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Joseph A. Santanello Jr. and Toby N. Carlson

Abstract

Rapid soil-surface drying, which is called “decoupling,” accompanied by an increase in near-surface air temperature and sensible heat flux, is typically confined to the top 1–2 cm of the soil, while the deeper layers remain relatively moist. Because decoupling depends also on a precise knowledge of fractional vegetation cover, soil properties, and soil water content, an accurate knowledge of these parameters is essential for making good predictions of temperature and humidity. Accordingly, some simulations centered on the Atmospheric Radiation Measurement Program Cloud and Radiation Test Bed Southern Great Plains site in Kansas and Oklahoma using a high-resolution substrate layer (Simulator for Hydrology and Energy Exchange at the Land Surface), the Fifth-Generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model, and derived and default values for soil water content and fractional vegetation cover are presented. In so doing, the following points are made: 1) decoupling occurs only within certain threshold ranges of soil water content that are closely related to the soil type and 2) a knowledge of fractional vegetation cover derived from concurrent observations is necessary for capturing the spatial variation in rapid soil drying in forecast models.

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Joshua K. Roundy and Joseph A. Santanello

Abstract

Feedbacks between the land and the atmosphere can play an important role in the water cycle, and a number of studies have quantified land–atmosphere (LA) interactions and feedbacks through observations and prediction models. Because of the complex nature of LA interactions, the observed variables are not always available at the needed temporal and spatial scales. This work derives the Coupling Drought Index (CDI) solely from satellite data and evaluates the input variables and the resultant CDI against in situ data and reanalysis products. NASA’s Aqua satellite and retrievals of soil moisture and lower-tropospheric temperature and humidity properties are used as input. Overall, the Aqua-based CDI and its inputs perform well at a point, spatially, and in time (trends) compared to in situ and reanalysis products. In addition, this work represents the first time that in situ observations were utilized for the coupling classification and CDI. The combination of in situ and satellite remote sensing CDI is unique and provides an observational tool for evaluating models at local and large scales. Overall, results indicate that there is sufficient information in the signal from simultaneous measurements of the land and atmosphere from satellite remote sensing to provide useful information for applications of drought monitoring and coupling metrics.

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Ahmed B. Tawfik, Paul A. Dirmeyer, and Joseph A. Santanello Jr.

Abstract

This study extends the heated condensation framework (HCF) presented in Tawfik and Dirmeyer to include variables for describing the convective background state of the atmosphere used to quantify the contribution of the atmosphere to convective initiation within the context of land–atmosphere coupling. In particular, the ability for the full suite of HCF variables to 1) quantify the amount of latent and sensible heat energy necessary for convective initiation, 2) identify the transition from moistening advantage to boundary layer growth advantage, 3) identify locally originating convection, and 4) compare models and observations, directly highlighting biases in the convective state, is demonstrated. These capabilities are illustrated for a clear-sky and convectively active day over the Atmospheric Radiation Measurement Program Southern Great Plains central station using observations, the Rapid Update Cycle (RUC) operational model, and the North American Regional Reanalysis (NARR). The clear-sky day had a higher and unattainable convective threshold, making convective initiation unlikely. The convectively active day had a lower threshold that was attained by midafternoon, reflecting local convective triggering. Compared to observations, RUC tended to have the most difficulty representing the convective state and captured the threshold for the clear-sky case only because of compensating biases in the moisture and temperature profiles. Despite capturing the observed moisture profile very well, a stronger surface inversion in NARR returned overestimates in the convective threshold. The companion paper applies the HCF variables introduced here across the continental United States to examine the climatological behavior of convective initiation and local land–atmosphere coupling.

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Joseph A. Santanello Jr., Mark A. Friedl, and Michael B. Ek

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.

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Ahmed B. Tawfik, Paul A. Dirmeyer, and Joseph A. Santanello Jr.

Abstract

This is Part II of a two-part study introducing the heated condensation framework (HCF), which quantifies the potential convective state of the atmosphere in terms of land–atmosphere interactions. Part I introduced the full suite of HCF variables and applied them to case studies with observations and models over a single location in the southern Great Plains. It was shown in Part I that the HCF was capable of identifying locally initiated convection and quantifying energetically favorable pathways for initiation. Here, the HCF is applied to the entire conterminous United States and the climatology of convective initiation (CI) in relation to local land–atmosphere coupling (LoCo) is explored for 34 summers (June–August) using the North American Regional Reanalysis (NARR) and observations. NARR is found to be capable of capturing the convective threshold (buoyant mixing potential temperature θ BM) and energy advantage transition (energy advantage potential temperature θ adv) for most of the United States. However, there are compensating biases in the components of moisture q mix and temperature q*, resulting in low θ BM biases for the wrong reason. The HCF has been used to show that local CI occurred over the Rocky Mountains and the southern Great Plains 35%–65% of the time. Finally, the LoCo process chain has been recast in light of the HCF. Both positive and negative soil moisture–convective feedbacks are possible, with negative feedbacks producing a stronger response in CI likelihood under weak convective inhibition. Positive feedbacks are present but weaker.

