Factors affecting the comparisons of planetary boundary layer height

Atmospheric Environment 74 (2013) 360e366

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Factors affecting the comparisons of planetary boundary layer height retrievals from CALIPSO, ECMWF and radiosondes over Thessaloniki, Greece E. Leventidou a, *,1, P. Zanis b, D. Balis a, E. Giannakaki c, I. Pytharoulis b, V. Amiridis d a

Laboratory of Atmospheric Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece Department of Meteorology and Climatology, Aristotle University of Thessaloniki, Thessaloniki, Greece Finnish Meteorological Institute, Kuopio, Finland d Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens, Athens 15236, Greece b c

h i g h l i g h t s Significant agreement between CALIPSO PBL observations and ECMWF estimates. CALIPSO PBL estimates depend on aerosol feature mask. Correlation between CALIPSO and ECMWF improves by abstracting dust convection cases CALIPSO products could be valuable on evaluating atmospheric models- retrieving PBL

a r t i c l e i n f o

a b s t r a c t

Article history: Received 18 February 2013 Received in revised form 2 April 2013 Accepted 4 April 2013

The aim of this study is to propose an evaluation methodology of CALIPSO retrievals of the planetary boundary layer (PBL) height using the analyses of the operational early-delivery assimilation system of the European Centre for Medium-Range Weather Forecast (ECMWF) and Radiosonde observations. The investigation is performed over Thessaloniki, Greece, for a period of almost 5 years between 2006 and 2011. Low correlations between CALIPSO and ECMWF are found when CALIPSO aerosol classification scheme reveals dust presence over Thessaloniki. When eliminating cases of dust advection, the correlation between CALIPSO and ECMWF improves considerably, reaching a value of 0.82, while the correlation between CALIPSO and radiosondes reaches 0.74. The proposed methodology for evaluation shows a good potential for future work when more stations will be considered. Taking into account the aforementioned limitations due to the presence of advected dust layers for the Mediterranean site investigated here, the CALIPSO PBL height could be considered a valuable satellite product for investigating the atmospheric boundary layer processes and for evaluating global and regional atmospheric models. Ó 2013 Elsevier Ltd. All rights reserved.

Keywords: Planetary boundary layer CALIPSO

1. Introduction A successful weather and air quality forecast is critically dependent on the determination of the Planetary Boundary Layer (PBL) height. With active remote sensing instruments, such as Lidars, aerosols can be detected and used as tracers of PBL dynamics (Delgado et al., 2011). The optical power measured by Lidar is

* Corresponding author. E-mail address: [email protected] (E. Leventidou). 1 Present address: Institute of Environmental Physics, University of Bremen, NW1, Otto-Hahn-Alle 1, D-28359 Bremen, Germany. 1352-2310/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.atmosenv.2013.04.007

proportional to the aerosol content of the atmosphere (Sicard et al., 2004). Because the mixing layer is typically moister, denser and has a greater aerosol content than the free atmosphere, more scattering of laser light is caused and hence Lidar can detect the boundary between the two layers (e.g. Kunkel et al., 1977). Methods used to retrieve PBL height by Lidar are relevant to the physical characteristics of the entrainment zone (Flamant et al., 1997). With the evolution of remote sensing, PBL height determination is possible using data from spaceborne Lidars. PBL derived from satellite Lidar data has been used to validate Global Circulation Models (GCM). For example the analysis of PBL height from LITE (Lidar In-space Technology) mission (Randall et al., 1998) was

