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 Simulating carbon exchange using a regional atmospheric model coupled to an advanced land-surface model

2008 ◽  
Vol 5 (5) ◽  
pp. 4161-4207 ◽  
Author(s):  
H. W. Ter Maat ◽  
R. W. A. Hutjes
Keyword(s):  
Carbon Dioxide ◽  
Land Surface ◽  
Large Scale ◽  
Regional Scale ◽  
Atmospheric Model ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Surface Model ◽  
Carbon Exchange ◽  
Regional Atmospheric Modelling System

Abstract. A large scale mismatch exists between our understanding and quantification of ecosystem atmosphere exchange of carbon dioxide at local scale and continental scales. This paper will focus on the carbon exchange on the regional scale to address the following question: What are the main controlling factors determining atmospheric carbon dioxide content at a regional scale? We use the Regional Atmospheric Modelling System (RAMS), coupled with a land surface scheme simulating carbon, heat and momentum fluxes (SWAPS-C), and including also sub models for urban and marine fluxes, which in principle include the main controlling mechanisms and capture the relevant dynamics of the system. To validate the model, observations are used which were taken during an intensive observational campaign in the central Netherlands in summer 2002. These included flux-site observations, vertical profiles at tall towers and spatial fluxes of various variables taken by aircraft. The coupled regional model (RAMS-SWAPS-C) generally does a good job in simulating results close to reality. The validation of the model demonstrates that surface fluxes of heat, water and CO2 are reasonably well simulated. The comparison against aircraft data shows that the regional meteorology is captured by the model. Comparing spatially explicit simulated and observed fluxes we conclude that in general simulated latent heat fluxes are underestimated by the model to the observations which exhibit large standard deviation for all flights. Sensitivity experiments demonstrated the relevance of the urban emissions of carbon dioxide for the carbon balance in this particular region. The same test also show the relation between uncertainties in surface fluxes and those in atmospheric concentrations.

scholarly journals Closing the Energy Balance using a Canopy Heat Capacity – A physically based Approach for the Land Component JSBACHv3.11

2018 ◽  
Author(s):  
Marvin Heidkamp ◽  
Andreas Chlond ◽  
Felix Ament
Keyword(s):  
Heat Capacity ◽  
Energy Balance ◽  
Diurnal Cycle ◽  
Land Surface ◽  
Climate Models ◽  
Finite Thickness ◽  
Soil Layer ◽  
Surface Fluxes ◽  
Delayed Response ◽  
Stable Conditions

Abstract. Land surface-atmosphere interaction is one of the most important characteristic for understanding the terrestrial climate system, as it determines the exchange fluxes of energy and water between the land and the overlying air mass. In several current climate models, it is common practice to use an unphysical approach to close the surface energy balance within the uppermost soil layer with finite thickness and heat capacity. In this study, a different approach is investigated by means of a physical based estimation of the canopy heat capacity SkIn+. Therefore, in a first step, results of an offline simulation of the land component JSBACH of the MPI-ESM – constrained with atmospheric observations – are compared to energy- and water fluxes derived from eddy covariance measurements observed at the CASES-99 field experiment in Kansas where only shallow vegetation prevails. This comparison of energy and evapotranspiration fluxes with observations at the site-level provides an assessment of the model's capacity to correctly reproduce the coupling between the land and the atmosphere throughout the diurnal cycle. In a further step, a global coupled land-atmosphere experiment is performed using an AMIP type simulation over thirty years to evaluate the regional impact of the SkIn+ scheme on longer time scale, in particular, in respect to the effect of the canopy heat capacity. The results of the offline experiment show that SkIn+ leads to a warming during the day and to a cooling in the night relative to the old reference scheme, thereby improving the performance in the representation of the modeled surface fluxes on diurnal time scales. In particular: nocturnal heat releases unrealistically destroying the stable boundary layer disappear and phase errors are removed. On the global scale, for regions with no or low vegetation and a pronounced diurnal cycle, the nocturnal cooling prevails due to the fact that stable conditions at night maintain the delayed response in temperature, whereas the daytime turbulent exchange amplifies it. For the tropics and boreal forests as well as high latitudes, the scheme tends to warm the system.

scholarly journals Use of microwave remote sensing data to monitor spatio temporal characteristics of surface soil moisture at local and regional scales