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Joseph A. Santanello Jr., Patricia Lawston, Sujay Kumar, and Eli Dennis

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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Benjamin F. Zaitchik, Joseph A. Santanello, Sujay V. Kumar, and Christa D. Peters-Lidard

Abstract

Positive soil moisture–precipitation feedbacks can intensify heat and prolong drought under conditions of precipitation deficit. Adequate representation of these processes in regional climate models is, therefore, important for extended weather forecasts, seasonal drought analysis, and downscaled climate change projections. This paper presents the first application of the NASA Unified Weather Research and Forecasting Model (NU-WRF) to simulation of seasonal drought. Simulations of the 2006 southern Great Plains drought performed with and without soil moisture memory indicate that local soil moisture feedbacks had the potential to concentrate precipitation in wet areas relative to dry areas in summer drought months. Introduction of a simple dynamic surface albedo scheme that models albedo as a function of soil moisture intensified the simulated feedback pattern at local scale—dry, brighter areas received even less precipitation while wet, whereas darker areas received more—but did not significantly change the total amount of precipitation simulated across the drought-affected region. This soil-moisture-mediated albedo land–atmosphere coupling pathway is structurally excluded from standard versions of WRF.

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Jinwoong Yoo, Joseph A. Santanello Jr., Marshall Shepherd, Sujay Kumar, Patricia Lawston, and Andrew M. Thomas

Abstract

An investigation of Tropical Cyclone (TC) Kelvin in February 2018 over northeast Australia was conducted to understand the mechanisms of the brown ocean effect (BOE) and to develop a comprehensive analysis framework for landfalling TCs in the process. NASA’s Land Information System (LIS) coupled to the NASA Unified WRF (NU-WRF) system was employed as the numerical model framework for 12 land/soil moisture perturbation experiments. Impacts of soil moisture and surface enthalpy flux conditions on TC Kelvin were investigated by closely evaluating simulated track and intensity, midlevel atmospheric thermodynamic properties, vertical wind shear, total precipitable water (TPW), and surface moisture flux. The results suggest that there were recognized differentiations among the sensitivity simulations as a result of land surface (e.g., soil moisture and texture) conditions. However, the intensification of TC Kelvin over land was more strongly related to atmospheric moisture advection and the diurnal cycle of solar radiation (i.e., radiative cooling) than to overall soil moisture conditions or surface fluxes. The analysis framework employed here for TC Kelvin can serve as a foundation to specifically quantify the factors governing the BOE. It also demonstrates that the BOE is not a binary influence (i.e., all or nothing), but instead operates in a continuum from largely to minimally influential such that it could be utilized to help improve prediction of inland effects for all landfalling TCs.

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Joseph A. Santanello Jr., Christa D. Peters-Lidard, and Sujay V. Kumar

Abstract

The inherent coupled nature of earth’s energy and water cycles places significant importance on the proper representation and diagnosis of land–atmosphere (LA) interactions in hydrometeorological prediction models. However, the precise nature of the soil moisture–precipitation relationship at the local scale is largely determined by a series of nonlinear processes and feedbacks that are difficult to quantify. To quantify the strength of the local LA coupling (LoCo), this process chain must be considered both in full and as individual components through their relationships and sensitivities. To address this, recent modeling and diagnostic studies have been extended to 1) quantify the processes governing LoCo utilizing the thermodynamic properties of mixing diagrams, and 2) diagnose the sensitivity of coupled systems, including clouds and moist processes, to perturbations in soil moisture. This work employs NASA’s Land Information System (LIS) coupled to the Weather Research and Forecasting (WRF) mesoscale model and simulations performed over the U.S. Southern Great Plains. The behavior of different planetary boundary layers (PBL) and land surface scheme couplings in LIS–WRF are examined in the context of the evolution of thermodynamic quantities that link the surface soil moisture condition to the PBL regime, clouds, and precipitation. Specifically, the tendency toward saturation in the PBL is quantified by the lifting condensation level (LCL) deficit and addressed as a function of time and space. The sensitivity of the LCL deficit to the soil moisture condition is indicative of the strength of LoCo, where both positive and negative feedbacks can be identified. Overall, this methodology can be applied to any model or observations and is a crucial step toward improved evaluation and quantification of LoCo within models, particularly given the advent of next-generation satellite measurements of PBL and land surface properties along with advances in data assimilation schemes.

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Joseph A. Santanello Jr., Christa D. Peters-Lidard, Sujay V. Kumar, Charles Alonge, and Wei-Kuo Tao

Abstract

Land–atmosphere interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture states. The degree of coupling between the land surface and PBL in numerical weather prediction and climate models remains largely unexplored and undiagnosed because of the complex interactions and feedbacks present across a range of scales. Furthermore, uncoupled systems or experiments [e.g., the Project for the Intercomparison of Land-Surface Parameterization Schemes (PILPS)] may lead to inaccurate water and energy cycle process understanding by neglecting feedback processes such as PBL-top entrainment. In this study, a framework for diagnosing local land–atmosphere coupling is presented using a coupled mesoscale model with a suite of PBL and land surface model (LSM) options along with observations during field experiments in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting Model (WRF) has been coupled to the Land Information System (LIS), which provides a flexible and high-resolution representation and initialization of land surface physics and states. Within this framework, the coupling established by each pairing of the available PBL schemes in WRF with the LSMs in LIS is evaluated in terms of the diurnal temperature and humidity evolution in the mixed layer. The coevolution of these variables and the convective PBL are sensitive to and, in fact, integrative of the dominant processes that govern the PBL budget, which are synthesized through the use of mixing diagrams. Results show how the sensitivity of land–atmosphere interactions to the specific choice of PBL scheme and LSM varies across surface moisture regimes and can be quantified and evaluated against observations. As such, this methodology provides a potential pathway to study factors controlling local land–atmosphere coupling (LoCo) using the LIS–WRF system, which will serve as a test bed for future experiments to evaluate coupling diagnostics within the community.

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