Self-organized classification of boundary layer meteorology and associated characteristics of air quality in Beijing

Abstract. Self-organizing maps (SOMs; a feature-extracting technique based on an unsupervised machine learning algorithm) are used to classify atmospheric boundary layer (ABL) meteorology over Beijing through detecting topological relationships among the 5-year (2013–2017) radiosonde-based virtual potential temperature profiles. The classified ABL types are then examined in relation to near-surface pollutant concentrations to understand the modulation effects of the changing ABL meteorology on Beijing's air quality. Nine ABL types (i.e., SOM nodes) are obtained through the SOM classification technique, and each is characterized by distinct dynamic and thermodynamic conditions. In general, the self-organized ABL types are able to distinguish between high and low loadings of near-surface pollutants. The average concentrations of PM2.5, NO2 and CO dramatically increased from the near neutral (i.e., Node 1) to strong stable conditions (i.e., Node 9) during all seasons except for summer. Since extremely strong stability can isolate the near-surface observations from the influence of elevated SO2 pollution layers, the highest average SO2 concentrations are typically observed in Node 3 (a layer with strong stability in the upper ABL) rather than Node 9. In contrast, near-surface O3 shows an opposite dependence on atmospheric stability, with the lowest average concentration in Node 9. Analysis of three typical pollution months (i.e., January 2013, December 2015 and December 2016) suggests that the ABL types are the primary drivers of day-to-day variations in Beijing's air quality. Assuming a fixed relationship between ABL type and PM2.5 loading for different years, the relative (absolute) contributions of the ABL anomaly to elevated PM2.5 levels are estimated to be 58.3 % (44.4 µg m−3) in January 2013, 46.4 % (22.2 µg m−3) in December 2015 and 73.3 % (34.6 µg m−3) in December 2016.

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Influence of boundary layer structure on air quality in Beijing: Long-term analysis based on self-organizing maps

10.5194/acp-2017-1046 ◽

2017 ◽

Author(s):

Zhiheng Liao ◽

Jiaren Sun ◽

Jialin Yao ◽

Li Liu ◽

Haowen Li ◽

...

Keyword(s):

Boundary Layer ◽

Air Quality ◽

Radiative Forcing ◽

Learning Algorithm ◽

Layer Structure ◽

Surface Wind ◽

Atmospheric Stability ◽

Stable Condition ◽

Self Organizing Maps ◽

Self Organizing

Abstract. Self-organizing maps (SOMs; a feather-extracting technique based on an unsupervised machine learning algorithm) are used to classify the atmospheric boundary layer (ABL) types over Beijing by detecting topological relationships among the 4-yr (2013–2016) radiosonde profiles. The resulting ABL types are then examined in relation to air quality, including surface pollutant concentrations and columnar aerosol properties, to understand the regulating effects of different ABL structures on Beijing's air quality. The SOM provides nine ABL types (i.e., SOM nodes), and each type is characterized by distinct dynamic and thermodynamic conditions. On average, SO2, NO2, CO, PM10 and PM2.5 increase 120–220 % from a near neutral (i.e., node 1) to strong stable condition (i.e., node 9). The ABL controls on diurnal cycles of pollutants are as follows: (1) elevated inversion enhances the afternoon baseline; and (2) surface inversion improves the evening increment. Comparing the CO / SO2 ratios for the different ABL types demonstrates that the local contribution increases with enhanced static stability near the ground, and it is the stable ABL stratification rather than weak surface wind that confines the regional contribution. Due to regional transport, node 3 (dominated by elevated inversion with high relative humidity) corresponds to the most severe columnar aerosol pollution, characterized by the highest optical depth (1.22) and volume concentration (0.30 μm3/μm2). The larger aerosol radiative forcing (ARF) within the atmosphere (> 60 W/m2) in nodes 3, 6 and 9 is likely to strengthen the atmospheric stability and thus induce a positive feedback loop for causing high surface pollution. Analysis of the typical pollution period suggests that the ABL types are the primary drivers of day-to-day variations in Beijing's air quality. Assuming a fixed relationship between ABL type and PM2.5 loading for different years, the relative (absolute) contribution of the ABL anomaly to elevated PM2.5 levels are estimated to be 65.8 % (46.2 μg/m3) during January 2013, 46.7 % (20.2 μg/m,sup>3) during December 2015, and 94.6 % (35.3 μg/m3) during December 2016.