2005 ◽  
Vol 5 ◽  
pp. 49-56 ◽  
Author(s):  
A. Löw ◽  
R. Ludwig ◽  
W. Mauser
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Electromagnetic Waves ◽  
Regional Scale ◽  
Soil Layer ◽  
Remote Sensing Data ◽  
Microwave Remote Sensing ◽  
Electromagnetic Spectrum ◽  
Envisat Asar ◽  
Spatio Temporal

Abstract. Hydrologic processes, such as runoff production or evapotranspiration, largely depend on the variation of soil moisture and its spatial pattern. The interaction of electromagnetic waves with the land surface can be dependant on the water content of the uppermost soil layer. Especially in the microwave domain of the electromagnetic spectrum, this is the case. New sensors as e.g. ENVISAT ASAR, allow for frequent, synoptically and homogeneous image acquisitions over larger areas. Parameter inversion models are therefore developed to derive bio- and geophysical parameters from the image products. The paper presents a soil moisture inversion model for ENVISAT ASAR data for local and regional scale applications. The model is validated against in situ soil moisture measurements. The various sources of uncertainties, being related to the inversion process are assessed and quantified.

scholarly journals Diurnal Cycle of Passive Microwave Brightness Temperatures over Land at a Global Scale

2021 ◽  
Vol 13 (4) ◽  
pp. 817
Author(s):  
Zahra Sharifnezhad ◽  
Hamid Norouzi ◽  
Satya Prakash ◽  
Reginald Blake ◽  
Reza Khanbilvardi
Keyword(s):  
Land Cover ◽  
Diurnal Cycle ◽  
Land Surface ◽  
Global Scale ◽  
Passive Microwave ◽  
Surface Emissivity ◽  
Land Cover Types ◽  
Land Surface Emissivity ◽  
Microwave Imager ◽  
Microwave Sensors

Satellite-borne passive microwave radiometers provide brightness temperature (TB) measurements in a large spectral range which includes a number of frequency channels and generally two polarizations: horizontal and vertical. These TBs are widely used to retrieve several atmospheric and surface variables and parameters such as precipitation, soil moisture, water vapor, air temperature profile, and land surface emissivity. Since TBs are measured at different microwave frequencies with various instruments and at various incidence angles, spatial resolutions, and radiometric characteristics, a mere direct integration of them from different microwave sensors would not necessarily provide consistency. However, when appropriately harmonized, they can provide a complete dataset to estimate the diurnal cycle. This study first constructs the diurnal cycle of land TBs using the non-sun-synchronous Global Precipitation Measurement (GPM) Microwave Imager (GMI) observations by utilizing a cubic spline fit. The acquisition times of GMI vary from day to day and, therefore, the shape (amplitude and phase) of the diurnal cycle for each month is obtained by merging several days of measurements. This diurnal pattern is used as a point of reference when intercalibrated TBs from other passive microwave sensors with daily fixed acquisition times (e.g., Special Sensor Microwave Imager/Sounder, and Advanced Microwave Scanning Radiometer 2) are used to modify and tune the monthly diurnal cycle to daily diurnal cycle at a global scale. Since the GMI does not cover polar regions, the proposed method estimates a consistent diurnal cycle of land TBs at global scale. Results show that the shape and peak of the constructed TB diurnal cycle is approximately similar to the diurnal cycle of land surface temperature. The diurnal brightness temperature range for different land cover types has also been explored using the derived diurnal cycle of TBs. In general, a large diurnal TB range of more than 15 K has been observed for the grassland, shrubland, and tundra land cover types, whereas it is less than 5K over forests. Furthermore, seasonal variations in the diurnal TB range for different land cover types show a more consistent result over the Southern Hemisphere than over the Northern Hemisphere. The calibrated TB diurnal cycle may then be used to consistently estimate the diurnal cycle of land surface emissivity. Moreover, since changes in land surface emissivity are related to moisture change and freeze–thaw (FT) transitions in high-latitude regions, the results of this study enhance temporal detection of FT state, particularly during the transition times when multiple FT changes may occur within a day.

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.

