term reclamation activities that have been going on in the area for more than half acentury, occurs under the given conditions. The Lake Most, our study area, was planned and created as a hydric recultivation of theformer surface Most-Ležáky mine located near the town of Most, in the foothills of the Ore Mountains, approximately 80 kilometersnorthwest of the capital of the Czech Republic - Prague. The Lake Most represents extensive hydric reclamation, which is unique in thesense that it does not have a natural inflow and runoff, therefore an artificial feeder from the Ohře River had to be built. The main goalof the ongoing research is to construct a mathematical model predicting the water balance of Lake Most. Therefore, it is important toseparate amount of water that is lost by the evaporation and amount of water that is lost into the subsoil. If we do not wish to use onlytemperature equations but more complex methods and equations to calculate evaporation instead, we need to have relative humidity,atmospheric pressure, wind speed, and daylight length values. In addition to the climatic data needed to calculate the evaporation,the amount of precipitation is needed to construct the balance equation of the area. An important objective in planning all hydricreclamations is to ensure their long-term sustainability, which is based on a detailed description of the study area's climate and localhydrological conditions. In our article we focus on assessing the evolution of climate in the area of this hydric reclamation. We haveprocessed a long-term series of measurements in monthly averages from the Kopisty meteostation data provided by the Institute ofAtmospheric Physics of the CAS.

Insight into PM<sub>2.5</sub> sources by applying positive matrix factorization (PMF) at urban and rural sites of Beijing

Abstract. This study presents the source apportionment of PM2.5 performed by positive matrix factorization (PMF) on data presented here which were collected at urban (Institute of Atmospheric Physics – IAP) and rural (Pinggu – PG) sites in Beijing as part of the Atmospheric Pollution and Human Health in a Chinese megacity (APHH-Beijing) field campaigns. The campaigns were carried out from 9 November to 11 December 2016 and from 22 May to 24 June 2017. The PMF analysis included both organic and inorganic species, and a seven-factor output provided the most reasonable solution for the PM2.5 source apportionment. These factors are interpreted as traffic emissions, biomass burning, road dust, soil dust, coal combustion, oil combustion, and secondary inorganics. Major contributors to PM2.5 mass were secondary inorganics (IAP: 22 %; PG: 24 %), biomass burning (IAP: 36 %; PG: 30 %), and coal combustion (IAP: 20 %; PG: 21 %) sources during the winter period at both sites. Secondary inorganics (48 %), road dust (20 %), and coal combustion (17 %) showed the highest contribution during summer at PG, while PM2.5 particles were mainly composed of soil dust (35 %) and secondary inorganics (40 %) at IAP. Despite this, factors that were resolved based on metal signatures were not fully resolved and indicate a mixing of two or more sources. PMF results were also compared with sources resolved from another receptor model (i.e. chemical mass balance – CMB) and PMF performed on other measurements (i.e. online and offline aerosol mass spectrometry, AMS) and showed good agreement for some but not all sources. The biomass burning factor in PMF may contain aged aerosols as a good correlation was observed between biomass burning and oxygenated fractions (r2= 0.6–0.7) from AMS. The PMF failed to resolve some sources identified by the CMB and AMS and appears to overestimate the dust sources. A comparison with earlier PMF source apportionment studies from the Beijing area highlights the very divergent findings from application of this method.

Modelling spatiotemporal variations of the canopy layer urban heat island in Beijing at the neighbourhood scale

Abstract. Information on the spatiotemporal characteristics of Beijing's urban–rural near-surface air temperature difference, known as the canopy layer urban heat island (UHI), is important for future urban climate management strategies. This paper investigates the variation of near-surface air temperatures within Beijing at a neighbourhood-scale resolution (∼ 100 m) during winter 2016 and summer 2017. We perform simulations using the urban climate component of the ADMS-Urban model with land surface parameters derived from both local climate zone classifications and OpenStreetMap land use information. Through sensitivity simulations, the relative impacts of surface properties and anthropogenic heat emissions on the temporal variation of Beijing's UHI are quantified. Measured UHI intensities between central Beijing (Institute of Atmospheric Physics) and a rural site (Pinggu) during the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-China) campaigns, peak during the evening at ∼ 4.5 ∘C in both seasons. In winter, the nocturnal UHI is dominated by anthropogenic heat emissions but is underestimated by the model. Higher-resolution anthropogenic heat emissions may capture the effects of local sources (e.g. residential buildings and adjacent major roads). In summer, evening UHI intensities are underestimated, especially during heatwaves. The inability to fully replicate the prolonged release of heat stored in the urban fabric may explain this. Observed negative daytime UHI intensities in summer are more successfully captured when surface moisture levels in central Beijing are increased. However, the spatial correlation between simulated air temperatures and satellite-derived land surface temperatures is stronger with a lower urban moisture scenario. This result suggests that near-surface air temperatures at the urban meteorological site are likely influenced by fine-scale green spaces that are unresolved by the available land cover data and demonstrates the expected differences between surface and air temperatures related to canopy layer advection. This study lays the foundations for future studies of heat-related health risks and UHI mitigation strategies across Beijing and other megacities.

