scholarly journals Variability of the Boundary Layer Over an Urban Continental Site Based on 10 Years of Active Remote Sensing Observations in Warsaw

2020 ◽  
Vol 12 (2) ◽  
pp. 340 ◽  
Author(s):  
Dongxiang Wang ◽  
Iwona S. Stachlewska ◽  
Xiaoquan Song ◽  
Birgit Heese ◽  
Anca Nemuc
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Standard Deviation ◽  
Diurnal Cycle ◽  
Log P ◽  
Transform Method ◽  
Boundary Layer Height ◽  
Clear Sky ◽  
The Difference ◽  
Good Agreement

Atmospheric boundary layer height (ABLH) was observed by the CHM15k ceilometer (January 2008 to October 2013) and the PollyXT lidar (July 2013 to December 2018) over the European Aerosol Research LIdar NETwork to Establish an Aerosol Climatology (EARLINET) site at the Remote Sensing Laboratory (RS-Lab) in Warsaw, Poland. Out of a maximum number of 4017 observational days within this period, a subset of quasi-continuous measurements conducted with these instruments at the same wavelength (1064 nm) was carefully chosen. This provided a data sample of 1841 diurnal cycle ABLH observations. The ABLHs were derived from ceilometer and lidar signals using the wavelet covariance transform method (WCT), gradient method (GDT), and standard deviation method (STD). For comparisons, the rawinsondes of the World Meteorological Organization (WMO 12374 site in Legionowo, 25 km distance to the RS-Lab) were used. The ABLHs derived from rawinsondes by the skew-T-log-p method and the bulk Richardson (bulk-Ri) method had a linear correlation coefficient (R2) of 0.9 and standard deviation (SD) of 0.32 km. A comparison of the ABLHs obtained for different methods and instruments indicated a relatively good agreement. The ABLHs estimated from the rawinsondes with the bulk-Ri method had the highest correlations, R2 of 0.80 and 0.70 with the ABLHs determined using the WCT method on ceilometer and lidar signals, respectively. The three methods applied to the simultaneous, collocated lidar, and ceilometer observations (July to October 2013) showed good agreement, especially for the WCT method (R2 of 0.94, SD of 0.19 km). A scaling threshold-based algorithm was proposed to homogenize ceilometer and lidar datasets, which were applied on the lidar data, and significantly improved the coherence of the results (R2 of 0.98, SD of 0.11 km). The difference of ABLH between clear-sky and cloudy conditions was on average below 230 m for the ceilometer and below 70 m for the lidar retrievals. The statistical analysis of the long-term observations indicated that the monthly mean ABLHs varied throughout the year between 0.6 and 1.8 km. The seasonal mean ABLH was of 1.16 ± 0.16 km in spring, 1.34 ± 0.15 km in summer, 0.99 ± 0.11 km in autumn, and 0.73 ± 0.08 km in winter. In spring and summer, the daytime and nighttime ABLHs appeared mainly in a frequency distribution range of 0.6 to 1.0 km. In winter, the distribution was common between 0.2 and 0.6 km. In autumn, it was relatively balanced between 0.2 and 1.2 km. The annual mean ABLHs maintained between 0.77 and 1.16 km, whereby the mean heights of the well-mixed, residual, and nocturnal layer were 1.14 ± 0.11, 1.27 ± 0.09, and 0.71 ± 0.06 km, respectively (for clear-sky conditions). For the whole observation period, the ABLHs below 1 km constituted more than 60% of the retrievals. A strong seasonal change of the monthly mean ABLH diurnal cycle was evident; a mild weakly defined autumn diurnal cycle, followed by a somewhat flat winter diurnal cycle, then a sharp transition to a spring diurnal cycle, and a high bell-like summer diurnal cycle. A prolonged summertime was manifested by the September cycle being more similar to the summer than autumn cycles.

scholarly journals Observed Diurnal Cycle Climatology of Planetary Boundary Layer Height

