scholarly journals Spatial and Temporal Scales of Boundary Layer Wind Predictability in Response to Small-Amplitude Land Surface Uncertainty

2010 ◽  
Vol 67 (1) ◽  
pp. 217-233 ◽  
Author(s):  
Joshua P. Hacker
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Land Surface ◽  
Small Amplitude ◽  
Deep Convection ◽  
Wrf Model ◽  
Atmospheric Conditions ◽  
Temporal Scales ◽  
Spatial And Temporal Scales ◽  
Local Loss

Abstract Predictability experiments with the Weather Research and Forecast (WRF) model as a proxy for the atmosphere are analyzed to quantify the spatial and temporal scales of boundary layer wind response to land surface perturbations. Soil moisture is chosen as the land surface variable subject to uncertainty because the atmosphere is known to be sensitive to its state. A range of experiments with spatially correlated, small-amplitude perturbations to soil moisture leads to results that show the dependence of predictability on atmospheric conditions. The primary conclusions are as follows: 1) atmospheric conditions, including static instability and the presence of deep convection, determine whether large errors and local loss of predictability are possible in response to soil moisture errors; 2) the scale of soil moisture uncertainty determines scales of PBL wind predictability when the atmosphere is resistant to upscale error transfer, but when the atmosphere is sensitive the scale and magnitude of soil moisture uncertainty are not important after a few hours; and 3) nonlinear error growth is present whether or not the atmosphere is relatively sensitive to soil moisture uncertainty, leading to doubling times of minutes to hours for finite-sized perturbations. Similar results could be expected from other land surface variables or parameters that exert time-dependent forcing on the atmosphere that is similar in magnitude and scale to that of soil moisture.

scholarly journals Observed Land–Atmosphere Coupling from Satellite Remote Sensing and Reanalysis

2011 ◽  
Vol 12 (6) ◽  
pp. 1221-1254 ◽  
Author(s):  
Craig R. Ferguson ◽  
Eric F. Wood
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Land Surface ◽  
Satellite Remote Sensing ◽  
Deep Convection ◽  
Weather Prediction ◽  
Remote Sensing Data ◽  
Feedback Signal ◽  
Atmospheric Conditions ◽  
Global Land

Abstract The lack of observational data for use in evaluating the realism of model-based land–atmosphere feedback signal and strength has been deemed a major obstacle to future improvements to seasonal weather prediction by the Global Land–Atmosphere Coupling Experiment (GLACE). To address this need, a 7-yr (2002–09) satellite remote sensing data record is exploited to produce for the first time global maps of predominant coupling signals. Specifically, a previously implemented convective triggering potential (CTP)–humidity index (HI) framework for describing atmospheric controls on soil moisture–rainfall feedbacks is revisited and generalized for global application using CTP and HI from the Atmospheric Infrared Sounder (AIRS), soil moisture from the Advanced Microwave Scanning Radiometer for Earth Observing System (EOS) (AMSR-E), and the U.S. Climate Prediction Center (CPC) merged satellite rainfall product (CMORPH). Based on observations taken during an AMSR-E-derived convective rainfall season, the global land area is categorized into four convective regimes: 1) those with atmospheric conditions favoring deep convection over wet soils, 2) those with atmospheric conditions favoring deep convection over dry soils, 3) those with atmospheric conditions that suppress convection over any land surface, and 4) those with atmospheric conditions that support convection over any land surface. Classification maps are produced using both the original and modified frameworks, and later contrasted with similarly derived maps using inputs from the National Aeronautics and Space Administration (NASA) Modern Era Retrospective Analysis for Research and Applications (MERRA). Both AIRS and MERRA datasets of CTP and HI are validated using radiosonde observations. The combinations of methods and data sources employed in this study enable evaluation of not only the sensitivity of the classification schemes themselves to their inputs, but also the uncertainty in the resultant classification maps. The findings are summarized for 20 climatic regions and three GLACE coupling hot spots, as well as zonally and globally. Globally, of the four-class scheme, regions for which convection is favored over wet and dry soils accounted for the greatest and least extent, respectively. Despite vast differences among the maps, many geographically large regions of concurrence exist. Through its ability to compensate for the latitudinally varying CTP–HI–rainfall tendency characteristics observed in this study, the revised classification framework overcomes limitations of the original framework. By identifying regions where coupling persists using satellite remote sensing this study provides the first observationally based guidance for future spatially and temporally focused studies of land–atmosphere interactions. Joint distributions of CTP and HI and soil moisture, rainfall occurrence, and depth demonstrate the relevance of CTP and HI in coupling studies and their potential value in future model evaluation, rainfall forecast, and/or hydrologic consistency applications.