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compared with a GCM and the NCAR climate model (National Center for Atmospheric Research). Additionally, GLAS (Geosciences Laser Altimeter System) data were used in validation of ECMWF (European Center for Medium-Range Weather Forecast) model (Palm et al., 2005). PBL height can be also defined by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), part of NASA ATrain satellite constellation. Onboard CALIPSO, the dual wavelength polarization-sensitive backscatter Lidar (CALIOP) measures vertical profiles of the spatial and optical characteristics of clouds and aerosols in the atmosphere since June 2006 (Winker, 2006). A synergistic use of NASA’s A-Train observations to characterize the PBL was revealed in the study of Zavodsky et al. (2010). They evaluated the retrieval of PBL structure, temperature and moisture properties from measurements made by CALIPSO, MODIS (Moderate Resolution Imaging Spectroradiometer), and AIRS (Atmospheric Infrared Sounder) using radiosonde data. The first hemispheric evaluation study of PBL heights using CALIPSO was carried out by Jordan et al. (2010), through comparisons with the GEOS-5 MERRA model. Comparisons between the model output and the satellite observations in the Western Hemisphere and over Africa gave correlation coefficients (R) ranging between 0.47 and 0.73. Another study by McGrath-Spangler and Denning (2012) used CALIPSO’s estimates of PBL depth and compared them with modelbased PBL height retrievals and AMDAR (Aircraft Meteorological DAta Reporting) estimates over North America. They found that these Lidar-based estimates of PBL height tend to be shallower than aircraft estimates in coastal areas. Additionally they concluded that CALIPSO PBL height compared to reanalysis products is greater over the oceans and areas of the boreal forest and shallower over the arid and semiarid regions of North America. Comparisons of aerosol-cloud observations between a ground-based Raman-Mie Lidar and CALIPSO over US East Coast showed that CALIPSO-derived aerosol-layer-tops are found to be consistent with ground-Lidar derived PBL heights with a correlation coefficient of 0.84. This result indicated that the CALIPSO-derived aerosol-layer-top can be used as a robust indicator of PBL height (Wu et al., 2010). The aim of this study is to evaluate the CALIPSO PBL height product with PBL height derived from Radiosonde observations and the analyses of the operational early-delivery assimilation system of ECMWF model and assess the role for this evaluation of a number of selection criteria applied on the CALIPSO data. The analysis was carried out for Thessaloniki, Greece, between 01/06/2006 and 31/ 03/2011. In Section 2, the data and methods used are presented. Section 3 presents our results and discussions, and Section 4 a brief summary and our conclusions.

Onboard CALIPSO the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) is an elastically backscattered Lidar operating at 532 and 1064 nm, equipped with a depolarization channel at 532 nm that provides high-resolution vertical profiles of aerosols and clouds. The lasers operate at 20.16 Hz and are Q-switched to provide a pulse length of about 20 ns. Each laser generates nominally 220 mJ per pulse at 1064 nm, which is frequency-doubled to produce about 110 mJ of pulse energy at each of the two wavelengths. Beam expanders reduce the angular divergence of the transmitted laser beam to produce a beam diameter of 70 m at the Earth’s surface (Winker, 2006). CALIPSO releases scientific data as Level 1 and Level 2 products. Level 1 data include Lidar calibrated and geolocated attenuated backscatter coefficient profiles with associated browse imagery. The horizontal resolution is 1/3 km, 1 km and 5 km. CALIPSO Level 2 aerosol layer product provides a description of the aerosol layers, including their top heights and bottoms, identified by the use of automated algorithms from the Level 1 data. Detailed description of the aforementioned algorithms is given in Vaughan et al. (2004) and Winker (2006). In order to determine the PBL height by lidars, several methods have been developed using Level 1B data, such as:

2. Data and methods

A number of methods have been developed in order to determine the PBL height from Radiosonde measurements with the use of measurements of tropospheric temperature and relative humidity. The base of an elevated temperature (T) inversion which serves as a cap to mixing below can be considered as the PBL height. Consequently we estimated the level of the maximum vertical gradient of potential temperature (q) (Stull, 1988; Oke, 1988; Sorbjan, 1989; Garratt, 1992), indicative of a transition from a convectively less stable region below to a more stable region above. In addition the levels of the minimum vertical gradient of specific humidity (q) or relative humidity (RH) (Ao et al., 2008) were used. While the aforementioned methods enable the possibility of an unstable or neutral PBL, a surface-based temperature inversion is a clear indicator of a stable boundary layer, whose top can define a PBL height (Bradley et al., 1993). We used the estimation of bulk-Richardson number for determining the PBL height. Bulk-Richardson number is the ratio of the static stability to the square of the wind shear. According to