2010 ◽  
Vol 23 (21) ◽  
pp. 5790-5809 ◽  
Author(s):  
Shuyan Liu ◽  
Xin-Zhong Liang
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Diurnal Cycle ◽  
Surface Characteristics ◽  
Planetary Boundary Layer Height ◽  
Layer Height ◽  
Boundary Layer Height ◽  
Tropical Oceans ◽  
Critical Model ◽  
Fine Resolution

Abstract An observational climatology of the planetary boundary layer height (PBLH) diurnal cycle, specific to surface characteristics, is derived from 58 286 fine-resolution soundings collected in 14 major field campaigns around the world. An objective algorithm determining PBLH from sounding profiles is first developed and then verified by available lidar and sodar retrievals. The algorithm is robust and produces realistic PBLH as validated by visual examination of several thousand additional soundings. The resulting PBLH from all existing data is then subject to various statistical analyses. It is demonstrated that PBLH occurrence frequencies under stable, neutral, and unstable regimes follow a narrow, intermediate, and wide Gamma distribution, respectively, over both land and oceans. Over ice all exhibit a narrow distribution. The climatological PBLH diurnal cycle is strong over land and oceans, with a distinct peak at 1500 and 1200 LT, whereas the cycle is weak over ice. Relative to midlatitude land, the PBLH variability over tropical oceans is larger during the morning and at night but much smaller in the afternoon. This study provides a unique observational database for critical model evaluation on the PBLH diurnal cycle and its temporal/spatial variability.

scholarly journals Ceilometers as planetary boundary layer height detectors and a corrective tool for COSMO and IFS models

2020 ◽  
Vol 20 (20) ◽  
pp. 12177-12192
Author(s):  
Leenes Uzan ◽  
Smadar Egert ◽  
Pavel Khain ◽  
Yoav Levi ◽  
Elyakom Vadislavsky ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Small Scale ◽  
Transform Method ◽  
Pollution Dispersion ◽  
Boundary Layer Height ◽  
Scale Modeling ◽  
Richardson Method ◽  
Parcel Method

Abstract. The significance of planetary boundary layer (PBL) height detection is apparent in various fields, especially in air pollution dispersion assessments. Numerical weather models produce a high spatial and temporal resolution of PBL heights; however, their performance requires validation. This necessity is addressed here by an array of eight ceilometers; a radiosonde; and two models – the Integrated Forecast System (IFS) global model and COnsortium for Small-scale MOdeling (COSMO) regional model. The ceilometers were analyzed with the wavelet covariance transform method, and the radiosonde and models with the parcel method and the bulk Richardson method. Good agreement for PBL height was found between the ceilometer and the adjacent Bet Dagan radiosonde (33 m a.s.l.) at 11:00 UTC launching time (N=91 d, ME =4 m, RMSE =143 m, R=0.83). The models' estimations were then compared to the ceilometers' results in an additional five diverse regions where only ceilometers operate. A correction tool was established based on the altitude (h) and distance from shoreline (d) of eight ceilometer sites in various climate regions, from the shoreline of Tel Aviv (h=5 m a.s.l., d=0.05 km) to eastern elevated Jerusalem (h=830 m a.s.l., d=53 km) and southern arid Hazerim (h=200 m a.s.l., d=44 km). The tool examined the COSMO PBL height approximations based on the parcel method. Results from a 14 August 2015 case study, between 09:00 and 14:00 UTC, showed the tool decreased the PBL height at the shoreline and in the inner strip of Israel by ∼100 m and increased the elevated sites of Jerusalem and Hazerim up to ∼400 m, and ∼600 m, respectively. Cross-validation revealed good results without Bet Dagan. However, without measurements from Jerusalem, the tool underestimated Jerusalem's PBL height by up to ∼600 m.

scholarly journals Estimating the urban atmospheric boundary layer height from remote sensing applying machine learning techniques

