scholarly journals Simultaneous parameterization of the two-source evapotranspiration model by Bayesian approach: application to spring maize in an arid region of northwest China

2014 ◽  
Vol 7 (1) ◽  
pp. 741-775 ◽  
Author(s):  
G. F. Zhu ◽  
X. Li ◽  
Y. H. Su ◽  
K. Zhang ◽  
Y. Bai ◽  
...  
Keyword(s):  
Land Surface ◽  
Soil Surface ◽  
Northwest China ◽  
Heat Fluxes ◽  
Canopy Interception ◽  
Spring Maize ◽  
Direct Measurements ◽  
Good Agreement ◽  
Arid Northwest China

Abstract. Based on direct measurements of half-hourly canopy evapotranspiration (ET; W m−2) using the eddy covariance (EC) system and daily soil evaporation (E; mm d−1) using microlysimeters over a crop ecosystem in arid northwest China from 27 May to 14 September in 2013, a Bayesian method was used to simultaneously parameterize the soil surface and canopy resistances in the Shuttleworth–Wallace (S–W) model. The posterior distributions of the parameters in most cases were well updated by the multiple measuring dataset with relatively narrow high-probability intervals. There was a good agreement between measured and simulated values of half-hourly ET and daily E with a linear regression being y = 0.84x +0.18 (R2 = 0.83) and y = 1.01x + 0.01 (R2 = 0.82), respectively. The causes of underestimations of ET by the S–W model was mainly attributed to the micro-scale advection, which can contribute an added energy in the form of downward sensible heat fluxes to the ET process. Therefore, the advection process should be taken into accounted in simulating ET in heterogeneous land surface. Also, underestimations were observed on or shortly after rainy days due to direct evaporation of liquid water intercepted in the canopy. Thus, the canopy interception model should be coupled to the S–W model in the long-term ET simulation.

scholarly journals Simultaneously assimilating multivariate data sets into the two-source evapotranspiration model by Bayesian approach: application to spring maize in an arid region of northwestern China

2014 ◽  
Vol 7 (4) ◽  
pp. 1467-1482 ◽  
Author(s):  
G. F. Zhu ◽  
X. Li ◽  
Y. H. Su ◽  
K. Zhang ◽  
Y. Bai ◽  
...  
Keyword(s):  
Soil Surface ◽  
Heat Fluxes ◽  
Northwestern China ◽  
Data Sets ◽  
Canopy Interception ◽  
Arid Northwestern China ◽  
Spring Maize ◽  
Direct Measurements ◽  
Land Surfaces

Abstract. Based on direct measurements of half-hourly canopy evapotranspiration (ET; W m−2) using the eddy covariance (EC) system and daily soil evaporation (E; mm day−1) using microlysimeters over a crop ecosystem in arid northwestern China from 27 May to 14 September in 2013, a Bayesian method was used to simultaneously parameterize the soil surface and canopy resistances in the Shuttleworth–Wallace (S–W) model. Four of the six parameters showed relatively larger uncertainty reductions (> 50%), and their posterior distributions became approximately symmetric with distinctive modes. There was a moderately good agreement between measured and simulated values of half-hourly ET and daily E with a linear regression being y = 0.84 x + 0.18 (R2 = 0.83) and y = 1.01 x + 0.01 (R2 = 0.82), respectively. The causes of underestimations of ET by the S–W model was possibly attributed to the microscale advection, which can contribute an added energy in the form of downward sensible heat fluxes to the ET process. Therefore, the advection process should be taken into account in simulating ET in heterogeneous land surfaces. Also, underestimations were observed on or shortly after rainy days, which may be due to direct evaporation of liquid water intercepted in the canopy. Thus, the canopy interception model should be coupled to the S–W model in the long-term ET simulation.

scholarly journals CONSTRUCTION AND ANALYSIS OF LONG-TERM SURFACE TEMPERATURE DATASET IN FUJIAN PROVINCE

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 1223-1227 ◽  
Author(s):  
W. E. Li ◽  
X. Q. Wang ◽  
H. Su
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Land Surface ◽  
Rapid Development ◽  
Temporal Distribution ◽  
Heat Fluxes ◽  
Urban Region ◽  
Fujian Province ◽  
Spatio Temporal

Land surface temperature (LST) is a key parameter of land surface physical processes on global and regional scales, linking the heat fluxes and interactions between the ground and atmosphere. Based on MODIS 8-day LST products (MOD11A2) from the split-window algorithms, we constructed and obtained the monthly and annual LST dataset of Fujian Province from 2000 to 2015. Then, we analyzed the monthly and yearly time series LST data and further investigated the LST distribution and its evolution features. The average LST of Fujian Province reached the highest in July, while the lowest in January. The monthly and annual LST time series present a significantly periodic features (annual and interannual) from 2000 to 2015. The spatial distribution showed that the LST in North and West was lower than South and East in Fujian Province. With the rapid development and urbanization of the coastal area in Fujian Province, the LST in coastal urban region was significantly higher than that in mountainous rural region. The LST distributions might affected by the climate, topography and land cover types. The spatio-temporal distribution characteristics of LST could provide good references for the agricultural layout and environment monitoring in Fujian Province.

