scholarly journals Climatology of Planetary Boundary Layer Height-Controlling Meteorological Parameters Over the Korean Peninsula

2020 ◽  
Vol 12 (16) ◽  
pp. 2571
Author(s):  
Shaik Allabakash ◽  
Sanghun Lim
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Planetary Boundary Layer ◽  
Korean Peninsula ◽  
Meteorological Parameters ◽  
Weather Forecasting ◽  
High Elevation ◽  
Transport Processes ◽  
Surface Fluxes ◽  
Pollution Transport

Planetary boundary layer (PBL) height plays a significant role in climate modeling, weather forecasting, air quality prediction, and pollution transport processes. This study examined the climatology of PBL-associated meteorological parameters over the Korean peninsula and surrounding sea using data from the ERA5 dataset produced by the European Centre for Medium-range Weather Forecasts (ECMWF). The data covered the period from 2008 to 2017. The bulk Richardson number methodology was used to determine the PBL height (PBLH). The PBLH obtained from the ERA5 data agreed well with that derived from sounding and Global Positioning System Radio Occultation datasets. Significant diurnal and seasonal variability in PBLH was observed. The PBLH increases from morning to late afternoon, decreases in the evening, and is lowest at night. It is high in the summer, lower in spring and autumn, and lowest in winter. The variability of the PBLH with respect to temperature, relative humidity, surface pressure, wind speed, lower tropospheric stability, soil moisture, and surface fluxes was also examined. The growth of the PBLH was high in the spring and in southern regions due to the low soil moisture content of the surface. A high PBLH pattern is evident in high-elevation regions. Increasing trends of the surface temperature and accordingly PBLH were observed from 2008 to 2017.

Development and Evaluation of a Coupled Photosynthesis-Based Gas Exchange Evapotranspiration Model (GEM) for Mesoscale Weather Forecasting Applications

2009 ◽  
Vol 48 (2) ◽  
pp. 349-368 ◽  
Author(s):  
Dev Niyogi ◽  
Kiran Alapaty ◽  
Sethu Raman ◽  
Fei Chen
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Gas Exchange ◽  
Surface Energy ◽  
Land Surface ◽  
Weather Forecasting ◽  
Stomatal Resistance ◽  
Surface Fluxes ◽  
Surface Model ◽  
Area Index

Abstract Current land surface schemes used for mesoscale weather forecast models use the Jarvis-type stomatal resistance formulations for representing the vegetation transpiration processes. The Jarvis scheme, however, despite its robustness, needs significant tuning of the hypothetical minimum-stomatal resistance term to simulate surface energy balances. In this study, the authors show that the Jarvis-type stomatal resistance/transpiration model can be efficiently replaced in a coupled land–atmosphere model with a photosynthesis-based scheme and still achieve dynamically consistent results. To demonstrate this transformative potential, the authors developed and coupled a photosynthesis, gas exchange–based surface evapotranspiration model (GEM) as a land surface scheme for mesoscale weather forecasting model applications. The GEM was dynamically coupled with a prognostic soil moisture–soil temperature model and an atmospheric boundary layer (ABL) model. This coupled system was then validated over different natural surfaces including temperate C4 vegetation (prairie grass and corn field) and C3 vegetation (soybean, fallow, and hardwood forest) under contrasting surface conditions (such as different soil moisture and leaf area index). Results indicated that the coupled model was able to realistically simulate the surface fluxes and the boundary layer characteristics over different landscapes. The surface energy fluxes, particularly for latent heat, are typically within 10%–20% of the observations without any tuning of the biophysical–vegetation characteristics, and the response to the changes in the surface characteristics is consistent with observations and theory. This result shows that photosynthesis-based transpiration/stomatal resistance models such as GEM, despite various complexities, can be applied for mesoscale weather forecasting applications. Future efforts for understanding the different scaling parameterizations and for correcting errors for low soil moisture and/or wilting vegetation conditions are necessary to improve model performance. Results from this study suggest that the GEM approach using the photosynthesis-based soil vegetation atmosphere transfer (SVAT) scheme is thus superior to the Jarvis-based approaches. Currently GEM is being implemented within the Noah land surface model for the community Weather Research and Forecasting (WRF) Advanced Research Version Modeling System (ARW) and the NCAR high-resolution land data assimilation system (HRLDAS), and validation is under way.