scholarly journals A Study of the Role of Daytime Land–Atmosphere Interactions on Nocturnal Convective Activity in the Southern Great Plains during CLASIC

2014 ◽  
Vol 15 (5) ◽  
pp. 1932-1953 ◽  
Author(s):  
Jessica M. Erlingis ◽  
Ana P. Barros
Keyword(s):  
Boundary Layer ◽  
Great Plains ◽  
Land Surface ◽  
Initial Conditions ◽  
Cold Pool ◽  
Convective System ◽  
Temporal Scales ◽  
Spatial And Temporal Scales ◽  
Southern Great Plains ◽  
Low Level

Abstract This study examines whether and how land–atmosphere interactions can have an impact on nocturnal convection over the southern Great Plains (SGP) through numerical simulations of an intense nocturnal mesoscale convective system (MCS) on 19–20 June 2007 with the Weather Research and Forecasting (WRF) Model. High-resolution nested simulations were conducted using realistic and idealized land surfaces and two planetary boundary layer (PBL) parameterizations (PBLp): Yonsei University (YSU) and Mellor–Yamada–Janjić (MYJ). Differences in timing and amount of MCS precipitation among observations and model results were examined in the light of daytime land–atmosphere interactions, nocturnal prestorm environment, and cold pool strength. At the meso-γ scale, land cover and soil type have as much of an effect on the simulated prestorm environment as the choice of PBLp: MYJ simulations exhibit strong sensitivity to changes in the land surface in contrast to negligible impact in the case of YSU. At the end of the afternoon, as the boundary layer collapses, a more homogeneous and deeper PBL (and stronger low-level shear) is evident for YSU as compared to MYJ when initial conditions and land surface properties are the same. At the meso-β scale, propagation speed is faster and organization (bow echo morphology) and cold pool strength are enhanced when nocturnal PBL heights are higher, and there is stronger low-level shear in the prestorm environment independent of the boundary layer parameterization for different land surface conditions. A comparison of one- and two-way nested MYJ results demonstrates how daytime land–atmosphere interactions modify the prestorm environment remotely through advection of low-level thermodynamic features. This remote feedback strongly impacts the MCS development phase as well as its spatial organization and propagation velocity and, consequently, nocturnal rainfall. These results indicate that synoptic- and meso-α-scale dynamics can play an important role in determining the spatial and temporal scales over which precipitation feedbacks of land–atmosphere interactions emerge regionally. Finally, this study demonstrates the high degree of uncertainty in defining the spatial and temporal scales of land–atmosphere interactions where and when organized convection is dominant.

scholarly journals Reconstructing and analyzing China's fifty-nine year (1951–2009) drought history using hydrological model simulation

2011 ◽  
Vol 15 (9) ◽  
pp. 2881-2894 ◽  
Author(s):  
Z. Y. Wu ◽  
G. H. Lu ◽  
L. Wen ◽  
C. A. Lin
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Inner Mongolia ◽  
Agricultural Drought ◽  
Daily Maximum ◽  
Severe Drought ◽  
Drought Event ◽  
Temporal Scales ◽  
Spatial And Temporal Scales ◽  
Regional Drought