2.1. PBL height product from CALIPSO The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission is a collaborative effort between NASA Langley Research Center (LaRC), the French space agency (CNES), Hampton University (HU), the Institute Pierre Simon Laplace (IPSL), and Ball Aerospace and Technologies Corporation (BATC) to study global radiative effects of aerosols and clouds on climate. CALIPSO is an Earth Science observation mission that was launched on 28 April 2006 and flies in nominal orbital altitude of 705 km and an inclination of 98 as part of a constellation of Earth-observing satellites including Aqua, PARASOL, and Auraecollectively known as the “A-train” (http://www-calipso.larc.nasa.gov/about/atrain. php). The CALIPSO mission provides crucial Lidar and passive sensors to obtain unique data on aerosol and cloud vertical structure and optical properties.

(1) The gradient technique (Melfi et al., 1985; Boers and Eloranta, 1986; Palm et al., 1998, 2005), (2) The Haar wavelet technique (Davis et al., 2000; Brooks, 2003), and (3) The maximum variance technique (Jordan et al., 2010). The application of these methods on CALIPSO is difficult due to the low signal to noise ratio (SNR, e.g. Giannakaki, 2009) of the Level 1 products. Low SNRs makes difficult the detection of a backscatter (e.g. Jordan et al., 2010). In this study we evaluate the PBL height derived by Level 2 Aerosol Layer products. Taking into account that CALIPSO Level 2 Aerosol Layer products provide information about base and top heights of existing aerosol layers (reported at a uniform 5-km horizontal resolution), we consider the lowest layer top altitude as the PBL height (analogous to the more conventional thermodynamic definition; Palm et al., 2005). The CALIOP layer detection algorithm is described in detail in Vaughan et al. (2009) and in the http://www-calipso.larc.nasa.gov/resources/ pdfs/PC-SCI-202_Part2_rev1x01.pdf (Section 5; see http://eosweb. larc.nasa.gov/PRODOCS/calipso/Quality_Summaries/CALIOP_L2Layer Products_3.01.html). 2.2. PBL height from radiosondes

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Vogelezang and Holtslag (1996), the bulk-Richardson number is calculated as:

Ribulk ¼

g DqDz hqv i ðDUÞ2 þ ðDVÞ2

(1)

where the gradients are evaluated between the surface and level z. Dq is the difference between the potential temperature at z and the surface potential temperature, is the layer average virtual potential temperature, U and V are the horizontal and vertical wind components and g is the acceleration of gravity. The vertical component is set equal to zero. The bulk-Richardson number is useful to indicate the presence of turbulence, using it to determine the stability of a level of the atmosphere (Wallace and Hobbs, 2006). As long as values of bulk-Richardson number are less than 0.25 the air flow is considered as turbulent (Glickman, 2000) but when this value is greater it is anticipated that gradually the flow becomes laminar (Wallace and Hobbs, 2006). Nevertheless, bulk-Richardson number gives reasonable estimates of PBL height taking bulkRichardson number in the interval of 0.2 < Ricb < 0.5 (Zilitinkevich and Baklanov, 2001). Some of bulk-Richardson’s number advantages are the fact that it does not require resolution of the capping inversion (when it exists) and allows for a continuous transition between the stable and unstable boundary layer. The uncertainties with this method can reach 50% of the estimated height for heights lower than 1 km but they are smaller to higher heights (Seidel Dian et al., 2010). The Radiosonde data used in this study have been derived from the launches at Thessaloniki’s airport at 12:00 UTC for the time period of the study between 01/06/2006 and 31/03/2011. The Radiosonde data were provided from Wyoming University’s site (http://weather.uwyo.edu/upperair/sounding.html).