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Characteristics of the Springtime Alpine Valley Atmospheric Boundary Layer Using Self-Organizing Maps

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-14-0317.1 ◽

2015 ◽

Vol 54 (10) ◽

pp. 2077-2085 ◽

Cited By ~ 8

Author(s):

Marwan Katurji ◽

Bob Noonan ◽

Peyman Zawar-Reza ◽

Tobias Schulmann ◽

Andrew Sturman

Keyword(s):

Boundary Layer ◽

Wind Speed ◽

Atmospheric Boundary Layer ◽

Learning Algorithm ◽

Potential Temperature ◽

Atmospheric Stability ◽

Weather Conditions ◽

Self Organizing Maps ◽

Alpine Valley ◽

Self Organizing

AbstractVertical profiles of wind velocity and air temperature from a sound detection and ranging (sodar) radio acoustic sounding system (RASS)-derived dataset within an alpine valley of the New Zealand Southern Alps were analyzed. The data covered the month of September 2013, and self-organizing maps (SOM; a data-clustering approach that is based on an unsupervised machine-learning algorithm) are used to detect topological relationships between profiles. The results of the SOM were shown to reflect the physical processes within the valley boundary layer by preserving valley boundary layer dynamics and its response to wind shear. By examining the temporal evolution of ridgetop wind speed and direction and SOM node transitions, the sensitivity of the valley boundary layer to ridgetop weather conditions was highlighted. The approach of using a composite variable (wind speed and potential temperature) with SOM was successful in revealing the coupling of dynamics and atmospheric stability. The results reveal the capabilities of SOM in analyzing large datasets of atmospheric boundary layer measurements and elucidating the connectivity of ridgetop wind speeds and valley boundary layers.

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Inference of Marine Atmospheric Boundary Layer Moisture and Temperature Structure Using Airborne Lidar and Infrared Radiometer Data

Journal of Applied Meteorology ◽

10.1175/1520-0450-37.3.308 ◽

1998 ◽

Vol 37 (3) ◽

pp. 308-324 ◽

Cited By ~ 10

Author(s):

Stephen P. Palm ◽

Denise Hagan ◽

Geary Schwemmer ◽

S. H. Melfi

Keyword(s):

Boundary Layer ◽

Atmospheric Boundary Layer ◽

Potential Temperature ◽

Airborne Lidar ◽

Temperature Structure ◽

Marine Atmospheric Boundary Layer ◽

Space Technology ◽

Near Surface ◽

Surface Moisture ◽

Infrared Radiometer

Abstract A new technique for retrieving near-surface moisture and profiles of mixing ratio and potential temperature through the depth of the marine atmospheric boundary layer (MABL) using airborne lidar and multichannel infrared radiometer data is presented. Data gathered during an extended field campaign over the Atlantic Ocean in support of the Lidar In-space Technology Experiment are used to generate 16 moisture and temperature retrievals that are then compared with dropsonde measurements. The technique utilizes lidar-derived statistics on the height of cumulus clouds that frequently cap the MABL to estimate the lifting condensation level. Combining this information with radiometer-derived sea surface temperature measurements, an estimate of the near-surface moisture can be obtained to an accuracy of about 0.8 g kg−1. Lidar-derived statistics on convective plume height and coverage within the MABL are then used to infer the profiles of potential temperature and moisture with a vertical resolution of 20 m. The rms accuracy of derived MABL average moisture and potential temperature is better than 1 g kg−1 and 1°C, respectively. The method relies on the presence of a cumulus-capped MABL, and it was found that the conditions necessary for use of the technique occurred roughly 75% of the time. The synergy of simple aerosol backscatter lidar and infrared radiometer data also shows promise for the retrieval of MABL moisture and temperature from space.

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Evaluation of Boundary Layer Similarity Theory for Stable Conditions in CASES-99

Monthly Weather Review ◽

10.1175/mwr3488.1 ◽

2007 ◽

Vol 135 (10) ◽

pp. 3474-3483 ◽

Cited By ~ 23

Author(s):

Kyung-Ja Ha ◽

Yu-Kyung Hyun ◽

Hyun-Mi Oh ◽

Kyung-Eak Kim ◽

Larry Mahrt

Keyword(s):

