Evaluating Error Propagation in Coupled Land–Atmosphere Models

2011 ◽  
Vol 15 (28) ◽  
pp. 1-25 ◽  
Author(s):  
Bryan Pijanowski ◽  
Nathan Moore ◽  
Dasaraden Mauree ◽  
Dev Niyogi
Keyword(s):  
Land Use ◽  
Heat Flux ◽  
Soil Moisture ◽  
Land Cover ◽  
Surface Temperature ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Error Propagation ◽  
Change Model ◽  
Climate Variables

Abstract This study examines how land-use errors from the Land Transformation Model (LTM) propagate through to climate as simulated by the Regional Atmospheric Model System (RAMS). The authors conducted five simulations of regional climate over East Africa: one using observed land cover/land use (LULC) and four utilizing LTM-derived LULC. The study examined how quantifiable errors generated by the LTM impact typical land–climate variables: precipitation, land surface temperature, air temperature, soil moisture, and latent heat flux. Error propagation was not evident when domain averages for the land–climate variables of the yearlong simulation were examined. However, the authors found that spatial errors from the LTM propagate through in complex ways, temporally affecting the seasonal distributions of rainfall, surface temperature, soil moisture, and latent heat flux. In particular, rainy seasons exhibited greater precipitation in LTM-RAMS simulations than in the reference simulation and less precipitation occurred during the dry season. Complex interactions of precipitation and soil moisture were also evident. Overall, results indicate that small errors from a land change model could grow as a “coupling drift” if both are used to forecast into the future; these couplings could create larger combined errors of land–climate interactions because of time-scale differences into the future. Thus, although land-use change projection is necessary for a more accurate climate projection, existing errors from a land change model will likely amplify through the climate simulation. This finding affects interpretation of large-scale versus land-use/land-cover feedbacks on climate projections.

Land-atmosphere coupling during compound extreme heat and drought events in the LUCAS experiment: a new coupling metric for climate extremes

2021 ◽  
Author(s):  
Rita M. Cardoso ◽  
Daniela D. C. A. Lima ◽  
Pedro M. M. Soares ◽  
Diana Rechid ◽  
Marcus Breil ◽  
...  
Keyword(s):  
Land Use ◽  
Heat Flux ◽  
Soil Moisture ◽  
Land Cover ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Heat Waves ◽  
Extreme Heat ◽  
Positive Temperature ◽  
The Impact

<p>Land-atmosphere energy and water exchanges are fundamentally linked to soil-moisture. The distribution of the planets’ biomes hinges on the surface-atmosphere coupling since soil moisture and temperature feedbacks have a strong influence on plant transpiration and photosynthesis. Land use/land cover changes (LUC) modify locally land surface properties that control the land-atmosphere mass, energy, and momentum exchanges. The impact of these changes depends on the scale and nature of land cover modifications and is very difficult to quantify. However, large inconsistencies in the LUC impacts are observed between models, highlighting the need for common LUC across a large ensemble of models. The Flagship Pilot Study LUCAS (Land Use & Climate Across Scales) provides a coordinated effort to study LUC using an ensemble of regional climate models (RCMs). In the first phase of the project 3 experiments were performed for continental Europe: EVAL (current climate); GRASS (trees replaced by grassland) and FOREST (grasses and shrubs replaced by trees).  An analysis of the energy and moisture balance for the three experiments is performed, focusing on the relationship between the fluxes partitioning, heat waves and droughts. To better asses the link between extreme temperatures and soil moisture or evapotranspiration, a new coupling metric for short time scales is proposed, the Latent Heat Flux-Temperature Coupling Magnitude (LETCM). This new metric is computed for a specific period, considering the positive temperature extremes and the negative latent heat flux extremes. Areas with positive magnitude values imply higher temperature anomaly, due to a negative latent heat flux anomaly. This new metric only considers periods of strong coupling, with positive signals in areas of high temperatures and evaporative stress, allowing for the detection of events that are extreme for energy and water cycle. Concurrently, a new decile based normalised drought index is used to examine the concurrent heat extremes and droughts. The analysis focuses on the three experiments revealing that the number, amplitude and spatial distribution of compound extreme heat and drought is highly model dependant. The impact of afforestation or deforestation is not consistent across models.</p><p><strong>Acknowledgements</strong></p><p> The authors wish to acknowledge project LEADING (PTDC/CTA-MET/28914/2017) and FCT - project UIDB/50019/2020 - Instituto Dom Luiz.</p>

