scholarly journals On the Representation of Heterogeneity in Land-Surface–Atmosphere Coupling

2016 ◽  
Vol 160 (1) ◽  
pp. 157-183 ◽  
Author(s):  
Philipp de Vrese ◽  
Jan-Peter Schulz ◽  
Stefan Hagemann
Keyword(s):  
Land Surface ◽  
Surface Atmosphere

Land-surface/atmosphere exchange in high-latitude landscapes

2001 ◽  
Vol 70 (1-4) ◽  
pp. 1-3 ◽  
Author(s):  
S. Halldin ◽  
S.-E. Gryning ◽  
C. R. Lloyd
Keyword(s):  
High Latitude ◽  
Land Surface ◽  
Surface Atmosphere

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 Soil Moisture Variability in India: Relationship of Land Surface–Atmosphere Fields Using Maximum Covariance Analysis

2019 ◽  
Vol 11 (3) ◽  
pp. 335 ◽  
Author(s):  
Kishore Pangaluru ◽  
Isabella Velicogna ◽  
Geruo A ◽  
Yara Mohajerani ◽  
Enrico Ciracì ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Land Surface ◽  
Water Storage ◽  
Surface Air Temperature ◽  
Covariance Analysis ◽  
Positive Trend ◽  
Total Water ◽  
Maximum Covariance Analysis ◽  
Surface Atmosphere

This study investigates the spatial and temporal variability of the soil moisture in India using Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) gridded datasets from June 2002 to April 2017. Significant relationships between soil moisture and different land surface–atmosphere fields (Precipitation, surface air temperature, total cloud cover, and total water storage) were studied, using maximum covariance analysis (MCA) to extract dominant interactions that maximize the covariance between two fields. The first leading mode of MCA explained 56%, 87%, 81%, and 79% of the squared covariance function (SCF) between soil moisture with precipitation (PR), surface air temperature (TEM), total cloud count (TCC), and total water storage (TWS), respectively, with correlation coefficients of 0.65, −0.72, 0.71, and 0.62. Furthermore, the covariance analysis of total water storage showed contrasting patterns with soil moisture, especially over northwest, northeast, and west coast regions. In addition, the spatial distribution of seasonal and annual trends of soil moisture in India was estimated using a robust regression technique for the very first time. For most regions in India, significant positive trends were noticed in all seasons. Meanwhile, a small negative trend was observed over southern India. The monthly mean value of AMSR soil moisture trend revealed a significant positive trend, at about 0.0158 cm3/cm3 per decade during the period ranging from 2002 to 2017.

scholarly journals Effects of shrub and tree cover increase on the near-surface atmosphere in northern Fennoscandia

2017 ◽  
Vol 14 (18) ◽  
pp. 4209-4227 ◽  
Author(s):  
Johanne H. Rydsaa ◽  
Frode Stordal ◽  
Anders Bryn ◽  
Lena M. Tallaksen
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Wrf Model ◽  
Tree Cover ◽  
Atmospheric Response ◽  
Study Region ◽  
Near Surface ◽  
Positive Feedbacks ◽  
Surface Atmosphere ◽  
Northern Fennoscandia

Abstract. Increased shrub and tree cover in high latitudes is a widely observed response to climate change that can lead to positive feedbacks to the regional climate. In this study we evaluate the sensitivity of the near-surface atmosphere to a potential increase in shrub and tree cover in the northern Fennoscandia region. We have applied the Weather Research and Forecasting (WRF) model with the Noah-UA land surface module in evaluating biophysical effects of increased shrub cover on the near-surface atmosphere at a fine resolution (5.4 km  ×  5.4 km). Perturbation experiments are performed in which we prescribe a gradual increase in taller vegetation in the alpine shrub and tree cover according to empirically established bioclimatic zones within the study region. We focus on the spring and summer atmospheric response. To evaluate the sensitivity of the atmospheric response to inter-annual variability in climate, simulations were conducted for two contrasting years, one warm and one cold. We find that shrub and tree cover increase leads to a general increase in near-surface temperatures, with the highest influence seen during the snowmelt season and a more moderate effect during summer. We find that the warming effect is stronger in taller vegetation types, with more complex canopies leading to decreases in the surface albedo. Counteracting effects include increased evapotranspiration, which can lead to increased cloud cover, precipitation, and snow cover. We find that the strength of the atmospheric feedback is sensitive to snow cover variations and to a lesser extent to summer temperatures. Our results show that the positive feedback to high-latitude warming induced by increased shrub and tree cover is a robust feature across inter-annual differences in meteorological conditions and will likely play an important role in land–atmosphere feedback processes in the future.