Boundary Layer ◽

Large Scale ◽

Similarity Theory ◽

Unknown Origin ◽

Strong Stability ◽

Surface Exchange ◽

Stability Functions ◽

Stable Conditions ◽

Mean Wind Speed ◽

Strong Winds

Abstract The Monin–Obukhov similarity theory and a generalized formulation of the mixing length for the stable boundary layer are evaluated using the Cooperative Atmosphere–Surface Exchange Study-1999 (CASES-99) data. The large-scale wind forcing is classified into weak, intermediate, and strong winds. Although the stability parameter, z/L, is inversely dependent on the mean wind speed, the speed of the large-scale flow includes independent influences on the flux–gradient relationship. The dimensionless mean wind shear is found to obey existing stability functions when z/L is less than unity, particularly for the strong and intermediate wind classes. For weak mean winds and/or strong stability (z/L > 1), this similarity theory breaks down. Deviations from similarity theory are examined in terms of intermittency. A case study of a weak-wind night indicates important modulation of the turbulence flux by mesoscale motions of unknown origin.

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Impacts of Modifications to a Local Planetary Boundary Layer Scheme on Forecasts of the Great Plains Low-Level Jet Environment

Weather and Forecasting ◽

10.1175/waf-d-18-0036.1 ◽

2018 ◽

Vol 33 (5) ◽

pp. 1109-1120 ◽

Cited By ~ 3

Author(s):

David E. Jahn ◽

William A. Gallus

Keyword(s):

Boundary Layer ◽

Wind Speed ◽

Planetary Boundary Layer ◽

Great Plains ◽

Potential Temperature ◽

Specific Humidity ◽

Low Level ◽

Stable Conditions ◽

Pbl Scheme ◽

Low Level Jet

Abstract The Great Plains low-level jet (LLJ) is influential in the initiation and evolution of nocturnal convection through the northward advection of heat and moisture, as well as convergence in the region of the LLJ nose. However, accurate numerical model forecasts of LLJs remain a challenge, related to the performance of the planetary boundary layer (PBL) scheme in the stable boundary layer. Evaluated here using a series of LLJ cases from the Plains Elevated Convection at Night (PECAN) program are modifications to a commonly used local PBL scheme, Mellor–Yamada–Nakanishi–Niino (MYNN), available in the Weather Research and Forecasting (WRF) Model. WRF forecast mean absolute error (MAE) and bias are calculated relative to PECAN rawinsonde observations. The first MYNN modification invokes a new set of constants for the scheme closure equations that, in the vicinity of the LLJ, decreases forecast MAEs of wind speed, potential temperature, and specific humidity more than 19%. For comparison, the Yonsei University (YSU) scheme results in wind speed MAEs 22% lower but specific humidity MAEs 17% greater than in the original MYNN scheme. The second MYNN modification, which incorporates the effects of potential kinetic energy and uses a nonzero mixing length in stable conditions as dependent on bulk shear, reduces wind speed MAEs 66% for levels below the LLJ, but increases MAEs at higher levels. Finally, Rapid Refresh analyses, which are often used for forecast verification, are evaluated here and found to exhibit a relatively large average wind speed bias of 3 m s−1 in the region below the LLJ, but with relatively small potential temperature and specific humidity biases.

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Identifying persistent temperature inversion events in a subalpine basin using radon-222

Atmospheric Measurement Techniques ◽

10.5194/amt-12-4455-2019 ◽

2019 ◽

Vol 12 (8) ◽

pp. 4455-4477 ◽

Cited By ~ 4

Author(s):

Dafina Kikaj ◽

Janja Vaupotič ◽

Scott D. Chambers

Keyword(s):