Observed heatwave changes in arid northwest China: Physical mechanism and long-term trend

2020 ◽  
Vol 242 ◽  
pp. 105009
Author(s):  
Ming Luo ◽  
Guicai Ning ◽  
Feng Xu ◽  
Shigong Wang ◽  
Zhen Liu ◽  
...  
Keyword(s):  
Physical Mechanism ◽  
Northwest China ◽  
Term Trend ◽  
Long Term Trend ◽  
Arid Northwest China

The evaluation of land surface parameters for model to derive land surface fluxes in the Tibetan Plateau

2021 ◽  
Author(s):  
Weiqiang Ma ◽  
Yaoming Ma ◽  
Yizhe Han ◽  
Wei Hu ◽  
Lei Zhong ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Atmospheric Model ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
The Tibetan Plateau ◽  
Default Model ◽  
Model Configuration

<p>Firstly, based on the difference of model and in-situ observations, a serious of sensitive experiments were done by using WRF. In order to use remote sensing products, a land-atmosphere model was initialized by ingesting land surface parameters, such as AMSR-E RS products, and the results were compared with the default model configuration and with in-situ long-term CAMP/Tibet observations.</p><p>Secondly, a land-atmosphere model was initialized by ingesting AMSR-E products, and the results were compared with the default model configuration and with in-situ long-term CAMP/Tibet observations. The differences between the AMSR-E initialized model runs with the default model configuration and in situ data showed an apparent inconsistency in the model-simulated land surface heat fluxes. The results showed that the soil moisture was sensitive to the specific model configuration. To evaluate and verify the model stability, a long-term modeling study with AMSR-E soil moisture data ingestion was performed. Based on test simulations, AMSR-E data were assimilated into an atmospheric model for July and August 2007. The results showed that the land surface fluxes agreed well with both the in-situ data and the results of the default model configuration. Therefore, the simulation can be used to retrieve land surface heat fluxes from an atmospheric model over the Tibetan Plateau.</p><p>All of the different methods will clarify the land surface heating field in complex plateau, it also can affect atmospheric cycle over the Tibetan Plateau even all of the global atmospheric cycle pattern.</p>

Prospective upscaling of quantification of non-rainfall water inputs to regional scale

2020 ◽  
Author(s):  
Nurit Agam ◽  
Dilia Kool
Keyword(s):  
Diurnal Cycle ◽  
Land Surface ◽  
Regional Scale ◽  
Broad Band ◽  
Soil Layer ◽  
Soil Surface ◽  
Heat Fluxes ◽  
Surface Emissivity ◽  
Undisturbed Soil ◽  
Small Magnitude

<p>In drylands, the annual amount of non-rainfall water inputs (NRWIs), i.e., a gain of water to the surface soil layer that is not caused by rainfall, can exceed that of rainfall.  They thus significantly contribute to the water cycle and to biogeochemical dynamics.  However, the small magnitude of the fluxes involved in the formation and evaporation of NRWIs challenges their measurement.  Various methods were applied in attempting to quantify NRWIs amount and duration, all being point/local measurements.  Given the large heterogeneity of soils, both at local and at regional scale, upscaling from the small point measurement methods to larger scales is necessary in order to fully understand the environmental factors controlling NRWIs and the role of NRWIs in dryland ecosystems.  Numerous remote sensing-based models have been developed to assess spatially distributed latent heat fluxes, greatly varying in complexity.  Unfortunately, the magnitude of diurnal fluxes due to NRWIs is too small to be detected by any of the existing models.  Hypothesizing that soil surface emissivity is sensitive to very small changes in water content at the top soil layer, our objective was to quantify NRWIs by analyzing the temporal changes in land surface emissivity over bare loess soil in the Negev desert, Israel.  Proven successful, this can be utilized over large areas. </p><p>Intensive measurements using a longwave infrared radiometer (CLIMAT 312-2n ASTER, Cimel Electronique, Paris, France) were conducted in summer 2019 at the Wadi Mashash Experimental Farm (31<sup>o</sup>08’N, 34<sup>o</sup>53’E).  Radiance and temperature measurements were obtained for a broad band (8.01-13.34 μm) and 5 subsections of this bandwidth.  The radiometer was mounted at 0.5 m directly above one of four microlysimeters (undisturbed soil samples installed flash with the soil surface and weighed continuously).  Radiometer readings were automatically taken every 15 min for 24-h cycles. </p><p>Initial results indicate an agreement between the diurnal cycle of NRWIs detected by the microlysimeters and between the diurnal cycle of an index derived from the radiometer bands: (e<sub>11.3</sub>-e<sub>8.3</sub>)/ e<sub>10.6</sub> (the numbers are the center of the band in µm).  These preliminary results show the potential to upscale quantifying NRWIs to regional scale.</p>

scholarly journals A Long-Term Hydrologically Based Dataset of Land Surface Fluxes and States for the Conterminous United States: Update and Extensions