scholarly journals Simulation of Land Surface Climate over China with RegCM4.5: Verification and Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Minghao Yang ◽  
Ruiting Zuo ◽  
Liqiong Wang ◽  
Xiong Chen
Keyword(s):  
Heat Flux ◽  
Soil Moisture ◽  
Surface Temperature ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface Temperature ◽  
South China ◽  
Land Surface ◽  
Reanalysis Data ◽  
Surface Evaporation

The ability of RegCM4.5 using land surface scheme CLM4.5 to simulate the physical variables related to land surface state was investigated. The NCEP-NCAR reanalysis data for the period 1964–2003 were used to drive RegCM4.5 to simulate the land surface temperature, precipitation, soil moisture, latent heat flux, and surface evaporation. Based on observations and reanalysis data, a few land surface variables were analyzed over China. The results showed that some seasonal features of land surface temperature in summer and winter as well as its magnitude could be simulated well. The simulation of precipitation was sensitive to region and season. The model could, to a certain degree, simulate the seasonal migration of rainband in East China. The overall spatial distribution of the simulated soil moisture was better in winter than in summer. The simulation of latent heat flux was also better in winter. In summer, the latent heat flux bias mainly arose from surface evaporation bias in Northwest China, and it primarily arose from vegetation evapotranspiration bias in South China. In addition, the large latent heat flux bias in South China during summer was probably due to less precipitation generated in the model and poor representation of vegetation cover in this region.

scholarly journals Identifying the Sources of Continental Summertime Temperature Variance Using a Diagnostic Model of Land–Atmosphere Interactions

2020 ◽  
Vol 33 (9) ◽  
pp. 3547-3564 ◽  
Author(s):  
L. R. Vargas Zeppetello ◽  
Étienne Tétreault-Pinard ◽  
D. S. Battisti ◽  
M. B. Baker
Keyword(s):  
Heat Flux ◽  
Soil Moisture ◽  
Surface Temperature ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Air Temperature ◽  
Climate Models ◽  
Temperature Variability ◽  
Diagnostic Model ◽  
Temperature Variance

AbstractClimate models show that soil moisture and its subseasonal fluctuations have important impacts on the surface latent heat flux, thus regulating surface temperature variations. Using correlations between monthly anomalies in net absorbed radiative fluxes, precipitation, 2-m air temperature, and soil moisture in the ERA-Interim reanalysis and the HadCM3 climate model, we develop a linear diagnostic model to quantify the major effects of land–atmosphere interactions on summertime surface temperature variability. The spatial patterns in 2-m air temperature and soil moisture variance from the diagnostic model are consistent with those from the products from which it was derived, although the diagnostic model generally underpredicts soil moisture variance. We use the diagnostic model to quantify the impact of soil moisture, shortwave radiation, and precipitation anomalies on temperature variance in wet and dry regions. Consistent with other studies, we find that fluctuations in soil moisture amplify temperature variance in dry regions through their impact on latent heat flux, whereas in wet regions temperature variability is muted because of high mean evapotranspiration rates afforded by plentiful surface soil moisture. We demonstrate how the diagnostic model can be used to identify sources of temperature variance bias in climate models.