Public Health ◽

Air Quality ◽

Atmospheric Stability ◽

Poor Performance ◽

Temperature Inversion ◽

Relative Magnitude ◽

World Health ◽

Winter Period ◽

Intermittent Turbulence ◽

Stable Conditions

Abstract. One year of meteorological and atmospheric radon observations in a topographically complex subalpine basin are used to identify persistent temperature inversion (PTI) events. PTI events play a key role in public health due to the accumulation of urban pollutants that they cause. Two techniques are compared: a new radon-based method (RBM), based on single-height 222Rn measurements from a single centrally located station, and an existing pseudo-vertical temperature gradient method (TGM) based on observations from eight weather stations around the subalpine basin. The RBM identified six PTI events (four in winter, two in autumn), a subset of the 17 events identified by the TGM. The RBM was more consistent in its identification of PTI events for all seasons and more selective of persistent strongly stable conditions. The comparatively poor performance of the TGM was attributed to seasonal inconsistencies in the validity of the method's key assumptions (influenced by mesoscale processes, such as local drainage flows, nocturnal jets, and intermittent turbulence influence) and a lack of snow cover in the basin for the 2016–2017 winter period. Corresponding meteorological quantities for RBM PTI events (constituting 27 % of the autumn–winter cold season) were well characterized. PTI wind speeds in the basin were consistently low over the whole diurnal cycle (typically 0.2–0.6 m s−1). Suitability of the two techniques for air quality assessment was compared using hourly PM10 observations. Peak PM10 concentrations for winter (autumn) PTI events were underestimated by 13 µg m−3 (11 µg m−3) by the TGM compared with the RBM. Only the RBM indicated that nocturnal hourly mean PM10 values in winter PTI events can exceed 100 µg m−3, the upper threshold of low-level short-term PM10 exposure according to World Health Organization guidelines. The efficacy, simplicity, and cost effectiveness of the RBM for identifying PTI events has the potential to make it a powerful tool for urban air quality management in complex terrain regions, for which it adds an additional dimension to contemporary atmospheric stability classification tools. Furthermore, the long-term consistency of the radon source function will enable the RBM to be used in the same way in future studies, enabling the relative magnitude of PTI events to be gauged, which is expected to assist with the assessment of public health risks.

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The Development of Boundary Layer Structure Index (BLSI) and Its Relationship with Ground Air Quality

Atmosphere ◽

10.3390/atmos10010003 ◽

2018 ◽

Vol 10 (1) ◽

pp. 3 ◽

Cited By ~ 2

Author(s):

Xiang Zheng ◽

Jun Qin ◽

Shengwen Liang ◽

Zhengxuan Yuan ◽

Yassin Mbululo

Keyword(s):

Boundary Layer ◽

Air Quality ◽

Layer Structure ◽

Ambient Air ◽

Air Quality Monitoring ◽

Ambient Air Quality ◽

Vertical Diffusion ◽

Near Surface ◽

Boundary Layer Structure ◽

Structure Index

Ambient air quality monitoring data and radar tracking sonde data were used to study the atmospheric boundary layer structure (ABLS) and its changing characteristics over Wuhan. The boundary layer structure index (BLSI), which can effectively describe the ABLS, was accordingly developed and its ability to describe the near-surface air quality was analyzed. The results can be summarized as follows. (1) An analysis of the ABLS during seriously polluted cases revealed that the ABLS was usually dry and warm with a small ventilation index (VI); meanwhile, the ABLS during clean cases was usually wet and cold with a large VI. (2) The correlation between the air quality and BLSI at 100~300 m was good and passed the confidence level limit at 99%. Moreover, the correlation coefficient increased with the altitude at 10~250 m and showed a downward trend at 250~500 m. The correlation between the BLSI at 250 m and the ground air quality was the most significant (r = 0.312), indicating that the layer ranging from 0 to 250 m is essential for determining the ground air quality. (3) The BLSI considers both the vertical diffusion capability and horizontal removal capability of the atmosphere. Therefore, it is highly capable of describing the ABLS and the ground air quality.

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Homogenized Variability of Radiosonde-Derived Atmospheric Boundary Layer Height over the Global Land Surface from 1973 to 2014

Journal of Climate ◽

10.1175/jcli-d-15-0766.1 ◽

2016 ◽

Vol 29 (19) ◽

pp. 6893-6908 ◽

Cited By ~ 16

Author(s):

Xiaoyan Wang ◽

Kaicun Wang

Keyword(s):

