scholarly journals Evaluation of retrieval methods for planetary boundary layer height based on radiosonde data

2021 ◽  
Vol 14 (9) ◽  
pp. 5977-5986
Author(s):  
Hui Li ◽  
Boming Liu ◽  
Xin Ma ◽  
Shikuan Jin ◽  
Yingying Ma ◽  
...  

Abstract. Radiosonde (RS) is widely used to detect the vertical structures of the planetary boundary layer (PBL), and numerous methods have been proposed for retrieving PBL height (PBLH) from RS data. However, an algorithm that is suitable under all atmospheric conditions does not exist. This study evaluates the performance of four common PBLH algorithms under different thermodynamic stability conditions based on RS data collected from nine sites in January–December 2019. The four RS algorithms are the potential temperature gradient method (GMθ), relative humidity (RH) gradient method (GMRH), parcel method (PM) and Richardson number method (RM). Atmospheric conditions are divided into convective boundary layer (CBL), neutral boundary layer (NBL) and stable boundary layer (SBL) on the basis of the potential temperature profile. Results indicate that SBL is dominant at nighttime, whilst CBL dominates at daytime. Under all and SBL classifications, PBLH retrieved by RM is typically higher than those retrieved using the other methods. On the contrary, the PBLH result retrieved by PM is the lowest. Under CBL and NBL classifications, PBLH retrieved by PM is the highest. PBLH retrieved by GMθ and GMRH is relatively low under all classifications. Moreover, the uncertainty analysis shows that the consistency of PBLH retrieved by different algorithms is more than 80 % under CBL and NBL classifications. By contrast, the consistency of PBLH is less than 60 % under SBL classification. The average profiles and standard deviations of wind speed and potential temperature under consistent and inconsistent conditions are also investigated. The results indicate that consistent cases are typically accompanied by evident atmospheric stratification, such as a large gradient in the potential temperature profile or a low-level jet in the wind speed profile. These results indicate that the reliability of the PBLH results retrieved from RS data is affected by the structure of the boundary layer. Overall, GMθ and RM are appropriate for CBL condition. GMθ and PM are recommended for NBL condition. GMθ and GMRH are robust for SBL condition. This comprehensive comparison provides a reference for selecting the appropriate algorithm when retrieving PBLH from RS data.

2021 ◽  
Author(s):  
Hui Li ◽  
Boming Liu ◽  
Xin Ma ◽  
Shikuan Jin ◽  
Yingying Ma ◽  
...  

Abstract. Radiosonde (RS) is widely used to detect the vertical structures of the planetary boundary layer (PBL), and numerous methods have been proposed for retrieving PBL height (PBLH) from RS data. However, an algorithm that is suitable under all atmospheric conditions does not exist. This study evaluates the performance of four common PBLH algorithms under different thermodynamic stability conditions based on RS data collected from nine sites in January–December 2019. The four RS algorithms are the potential temperature gradient method (GMθ), relative humidity (RH) gradient method (GMRH), parcel method (PM) and Richardson number method (RM). Atmospheric conditions are divided into convective boundary layer (CBL), neutral boundary layer (NBL) and stable boundary layer (SBL) on the basis of the potential temperature profile. Results indicate that SBL is dominant at nighttime, whilst CBL dominates at daytime. Intercomparisons show that PBLH retrieved via RM is typically higher than those retrieved using the other methods under all and SBL conditions. PBLH retrieved using GMθ and GMRH is relatively low. PBLH from PM is the lowest under all and SBL classifications, and the highest under CBL and NBL classifications. Moreover, the uncertainty analysis shows that PBLH retrieved using different algorithms is consistent in most cases (more than 80 %) under CBL and NBL conditions. By contrast, the consistency of PBLH is less than 60 % under SBL condition. The average profiles and standard deviations of wind speed and potential temperature under consistent and inconsistent conditions indicate that consistent cases are typically accompanied by evident atmospheric stratification, such as a large gradient in the potential temperature profile or a low-level jet in the wind speed profile. These findings indicate that the reliability of the PBLH results retrieved from RS data is affected by the structure of the boundary layer. Overall, GMθ and RM are appropriate for CBL condition. GMθ and PM are recommended for NBL condition. GMθ and GMRH are robust for SBL condition. This comprehensive comparison provides a reference for selecting the appropriate algorithm when retrieving PBLH from RS data.