2013 ◽  
Vol 26 (23) ◽  
pp. 9384-9392 ◽  
Author(s):  
Ben Livneh ◽  
Eric A. Rosenberg ◽  
Chiyu Lin ◽  
Bart Nijssen ◽  
Vimal Mishra ◽  
...  
Keyword(s):  
United States ◽  
Spatial Resolution ◽  
Land Surface ◽  
Snow Water Equivalent ◽  
Meteorological Data ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Infiltration Capacity ◽  
Surface Heat Fluxes

This paper describes a publicly available, long-term (1915–2011), hydrologically consistent dataset for the conterminous United States, intended to aid in studies of water and energy exchanges at the land surface. These data are gridded at a spatial resolution of [Formula: see text] latitude/longitude and are derived from daily temperature and precipitation observations from approximately 20 000 NOAA Cooperative Observer (COOP) stations. The available meteorological data include temperature, precipitation, and wind, as well as derived humidity and downwelling solar and infrared radiation estimated via algorithms that index these quantities to the daily mean temperature, temperature range, and precipitation, and disaggregate them to 3-hourly time steps. Furthermore, the authors employ the variable infiltration capacity (VIC) model to produce 3-hourly estimates of soil moisture, snow water equivalent, discharge, and surface heat fluxes. Relative to an earlier similar dataset by Maurer and others, the improved dataset has 1) extended the period of analysis (1915–2011 versus 1950–2000), 2) increased the spatial resolution from ⅛° to [Formula: see text], and 3) used an updated version of VIC. The previous dataset has been widely used in water and energy budget studies, climate change assessments, drought reconstructions, and for many other purposes. It is anticipated that the spatial refinement and temporal extension will be of interest to a wide cross section of the scientific community.

scholarly journals Evaluation of Surface Flux Parameterizations with Long-Term ARM Observations

2013 ◽  
Vol 141 (2) ◽  
pp. 773-797 ◽  
Author(s):  
Gang Liu ◽  
Yangang Liu ◽  
Satoshi Endo
Keyword(s):  
Latent Heat ◽  
Land Surface ◽  
Bowen Ratio ◽  
Surface Flux ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Parameterization Schemes ◽  
Surface Models ◽  
Flux Parameterization

Abstract Surface momentum, sensible heat, and latent heat fluxes are critical for atmospheric processes such as clouds and precipitation, and are parameterized in a variety of models ranging from cloud-resolving models to large-scale weather and climate models. However, direct evaluation of the parameterization schemes for these surface fluxes is rare due to limited observations. This study takes advantage of the long-term observations of surface fluxes collected at the Southern Great Plains site by the Department of Energy Atmospheric Radiation Measurement program to evaluate the six surface flux parameterization schemes commonly used in the Weather Research and Forecasting (WRF) model and three U.S. general circulation models (GCMs). The unprecedented 7-yr-long measurements by the eddy correlation (EC) and energy balance Bowen ratio (EBBR) methods permit statistical evaluation of all six parameterizations under a variety of stability conditions, diurnal cycles, and seasonal variations. The statistical analyses show that the momentum flux parameterization agrees best with the EC observations, followed by latent heat flux, sensible heat flux, and evaporation ratio/Bowen ratio. The overall performance of the parameterizations depends on atmospheric stability, being best under neutral stratification and deteriorating toward both more stable and more unstable conditions. Further diagnostic analysis reveals that in addition to the parameterization schemes themselves, the discrepancies between observed and parameterized sensible and latent heat fluxes may stem from inadequate use of input variables such as surface temperature, moisture availability, and roughness length. The results demonstrate the need for improving the land surface models and measurements of surface properties, which would permit the evaluation of full land surface models.

scholarly journals Large-Eddy Simulation of Shallow Cumulus over Land: A Composite Case Based on ARM Long-Term Observations at Its Southern Great Plains Site

2017 ◽  
Vol 74 (10) ◽  
pp. 3229-3251 ◽  
Author(s):  
Yunyan Zhang ◽  
Stephen A. Klein ◽  
Jiwen Fan ◽  
Arunchandra S. Chandra ◽  
Pavlos Kollias ◽  
...  
Keyword(s):  
Great Plains ◽  
Mass Flux ◽  
Land Surface ◽  
Large Scale ◽  
Cloud Amount ◽  
Heat Fluxes ◽  
Southern Great Plains ◽  
Shallow Cumulus ◽  
Large Eddy