layer in the deterministic atmospheric model of ECMWF uses a boundary layer height from an entraining parcel model (ECMWF, 2009b). ECMWF model defines the top of the PBL as the level where the bulk-Richardson number (Eq. (1)), based on the difference between quantities at that level and the lowest model level, reaches the critical value of 0.25 (Troen and Mahrt, 1986). The bulkRichardson number is essentially the ratio of stability to vertical wind shear and may reach this critical value at a height somewhat below the PBL top as defined by other means (Palm et al., 2005). If the PBL height is found to be between two model levels, the exact height is calculated through linear interpolation. The PBL height analysis of the operational early-delivery assimilation system of ECMWF consists of two 6 h 4D-Var analysis cycles, at 00:00 and 12:00 UTC. The deterministic and ensemble prediction forecasts of ECMWF are based on the analyses of the early-delivery system (Persson and Grazzini, 2007). A very large amount of observations from various sources is introduced in the data assimilation system. Typically, before the quality control there is a total of 75 million pieces of data available worldwide, around 98% from satellites, in a 12 h period (Persson and Grazzini, 2005). These data are divided into surface observations, upper-air observations from Radiosondes, aircrafts, and satellite observations (ECMWF, 2009a). It is noted that during the period of our study (2006e2011) the deterministic ECMWF model used 91 vertical levels up to 0.01 hPa, with a high vertical resolution in the boundary layer (approximately 14 hybrid levels in the lowest 150 hPa). In this study, the height of the model topography is added to the grid-point values of ECMWF PBL heights in order to make them comparable to the satellite data that provide heights above sea level. The PBL height from the ECMWF model is chosen in such a way as to correspond to the nearest CALIPSO satellite crossing point to each city at 12:00 UTC.

2.3. PBL heights from ECMWF 2.4. Methodology ECMWF model provides a diagnostic of the PBL height at 12hourly intervals. The PBL heights became available at a 0.25ｰ 0.25ｰ latitude-longitude resolution. The parameterization of the mixed

The objective of this study is to evaluate the PBL height derived from Level 2 aerosol Layer products of CALIPSO satellite with the

Fig. 1. Study region, Thessaloniki. The satellite overpass close to Thessaloniki (max 40.81 N, 24 E, min 40.8 N, 22.4 E). CALIPSO covers Thessaloniki’s area by two overpass zones (black circles), at about 40 km and 80 km from Thessaloniki’s airport.


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Fig. 2. Bar chart of PBL height’s seasonal variation by radiosondes (green), CALIPSO (blue) and ECMWF model (red) in metres for Thessaloniki. The number of available data per month is shown at the top of each column. For all measurement methods varies from 10 to 2. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

equivalent PBL height from ECMWF model and Radiosondes. The analysis was carried out for Thessaloniki, Greece (lat 40.6 and long 22.97 ) for a period of almost 5 years (between 01/07/2006 and 31/ 03/2011). In order to select the most appropriate data for the needs of the current study, we followed the methodology and criteria below: 1) A grid that included the city of Thessaloniki was selected initially. Following the methodology of Wu et al. (2010), the closest CALIPSO overpass distance selected for our comparison was 90 km from the coordinates of the Thessaloniki’s airport (where the radiosondes are systematically launched). As it is seen in Fig. 1, this area corresponds to two CALIPSO overpasses over Thessaloniki with mean distances about 40 km and 80 km from Thessaloniki’s airport. We tested the measurement variability within the limit of 90 km from the airport and we found that the distance does not affect the variance of measurements within this limit (VAR ¼ 683,310.8 m2 for mean distance of 40 km from Thessaloniki’s airport and VAR ¼ 704,664.7 m2 for mean distance of 80 km from Thessaloniki’s airport). 2) Following the work of Wu et al. (2010), we rejected among all cases, those with very thin layers (