Research on Improved Thermal Inertia Model for Retrieving Soil Moisture

2013 ◽  
Vol 295-298 ◽  
pp. 2075-2083
Author(s):  
Zhen Hua Liu ◽  
Ying Shi Zhao ◽  
Yue Ming Hu
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Regional Scale ◽  
Sensible Heat Flux ◽  
Thermal Inertia ◽  
Soil Surface ◽  
Temperature Inversion ◽  
Average Error ◽  
Inertia Model ◽  
Component Temperature

Soil moisture is one of the most important land environmental variables, relative to land surface climatology, hydrology, and ecology. A method to estimate soil moisture content from optical and thermal spectral in-formation of ASTER imagery based on thermal inertia is presented in this paper. Compared to models published previously, four improvements have been made: (1) as a key component of soil surface energy balance, the series two-layer is applied to solving soil latent and sensible heat flux in the better-covered vegetation area. And the Shuttleworth and Wallace (S-W) ET model is used to simulate soil latent flux; (2) because component temperature inversion is still an ill-posed problem, genetic inverse algorithm (GIA) is used to realize retrieval of component temperature; (3) in order to extend the scope of the thermal inertia model, B in the equation is derived from mechanism; (4) to eliminate partly atmospheric and the surface structure influence, the improved thermal inertia was normalized to fulfill the inversion of soil moisture. Taking YingKe green land in china for example, field experiment were carried out to validate the developed model. The method successfully estimated better-covered vegetation region surface soil moisture with an average error of 0.067. This model provides a new way of thinking about remote sensing thermal inertia methods to acquire regional-scale soil moisture.

scholarly journals Some practical notes on the land surface modeling in the Tibetan Plateau

2009 ◽  
Vol 6 (1) ◽  
pp. 1291-1320 ◽  
Author(s):  
K. Yang ◽  
Y.-Y. Chen ◽  
J. Qin
Keyword(s):  
Soil Moisture ◽  
Tibetan Plateau ◽  
Land Surface ◽  
Soil Surface ◽  
Bare Soil ◽  
Heat Fluxes ◽  
The Tibetan Plateau ◽  
Central Plateau ◽  
Alpine Meadows ◽  
Common Land Model

Abstract. The Tibetan Plateau is a key region of land-atmosphere interactions, as it provides an elevated heat source to the middle-troposphere. The Plateau surfaces are typically characterized by alpine meadows and grasslands in the central and eastern part while by alpine deserts in the western part. This study evaluates performance of three state-of-the-art land surface models (LSMs) for the Plateau typical land surfaces. The LSMs of interest are SiB2 (the Simple Biosphere), CoLM (Common Land Model), and Noah. They are run with default parameters at typical alpine meadow sites in the central Plateau and typical alpine desert sites in the western Plateau. The recognized key processes and modeling issues are as follows. First, soil stratification is a typical phenomenon beneath the alpine meadows, with dense roots and soil organic matters within the topsoil, and it controls the profile of soil moisture in the central and eastern Plateau; all models significantly under-estimate the soil moisture within the topsoil. Second, a soil surface resistance controls the surface evaporation from the alpine deserts but it has not been reasonably modeled in LSMs; a new scheme is proposed to determine this resistance from soil water content. Third, an excess resistance controls sensible heat fluxes from dry bare-soil or sparsely vegetated surfaces, and all LSMs significantly under-predict the ground-air temperature difference in the daytime. A parameterization scheme for this resistance has been shown effective to remove this bias.

scholarly journals Variational Estimation of Land–Atmosphere Heat Fluxes and Land Surface Parameters Using MODIS Remote Sensing Data

2013 ◽  
Vol 14 (2) ◽  
pp. 608-621 ◽  
Author(s):  
Chunlei Meng ◽  
Chaolin Zhang ◽  
Ronglin Tang
Keyword(s):  
Data Assimilation ◽  
Surface Temperature ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Soil Surface ◽  
Energy Balance Equation ◽  
Heat Fluxes ◽  
Area Index ◽  
Common Land Model ◽  
Modis Lai

Abstract A variational data assimilation algorithm for assimilating the land surface temperature (LST) into the Common Land Model (CLM) was implemented using the land surface energy balance equation as the adjoint physical constraint. In this data assimilation algorithm, the evaporative fractions of the soil and canopy were adjusted according to the remotely sensed surface temperature observations. This paper developed a very simple analytical algorithm to characterize the errors’ weighting matrices in the cost function. The leaf area index (LAI) retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) was also assimilated into CLM using the direct insertion method. The analysis results from the CLM with the LST assimilation algorithm compare well with MODIS and field observations for the Yucheng site, especially in daytime. On the basis of the histogram of the error of the LST, it can be concluded that after assimilation, the LST was greatly improved in comparison with the MODIS observations, especially in daytime. These results indicate that this surface temperature assimilation method is efficient and effective, even when only one time observational LST data point is available for each day, especially in daytime. The regional spatial patterns of evapotranspiration and soil surface moisture were also compared before assimilation on the basis of LAI data calculated using the empirical formula, before assimilation on the basis of MODIS LAI data, and after assimilation on the basis of MODIS LAI data.