Abstract. The 1951–2009 drought history of China is reconstructed using daily soil moisture values generated by the Variable Infiltration Capacity (VIC) land surface macroscale hydrology model. VIC is applied over a grid of 10 458 points with a spatial resolution of 30 km × 30 km, and is driven by observed daily maximum and minimum air temperature and precipitation from 624 long-term meteorological stations. The VIC soil moisture is used to calculate the Soil Moisture Anomaly Percentage Index (SMAPI), which can be used as a measure of the severity of agricultural drought on a global basis. We have developed a SMAPI-based drought identification procedure for practical uses in the identification of both grid point and regional drought events. As a result, a total of 325 regional drought events varying in time and strength are identified from China's nine drought study regions. These drought events can thus be assessed quantitatively at different spatial and temporal scales. The result shows that the severe drought events of 1978, 2000 and 2006 are well reconstructed, which indicates that the SMAPI is capable of identifying the onset of a drought event, its progression, as well as its termination. Spatial and temporal variations of droughts in China's nine drought study regions are studied. Our result shows that on average, up to 30% of the total area of China is prone to drought. Regionally, an upward trend in drought-affected areas has been detected in three regions (Inner Mongolia, Northeast and North) from 1951–2009. However, the decadal variability of droughts has been weak in the rest of the five regions (South, Southwest, East, Northwest, and Tibet). Xinjiang has even been showing steadily wetter since the 1950s. Two regional dry centres are discovered in China as the result of a combined analysis on the occurrence of drought events from both grid points and drought study regions. The first centre is located in the area partially covered by the North and the Northwest, which extends to the southeastern portion of Inner Mongolia and the southwest part of Northeast. The second one is found on the central to southern portion of the South. Our study demonstrates the applicability and the value of using modeled soil moisture for reconstructing drought histories, and the SMAPI is useful for analyzing drought at different spatial and temporal scales.

scholarly journals Summer temperature response to extreme soil water conditions in the Mediterranean transitional climate regime

2021 ◽  
Author(s):  
Stefano Materia ◽  
Constantin Ardilouze ◽  
Chloé Prodhomme ◽  
Markus G. Donat ◽  
Marianna Benassi ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Soil Water ◽  
Land Surface ◽  
Heat Waves ◽  
Climate Regime ◽  
Seasonal Forecasts ◽  
Near Surface ◽  
Surface Temperatures ◽  
The Mediterranean

AbstractLand surface and atmosphere are interlocked by the hydrological and energy cycles and the effects of soil water-air coupling can modulate near-surface temperatures. In this work, three paired experiments were designed to evaluate impacts of different soil moisture initial and boundary conditions on summer temperatures in the Mediterranean transitional climate regime region. In this area, evapotranspiration is not limited by solar radiation, rather by soil moisture, which therefore controls the boundary layer variability. Extremely dry, extremely wet and averagely humid ground conditions are imposed to two global climate models at the beginning of the warm and dry season. Then, sensitivity experiments, where atmosphere is alternatively interactive with and forced by land surface, are launched. The initial soil state largely affects summer near-surface temperatures: dry soils contribute to warm the lower atmosphere and exacerbate heat extremes, while wet terrains suppress thermal peaks, and both effects last for several months. Land-atmosphere coupling proves to be a fundamental ingredient to modulate the boundary layer state, through the partition between latent and sensible heat fluxes. In the coupled runs, early season heat waves are sustained by interactive dry soils, which respond to hot weather conditions with increased evaporative demand, resulting in longer-lasting extreme temperatures. On the other hand, when wet conditions are prescribed across the season, the occurrence of hot days is suppressed. The land surface prescribed by climatological precipitation forcing causes a temperature drop throughout the months, due to sustained evaporation of surface soil water. Results have implications for seasonal forecasts on both rain-fed and irrigated continental regions in transitional climate zones.

scholarly journals Land–atmosphere interactions in the tropics

2019 ◽  
Author(s):  
Pierre Gentine ◽  
Adam Massmann ◽  
Benjamin R. Lintner ◽  
Sayed Hamed Alemohammad ◽  
Rong Fu ◽  
...  
Keyword(s):  
Land Surface ◽  
Deep Convection ◽  
Lower Troposphere ◽  
Surface Fluxes ◽  
Surface Radiation ◽  
Spatial And Temporal Scales ◽  
Wide Range ◽  
Shallow Clouds ◽  
The Tropics ◽  
The Impact