Land–Atmosphere Interaction in Tropical Africa

2020 ◽  
Author(s):  
Cathy Hohenegger
Keyword(s):  
Heat Flux ◽  
Soil Moisture ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Surface State ◽  
Land Surface ◽  
Large Scale ◽  
Moisture Distribution ◽  
Sahel Region ◽  
The Impact

Even though many features of the vegetation and of the soil moisture distribution over Africa reflect its climatic zones, the land surface has the potential to feed back on the atmosphere and on the climate of Africa. The land surface and the atmosphere communicate via the surface energy budget. A particularly important control of the land surface, besides its control on albedo, is on the partitioning between sensible and latent heat flux. In a soil moisture-limited regime, for instance, an increase in soil moisture leads to an increase in latent heat flux at the expanse of the sensible heat flux. The result is a cooling and a moistening of the planetary boundary layer. On the one hand, this thermodynamically affects the atmosphere by altering the stability and the moisture content of the vertical column. Depending on the initial atmospheric profile, convection may be enhanced or suppressed. On the other hand, a confined perturbation of the surface state also has a dynamical imprint on the atmospheric flow by generating horizontal gradients in temperature and pressure. Such gradients spin up shallow circulations that affect the development of convection. Whereas the importance of such circulations for the triggering of convection over the Sahel region is well accepted and well understood, the effect of such circulations on precipitation amounts as well as on mature convective systems remains unclear. Likewise, the magnitude of the impact of large-scale perturbations of the land surface state on the large-scale circulation of the atmosphere, such as the West African monsoon, has long been debated. One key issue is that such interactions have been mainly investigated in general circulation models where the key involved processes have to rely on uncertain parameterizations, making a definite assessment difficult.

scholarly journals Evaluation of functional properties of various types of vegetation cover using remotely sensed data analysis

2010 ◽  
Vol 4 (Special Issue 2) ◽  
pp. S49-S58 ◽  
Author(s):  
J. Brom ◽  
J. Procházka ◽  
A. Rejšková
Keyword(s):  
Heat Flux ◽  
Surface Temperature ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Sensible Heat Flux ◽  
Sensible Heat ◽  
Remotely Sensed Data ◽  
Mean Values

The dissipation of solar energy and consequently the formation of the hydrological cycle are largely dependent on the structural and optical characteristics of the land surface. In our study, we selected seven units with different types of vegetation in the Mlýnský and Horský catchments (South-Eastern part of the Šumava Mountains, Czech Republic) for the assessment of the differences in their functioning expressed through the surface temperature, humidity, and energy dissipation. For our analyses, we used Landsat 5 TM satellite data from June 25<SUP>th</SUP>, 2008. The results showed that the microclimatic characteristics and energy fluxes varied in different units according to their vegetation characteristics. A cluster analysis of the mean values was used to divide the vegetation units into groups according to their functional characteristics. The mown meadows were characterised by the highest surface temperature and sensible heat flux and the lowest humidity and latent heat flux. On the contrary, the lowest surface temperature and sensible heat flux and the highest humidity and latent heat flux were found in the forest. Our results showed that the climatic and energetic features of the land surface are related to the type of vegetation. We state that the spatial distribution of different vegetation units and the amount of biomass are crucial variables influencing the functioning of the landscape.

Studies on lichen-dominated systems. XX. An examination of some aspects of the northern boreal lichen woodlands in Canada

1977 ◽  
Vol 55 (4) ◽  
pp. 393-410 ◽  
Author(s):  
K. A. Kershaw
Keyword(s):  
Heat Flux ◽  
Soil Moisture ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Higher Plants ◽  
Sensible Heat Flux ◽  
Subsequent Development ◽  
Sensible Heat ◽  
Early Recovery ◽  
Lichen Woodland

