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

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.

Author(s):  
Cathy Hohenegger

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.


2010 ◽  
Vol 4 (Special Issue 2) ◽  
pp. S49-S58 ◽  
Author(s):  
J. Brom ◽  
J. Procházka ◽  
A. Rejšková

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.


2016 ◽  
Author(s):  
Mostaquimur Rahman ◽  
Rafael Rosolem

Abstract. Modelling and monitoring of hydrological processes in the unsaturated zone of the chalk, which is a porous medium with fractures, is important to optimize water resources assessment and management practices in the United Kingdom (UK). However, efficient simulations of water movement through chalk unsaturated zone is difficult mainly due to the fractured nature of chalk, which creates high-velocity preferential flow paths in the subsurface. Complex hydrology in the chalk aquifers may also influence land surface mass and energy fluxes because processes in the hydrological cycle are connected via non-linear feedback mechanisms. In this study, it is hypothesized that explicit representation of chalk hydrology in a land surface model influences land surface processes by affecting water movement through the shallow subsurface. In order to substantiate this hypothesis, a macroporosity parameterization is implemented in the Joint UK Land Environment Simulator (JULES), which is applied on a study area encompassing the Kennet catchment in the Southern UK. The simulation results are evaluated using field measurements and satellite remote sensing observations of various fluxes and states in the hydrological cycle (e.g., soil moisture, runoff, latent heat flux) at two distinct spatial scales (i.e., point and catchment). The results reveal the influence of representing chalk hydrology on land surface mass and energy balance components such as surface runoff and latent heat flux via subsurface processes (i.e., soil moisture dynamics) in JULES, which corroborates the proposed hypothesis.


2020 ◽  
Vol 33 (9) ◽  
pp. 3547-3564 ◽  
Author(s):  
L. R. Vargas Zeppetello ◽  
Étienne Tétreault-Pinard ◽  
D. S. Battisti ◽  
M. B. Baker

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.


2020 ◽  
Vol 21 (2) ◽  
pp. 183-203 ◽  
Author(s):  
Yang Lu ◽  
Susan C. Steele-Dunne ◽  
Gabriëlle J. M. De Lannoy

AbstractSurface heat fluxes are vital to hydrological and environmental studies, but mapping them accurately over a large area remains a problem. In this study, brightness temperature (TB) observations or soil moisture retrievals from the NASA Soil Moisture Active Passive (SMAP) mission and land surface temperature (LST) product from the Geostationary Operational Environmental Satellite (GOES) are assimilated together into a coupled water and heat transfer model to improve surface heat flux estimates. A particle filter is used to assimilate SMAP data, while a particle smoothing method is adopted to assimilate GOES LST time series, correcting for both systematic biases via parameter updating and for short-term error via state updating. One experiment assimilates SMAP TB at horizontal polarization and GOES LST, a second experiment assimilates SMAP TB at vertical polarization and GOES LST, and a third experiment assimilates SMAP soil moisture retrievals along with GOES LST. The aim is to examine if the assimilation of physically consistent TB and LST observations could yield improved surface heat flux estimates. It is demonstrated that all three assimilation experiments improved flux estimates compared to a no-assimilation case. Assimilating TB data tends to produce smaller bias in soil moisture estimates compared to assimilating soil moisture retrievals, but the estimates are influenced by the respective bias correction approaches. Despite the differences in soil moisture estimates, the flux estimates from different assimilation experiments are in general very similar.


2016 ◽  
Vol 9 (7) ◽  
pp. 2499-2532 ◽  
Author(s):  
Alexander Loew ◽  
Jian Peng ◽  
Michael Borsche

Abstract. Surface water and energy fluxes are essential components of the Earth system. Surface latent heat fluxes provide major energy input to the atmosphere. Despite the importance of these fluxes, state-of-the-art data sets of surface energy and water fluxes largely differ. The present paper introduces a new framework for the estimation of surface energy and water fluxes at the land surface, which allows for temporally and spatially high-resolved flux estimates at the quasi-global scale (50° S, 50° N) (High resOlution Land Atmosphere Parameters from Space – HOLAPS v1.0). The framework makes use of existing long-term satellite and reanalysis data records and ensures internally consistent estimates of the surface radiation and water fluxes. The manuscript introduces the technical details of the developed framework and provides results of a comprehensive sensitivity and evaluation study. Overall the root mean square difference (RMSD) was found to be 51.2 (30.7) W m−2 for hourly (daily) latent heat flux, and 84 (38) W m−2 for sensible heat flux when compared against 48 FLUXNET stations worldwide. The largest uncertainties of latent heat flux and net radiation were found to result from uncertainties in the solar radiation flux obtained from satellite data products.


MAUSAM ◽  
2022 ◽  
Vol 46 (3) ◽  
pp. 313-324
Author(s):  
P. K. MOHANTY ◽  
S. K. DASH

ABSTRACT. Characteristics of the surface fields. such as zonal and meridional components of pseudostress. surface pressure, latent and sensible heat fluxes, sea surface temperature (SST) and air temperature for the years 1985 and 1986, are studied using ECMWF model-analysed data and FSU data obtained from TOGA CD-ROM (1990). Three branches of monsoon. Viz. (i) Arabian Sea; (ii) Bay of Bengal and (iii) South China 1 Sea are observed in pseudostress, surface pressure and latent heat flux. However, the other three surface fieldsdo not reflect the branching phenomenon. The Arabian Sea and Bay of Bengal branches depict strong signals of variability in the surface fields in association with the monsoon variability compared to the south China Sea branch. Arabian Sea branch is observed to have the strongest signals in the pseudostress and latent heat flux transfer whereas surface pressure is having the lowest value over the Bay of Bengal. Southern Indian Ocean shows significant variability in surface pressure in comparison to the three branches of monsoon. Strong positive radient of pseudostress in association with sudden increase of latent heat flux front May to June, and the pre-monsoonal pressure drop (March to April) in 1985 are the most prominent features associated with better monsoon activity. Inter-annual variability in sea surface temperature (SST) is not well marked but differences in SST amongst the three branches are significant.  


2020 ◽  
pp. 1-39
Author(s):  
David O. Benson ◽  
Paul A. Dirmeyer

AbstractIncreased heatwave frequency across the United States has led to the need for improved predictability of heatwave events. A detailed understanding of land-atmosphere interactions and the relationship between soil moisture and temperature extremes could provide useful information for prediction. This study identifies, for many locations, a threshold of soil moisture below which there is an increase in the sensitivity of atmospheric temperature to declining soil moisture. This shift to a hypersensitive regime causes the atmosphere to be more susceptible to atmospherically driven heatwave conditions. The soil moisture breakpoint where the regime shift occurs is estimated using segmented regression applied to observations and reanalysis data. It is shown that as the soil gets drier, there is a concomitant change in the rate of decrease in latent heat flux and increase in sensible heat flux leading to a strong positive feedback of increased air temperature near the surface, which further dries out the soil. Central, southwestern and southeastern parts of the US seem to have regions of clear regime shifts, while the eastern part of the US generally does not get dry enough to reveal significant breakpoints. Sensible heat flux is seen to be a primary driver of this increased temperature sensitivity aided by the drop in latent heat flux. An investigation of flux tower sites verifies the breakpoint-flux relationships found in reanalysis data. Accurate estimation of these breakpoints can contribute to improved heatwave prediction.


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