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.

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.

scholarly journals Investigating the Impact of Soil Moisture and Atmospheric Stability on Cloud Development and Distribution Using a Coupled Large-Eddy Simulation and Land Surface Model

2011 ◽  
Vol 12 (5) ◽  
pp. 787-804 ◽  
Author(s):  
Hsin-Yuan Huang ◽  
Steven A. Margulis
Keyword(s):  
Thermal Stability ◽  
Soil Moisture ◽  
Land Surface ◽  
Atmospheric Stability ◽  
Land Surface Model ◽  
Coupled Model ◽  
Surface Fluxes ◽  
Surface Model ◽  
Eddy Simulation ◽  
Cloud Development

Abstract The influence of soil moisture and atmospheric thermal stability on surface fluxes, boundary layer characteristics, and cloud development are investigated using a coupled large-eddy simulation (LES)–land surface model (LSM) framework. The study day from the Cabauw site in the central part of the Netherlands has been studied to examine the soil moisture–cloud feedback using a parameterized single-column model (SCM) in previous work. Good agreement is seen in the comparison between coupled model results and observations collected at the Cabauw eddy-covariance tower. Simulation results confirm the hypothesis that both surface fluxes and atmospheric boundary layer (ABL) states are strongly affected by soil moisture and atmospheric stability, which was proposed by a previous study using an SCM with simple parameterization. While the ABL-top cloud development is a nonmonotonic function of surface water content under different thermal stability conditions, coupled model simulations find that weak thermal stability has significant impacts on both thermal and moisture fluxes and variances near the entrainment zone, especially for the dry surface cases. Additionally, the impacts of ABL-top stability on thermal and moisture entrainment processes are in a different magnitude. The explicitly resolved cloud cover fraction increases with increasing soil moisture only occurs in cases with strong atmospheric stability, and an opposite result is seen when weak atmospheric stability exists. The elevation of cloud base highly depends on the strength of sensible heat flux. However, results of cloud thickness show that a dry surface with weak thermal stability is able to form a large amount of cumulus cloud, even if the soil provides less water vapor.

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 An Empirical Investigation of Convective Planetary Boundary Layer Evolution and Its Relationship with the Land Surface

2005 ◽  
Vol 44 (6) ◽  
pp. 917-932 ◽  
Author(s):  
Joseph A. Santanello ◽  
Mark A. Friedl ◽  
William P. Kustas
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Surface Properties ◽  
Planetary Boundary Layer ◽  
Time Scales ◽  
Land Surface ◽  
Specific Humidity ◽  
Near Surface ◽  
Convective Planetary Boundary Layer ◽  
Daily Time

Abstract Relationships among convective planetary boundary layer (PBL) evolution and land surface properties are explored using data from the Atmospheric Radiation Measurement Program Cloud and Radiation Test Bed in the southern Great Plains. Previous attempts to infer surface fluxes from observations of the PBL have been constrained by difficulties in accurately estimating and parameterizing the conservation equation and have been limited to multiday averages or small samples of daily case studies. Using radiosonde and surface flux data for June, July, and August of 1997, 1999, and 2001, a conservation approach was applied to 132 sets of daily observations. Results highlight the limitations of using this method on daily time scales caused by the diurnal variability and complexity of entrainment. A statistical investigation of the relationship among PBL and both land surface and near-surface properties that are not explicitly included in conservation methods indicates that atmospheric stability in the layer of PBL growth is the most influential variable controlling PBL development. Significant relationships between PBL height and soil moisture, 2-m potential temperature, and 2-m specific humidity are also identified through this analysis, and it is found that 76% of the variance in PBL height can be explained by observations of stability and soil water content. Using this approach, it is also possible to use limited observations of the PBL to estimate soil moisture on daily time scales without the need for detailed land surface parameterizations. In the future, the general framework that is presented may provide a means for robust estimation of near-surface soil moisture and land surface energy balance over regional scales.

Adjoint retrieval of prognostic land surface model variables for an NWP model: Assimilation of ground surface temperature

2010 ◽  
Vol 2 (2) ◽  
Author(s):  
Diandong Ren
Keyword(s):  
Soil Moisture ◽  
Soil Temperature ◽  
Land Surface ◽  
Surface Soil ◽  
Land Surface Model ◽  
Initial Guess ◽  
Surface Model ◽  
Soil Moisture Condition ◽  
Wide Range ◽  
Surface Soil Temperature