Modelling land surface–atmosphere interactions over the Australian continent with an emphasis on the role of soil moisture

1998 ◽  
Vol 13 (3-4) ◽  
pp. 333-339 ◽  
Author(s):  
R.K. Munro ◽  
W.F. Lyons ◽  
Y. Shao ◽  
M.S. Wood ◽  
L.M. Hood ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Surface Atmosphere ◽  
Australian Continent

Implementation of Modeling the Land-Surface/Atmosphere Interactions to Mesoscale Model COAMPS

2010 ◽  
Author(s):  
Bogumil Jakubiak ◽  
Teddy Holt ◽  
Richard Hodur ◽  
Maciej Szpindler ◽  
Leszek Herman-Izycki
Keyword(s):  
Land Surface ◽  
Mesoscale Model ◽  
Surface Atmosphere

Implementation of Modeling the Land-Surface/Atmosphere Interactions to Mesoscale Model COAMPS

2011 ◽  
Author(s):  
Bogumil Jakubiak ◽  
Teddy Holt ◽  
Richard Hodur ◽  
Maciej Szpindler ◽  
Leszek Herman-Izycki
Keyword(s):  
Land Surface ◽  
Mesoscale Model ◽  
Surface Atmosphere

scholarly journals Evaluation of TOPMODEL-Based Land Surface–Atmosphere Transfer Scheme (TOPLATS) through a Soil Moisture Simulation

2018 ◽  
Vol 22 (15) ◽  
pp. 1-19 ◽  
Author(s):  
Xiaolei Fu ◽  
Lifeng Luo ◽  
Ming Pan ◽  
Zhongbo Yu ◽  
Ying Tang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Land Surface ◽  
Spatial Scales ◽  
Absolute Difference ◽  
Coarse Scale ◽  
Transfer Scheme ◽  
Surface Atmosphere ◽  
Spatial Coverage

Abstract Better quantification of the spatiotemporal distribution of soil moisture across different spatial scales contributes significantly to the understanding of land surface processes on the Earth as an integrated system. While observational data for root-zone soil moisture (RZSM) often have sparse spatial coverage, model-simulated soil moisture may provide a useful alternative. TOPMODEL-Based Land Surface–Atmosphere Transfer Scheme (TOPLATS) has been widely studied and actively modified in recent years, while a detailed regional application with evaluation currently is still lacking. Thus, TOPLATS was used to generate high-resolution (30 arc s) RZSM based on coarse-scale (0.125°) forcing data over part of the Arkansas–Red River basin. First, the simulated RZSM was resampled to coarse scale to compare with the results of Mosaic, Noah, and VIC from NLDAS. Second, TOPLATS performance was assessed based on the spatial absolute difference among the models. The comparison shows that TOPLATS performance is similar to VIC, but different from Mosaic and Noah. Last, the simulated RZSM was compared with in situ observations of 16 stations in the study area. The results suggest that the simulated spatial distribution of RZSM is largely consistent with the distribution of topographic index (TI) in most instances, as topography was traditionally considered a major, but not the only, factor in horizontal redistribution of soil moisture. In addition, the finer-resolution RZSM can reflect the in situ soil moisture change at most local sites to a certain degree. The evaluation confirms that TOPLATS is a useful tool to estimate high-resolution soil moisture and has great potential to provide regional soil moisture estimates.

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