Abstract Based on long-term observations by the Atmospheric Radiation Measurement program at its Southern Great Plains site, a new composite case of continental shallow cumulus (ShCu) convection is constructed for large-eddy simulations (LES) and single-column models. The case represents a typical daytime nonprecipitating ShCu whose formation and dissipation are driven by the local atmospheric conditions and land surface forcing and are not influenced by synoptic weather events. The case includes early morning initial profiles of temperature and moisture with a residual layer; diurnally varying sensible and latent heat fluxes, which represent a domain average over different land surface types; simplified large-scale horizontal advective tendencies and subsidence; and horizontal winds with prevailing direction and average speed. Observed composite cloud statistics are provided for model evaluation. The observed diurnal cycle is well reproduced by LES; however, the cloud amount, liquid water path, and shortwave radiative effect are generally underestimated. LES are compared between simulations with an all-or-nothing bulk microphysics and a spectral bin microphysics. The latter shows improved agreement with observations in the total cloud cover and the amount of clouds with depths greater than 300 m. When compared with radar retrievals of in-cloud air motion, LES produce comparable downdraft vertical velocities, but a larger updraft area, velocity, and updraft mass flux. Both observations and LES show a significantly larger in-cloud downdraft fraction and downdraft mass flux than marine ShCu.

scholarly journals Effects of Cropland Expansion on the Regional Land Surface Radiative Energy Balance and Heat Fluxes in Northern China

2021 ◽  
Vol 11 (4) ◽  
pp. 1556
Author(s):  
Jia Ning
Keyword(s):  
Heat Flux ◽  
Land Surface ◽  
Surface Heat Flux ◽  
Northeast China ◽  
Northern China ◽  
Northwest China ◽  
Surface Heat ◽  
Surface Radiation ◽  
Climate Zones ◽  
Arid Northwest China

Land use change can impact the land surface radiation budget and energy balance by changing surface biophysical processes. Based on satellite remote sensing data and land use data from 2000 to 2015, we quantitatively estimated radiative forcing induced by cropland expansion during the early 21st century in northern China. The results showed that heat flux from the land surface to the atmosphere due to cropland expansion was quite variable in different climate zones. The heat flux increased in humid North China, whereas it decreased in arid Northwest China, semiarid Inner Mongolia, and humid Northeast China. Cropland expansion from woodland areas led to a general decline in the land surface heat flux to the atmosphere, which led to a cooling effect on the climate. The surface heat flux to the atmosphere due to cropland expansion in grassland areas displayed significant variations in different climate zones. The surface heat flux decreased only in humid Northeast China and arid Northwest China. The net surface radiation and latent heat flux both increased when grasslands were changed into cropland, but to different extents, which produced the differences in the surface heat flux to the atmosphere between different zones.

Use of Satellite-Based Precipitation Observation in Improving the Parameterization of Canopy Hydrological Processes in Land Surface Models

2005 ◽  
Vol 6 (5) ◽  
pp. 745-763 ◽  
Author(s):  
Dagang Wang ◽  
Guiling Wang ◽  
Emmanouil N. Anagnostou
Keyword(s):  
Land Surface ◽  
Rain Rate ◽  
Climate Models ◽  
Climate Model ◽  
Model Simulation ◽  
Heat Fluxes ◽  
Land Surface Models ◽  
Canopy Interception ◽  
Surface Models ◽  
Rain Rates

Abstract Precipitation exhibits significant spatial variability at scales much smaller than the typical size of climate model grid cells. Neglecting such subgrid-scale variability in climate models causes unrealistic representation of land–atmosphere flux exchanges. It is especially problematic over densely vegetated land. This paper addresses this issue by incorporating satellite-based precipitation observations into the representation of canopy interception processes in land surface models. Rainfall data derived from passive microwave (PM) observations are used to obtain realistic estimates of 1) conditional mean rain rates, which together with the modeled rain rate are used to estimate the rainfall coverage fraction at each model grid cell in this study, and 2) the probability density function (pdf) of rain rates within the rain-covered areas. Both of these properties significantly impact the land–atmosphere water vapor exchanges. Based on the above information, a statistical–dynamical approach is taken to incorporate the representation of precipitation subgrid variability into canopy interception processes in land surface models. The results reveal that incorporation of precipitation subgrid variability significantly alters the partitioning between runoff and total evapotranspiration as well as the partitioning among the three components of evapotranspiration (i.e., canopy interception loss, ground evaporation, and plant transpiration). This further influences soil water, surface temperature, and surface heat fluxes. It is shown that the choice of the rain-rate pdf within rain-covered areas has an effect on the model simulation of land–atmosphere flux exchanges. This study demonstrates that land surface and climate models can substantially benefit from the fine-resolution remotely sensed rainfall observations.

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