The existence of two major types of lichen woodland in Canada, Cladonia stellaris woodland and Stereocaulon paschale woodland, is discussed in relation to their seral nature and their rarely developed theoretical climax type.Our own observations, coupled with previous descriptions from a wider area, suggest that Stereocaulon paschale woodland replaces Cladonia stellaris woodland in a more or less continuous zone from just west of Churchill across to Great Slave Lake, immediately north and south of latitude 60° N. Both woodland types are often typical of sandy soils (pH 6 or less) and almost always represent the final recovery phase after fire. Rarely, the lichen surface is replaced by a continuous moss cover as the spruce canopy closes. The lichen surface is thus dependent on the lack of competition from higher plants, the absence of which is characteristic of the climate of this northern boreal region. Cladonia stellaris woodland also occurs on palsas and peat plateaux where, again, lack of higher plant competition and a suitable pH exist.The recovery sequence after fire is a highly complex process and as yet only the following parameters have been categorized. In the early recovery phases, limited soil moisture and hence a reduced summer latent heat flux enhance the sensible heat flux. The surface conditions are analogous to those of a hot desert with very high surface temperatures and extremely large diurnal temperature fluctuations. The physiology of these initial moss and lichen colonizers presumably enables them to tolerate these harsh conditions. The establishment of a few spruce seedlings and the subsequent development of open lichen woodland modulates the harsh summer temperature regime and allows the further development of a vegetated surface. After humus accumulation, which acts as an effective mulch, summer soil moisture is elevated, enhancing the latent heat flux and correspondingly reducing the sensible heat flux. This probably allows the full development of mature lichen woodland with its almost monospecific ground cover of either Cladonia stellaris or Stereocaulon paschale. Limited data suggest that the net photosynthetic responses of these two species is favoured by the relatively warm mesic conditions established by the open spruce canopy. Good accumulation of snow in the winter is probably also important for protection of the lichen surface from low temperatures. The open nature of mature lichen woodland is apparently maintained by an active inhibition of spruce seedling establishment by the lichen mat, although the mechanism is not entirely clear.

scholarly journals Mesoscale Simulations of the Land Surface Effects of Historical Logging in a Moist Continental Climate Regime

2008 ◽  
Vol 47 (8) ◽  
pp. 2166-2182 ◽  
Author(s):  
Nicholas P. Klingaman ◽  
Jason Butke ◽  
Daniel J. Leathers ◽  
Kevin R. Brinson ◽  
Elsa Nickl
Keyword(s):  
Climate Change ◽  
Heat Flux ◽  
Land Cover ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface ◽  
Climate Regime ◽  
Clear Cut ◽  
Atmosphere System ◽  
Regional Climates

Abstract An enhanced knowledge of the feedbacks from land surface changes on regional climates is of great importance in the attribution of climate change. To explore the effects of deforestation on a midlatitude climate regime, two sets of two five-member ensembles of 28-day simulations were conducted using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) coupled to the “Noah” land surface model. The four ensembles represented conditions in summer (August) and winter (February) across the northern mid-Atlantic United States before and after extensive late-nineteenth-century logging of hardwood forests in central and northern Pennsylvania. Prelogging ensembles prescribed a vegetative cover of an evergreen needleleaf forest; postlogging ensembles prescribed sparse vegetation and bare soil to simulate clear-cut deforestation. The results of the MM5 experiments showed a decided seasonality in the response of the land surface–atmosphere system to deforestation, with much stronger effects arising in summer. In August, deforestation caused a repartitioning of the surface energy budget, beginning with a decrease in the latent heat flux of more than 60 W m−2 across the land cover–forcing area, representing almost one-half of the latent heat flux under prelogging land cover. Concomitant with this decrease in evapotranspiration, mean 2-m air temperatures warmed by at least 1.5°C. Increases in sensible heat flux led to a 150-m mean increase in the height of the atmospheric boundary layer over the deforested area. Low-level atmospheric mixing ratios and total precipitation decreased under clear-cut conditions. Mean soil moisture increased in all model levels to 150 cm because of a decrease in vegetative uptake of water, except at the 5-cm level at which such decreases were effectively balanced by greater soil evaporation and less precipitation. A strong diurnal variation in the response to deforestation of ground and lower-atmosphere temperatures and heat fluxes was also identified for the summer season. The February simulations showed the effects of deforestation during low-insolation months to be small and variable. The strong response of the summer land surface–atmosphere system to deforestation shown here suggests that land cover changes can appreciably affect regional climates. Thus, the role of human-induced and naturally occurring land cover variability should not be ignored in the attribution of climate change.

scholarly journals Latent Heat Flux Sensitivity to Sea Surface Temperature: Regional Perspectives

