scholarly journals Putting the "vap" into evaporation

2007 ◽  
Vol 11 (1) ◽  
pp. 210-244 ◽  
Author(s):  
W. J. Shuttleworth
Keyword(s):  
Land Surface ◽  
Field Experiments ◽  
Global Climate Models ◽  
Eddy Correlation ◽  
Turbulence Theory ◽  
Future Research ◽  
Correlation Technique ◽  
Theoretical Understanding ◽  
Near Surface ◽  
Made In

Abstract. In the spirit of the Special Issue of HESS to which it contributes, this paper documents the origin and development of the science of natural evaporation from land surfaces over the last 30–35 years, since the symposium A View from the Watershed was held to commemorate the opening of the new Institute of Hydrology (IH) building in 1973. Important subsequent technical progress includes the ability to measure routinely the diurnal cycle of near-surface meteorological variables using automatic weather stations, and of surface energy and momentum exchanges using automated implementations of the Bowen Ratio/Energy Budget technique and the Eddy Correlation technique, along with the capability to estimate the "fetch" for which these measurements apply. These improvements have been complemented by new methods to measure the separate components of evaporation, including: the interception process using randomly relocated below-canopy gauges, transpiration fluxes from individual leaves/shoots using porometers and from plants/plant components using stem-flow gauges and soil evaporation using micro-lysimeters and soil moisture depletion methods. In recent years progress has been made in making theory-based area-average estimates of evaporation using scintillometers, and model-based area-average estimates by assembling many streams of relevant data into Land Data Assimilation Systems. Theoretical progress has been made in extending near-surface turbulence theory to accommodate the effect of the "excess" boundary layer resistance to leaf-to-air transfer of energy and mass fluxes relative to that for momentum, and to allow for observed shortcoming in stability factors in the transition layer immediately above vegetation. Controversy regarding the relative merits of multi-layer model and "big leaf" representations of whole-canopy exchanges has been resolved in favour of the latter approach. Important gaps in the theory of canopy-atmosphere interactions have been filled, including recognising the need, separately, to represent dry-canopy and wet-canopy evaporation in models and the capability to describe wet-to-dry canopy transitions as well as the ability to describe sparse vegetation canopies which only partly cover the underlying soil. There is progress in methods of estimating crop water requirements, but an important recommendation of this paper is that this progress should continue by introducing use of an effective stomatal resistance rather than crop factors. The paper draws attention to relevant theoretical insight on this issue. Progress in theoretical understanding of evaporation processes has been used in the creation of numerous Land Surface Parameterisations (LSPs), the models used to represent land-surface interaction in climate and weather forecast models, and there have been important advances in describing the behaviour of plant stomata in LSPs. A major investment over the last 25 years in conducting Large-Scale Field Experiments, the better to measure, understand and model coupled land-surface/atmosphere interactions, has resulted in improvements in the capabilities of global climate models and the ability of mesoscale meteorological models to describe the enhanced circulation resulting from different forms of land-surface heterogeneity. Progress in understanding why early equations for potential evapotranspiration can be adequate in certain conditions is reviewed. The paper concludes with recommendations for future research.

scholarly journals Calculating the turbulent fluxes in the atmospheric surface layer with neural networks

2018 ◽  
Author(s):  
Lukas Hubert Leufen ◽  
Gerd Schädler
Keyword(s):  
Land Surface ◽  
Field Experiments ◽  
Climate Models ◽  
Similarity Theory ◽  
Turbulent Fluxes ◽  
Global Climate Models ◽  
Surface Model ◽  
Time Step ◽  
One Dimensional ◽  
Stability Functions