Abstract. The continental tropics play a leading role in the terrestrial water and carbon cycles. Land–atmosphere interactions are integral in the regulation of surface energy, water and carbon fluxes across multiple spatial and temporal scales over tropical continents. We review here some of the important characteristics of tropical continental climates and how land–atmosphere interactions regulate them. Along with a wide range of climates, the tropics manifest a diverse array of land–atmosphere interactions. Broadly speaking, in tropical rainforests, light and energy are typically more limiting than precipitation and water supply for photosynthesis and evapotranspiration; whereas in savanna and semi-arid regions water is the critical regulator of surface fluxes and land–atmosphere interactions. We discuss the impact of the land surface, how it affects shallow clouds and how these clouds can feedback to the surface by modulating surface radiation. Some results from recent research suggest that shallow clouds may be especially critical to land–atmosphere interactions as these regulate the energy budget and moisture transport to the lower troposphere, which in turn affects deep convection. On the other hand, the impact of land surface conditions on deep convection appear to occur over larger, non-local, scales and might be critically affected by transitional regions between the climatologically dry and wet tropics.

scholarly journals Soil Moisture-Boundary Layer Feedbacks on the Loess Plateau in China Using Radiosonde Data with 1-D Atmospheric Boundary Layer Model

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1619
Author(s):  
Yingsai Ma ◽  
Xianhong Meng ◽  
Yinhuan Ao ◽  
Ye Yu ◽  
Guangwei Li ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Atmospheric Boundary Layer ◽  
Loess Plateau ◽  
Atmospheric Stability ◽  
Heat Fluxes ◽  
Radiosonde Data ◽  
Atmospheric Conditions ◽  
The Loess Plateau ◽  
The Impact

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.

scholarly journals Soil Moisture Impacts on Convective Margins

2009 ◽  
Vol 10 (4) ◽  
pp. 1026-1039 ◽  
Author(s):  
Benjamin R. Lintner ◽  
J. David Neelin
Keyword(s):  
Soil Moisture ◽  
Hot Spots ◽  
Land Surface ◽  
Convection Zone ◽  
Deep Convection ◽  
Radiative Heating ◽  
Convective Parameterization ◽  
Surface Atmosphere ◽  
Moisture Conditions ◽  
Land Region

Abstract An idealized prototype for the location of the margins of tropical land region convection zones is extended to incorporate the effects of soil moisture and associated evaporation. The effect of evaporation, integrated over the inflow trajectory into the convection zone, is realized nonlocally where the atmosphere becomes favorable to deep convection. This integrated effect produces “hot spots” of land surface–atmosphere coupling downstream of soil moisture conditions. Overall, soil moisture increases the variability of the convective margin, although how it does so is nontrivial. In particular, there is an asymmetry in displacements of the convective margin between anomalous inflow and outflow conditions that is absent when soil moisture is not included. Furthermore, the simple cases presented here illustrate how margin sensitivity depends strongly on the interplay of factors, including net top-of-the-atmosphere radiative heating, the statistics of inflow wind, and the convective parameterization.

scholarly journals Flash Flood and Extreme Rainfall Forecast through One-Way Coupling of WRF-SMAP Models: Natural Hazards in Rio de Janeiro State

Atmosphere ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 834
Author(s):  
Priscila da Cunha Luz Barcellos ◽  
Marcio Cataldi
Keyword(s):  
Natural Hazards ◽  
Land Surface ◽  
Rio De Janeiro ◽  
Flash Flood ◽  
Weather Prediction ◽  
Wrf Model ◽  
Temporal Distribution ◽  
Atmospheric Conditions ◽  
Streamflow Forecast ◽  
Janeiro State

Flash floods and extreme rains are destructive phenomena and difficult to forecast. In 2011, the mountainous region of Rio de Janeiro state suffered one of the largest natural hazards in Brazil, affecting more than 300,000 people, leaving more than 900 dead. This article simulates this natural hazard through Quantitative Precipitation Forecasting (QPF) and streamflow forecast ensemble, using 18 combinations of parameterizations between cumulus, microphysics, surface layer, planetary boundary layer, land surface and lateral contour conditions of the Weather Research and Forecasting (WRF) Model, coupling to the Soil Moisture Accounting Procedure (SMAP) hydrological model, seeking to find the best set of parametrizations for the forecasting of extreme events in the region. The results showed rainfall and streamflow forecast were underestimated by the models, reaching an error of 57.4% to QPF and 24.6% error to streamflow, and part of these errors are related to the lack of skill of the atmospheric model in predicting the intensity and the spatial-temporal distribution of rainfall. These results bring to light the limitations of numerical weather prediction, possibly due to the lack of initiatives involving the adaptation of empirical constants, intrinsic in the parametrization models, to the specific atmospheric conditions of each region of the country.

scholarly journals What climate signal is contained in decadal- to centennial-scale isotope variations from Antarctic ice cores?