2021 ◽  
pp. 105962
Author(s):  
Gregori de Arruda Moreira ◽  
Guadalupe Sánchez-Hernández ◽  
Juan Luis Guerrero-Rascado ◽  
Alberto Cazorla ◽  
Lucas Alados-Arboledas
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Machine Learning Techniques ◽  
Layer Height ◽  
Boundary Layer Height ◽  
Learning Techniques ◽  
Atmospheric Boundary Layer Height

scholarly journals Radiative Effect of Clouds at Ny-Ålesund, Svalbard, as Inferred from Ground-Based Remote Sensing Observations

2020 ◽  
Vol 59 (1) ◽  
pp. 3-22 ◽  
Author(s):  
Kerstin Ebell ◽  
Tatiana Nomokonova ◽  
Marion Maturilli ◽  
Christoph Ritter
Keyword(s):  
Remote Sensing ◽  
The Arctic ◽  
Radiative Effect ◽  
Liquid Water Path ◽  
Ice Clouds ◽  
Surface Warming ◽  
Clear Sky ◽  
Cloud Properties ◽  
Cloud Radiative Effect ◽  
The Difference

AbstractFor the first time, the cloud radiative effect (CRE) has been characterized for the Arctic site Ny-Ålesund, Svalbard, Norway, including more than 2 years of data (June 2016–September 2018). The cloud radiative effect, that is, the difference between the all-sky and equivalent clear-sky net radiative fluxes, has been derived based on a combination of ground-based remote sensing observations of cloud properties and the application of broadband radiative transfer simulations. The simulated fluxes have been evaluated in terms of a radiative closure study. Good agreement with observed surface net shortwave (SW) and longwave (LW) fluxes has been found, with small biases for clear-sky (SW: 3.8 W m−2; LW: −4.9 W m−2) and all-sky (SW: −5.4 W m−2; LW: −0.2 W m−2) situations. For monthly averages, uncertainties in the CRE are estimated to be small (~2 W m−2). At Ny-Ålesund, the monthly net surface CRE is positive from September to April/May and negative in summer. The annual surface warming effect by clouds is 11.1 W m−2. The longwave surface CRE of liquid-containing cloud is mainly driven by liquid water path (LWP) with an asymptote value of 75 W m−2 for large LWP values. The shortwave surface CRE can largely be explained by LWP, solar zenith angle, and surface albedo. Liquid-containing clouds (LWP > 5 g m−2) clearly contribute most to the shortwave surface CRE (70%–98%) and, from late spring to autumn, also to the longwave surface CRE (up to 95%). Only in winter are ice clouds (IWP > 0 g m−2; LWP < 5 g m−2) equally important or even dominating the signal in the longwave surface CRE.

scholarly journals Improving Daytime Planetary Boundary Layer Height Determination from CALIOP: Validation Based on Ground-Based Lidar Station

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Zhao Liu ◽  
Augustin Mortier ◽  
Zhengqiang Li ◽  
Weizhen Hou ◽  
Philippe Goloub ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Absolute Difference ◽  
Aerosol Layer ◽  
Planetary Boundary Layer Height ◽  
Layer Height ◽  
Boundary Layer Height ◽  
Clear Sky ◽  
Ground Based Lidar ◽  
Sky Conditions

An integrated algorithm by combining the advantages of the wavelet covariance method and the improved maximum variance method was developed to determine the planetary boundary layer height (PBLH) from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements, and an aerosol fraction threshold was applied to the integrated algorithm considering the applicability of the two methods. We compared the CALIOP retrieval with the measurements of PBLH derived from nine years of ground-based Lidar synchronous observations located in Lille, north of France. The results indicate that a good correlation (R≥0.79) exists between the PBLHs derived from CALIOP and ground-based Lidar under clear sky conditions. The mean absolute differences of PBLHs are, respectively, of 206 m and 106 m before and after the removal of the aloft aerosol layer. The results under cloudy sky conditions show a lower agreement (R=0.48) in regard of the comparisons performed under clear sky conditions. Besides, the spatial correlation of PBLHs decreases with the increasing spatial distance between CALIOP footprint and Lille observation platform. Based on the above analysis, the PBLHs can be effectively derived by the integrated algorithm under clear sky conditions, while larger mean absolute difference (i.e., 527 m) exists under cloudy sky conditions.