Assimilation of SMAP-enhanced and SMAP/Sentinel-1A/B soil moisture data into land surface models

2020 ◽  
Author(s):  
Hyunglok Kim ◽  
Venkataraman Lakshmi ◽  
Sujay Kumar ◽  
Yonghwan Kwon
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Regional Scale ◽  
Land Surface Model ◽  
The United States ◽  
Heat Fluxes ◽  
Surface Model ◽  
Data Sets ◽  
Surface Models ◽  
Band Radiometer

<p>Prediction of water-related natural disasters such as droughts, floods, wildfires, landslides, and dust outbreaks on a regional-scale can benefit from the high-spatial-resolution soil moisture (SM) data of both satellite and modeled products. The reason is that the amount of surface SM controls in the partitioning of outgoing energy fluxes into latent and sensible heat fluxes.</p><p>Recently, NASA’s SMAP mission has been implemented, in order to provide 3-km and 1-km SM data from a combination of SMAP and Sentinel-1A/B observations along with 9- and 36-km SM data retrieved from an L-band radiometer brightness temperature (TB). The 3-km and 1-km SM products were produced by combining the Sentinel-1A/B C-band radar backscatter and SMAP radiometer TB observations.</p><p>In the present study, we assimilated SMAP-enhanced (9-km) and SMAP/Sentinel-1A/B SM (3-km and 1-km) products into a land surface model (LSM): SMAP-enhanced and SMAP/Sentinel-1A/B SM data were assimilated into Noah-MP3.6 LSM. Then, these products were evaluated against ground observations in the United States. Three DA products’ error characteristics were intercompared: (1) SMAP-enhanced 9-km DA, (2) SMAP/Sentinel-1A/B 3-km DA and (3) SMAP/Sentinel-1A/B 1-km DA.</p><p>When SMAP and SMAP/Sentinel SM data sets were assimilated into LSM, the R- and ubRMSE values for 9-, 3-, and 1-km SM data were greatly improved.</p>

scholarly journals How Well Can Land-Surface Models Represent the Diurnal Cycle of Turbulent Heat Fluxes?

2021 ◽  
Vol 22 (1) ◽  
pp. 77-94
Author(s):  
Maik Renner ◽  
Axel Kleidon ◽  
Martyn Clark ◽  
Bart Nijssen ◽  
Marvin Heidkamp ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Diurnal Variation ◽  
Diurnal Cycle ◽  
Land Surface ◽  
Heat Fluxes ◽  
Turbulent Heat ◽  
Phase Lag ◽  
Land Surface Models ◽  
Turbulent Heat Exchange ◽  
Surface Models

AbstractThe diurnal cycle of solar radiation represents the strongest energetic forcing and dominates the exchange of heat and mass of the land surface with the atmosphere. This diurnal heat redistribution represents a core of land–atmosphere coupling that should be accurately represented in land surface models (LSMs), which are critical parts of weather and climate models. We employ a diagnostic model evaluation approach using a signature-based metric that describes the diurnal variation of heat fluxes. The metric is obtained by decomposing the diurnal variation of surface heat fluxes into their direct response and the phase lag to incoming solar radiation. We employ the output of 13 different LSMs driven with meteorological forcing of 20 FLUXNET sites (PLUMBER dataset). All LSMs show a poor representation of the evaporative fraction and thus the diurnal magnitude of the sensible and latent heat flux under cloud-free conditions. In addition, we find that the diurnal phase of both heat fluxes is poorly represented. The best performing model only reproduces 33% of the evaluated evaporative conditions across the sites. The poor performance of the diurnal cycle of turbulent heat exchange appears to be linked to how models solve for the surface energy balance and redistribute heat into the subsurface. We conclude that a systematic evaluation of diurnal signatures is likely to help to improve the simulated diurnal cycle, better represent land–atmosphere interactions, and therefore improve simulations of the near-surface climate.

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