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.

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

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

scholarly journals Improving the representation of high-latitude vegetation distribution in dynamic global vegetation models

2021 ◽  
Vol 18 (1) ◽  
pp. 95-112
Author(s):  
Peter Horvath ◽  
Hui Tang ◽  
Rune Halvorsen ◽  
Frode Stordal ◽  
Lena Merete Tallaksen ◽  
...  
Keyword(s):  
High Latitude ◽  
Vegetation Cover ◽  
Land Surface ◽  
Snow Water Equivalent ◽  
Radiative Properties ◽  
Community Land Model ◽  
Precipitation Seasonality ◽  
Dynamic Global Vegetation Models ◽  
Vegetation Models ◽  
Global Vegetation

Abstract. Vegetation is an important component in global ecosystems, affecting the physical, hydrological and biogeochemical properties of the land surface. Accordingly, the way vegetation is parameterized strongly influences predictions of future climate by Earth system models. To capture future spatial and temporal changes in vegetation cover and its feedbacks to the climate system, dynamic global vegetation models (DGVMs) are included as important components of land surface models. Variation in the predicted vegetation cover from DGVMs therefore has large impacts on modelled radiative and non-radiative properties, especially over high-latitude regions. DGVMs are mostly evaluated by remotely sensed products and less often by other vegetation products or by in situ field observations. In this study, we evaluate the performance of three methods for spatial representation of present-day vegetation cover with respect to prediction of plant functional type (PFT) profiles – one based upon distribution models (DMs), one that uses a remote sensing (RS) dataset and a DGVM (CLM4.5BGCDV; Community Land Model 4.5 Bio-Geo-Chemical cycles and Dynamical Vegetation). While DGVMs predict PFT profiles based on physiological and ecological processes, a DM relies on statistical correlations between a set of predictors and the modelled target, and the RS dataset is based on classification of spectral reflectance patterns of satellite images. PFT profiles obtained from an independently collected field-based vegetation dataset from Norway were used for the evaluation. We found that RS-based PFT profiles matched the reference dataset best, closely followed by DM, whereas predictions from DGVMs often deviated strongly from the reference. DGVM predictions overestimated the area covered by boreal needleleaf evergreen trees and bare ground at the expense of boreal broadleaf deciduous trees and shrubs. Based on environmental predictors identified by DM as important, three new environmental variables (e.g. minimum temperature in May, snow water equivalent in October and precipitation seasonality) were selected as the threshold for the establishment of these high-latitude PFTs. We performed a series of sensitivity experiments to investigate if these thresholds improve the performance of the DGVM method. Based on our results, we suggest implementation of one of these novel PFT-specific thresholds (i.e. precipitation seasonality) in the DGVM method. The results highlight the potential of using PFT-specific thresholds obtained by DM in development of DGVMs in broader regions. Also, we emphasize the potential of establishing DMs as a reliable method for providing PFT distributions for evaluation of DGVMs alongside RS.

scholarly journals Studying of solar-terrestrial connections in the dynamics of the surface atmospheric electric field

2020 ◽  
Vol 196 ◽  
pp. 01010
Author(s):  
Tatyana Kudrinskaya ◽  
Gennady Kupovykh ◽  
Anatoly Adzhiev ◽  
Bulat Zainetdinov
Keyword(s):  
Electric Field ◽  
High Altitude ◽  
Geomagnetic Activity ◽  
Field Intensity ◽  
High Latitude ◽  
Electric Field Intensity ◽  
Atmospheric Electric Field ◽  
Surface Atmosphere

The paper presents the results of the analysis of variations in the electric field intensity of the surface atmosphere obtained in high-latitude, high-altitude and lowland observation points, together with the parameters of solar and geomagnetic activity.

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