Development and Testing of a Surface Flux and Planetary Boundary Layer Model for Application in Mesoscale Models

1995 ◽  
Vol 34 (1) ◽  
pp. 16-32 ◽  
Author(s):  
Jonathan E. Pleim ◽  
Aijun Xiu
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Planetary Boundary Layer ◽  
Land Surface ◽  
Field Experiments ◽  
Weather Prediction ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Global Climate Models ◽  
Pbl Model

Abstract Although the development of soil, vegetation, and atmosphere interaction models has been driven primarily by the need for accurate simulations of long-term energy and moisture budgets in global climate models, the importance of these processes at smaller scales for short-term numerical weather prediction and air quality studies is becoming more appreciated. Planetary boundary layer (PBL) development is highly dependent on the partitioning of the available net radiation into sensible and latent heat fluxes. Therefore, adequate treatmentof surface properties such as soil moisture and vegetation characteristics is essential for accurate simulation of PBL development, convective and low-level cloud processes, and the temperature and humidity of boundary layer air. In this paper, the development ofa simple coupled surface and PBL model, which is planned for incorporation into the Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM4/5), is described. The soil-vegetation model is based on a simple force-restore algorithm with explicit soil moisture and evapotranspiration. The PBL model is a hybrid of nonlocal closure for convective conditions and eddy diffusion for all other conditions. A one-dimensional version of the model has been applied to several case studies from field experiments in both dry desert-like conditions (Wangara) and moist vegetated conditions(First International Satellite Land Surface Climatology Project Field Experiment) to demonstrate the model's ability to realistically simulate surface fluxes as well as PBL development. This new surface-PBL model is currently being incorporated into the MM4-MM5 system.

scholarly journals Convective Planetary Boundary Layer Interactions with the Land Surface at Diurnal Time Scales: Diagnostics and Feedbacks

2007 ◽  
Vol 8 (5) ◽  
pp. 1082-1097 ◽  
Author(s):  
Joseph A. Santanello ◽  
Mark A. Friedl ◽  
Michael B. Ek
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Planetary Boundary Layer ◽  
Mixed Layer ◽  
Land Surface ◽  
Atmospheric Stability ◽  
Surface Fluxes ◽  
Surface Model ◽  
Wide Range ◽  
Convective Planetary Boundary Layer

Abstract The convective planetary boundary layer (PBL) integrates surface fluxes and conditions over regional and diurnal scales. As a result, the structure and evolution of the PBL contains information directly related to land surface states. To examine the nature and magnitude of land–atmosphere coupling and the interactions and feedbacks controlling PBL development, the authors used a large sample of radiosonde observations collected at the southern Atmospheric Research Measurement Program–Great Plains Cloud and Radiation Testbed (ARM-CART) site in association with simulations of mixed-layer growth from a single-column PBL/land surface model. The model accurately predicts PBL evolution and realistically simulates thermodynamics associated with two key controls on PBL growth: atmospheric stability and soil moisture. The information content of these variables and their influence on PBL height and screen-level temperature can be characterized using statistical methods to describe PBL–land surface coupling over a wide range of conditions. Results also show that the first-order effects of land–atmosphere coupling are manifested in the control of soil moisture and stability on atmospheric demand for evapotranspiration and on the surface energy balance. Two principal land–atmosphere feedback regimes observed during soil moisture drydown periods are identified that complicate direct relationships between PBL and land surface properties, and, as a result, limit the accuracy of uncoupled land surface and traditional PBL growth models. In particular, treatments for entrainment and the role of the residual mixed layer are critical to quantifying diurnal land–atmosphere interactions.

scholarly journals Estimating Daytime Planetary Boundary Layer Heights over a Valley from Rawinsonde Observations at a Nearby Airport: An Application to the Page Valley in Virginia, United States

2016 ◽  
Vol 55 (3) ◽  
pp. 791-809 ◽  
Author(s):  
Temple R. Lee ◽  
Stephan F. J. De Wekker
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Weather Forecasting ◽  
Wrf Model ◽  
Heat Fluxes ◽  
Weather Research And Forecasting ◽  
Dispersion Modeling ◽  
Blue Ridge Mountains ◽  
Terrain Following ◽  
Regional Reanalysis