The U.K.–China Climate Science to Service Partnership

AbstractWe present results from the first 6 years of this major U.K. government funded project to accelerate and enhance collaborative research and development in climate science, forge a strong strategic partnership between U.K. and Chinese climate scientists, and demonstrate new climate services developed in partnership. The development of novel climate services is described in the context of new modeling and prediction capability, enhanced understanding of climate variability and change, and improved observational datasets. Selected highlights are presented from over 300 peer reviewed studies generated jointly by U.K. and Chinese scientists within this project. We illustrate new observational datasets for Asia and enhanced capability through training workshops on the attribution of climate extremes to anthropogenic forcing. Joint studies on the dynamics and predictability of climate have identified new opportunities for skillful predictions of important aspects of Chinese climate such as East Asian summer monsoon rainfall. In addition, the development of improved modeling capability has led to profound changes in model computer codes and climate model configurations, with demonstrable increases in performance. We also describe the successes and difficulties in bridging the gap between fundamental climate research and the development of novel real-time climate services. Participation of dozens of institutes through subprojects in this program, which is governed by the Met Office Hadley Centre, the China Meteorological Administration, and the Institute of Atmospheric Physics, is creating an important legacy for future collaboration in climate science and services.

Ionosphere Influenced From Lower-Lying Atmospheric Regions

The ionosphere represents part of the upper atmosphere. Its variability is observed on a wide-scale temporal range from minutes, or even shorter, up to scales of the solar cycle and secular variations of solar energy input. Ionosphere behavior is predominantly determined by solar and geomagnetic forcing. However, the lower-lying atmospheric regions can contribute significantly to the resulting energy budget. The energy transfer between distant atmospheric parts happens due to atmospheric waves that propagate from their source region up to ionospheric heights. Experimental observations show the importance of the involvement of the lower atmosphere in ionospheric variability studies in order to accurately capture small-scale features of the upper atmosphere. In the Part I Coupling, we provide a brief overview of the influence of the lower atmosphere on the ionosphere and summarize the current knowledge. In the Part II Coupling Evidences Within Ionospheric Plasma—Experiments in Midlatitudes, we demonstrate experimental evidence from mid-latitudes, particularly those based on observations by instruments operated by the Institute of Atmospheric Physics, Czech Academy of Sciences. The focus will mainly be on coupling by atmospheric waves.

Assessment of FY-4A and Himawari-8 Cloud Top Height Retrieval through Comparison with Ground-Based Millimeter Radar at Sites in Tibet and Beijing

The accuracy of passive satellite cloud top height (CTH) retrieval shows regional dependence. This paper assesses the CTH derived from the FY-4A and Himawari-8 satellites through comparison with those from the ground-based millimeter radar at two sites: Yangbajing, Tibet, China (YBJ), and the Institute of Atmospheric Physics (IAP), Beijing, China. The comparison shows that Himawari-8 missed more CTHs at night than FY-4A, especially at YBJ. It is found that the CTH difference (CTHD; radar CTH minus satellite CTH) for FY-4A and Himawari-8 is 0.06 ± 1.90 km and −0.02 ± 2.40 km at YBJ respectively, and that is 0.93 ± 2.24 km and 0.99 ± 2.37 km at IAP respectively. The discrepancy between the satellites and radar at IAP is larger than that at YBJ. Both satellites show better performance for mid-level and low-level clouds than for high-level clouds at the two sites. The retrievals from FY-4A agree well with those from Himawari-8, with a mean difference of 0.08 km at YBJ and 0.06 km at IAP. It is found that the CTHD decreases as the cloud depth increases at both sites. However, the CTHD has no obvious dependence on cloud layers and fractions. Investigations show that aerosol concentration has little impact on the CTHD. For high and thin clouds, the CTHD increases gradually with the increase of the surface temperature, which might be a key factor causing the regional discrepancy between IAP and YBJ.