2018 ◽  
Vol 33 (5) ◽  
pp. 1109-1120 ◽  
Author(s):  
David E. Jahn ◽  
William A. Gallus

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.


2008 ◽  
Vol 47 (3) ◽  
pp. 752-768 ◽  
Author(s):  
Susanne Grossman-Clarke ◽  
Yubao Liu ◽  
Joseph A. Zehnder ◽  
Jerome D. Fast

Abstract A modified version of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) was applied to the arid Phoenix, Arizona, metropolitan region. The ability of the model to simulate characteristics of the summertime urban planetary boundary layer (PBL) was tested by comparing model results with observations from two field campaigns conducted in May/June 1998 and June 2001. The modified MM5 included a refined land use/cover classification and updated land use data for Phoenix and bulk approaches of characteristics of the urban surface energy balance. PBL processes were simulated by a version of MM5’s Medium-Range Forecast Model (MRF) scheme that was enhanced by new surface flux and nonlocal mixing approaches. Simulated potential temperature profiles were tested against radiosonde data, indicating that the modified MRF scheme was able to simulate vertical mixing and the evolution and height of the PBL with good accuracy and better than the original MRF scheme except in the late afternoon. During both simulation periods, it is demonstrated that the modified MM5 simulated near-surface air temperatures and wind speeds in the urban area consistently and considerably better than the standard MM5 and that wind direction simulations were improved slightly.


2013 ◽  
Vol 26 (17) ◽  
pp. 6575-6590 ◽  
Author(s):  
Axel von Engeln ◽  
João Teixeira

Abstract A planetary boundary layer (PBL) height climatology from ECMWF reanalysis data is generated and analyzed. Different methods are first compared to derive PBL heights from atmospheric temperature, pressure, and relative humidity (RH), which mostly make use of profile gradients, for example, in RH, refractivity, and virtual or potential temperature. Three methods based on the vertical gradient of RH, virtual temperature, and potential temperature were selected for the climatology generation. The RH-based method appears to capture the inversion that caps the convective boundary layer very well as a result of its temperature and humidity dependence, while the temperature-based methods appear to capture the PBL better at high latitudes. A validation of the reanalysis fields with collocated radiosonde data shows generally good agreement in terms of mean PBL height and standard deviation for the RH-based method. The generated ECMWF-based PBL height climatology shows many of the expected climatological features, such as a fairly low PBL height near the west coast of continents where stratus clouds are found and PBL growth as the air is advected over warmer waters toward the tropics along the trade winds. Large seasonal and diurnal variations are primarily found over land. The PBL height can exceed 3 km, mostly over desert areas during the day, although large values can also be found in areas such as the ITCZ. The robustness of the statistics was analyzed by using information on the percentage of outliers. Here in particular, the sea-based PBL was found to be very stable.


2020 ◽  
Vol 35 (6) ◽  
pp. 2255-2278
Author(s):  
Robert G. Fovell ◽  
Alex Gallagher

AbstractWhile numerical weather prediction models have made considerable progress regarding forecast skill, less attention has been paid to the planetary boundary layer. This study leverages High-Resolution Rapid Refresh (HRRR) forecasts on native levels, 1-s radiosonde data, and (primarily airport) surface observations across the conterminous United States. We construct temporally and spatially averaged composites of wind speed and potential temperature in the lowest 1 km for selected months to identify systematic errors in both forecasts and observations in this critical layer. We find near-surface temperature and wind speed predictions to be skillful, although wind biases were negatively correlated with observed speed and temperature biases revealed a robust relationship with station elevation. Above ≈250 m above ground level, below which radiosonde wind data were apparently contaminated by processing, biases were small for wind speed and potential temperature at the analysis time (which incorporates sonde data) but became substantial by the 24-h forecast. Wind biases were positive through the layer for both 0000 and 1200 UTC, and morning potential temperature profiles were marked by excessively steep lapse rates that persisted across seasons and (again) exaggerated at higher elevation sites. While the source or cause of these systematic errors are not fully understood, this analysis highlights areas for potential model improvement and the need for a continued and accessible archive of the data that make analyses like this possible.