AbstractThe planetary boundary layer (PBL) height is an essential parameter required for many applications, including weather forecasting and dispersion modeling for air quality. Estimates of PBL height are not easily available and often come from twice-daily rawinsonde observations at airports, typically at 0000 and 1200 UTC. Questions often arise regarding the applicability of PBL heights retrieved from these twice-daily observations to surrounding locations. Obtaining this information requires knowledge of the spatial variability of PBL heights. This knowledge is particularly limited in regions with mountainous terrain. The goal of this study is to develop a method for estimating daytime PBL heights in the Page Valley, located in the Blue Ridge Mountains of Virginia. The approach includes using 1) rawinsonde observations from the nearest sounding station [Dulles Airport (IAD)], which is located 90 km northeast of the Page Valley, 2) North American Regional Reanalysis (NARR) output, and 3) simulations with the Weather Research and Forecasting (WRF) Model. When selecting days on which PBL heights from NARR compare well to PBL heights determined from the IAD soundings, it is found that PBL heights are higher (on the order of 200–400 m) over the Page Valley than at IAD and that these differences are typically larger in summer than in winter. WRF simulations indicate that larger sensible heat fluxes and terrain-following characteristics of PBL height both contribute to PBL heights being higher over the Page Valley than at IAD.

Optimizing cloud cover prediction by the Ensemble for Stochastic Integration of Atmospheric Simulations (ESIAS)

2021 ◽  
Author(s):  
Yen-Sen Lu ◽  
Philipp Franke ◽  
Dorit Jerger
Keyword(s):  
Boundary Layer ◽  
Solar Radiation ◽  
Planetary Boundary Layer ◽  
Cloud Cover ◽  
Weather Forecasting ◽  
Extreme Weather ◽  
Atmospheric Modeling ◽  
The Other ◽  
Extreme Weather Events ◽  
Weather Events

<p>ESIAS is an atmospheric modeling system including the ensemble version of the Weather Forecasting and Research Model (WRF V3.7.1) and the ensemble version of the EURopean Air pollution Dispersion-Inverse Model (EURAD-IM), the latter uses the output of the WRF model to calculate, amongst others, the transportation of aerosols. <!-- Maybe you can make more clear that only the wrf ensemble is used in this presentation. -->To capture extreme weather events causing the uncertainty in the solar radiation and wind speed for the renewable energy industry, we employ ESIAS by using stochastic schemes, such as Stochastically Perturbed Parameterization Tendency (SPPT) and Stochastic Kinetic Energy Backscatter (SKEBS) schemes, to generate the random fields for ensembles of up to 4096 members.</p><p>     Our first goal is to produce 48 hourly weather predictions for the European domain with a 20 KM horizontal resolution to capture extreme weather events affecting wind, solar radiation, and cloud cover forecasts. We use the ensemble capability of ESIAS to optimize the physics configuration of WRF to have a more precise weather prediction. A total of 672 ensemble members are generated to study the effect of different microphysical schemes, cumulus schemes, and planetary boundary layer parameterization schemes. We examine our simulation outputs with 288 simulation hours in 2015 using model input from the Global Ensemble Forecast System (GEFS). Our results are validated by the cloud cover data from EUMETSAT CMSAF. Besides the precision of weather forecasting, we also determine the greatest spread by generating total 768 ensemble members: 16 stochastic members for each different configurations of physical parameterizations (48 combinations). The optimization of WRF will help for improving the air quality prediction<!-- 16 member out of 48 configurations? Is this a mistake? Otherwise maybe you can be a bit more precise --><!-- I agree with Philipp, this is most unclear. --><!-- Reply to Jerger, Dorit (01/07/2021, 17:15): "..." Well I tried my best for it. The “blue” and the “cross-out red” ones are the two versions, hopefully the “blue” one is better than the “cross-out red” one. --> by EURAD-IM, which will be demonstrated on a test case basis.</p><p>     Our results show that for the performed analysis the Community Atmosphere Model (CAM) 5.1, WRF Single-Moment 6-class scheme (WSM6), and the Goddard microphysics outstand the other 11 microphysics parameterizations, where the highest daily average matching rate is 64.2%. The Mellor–Yamada Nakanishi Niino (MYNN) 2 and MYNN3 schemes give better results compared to the other 8 planetary boundary layer schemes, and Grell 3D (Grell-3) works generally well with the above mentioned physical schemes. Overall, the combination of Goddard and MYNN3 produces the greatest spread comparing to the lowest spread (Morrison 2-moment & GFS) by 40%.</p>