Observed decreases in on-road CO<sub>2</sub> concentrations in Beijing during COVID-19 restrictions

Abstract. To prevent the spread of the COVID-19 epidemic, restrictions such as “lockdowns” were conducted globally, which led to a significant reduction in fossil fuel emissions, especially in urban areas. However, CO2 concentrations in urban areas are affected by many factors, such as weather, biological sinks and background CO2 fluctuations. Thus, it is difficult to directly observe the CO2 reductions from sparse ground observations. Here, we focus on urban ground transportation emissions, which were dramatically affected by the restrictions, to determine the reduction signals. We conducted six series of on-road CO2 observations in Beijing using mobile platforms before (BC), during (DC) and after (AC) the implementation of COVID-19 restrictions. To reduce the impacts of weather conditions and background fluctuations, we analyze vehicle trips with the most similar weather conditions possible and calculated the enhancement metric, which is the difference between the on-road CO2 concentration and the “urban background” CO2 concentration measured at the tower of the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences. The results showed that the DC CO2 enhancement was decreased by 41 (±1.3) parts per million (ppm) and 26 (±6.2) ppm compared to those for the BC and AC trips, respectively. Detailed analysis showed that, during COVID-19 restrictions, there was no difference between weekdays and weekends during working hours (09:00–17:00 local standard time; LST). The enhancements during rush hours (07:00–09:00 and 17:00–20:00 LST) were almost twice those during working hours, indicating that emissions during rush hours were much higher. For DC and BC, the enhancement reductions during rush hours were much larger than those during working hours. Our findings showed a clear CO2 concentration decrease during COVID-19 restrictions, which is consistent with the CO2 emissions reductions due to the pandemic. The enhancement method used in this study is an effective method to reduce the impacts of weather and background fluctuations. Low-cost sensors, which are inexpensive and convenient, could play an important role in further on-road and other urban observations.

The Road in Environmental Science

Long-term work, based on a physical and mathematical approach, that ultimately provided an explanation of a number of empirical and newly discovered laws of natural phenomena and processes, in particular, the energy spectrum of cosmic rays, the Gutenberg–Richter law for earthquakes, other cumulative distributions, and laws of turbulent diffusion pollution on the surface of water, is described. The history of predicting the global consequences of a hypothetical nuclear war using the analogy with global dust storms on Mars is also described. Full scale studies on the physical foundations of the changes in the Earth’s climate, especially on the interaction of cloudiness and radiation, first started at the Institute of Atmospheric Physics, USSR Academy of Sciences, in the mid-1980s, are mentioned. At the end of 2017, the author noticed that the works conducted by the outstanding Russian mathematician A.N. Kolmogorov in 1934 make it possible for the first time to explain many natural processes and phenomena: the spectra and features of sea wind waves, the enormous energy of hurricanes, spiral eddies on the surface of seas and oceans, features of the relief of celestial bodies, etc.

Model Evaluation and Uncertainty Analysis of PM2.5 Components over Pearl River Delta Region Using Monte Carlo Simulations

Sulfate, nitrate, ammonium, organic carbon (OC) and black carbon (BC) are the key components of PM2.5, but predicting their concentrations remains a challenge because of high uncertainties in the modeling. Employing the Nested Air Quality Prediction Modeling System (NAQPMS) developed by the Institute of Atmospheric Physics, Chinese Academy of Sciences, this study investigated the uncertainties in Monte Carlo simulations of these aerosols in the Pearl River Delta (PRD) region during 2015. 50 ensemble simulations with a 15 km horizontal resolution were derived by perturbing the emission data for sulfate, nitrate, ammonium, OC and BC from an emission inventory, which is one of the largest sources of uncertainty. Then, surface observations of these species collected from 10 sites across the region for 1 year were used to evaluate the performance of the ensemble simulations. The high correlation coefficients (> 0.74) and low mean biases (< 2 µg m–3) between the mean values of the ensemble and the observation data suggested that the model fairly accurately reproduced spatial and temporal variations in the nitrate, ammonium, OC and BC. However, the predicted sulfate concentrations, which displayed a correlation coefficient of 0.26, were far less reliable, particularly owing to the significant underestimation during winter. Further analysis revealed that uncertainties in the emission data explained most of the discrepancies for the OC and BC, but the mean biases for the sulfate and ammonium, especially during winter, probably stemmed from uncertainties in the heterogeneous reaction modeling.