Abstract. The turbulent fluxes of momentum, heat and water vapour link the Earth's surface with the atmosphere. The correct modelling of the flux interactions between these two systems with very different time scales is therefore vital for climate (resp. Earth system) models. Conventionally, these fluxes are modelled using Monin–Obukhov similarity theory (MOST) with stability functions derived from a small number of field experiments; this results in a range of formulations of these functions and thus also in the flux calculations; furthermore, the underlying equations are non-linear and have to be solved iteratively at each time step of the model. For these reasons, we tried here a different approach, namely using an artificial neural network (ANN) to calculate the fluxes resp. the scaling quantities u* and θ*, thus avoiding explicit formulas for the stability functions. The network was trained and validated with multi-year datasets from seven grassland, forest and wetland sites worldwide using the Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton backpropagation algorithm and six-fold cross validation. Extensive sensitivity tests showed that an ANN with six input variables and one hidden layer gave results comparable to (and in some cases even slightly better than) the standard method. Similar satisfying results were obtained when the ANN routine was implemented in a one-dimensional stand alone land surface model (LSM), opening the way to implementation in three-dimensional climate models. In case of the one-dimensional LSM, no CPU time was saved when using the ANN version, since the small time step of the standard version required only one iteration in most cases. This could be different in models with longer time steps, e.g. global climate models.

scholarly journals Quantifying the added value of convection-permitting climate simulations in complex terrain: a systematic evaluation of WRF over the Himalayas

2017 ◽  
Vol 8 (3) ◽  
pp. 507-528 ◽  
Author(s):  
Ramchandra Karki ◽  
Shabeh ul Hasson ◽  
Lars Gerlitz ◽  
Udo Schickhoff ◽  
Thomas Scholten ◽  
...  
Keyword(s):  
Land Surface ◽  
Regional Scale ◽  
Wrf Model ◽  
Global Climate Models ◽  
Added Value ◽  
Systematic Evaluation ◽  
Cold Bias ◽  
Near Surface ◽  
Monsoonal Precipitation ◽  
High Elevations

Abstract. Mesoscale dynamical refinements of global climate models or atmospheric reanalysis have shown their potential to resolve intricate atmospheric processes, their land surface interactions, and subsequently, realistic distribution of climatic fields in complex terrains. Given that such potential is yet to be explored within the central Himalayan region of Nepal, we investigate the skill of the Weather Research and Forecasting (WRF) model with different spatial resolutions in reproducing the spatial, seasonal, and diurnal characteristics of the near-surface air temperature and precipitation as well as the spatial shifts in the diurnal monsoonal precipitation peak over the Khumbu (Everest), Rolwaling, and adjacent southern areas. Therefore, the ERA-Interim (0.75°) reanalysis has been dynamically refined to 25, 5, and 1 km (D1, D2, and D3) for one complete hydrological year (October 2014–September 2015), using the one-way nested WRF model run with mild nudging and parameterized convection for the outer but explicitly resolved convection for the inner domains. Our results suggest that D3 realistically reproduces the monsoonal precipitation, as compared to its underestimation by D1 but overestimation by D2. All three resolutions, however, overestimate precipitation from the westerly disturbances, owing to simulating anomalously higher intensity of few intermittent events. Temperatures are generally reproduced well by all resolutions; however, winter and pre-monsoon seasons feature a high cold bias for high elevations while lower elevations show a simultaneous warm bias. Unlike higher resolutions, D1 fails to realistically reproduce the regional-scale nocturnal monsoonal peak precipitation observed in the Himalayan foothills and its diurnal shift towards high elevations, whereas D2 resolves these characteristics but exhibits a limited skill in reproducing such a peak on the river valley scale due to the limited representation of the narrow valleys at 5 km resolution. Nonetheless, featuring a substantial skill over D1 and D2, D3 simulates almost realistic shapes of the seasonal and diurnal precipitation and the peak timings even on valley scales. These findings clearly suggest an added value of the convective-scale resolutions in realistically resolving the topoclimates over the central Himalayas, which in turn allows simulating their interactions with the synoptic-scale weather systems prevailing over high Asia.

scholarly journals Intercomparison of In Situ Sensors for Ground-Based Land Surface Temperature Measurements

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5268
Author(s):  
Praveena Krishnan ◽  
Tilden P. Meyers ◽  
Simon J. Hook ◽  
Mark Heuer ◽  
David Senn ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Field Experiments ◽  
Prediction Models ◽  
Weather Prediction ◽  
Surface Air Temperature ◽  
Near Surface ◽  
Oak Ridge