scholarly journals Analyzing the turbulence in the Planetary Boundary Layer by the synergic use of remote sensing systems: Doppler wind lidar and aerosol elastic lidar

2018 ◽  
Author(s):  
Gregori de Arruda Moreira ◽  
Juan Luís Guerrero-Rascado ◽  
Jose Antonio Benavent-Oltra ◽  
Pablo Ortiz-Amezcua ◽  
Roberto Román ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Weather Forecasting ◽  
Saharan Dust ◽  
Aerosol Layer ◽  
Frequency Distributions ◽  
Sensing Systems ◽  
Turbulent Characteristics ◽  
Remote Sensing Systems

Abstract. The Planetary Boundary Layer (PBL) is the lowermost region of troposphere and endowed with turbulent characteristics, which can have mechanical or thermodynamic origins. Such behavior gives to this layer great importance, mainly in studies about pollutant dispersion and weather forecasting. However, the instruments usually applied in studies about turbulence in the PBL have limitations in spatial resolution (anemometer towers) or temporal resolution (aircrafts). In this study we propose the synergetic use of remote sensing systems (microwave radiometer [MWR], Doppler lidar [DL] and elastic lidar [EL]) to analyze the PBL behavior. Furthermore, we show how some meteorological variables such as air temperature, aerosol number density, vertical wind, relative humidity and net radiation might influence the PBL dynamic. The statistical moments of the high frequency distributions of the vertical velocity, derived from DL and of the backscattered coefficient derived from EL, are corrected by two methodologies, namely first lag and −2/3 correction. The corrected profiles present small differences when compare against the uncorrected profiles, showing low influence of noise and the viability of the proposed methodology. Two case studies were analyzed in detail, one corresponding to a well-defined PBL and another one corresponding to a situation with presence of a Saharan dust lofted aerosol layer and clouds. In both cases the results provided by the different instruments are complementary, thus the synergistic use of the different systems allow us performing a detailed monitoring of the PBL.

scholarly journals Modeling the diurnal cycle of conserved and reactive species in the convective boundary layer

2015 ◽  
Vol 8 (10) ◽  
pp. 9323-9372 ◽  
Author(s):  
D. H. Lenschow ◽  
D. Gurarie ◽  
E. G. Patton
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Chemical Reactions ◽  
Climate Models ◽  
Initial Conditions ◽  
Reactive Species ◽  
Second Order ◽  
Surface Fluxes ◽  
Great Promise ◽  
The Mean

Abstract. We have developed a one-dimensional second-order closure numerical model to study the vertical turbulent transport of trace reactive species in the convective (daytime) planetary boundary layer (CBL), which we call the Second-Order Model for Conserved and Reactive Unsteady Scalars (SOMCRUS). The temporal variation of the CBL depth is calculated using a simple mixed-layer model with a constant entrainment coefficient and zero-order discontinuity at the CBL top. We then calculate time-varying continuous profiles of mean concentrations and vertical turbulent fluxes, variances, and covariances of both conserved and chemically-reactive scalars in a diurnally-varying CBL. The set of reactive species is the O3–NO–NO2 triad. The results for both conserved and reactive species are compared with large-eddy simulations (LES) for the same free-convection case using the same boundary and initial conditions. For the conserved species, we compare three cases with different combinations of surface fluxes, and CBL and free-troposphere concentrations. We find good agreement of SOMCRUS with LES for the mean concentrations and fluxes of both conserved and reactive species except near the CBL top, where SOMCRUS predicts a somewhat shallower depth, and has sharp transitions in both the mean and turbulence variables, in contrast to more smeared out variations in the LES due to horizontal averaging. Furthermore, SOMCRUS generally underestimates the variances and species-species covariances. SOMCRUS predicts temperature-species covariances similar to LES near the surface, but much smaller magnitude peak values near the CBL top, and a change in sign of the covariances very near the CBL top, while the LES predicts a change in sign of the covariances in the lower half of the CBL. SOMCRUS is also able to estimate the intensity of segregation (the ratio of the species-species covariance to the product of their means), which can alter the rates of second-order chemical reactions; however, for the case considered here, this effect is small. The simplicity and extensibility of SOMCRUS means that it can be utilized for a broad range of turbulence mixing scenarios and sets of chemical reactions in the planetary boundary layer; it therefore holds great promise as a tool to incorporate these processes within air quality and climate models.