AbstractBased on a 2-layer land surface model, a rather general variational data assimilation framework for estimating model state variables is developed. The method minimizes the error of surface soil temperature predictions subject to constraints imposed by the prediction model. Retrieval experiments for soil prognostic variables are performed and the results verified against model simulated data as well as real observations for the Oklahoma Atmospheric Surface layer Instrumentation System (OASIS). The optimization scheme is robust with respect to a wide range of initial guess errors in surface soil temperature (as large as 30 K) and deep soil moisture (within the range between wilting point and saturation). When assimilating OASIS data, the scheme can reduce the initial guess error by more than 90%, while for Observing Simulation System Experiments (OSSEs), the initial guess error is usually reduced by over four orders of magnitude.Using synthetic data, the robustness of the retrieval scheme as related to information content of the data and the physical meaning of the adjoint variables and their use in sensitivity studies are investigated. Through sensitivity analysis, it is confirmed that the vegetation coverage and growth condition determine whether or not the optimally estimated initial soil moisture condition leads to an optimal estimation of the surface fluxes. This reconciles two recent studies.With the real data experiments, it is shown that observations during the daytime period are the most effective for the retrieval. Longer assimilation windows result in more accurate initial condition retrieval, underlining the importance of information quantity, especially for schemes assimilating noisy observations.

scholarly journals Development of a Unified Land Model for Prediction of Surface Hydrology and Land–Atmosphere Interactions

2011 ◽  
Vol 12 (6) ◽  
pp. 1299-1320 ◽  
Author(s):  
Ben Livneh ◽  
Pedro J. Restrepo ◽  
Dennis P. Lettenmaier
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Climate Models ◽  
A Priori ◽  
Model Performance ◽  
Surface Flux ◽  
Surface Fluxes ◽  
Frozen Soil ◽  
Surface Model ◽  
Soil Moisture Accounting

Abstract A unified land model (ULM) is described that combines the surface flux parameterizations in the Noah land surface model (used in most of NOAA’s coupled weather and climate models) with the Sacramento Soil Moisture Accounting model (Sac; used for hydrologic prediction within the National Weather Service). The motivation was to develop a model that has a history of strong hydrologic performance while having the ability to be run in the coupled land–atmosphere environment. ULM takes the vegetation, snow model, frozen soil, and evapotranspiration schemes from Noah and merges them with the soil moisture accounting scheme from Sac. ULM surface fluxes, soil moisture, and streamflow simulations were evaluated through comparisons with observations from the Ameriflux (surface flux), Illinois Climate Network (soil moisture), and Model Parameter Estimation Experiment (MOPEX; streamflow) datasets. Initially, a priori parameters from Sac and Noah were used, which resulted in ULM surface flux simulations that were comparable to those produced by Noah (Sac does not predict surface energy fluxes). ULM with the a priori parameters had streamflow simulation skill that was generally similar to Sac’s, although it was slightly better (worse) for wetter (more arid) basins. ULM model performance using a set of parameters identified via a Monte Carlo search procedure lead to substantial improvements relative to the a priori parameters. A scheme for transfer of parameters from streamflow simulations to nearby flux and soil moisture measurement points was also evaluated; this approach did not yield conclusive improvements relative to the a priori parameters.

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.

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.

scholarly journals Understanding the Impacts of Soil Moisture Initial Conditions on NWP in the Context of Land–Atmosphere Coupling

2019 ◽  
Vol 20 (5) ◽  
pp. 793-819 ◽  
Author(s):  
Joseph A. Santanello Jr. ◽  
Patricia Lawston ◽  
Sujay Kumar ◽  
Eli Dennis
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Land Surface ◽  
Initial Conditions ◽  
Land Surface Model ◽  
Surface Model ◽  
Coupled Models ◽  
Wide Range ◽  
Soil Moisture Initialization

Abstract The role of soil moisture in NWP has gained more attention in recent years, as studies have demonstrated impacts of land surface states on ambient weather from diurnal to seasonal scales. However, soil moisture initialization approaches in coupled models remain quite diverse in terms of their complexity and observational roots, while assessment using bulk forecast statistics can be simplistic and misleading. In this study, a suite of soil moisture initialization approaches is used to generate short-term coupled forecasts over the U.S. Southern Great Plains using NASA’s Land Information System (LIS) and NASA Unified WRF (NU-WRF) modeling systems. This includes a wide range of currently used initialization approaches, including soil moisture derived from “off the shelf” products such as atmospheric models and land data assimilation systems, high-resolution land surface model spinups, and satellite-based soil moisture products from SMAP. Results indicate that the spread across initialization approaches can be quite large in terms of soil moisture conditions and spatial resolution, and that SMAP performs well in terms of heterogeneity and temporal dynamics when compared against high-resolution land surface model and in situ soil moisture estimates. Case studies are analyzed using the local land–atmosphere coupling (LoCo) framework that relies on integrated assessment of soil moisture, surface flux, boundary layer, and ambient weather, with results highlighting the critical role of inherent model background biases. In addition, simultaneous assessment of land versus atmospheric initial conditions in an integrated, process-level fashion can help address the question of whether improvements in traditional NWP verification statistics are achieved for the right reasons.

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