2018 ◽  
Author(s):  
Konstantina Nakoudi ◽  
Elina Giannakaki ◽  
Aggeliki Dandou ◽  
Maria Tombrou ◽  
Mika Komppula

Abstract. Ground-based lidar measurements were performed at Gual Pahari measurement station, approximately 20 km South of New Delhi, India, from March 2008 to March 2009. The height of the Planetary Boundary Layer (PBL) was retrieved with a portable Raman lidar system, utilizing the modified Wavelet Covariance Transform (WCT) method. The lidar derived PBL heights were compared to radiosonde data, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite observations and two atmospheric models. The results were also analyzed on a seasonal basis. To examine the difficulties of PBL lidar detection under different meteorological and aerosol load conditions we focused on three case studies of PBL diurnal evolution. In the presence of a multiple aerosol layer structure, the WCT method exhibited high efficiency in PBL height determination. Good agreement with the European Center for Medium-range Weather Forecasts (ECMWF) and the Weather Research and Forecasting (WRF) estimations was found (r=0.69 and r=0.74, respectively) for a cumulus convection case. In the aforementioned cases, temperature, relative humidity and potential temperature radiosonde profiles were well compared to the respective WRF profiles. The Bulk Richardson Number scheme, which was applied to radiosonde profile data, was in good agreement with lidar data, especially during daytime (r=0.68). The overall comparison with CALIPSO satellite observations; namely, CALIOP Level 2 Aerosol Layer Product, was very satisfying (r=0.84), with CALIPSO Feature Detection Algorithms slightly overestimating PBL height. Lidar measurements revealed that the maximum PBL height was reached approximately three hours after the solar noon, whilst the daily evolution of the PBL was completed, on average, one hour earlier. The PBL diurnal cycle was also analyzed using ECMWF estimations, which produced a stronger cycle during the winter and pre-monsoon period. The seasonal analysis of lidar PBL heights yielded a less pronounced PBL cycle than the one expected from long term climate records. The lowest mean daytime PBL height (695 m) appeared in winter, while the highest mean daytime PBL height (1326 m) was found in the monsoon season as expected. PBL daily growth rates exhibited also a weak seasonal variability.


2018 ◽  
Vol 18 (20) ◽  
pp. 14813-14835 ◽  
Author(s):  
Liza I. Díaz-Isaac ◽  
Thomas Lauvaux ◽  
Kenneth J. Davis

Abstract. Atmospheric transport model errors are one of the main contributors to the uncertainty affecting CO2 inverse flux estimates. In this study, we determine the leading causes of transport errors over the US upper Midwest with a large set of simulations generated with the Weather Research and Forecasting (WRF) mesoscale model. The various WRF simulations are performed using different meteorological driver datasets and physical parameterizations including planetary boundary layer (PBL) schemes, land surface models (LSMs), cumulus parameterizations and microphysics parameterizations. All the different model configurations were coupled to CO2 fluxes and lateral boundary conditions from the CarbonTracker inversion system to simulate atmospheric CO2 mole fractions. PBL height, wind speed, wind direction, and atmospheric CO2 mole fractions are compared to observations during a month in the summer of 2008, and statistical analyses were performed to evaluate the impact of both physics parameterizations and meteorological datasets on these variables. All of the physical parameterizations and the meteorological initial and boundary conditions contribute 3 to 4 ppm to the model-to-model variability in daytime PBL CO2 except for the microphysics parameterization which has a smaller contribution. PBL height varies across ensemble members by 300 to 400 m, and this variability is controlled by the same physics parameterizations. Daily PBL CO2 mole fraction errors are correlated with errors in the PBL height. We show that specific model configurations systematically overestimate or underestimate the PBL height averaged across the region with biases closely correlated with the choice of LSM, PBL scheme, and cumulus parameterization (CP). Domain average PBL wind speed is overestimated in nearly every model configuration. Both planetary boundary layer height (PBLH) and PBL wind speed biases show coherent spatial variations across the Midwest, with PBLH overestimated averaged across configurations by 300–400 m in the west, and PBL winds overestimated by about 1 m s−1 on average in the east. We find model configurations with lower biases averaged across the domain, but no single configuration is optimal across the entire region and for all meteorological variables. We conclude that model ensembles that include multiple physics parameterizations and meteorological initial conditions are likely to be necessary to encompass the atmospheric conditions most important to the transport of CO2 in the PBL, but that construction of such an ensemble will be challenging due to ensemble biases that vary across the region.


Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1619
Author(s):  
Yingsai Ma ◽  
Xianhong Meng ◽  
Yinhuan Ao ◽  
Ye Yu ◽  
Guangwei Li ◽  
...  

The Loess Plateau is one land-atmosphere coupling hotspot. Soil moisture has an influence on atmospheric boundary layer development under specific early-morning atmospheric thermodynamic structures. This paper investigates the sensitivity of atmospheric convection to soil moisture conditions over the Loess Plateau in China by using the convective triggering potential (CTP)—humidity index (HIlow) framework. The CTP indicates atmospheric stability and the HIlow indicates atmospheric humidity in the low-level atmosphere. By comparing the model outcomes with the observations, the one-dimensional model achieves realistic daily behavior of the radiation and surface heat fluxes and the mixed layer properties with appropriate modifications. New CTP-HIlow thresholds for soil moisture-atmosphere feedbacks are found in the Loess Plateau area. By applying the new thresholds with long-time scales sounding data, we conclude that negative feedback is dominant in the north and west portion of the Loess Plateau; positive feedback is predominant in the south and east portion. In general, this framework has predictive significance for the impact of soil moisture on precipitation. By using this new CTP-HIlow framework, we can determine under what atmospheric conditions soil moisture can affect the triggering of precipitation and under what atmospheric conditions soil moisture has no influence on the triggering of precipitation.


2019 ◽  
Vol 23 (2) ◽  
pp. 1-27 ◽  
Author(s):  
Eugene S. Takle ◽  
Daniel A. Rajewski ◽  
Samantha L. Purdy

Abstract The Iowa Atmospheric Observatory was established to better understand the unique microclimate characteristics of a wind farm. The facility consists of a pair of 120-m towers identically instrumented to observe basic landscape–atmosphere interactions in a highly managed agricultural landscape. The towers, one within and one outside of a utility-scale low-density-array wind farm, are equipped to measure vertical profiles of temperature, wind, moisture, and pressure and can host specialized sensors for a wide range of environmental conditions. Tower measurements during the 2016 growing season demonstrate the ability to distinguish microclimate differences created by single or multiple turbines from natural conditions over homogeneous agricultural fields. Microclimate differences between the two towers are reported as contrasts in normalized wind speed, normalized turbulence intensity, potential temperature, and water vapor mixing ratio. Differences are analyzed according to conditions of no wind farm influence (i.e., no wake) versus wind farm influence (i.e., waked flow) with distance downwind from a single wind turbine or a large group of turbines. Differences are also determined for more specific atmospheric conditions according to thermal stratification. Results demonstrate agreement with most, but not all, currently available numerical flow-field simulations of large wind farm arrays and of individual turbines. In particular, the well-documented higher nighttime surface temperature in wind farms is examined in vertical profiles that confirm this effect to be a “suppression of cooling” rather than a warming process. A summary is provided of how the wind farm boundary layer differs from the natural boundary layer derived from concurrent measurements over the summer of 2016.


2020 ◽  
Vol 237 ◽  
pp. 02031
Author(s):  
Alexandros Pantazis ◽  
Alexandros Papayannis

In this work, a full set of recently developed algorithms and techniques is presented, for a single beam-single pointing lidar to be able to perform operational and independent accurate 3 Dimensional (3D) measurements, for slant range visibility, wind speed retrieval, atmospheric layers spatial distribution and categorization, as well as Planetary Boundary Layer Height (PBLH) retrieval, in real or Near Real Time (NRT).The idea behind this development was for any single lidar to be able to perform a set of accurately measured products, either mobile or stationary, with or without network connectivity with other sensors for data-information exchange. The products were determined by the needs of lidar remote scientific and commercial community, in order to be even more attractive and valuable to atmospheric scientists, meteorologists, aviation and shipping safety operators, as well as to the Space lidar community.


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