scholarly journals Random Sample Fitting Method to Determine the Planetary Boundary Layer Height Using Satellite-Based Lidar Backscatter Profiles

2020 ◽  
Vol 12 (23) ◽  
pp. 4006
Author(s):  
Lin Du ◽  
Ya’ni Pan ◽  
Wei Wang
Keyword(s):  
Boundary Layer ◽  
Random Sample ◽  
Planetary Boundary Layer ◽  
Weather Forecasting ◽  
Cloud Layer ◽  
Superior Performance ◽  
Planetary Boundary Layer Height ◽  
Layer Height ◽  
Boundary Layer Height ◽  
Fitting Method

The planetary boundary layer height (PBLH) is the atmospheric region closest to the earth’s surface and has important implications on weather forecasting, air quality, and climate research. However, lidar-based methods traditionally used to determine PBLH—such as the ideal profile fitting method (IPF), maximum gradient method, and wavelet covariance transform—are not only heavily influenced by cloud layers, but also rely heavily on a low signal-to-noise ratio (SNR). Therefore, a random sample fitting (RANSAF) method was proposed for PBLH detection based on combining the random sampling consensus and IPF methods. According to radiosonde measurements, the testing of simulated and satellite-based signals shows that the proposed RANSAF method can reduce the effects of the cloud layer and significantly fluctuating noise on lidar-based PBLH detection better than traditional algorithms. The low PBLH bias derived by the RANSAF method indicates that the improved algorithm has a superior performance in measuring PBLH under a low SNR or when a cloud layer exists where the traditional methods are mostly ineffective. The RANSAF method has the potential to determine regional PBLH on the basis of satellite-based lidar backscatter profiles.

Soil Moisture Feedbacks on Convection Triggers: The Role of Soil–Plant Hydrodynamics

2009 ◽  
Vol 10 (1) ◽  
pp. 96-112 ◽  
Author(s):  
Mario Siqueira ◽  
Gabriel Katul ◽  
Amilcare Porporato
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Water Vapor ◽  
Negative Feedback ◽  
Stomatal Closure ◽  
Inversion Layer ◽  
Self Regulation ◽  
Surface Fluxes ◽  
Plant Hydraulics ◽  
Wide Range

Abstract The linkages between soil moisture dynamics and convection triggers, defined here as the first crossing between the boundary layer height (hBL) and lifting condensation level (hLCL), are complicated by a large number of interacting processes occurring over a wide range of space and time scales. To progress on this problem, a soil–plant hydrodynamics model was coupled to a simplified ABL budget to explore the feedback of soil moisture on convection triggers. The soil–plant hydraulics formulation accounted mechanistically for features such as root water uptake, root water redistribution, and midday stomatal closure, all known to affect diurnal cycles of surface fluxes and, consequently, ABL growth. The ABL model considered the convective boundary layer as a slab with a discontinuity at the inversion layer. The model was parameterized using the wealth of data already collected for a maturing Loblolly pine plantation situated in the southeastern United States. A 30-day dry-down simulation was used to investigate the possible feedback mechanisms between soil moisture and convective rainfall triggers. Previous studies, which made use of surface flux measurements to drive an ABL model, have postulated that a negative feedback was possible, which could award the ecosystem with some degree of self-regulation of its water status. According to model simulation results here, this negative feedback is unlikely. However, drastic changes in external water sources to the ABL are needed for triggering convection when soil moisture is depleted. The apparent negative feedback originated from a decoupling between the water vapor sources needed to produce convection triggers and surface water vapor fluxes.

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