scholarly journals Retrieval of Atmospheric and Cloud Property Anomalies and Their Trend from Temporally and Spatially Averaged Infrared Spectra Observed from Space

2014 ◽  
Vol 27 (12) ◽  
pp. 4403-4420 ◽  
Author(s):  
Seiji Kato ◽  
Fred G. Rose ◽  
Xu Liu ◽  
Bruce A. Wielicki ◽  
Martin G. Mlynczak
Keyword(s):  
Standard Deviation ◽  
Confidence Interval ◽  
Spectral Radiance ◽  
True Temperature ◽  
Retrieval Error ◽  
Cloud Property ◽  
Clear Sky ◽  
Temperature And Humidity ◽  
Sky Radiance ◽  
The Difference

Abstract A surface, atmospheric, and cloud (fraction, height, optical thickness, and particle size) property anomaly retrieval from highly averaged longwave spectral radiances is simulated using 28 years of reanalysis. Instantaneous nadir-view spectral radiances observed from an instrument on a 90° inclination polar orbit are computed. Spectral radiance changes caused by surface, atmospheric, and cloud property perturbations are also computed and used for the retrieval. This study’s objectives are 1) to investigate whether or not separating clear sky from cloudy sky reduces the retrieval error and 2) to estimate the error in a trend of retrieved properties. This simulation differs from earlier studies in that annual 10° latitude zonal cloud and atmospheric property anomalies defined as the deviation from 28-yr climatological means are retrieved instead of the difference of these properties from two time periods. The root-mean-square (RMS) difference of temperature and humidity anomalies retrieved from all-sky radiance anomalies is similar to the RMS difference derived from clear-sky radiance anomalies computed by removing clouds. This indicates that the cloud property anomaly retrieval error does not affect the retrieved temperature and humidity anomalies. When retrieval errors are nearly random, the error in the trend of retrieved properties is small. Approximately 30% of 10° latitude zones meet conditions that the true temperature and water vapor amount trends are within a 95% confidence interval of retrieved trends, and that the standard deviation of retrieved anomalies σret is within 20% of the standard deviation of true anomalies σn. If σret/σn − 1 is within ±0.2, 91% of the true trends fall within the 95% confidence interval of the corresponding retrieved trend.

scholarly journals Evaluating the Absolute Calibration Accuracy and Stability of AIRS Using the CMC SST

2020 ◽  
Vol 12 (17) ◽  
pp. 2743
Author(s):  
Hartmut H. Aumann ◽  
Steven E. Broberg ◽  
Evan M. Manning ◽  
Thomas S. Pagano ◽  
Robert C. Wilson
Keyword(s):  
Time Series ◽  
Standard Deviation ◽  
Absolute Calibration ◽  
Atmospheric Infrared Sounder ◽  
Clear Sky ◽  
Tropical Oceans ◽  
Atmospheric Window ◽  
Surface Skin Temperature ◽  
Calibration Accuracy ◽  
The Difference

We compare the daily mean and standard deviation of the difference between the sea surface skin temperature (SST) derived from clear sky Atmospheric InfraRed Sounder (AIRS) data from seven atmospheric window channels between 2002 and 2020 and collocated Canadian Meteorological Centre (CMC) SST data from the tropical oceans. After correcting the mean difference for cloud contamination and diurnal effects, the remaining bias relative to the CMC SST, is reasonably consistent with estimates of the AIRS absolute accuracy based on the uncertainty of the pre-launch calibration. The time series of the bias produces trends well below the 10 mK/yr level required for climate change evaluations. The trends are in the 2 mK/yr range for the five window channels between 790 and 1231 cm−1, and +5 mK/yr for the shortwave channels. Between 2002 and 2020, the time series of the standard deviation of the difference between the AIRS SST and the CMC SST dropped fairly steadily to below 0.4 K in several AIRS window channels, a level previously only seen in gridded SST products relative to the Argo buoys.

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