2018 ◽  
Vol 14 (12) ◽  
pp. 2053-2070 ◽  
Author(s):  
Thomas Münch ◽  
Thomas Laepple
Keyword(s):  
Climate Variability ◽  
Ice Cores ◽  
Relative Magnitude ◽  
True Temperature ◽  
Large Set ◽  
Atmospheric Conditions ◽  
Temporal Scales ◽  
Simple Method ◽  
Climate Signal ◽  
Spatial And Temporal Scales

Abstract. Ice-core-based records of isotopic composition are a proxy for past temperatures and can thus provide information on polar climate variability over a large range of timescales. However, individual isotope records are affected by a multitude of processes that may mask the true temperature variability. The relative magnitude of climate and non-climate contributions is expected to vary as a function of timescale, and thus it is crucial to determine those temporal scales on which the actual signal dominates the noise. At present, there are no reliable estimates of this timescale dependence of the signal-to-noise ratio (SNR). Here, we present a simple method that applies spectral analyses to stable-isotope data from multiple cores to estimate the SNR, and the signal and noise variability, as a function of timescale. The method builds on separating the contributions from a common signal and from local variations and includes a correction for the effects of diffusion and time uncertainty. We apply our approach to firn-core arrays from Dronning Maud Land (DML) in East Antarctica and from the West Antarctic Ice Sheet (WAIS). For DML and decadal to multi-centennial timescales, we find an increase in the SNR by nearly 1 order of magnitude (∼0.2 at decadal and ∼1.0 at multi-centennial scales). The estimated spectrum of climate variability also shows increasing variability towards longer timescales, contrary to what is traditionally inferred from single records in this region. In contrast, the inferred variability spectrum for WAIS stays close to constant over decadal to centennial timescales, and the results even suggest a decrease in SNR over this range of timescales. We speculate that these differences between DML and WAIS are related to differences in the spatial and temporal scales of the isotope signal, highlighting the potentially more homogeneous atmospheric conditions on the Antarctic Plateau in contrast to the marine-influenced conditions on WAIS. In general, our approach provides a methodological basis for separating local proxy variability from coherent climate variations, which is applicable to a large set of palaeoclimate records.

The influence of the land surface on hydrometeorology and ecology: new advances from modeling and satellite remote sensing

2011 ◽  
Vol 42 (2-3) ◽  
pp. 95-112 ◽  
Author(s):  
Venkat Lakshmi ◽  
Seungbum Hong ◽  
Eric E. Small ◽  
Fei Chen
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Wrf Model ◽  
Land Surface Model ◽  
Surface Processes ◽  
Surface Model ◽  
Land Surface Processes ◽  
Area Index ◽  
Vegetation Fraction ◽  
Moisture Variation

The importance of land surface processes has long been recognized in hydrometeorology and ecology for they play a key role in climate and weather modeling. However, their quantification has been challenging due to the complex nature of the land surface amongst other reasons. One of the difficult parts in the quantification is the effect of vegetation that are related to land surface processes such as soil moisture variation and to atmospheric conditions such as radiation. This study addresses various relational investigations among vegetation properties such as Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), surface temperature (TSK), and vegetation water content (VegWC) derived from satellite sensors such as Moderate Resolution Imaging Spectroradiometer (MODIS) and EOS Advanced Microwave Scanning Radiometer (AMSR-E). The study provides general information about a physiological behavior of vegetation for various environmental conditions. Second, using a coupled mesoscale/land surface model, we examine the effects of vegetation and its relationship with soil moisture on the simulated land–atmospheric interactions through the model sensitivity tests. The Weather Research and Forecasting (WRF) model was selected for this study, and the Noah land surface model (Noah LSM) implemented in the WRF model was used for the model coupled system. This coupled model was tested through two parameterization methods for vegetation fraction using MODIS data and through model initialization of soil moisture from High Resolution Land Data Assimilation System (HRLDAS). Finally, this study evaluates the model improvements for each simulation method.

Sign in / Sign up

Export Citation Format

Share Document