2017 ◽  
Vol 30 (1) ◽  
pp. 129-143 ◽  
Author(s):  
B. Praveen Kumar ◽  
Meghan F. Cronin ◽  
Sudheer Joseph ◽  
M. Ravichandran ◽  
N. Sureshkumar
Keyword(s):  
Heat Flux ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Global Analysis ◽  
Surface Wind ◽  
Sea Surface ◽  
State Variables ◽  
Monsoon Period

A global analysis of latent heat flux (LHF) sensitivity to sea surface temperature (SST) is performed, with focus on the tropics and the north Indian Ocean (NIO). Sensitivity of LHF state variables (surface wind speed Ws and vertical humidity gradients Δq) to SST give rise to mutually interacting dynamical (Ws driven) and thermodynamical (Δq driven) coupled feedbacks. Generally, LHF sensitivity to SST is pronounced over tropics where SST increase causes Ws (Δq) changes, resulting in a maximum decrease (increase) of LHF by ~15 W m−2 (°C)−1. But the Bay of Bengal (BoB) and north Arabian Sea (NAS) remain an exception that is opposite to the global feedback relationship. This uniqueness is attributed to strong seasonality in monsoon Ws and Δq variations, which brings in warm (cold) continental air mass into the BoB and NAS during summer (winter), producing a large seasonal cycle in air–sea temperature difference ΔT (and hence in Δq). In other tropical oceans, surface air is mostly of marine origin and blows from colder to warmer waters, resulting in a constant ΔT ~ 1°C throughout the year, and hence a constant Δq. Thus, unlike other basins, when the BoB and NAS are warming, air temperature warms faster than SST. The resultant decrease in ΔT and Δq contributes to decrease the LHF with increased SST, contrary to other basins. This analysis suggests that, in the NIO, LHF variability is largely controlled by thermodynamic processes, which peak during the monsoon period. These observed LHF sensitivities are then used to speculate how the surface energetics and coupled feedbacks may change in a warmer world.

scholarly journals Temporal variations of evapotranspiration: reconstruction using instantaneous satellite measurements in the thermal infra red domain

2012 ◽  
Vol 9 (2) ◽  
pp. 1699-1740 ◽  
Author(s):  
E. Delogu ◽  
G. Boulet ◽  
A. Olioso ◽  
B. Coudert ◽  
J. Chirouze ◽  
...  
Keyword(s):  
Heat Flux ◽  
Surface Temperature ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Interpolation Method ◽  
Empirical Relationship ◽  
Surface Energy Budget ◽  
Evaporative Fraction ◽  
Clear Sky ◽  
Extrapolation Algorithm

Abstract. Evapotranspiration estimates can be derived from remote sensing data and ancillary, mostly meterorological, information. For this purpose, two types of methods are classically used: the first ones estimate a potential evapotranspiration rate from vegetation indices, and adjust this rate according to water availability derived from either a surface temperature index or a first guess obtained from a rough estimate of the water budget, while the second family of methods rely on the link between the surface temperature and the latent heat flux through the surface energy budget. The latter provide an instantaneous estimate at the time of satellite overpass. In order to compute daily evapotranspiration, one needs an extrapolation algorithm. Since no image is acquired during cloudy conditions, these methods can only be applied during clear sky days. In order to derive seasonal evapotranspiration, one needs an interpolation method. Two combined interpolation/extrapolation methods based on the self preservation of evaporative fraction and the stress factor are compared to reconstruct seasonal evapotranspiration from instantaneous measurements acquired in clear sky conditions. Those measurements are taken from instantaneous latent heat flux from 11 datasets in Southern France and Morocco. Results show that both methods have comparable performances with a clear advantage for the evaporative fraction for datasets with several water stress events. Both interpolation algorithms tend to underestimate evapotranspiration due to the energy limiting conditions that prevail during cloudy days. Taking into account the diurnal variations of the evaporative fraction according to an empirical relationship derived from a previous study improved the performance of the extrapolation algorithm and therefore the retrieval of the seasonal evapotranspiration for all but one datasets.

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