United States ◽

Boundary Layer ◽

Time Series ◽

Land Surface ◽

Statistical Significance ◽

Potential Temperature ◽

The United States ◽

Near Surface ◽

Layer Height ◽

Boundary Layer Height

Abstract Boundary layer height (BLH) significantly impacts near-surface air quality, and its determination is important for climate change studies. Integrated Global Radiosonde Archive data from 1973 to 2014 were used to estimate the long-term variability of the BLH based on profiles of potential temperature, relative humidity, and atmospheric refractivity. However, this study found that there was an obvious inhomogeneity in the radiosonde-derived BLH time series because of the presence of discontinuities in the raw radiosonde dataset. The penalized maximal F test and quantile-matching adjustment were used to detect the changepoints and to adjust the raw BLH series. The most significant inhomogeneity of the BLH time series was found over the United States from 1986 to 1992, which was mainly due to progress made in sonde models and processing procedures. The homogenization did not obviously change the magnitude of the daytime convective BLH (CBLH) tendency, but it improved the statistical significance of its linear trend. The trend of nighttime stable BLH (SBLH) is more dependent on the homogenization because the magnitude of SBLH is small, and SBLH is sensitive to the observational biases. The global daytime CBLH increased by about 1.6% decade−1 before and after homogenization from 1973 to 2014, and the nighttime homogenized SBLH decreased by −4.2% decade−1 compared to a decrease of −7.1% decade−1 based on the raw series. Regionally, the daytime CBLH increased by 2.8%, 0.9%, 1.6%, and 2.7% decade−1 and the nighttime SBLH decreased significantly by −2.7%, −6.9%, −7.7%, and −3.5% decade−1 over Europe, the United States, Japan, and Australia, respectively.

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Wind tunnel experiments: cold-air pooling and atmospheric decoupling above a melting snow patch

The Cryosphere ◽

10.5194/tc-10-445-2016 ◽

2016 ◽

Vol 10 (1) ◽

pp. 445-458 ◽

Cited By ~ 8

Author(s):

Rebecca Mott ◽

Enrico Paterna ◽

Stefan Horender ◽

Philip Crivelli ◽

Michael Lehning

Keyword(s):

Wind Tunnel ◽

Atmospheric Stability ◽

Strong Stability ◽

Snow Surface ◽

Near Surface ◽

Cold Air ◽

Melting Snow ◽

Ambient Flow ◽

Wind Speeds ◽

Two Factors

Abstract. The longevity of perennial snowfields is not fully understood, but it is known that strong atmospheric stability and thus boundary-layer decoupling limit the amount of (sensible and latent) heat that can be transmitted from the atmosphere to the snow surface. The strong stability is typically caused by two factors, (i) the temperature difference between the (melting) snow surface and the near-surface atmosphere and (ii) cold-air pooling in topographic depressions. These factors are almost always a prerequisite for perennial snowfields to exist. For the first time, this contribution investigates the relative importance of the two factors in a controlled wind tunnel environment. Vertical profiles of sensible heat and momentum fluxes are measured using two-component hot-wire and one-component cold-wire anemometry directly over the melting snow patch. The comparison between a flat snow surface and one that has a depression shows that atmospheric decoupling is strongly increased in the case of topographic sheltering but only for low to moderate wind speeds. For those conditions, the near-surface suppression of turbulent mixing was observed to be strongest, and the ambient flow was decoupled from the surface, enhancing near-surface atmospheric stability over the single snow patch.

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The Role of Atmospheric Stability and Turbulence in Offshore Wind-Farm Wakes in the German Bight

Boundary-Layer Meteorology ◽

10.1007/s10546-021-00668-4 ◽

2021 ◽

Author(s):

Andreas Platis ◽

Marie Hundhausen ◽

Astrid Lampert ◽

Stefan Emeis ◽

Jens Bange

Keyword(s):

German Bight ◽

Wind Farm ◽

Atmospheric Stability ◽

Wind Farms ◽

Offshore Wind ◽

Lapse Rate ◽

Offshore Wind Farm ◽

Near Surface ◽

Stable Conditions ◽

The Stability

AbstractAirborne meteorological in situ measurements as well as stationary measurements at the offshore masts FINO1 and FINO3 in the German Bight are evaluated in order to examine the hypothesis that the wake dissipation downstream of large offshore wind farms depends on atmospheric stability. A long-term study of the mast data for the years 2016 and 2017 demonstrates a clear dependence of stability on the wind direction. Stable conditions are predominantly expected during southerly winds coming from the land. The analysis of various stability and turbulence criteria shows that the lapse rate is the most robust parameter for stability classification in the German Bight, but further implies that stability depends on the measurement height. A near-surface (0 to 30 m), predominantly convective, layer is present and more stable conditions are found aloft (55 to 95 m). Combing the stability data with the airborne measurements of the offshore wind-farm wakes reveals the trend of a correlation between longer wake lengths and an increase in the initial wind-speed deficit downwind of a wind farm with stronger thermal stability. However, the stability correlation criteria with the wake length downstream of the four investigated wind farms, Godewind, Amrumbank West, Meerwind Süd/Ost, and Nordsee Ost, contain large variance. It is assumed that the observed scattering is due to the influence of the wind-farm architecture and temperature inversions around hub height. These, however, are crucial for the classification of stability and illustrate the complexity of a clear stability metric.

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