On Correlations between Fields of Temperature, Small Gas Impurities, and Wind in the Surface Layer of the Atmosphere

In a number of studies, including our studies performed at the Institute of Atmospheric Physics, Russian Academy of Sciences, stable correlations have been found between scalar fields of the surface layer (fields of temperature and concentrations of small gas impurities—ozone and water vapor), as well as correlations between these scalars and wind speed. This article shows that the correlations of scalars can be understood on the basis of the hypothesis of similarity of surfaces with equal concentrations of impurities and isothermal surfaces, and that temperature maps explain, at a qualitative level, the correlations of temperature and speed. The unique low-inertia devices developed for pulsed measurements of the density of ozone and water vapor are described. Experiments with synchronous registration of temperature, humidity, and ozone, which showed a high correlation of the above scalar fields, and experiments with the vertically multipoint synchronous registration of temperature, which made it possible to construct maps of sections of isothermal surfaces with a vertical plane along the wind direction, are considered.

Simulation and Improvements of Oceanic Circulation and Sea Ice by the Coupled Climate System Model FGOALS-f3-L

This study documents simulated oceanic circulations and sea ice by the coupled climate system model FGOALS-f3-L developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, under historical forcing from phase 6 of the Coupled Model Intercomparison Project (CMIP6). FGOALS-f3-L reproduces the fundamental features of global oceanic circulations, such as sea surface temperature (SST), sea surface salinity (SSS), mixed layer depth (MLD), vertical temperature and salinity, and meridional overturning circulations. There are notable improvements compared with the previous version, FGOALS-s2, such as a reduction in warm SST biases near the western and eastern boundaries of oceans and salty SSS biases in the tropical western Atlantic and eastern boundaries, and a mitigation of deep MLD biases at high latitudes. However, several obvious biases remain. The most significant biases include cold SST biases in the northwestern Pacific (over 4°C), freshwater SSS biases and deep MLD biases in the subtropics, and temperature and salinity biases in deep ocean at high latitudes. The simulated sea ice shows a reasonable distribution but stronger seasonal cycle than observed. The spatial patterns of sea ice are more realistic in FGOALS-f3-L than its previous version because the latitude-longitude grid is replaced with a tripolar grid in the ocean and sea ice model. The most significant biases are the overestimated sea ice and underestimated SSS in the Labrador Sea and Barents Sea, which are related to the shallower MLD and weaker vertical mixing.

Vertical profiles of biogenic volatile organic compounds as observed online at a tower in Beijing

Vertical profiles of isoprene and monoterpenes were measured by a proton transfer reaction-time of flight-mass spectrometry (PTR-ToF-MS) at heights of 3, 15, 32, 64, and 102 m above the ground on the Institute of Atmospheric Physics (IAP) tower in central Beijing during the winter of 2016 and the summer of 2017. Isoprene mixing ratios were larger in summer due to much stronger local emissions whereas monoterpenes were lower in summer due largely to their consumption by much higher levels of ozone. Isoprene mixing ratios were the highest at the 32 m in summer (1.64 ± 0.66 ppbV) and at 15 m in winter (1.41 ± 0.64 ppbV) with decreasing concentrations to the ground and to the 102 m, indicating emission from the tree canopy of the surrounding parks. Monoterpene mixing ratios were the highest at the 3 m height in both the winter (0.71 ± 0.42 ppbV) and summer (0.16 ± 0.10 ppbV) with a gradual decreasing trend to 102 m, indicting an emission from near the ground level. The lowest isoprene and monoterpene mixing ratios all occurred at 102 m, which were 0.71 ± 0.42 ppbV (winter) and 1.35 ± 0.51 ppbV (summer) for isoprene, and 0.42 ± 0.22 ppbV (winter) and 0.07 ± 0.06 ppbV (summer) for monoterpenes. Isoprene in the summer and monoterpenes in the winter, as observed at the five heights, showed significant mutual correlations. In the winter monoterpenes were positively correlated with combustion tracers CO and acetonitrile at 3 m, suggesting possible anthropogenic sources.