Land surface temperature (LST) is a key variable in the determination of land surface energy exchange processes from local to global scales. Accurate ground measurements of LST are necessary for a number of applications including validation of satellite LST products or improvement of both climate and numerical weather prediction models. With the objective of assessing the quality of in situ measurements of LST and to evaluate the quantitative uncertainties in the ground-based LST measurements, intensive field experiments were conducted at NOAA’s Air Resources Laboratory (ARL)’s Atmospheric Turbulence and Diffusion Division (ATDD) in Oak Ridge, Tennessee, USA, from October 2015 to January 2016. The results of the comparison of LSTs retrieved by three narrow angle broadband infrared temperature sensors (IRT), hemispherical longwave radiation (LWR) measurements by pyrgeometers, forward looking infrared camera with direct LSTs by multiple thermocouples (TC), and near surface air temperature (AT) are presented here. The brightness temperature (BT) measurements by the IRTs agreed well with a bias of <0.23 °C, and root mean square error (RMSE) of <0.36 °C. The daytime LST(TC) and LST(IRT) showed better agreement (bias = 0.26 °C and RMSE = 0.67 °C) than with LST(LWR) (bias > 1.1 and RMSE > 1.46 °C). In contrast, the difference between nighttime LSTs by IRTs, TCs, and LWR were <0.47 °C, whereas nighttime AT explained >81% of the variance in LST(IRT) with a bias of 2.64 °C and RMSE of 3.6 °C. To evaluate the annual and seasonal differences in LST(IRT), LST(LWR) and AT, the analysis was extended to four grassland sites in the USA. For the annual dataset of LST, the bias between LST (IRT) and LST (LWR) was <0.7 °C, except at the semiarid grassland (1.5 °C), whereas the absolute bias between AT and LST at the four sites were <2 °C. The monthly difference between LST (IRT) and LST (LWR) (or AT) reached up to 2 °C (5 °C), whereas half-hourly differences between LSTs and AT were several degrees in magnitude depending on the site characteristics, time of the day and the season.

scholarly journals Calculating the turbulent fluxes in the atmospheric surface layer with neural networks

2019 ◽  
Vol 12 (5) ◽  
pp. 2033-2047
Author(s):  
Lukas Hubert Leufen ◽  
Gerd Schädler
Keyword(s):  
Land Surface ◽  
Field Experiments ◽  
Climate Models ◽  
Similarity Theory ◽  
Turbulent Fluxes ◽  
Global Climate Models ◽  
Surface Model ◽  
Time Step ◽  
One Dimensional ◽  
Better Than

Abstract. The turbulent fluxes of momentum, heat and water vapour link the Earth's surface with the atmosphere. Therefore, the correct modelling of the flux interactions between these two systems with very different timescales is vital for climate and weather forecast models. Conventionally, these fluxes are modelled using Monin–Obukhov similarity theory (MOST) with stability functions derived from a small number of field experiments. This results in a range of formulations of these functions and thus also in differences in the flux calculations; furthermore, the underlying equations are non-linear and have to be solved iteratively at each time step of the model. In this study, we tried a different and more flexible approach, namely using an artificial neural network (ANN) to calculate the scaling quantities u* and θ* (used to parameterise the fluxes), thereby avoiding function fitting and iteration. The network was trained and validated with multi-year data sets from seven grassland, forest and wetland sites worldwide using the Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton backpropagation algorithm and six-fold cross validation. Extensive sensitivity tests showed that an ANN with six input variables and one hidden layer gave results comparable to (and in some cases even slightly better than) the standard method; moreover, this ANN performed considerably better than a multivariate linear regression model. Similar satisfying results were obtained when the ANN routine was implemented in a one-dimensional stand-alone land surface model (LSM), paving the way for implementation in three-dimensional climate models. In the case of the one-dimensional LSM, no CPU time was saved when using the ANN version, as the small time step of the standard version required only one iteration in most cases. This may be different in models with longer time steps, e.g. global climate models.

Development and Testing of a Surface Flux and Planetary Boundary Layer Model for Application in Mesoscale Models

1995 ◽  
Vol 34 (1) ◽  
pp. 16-32 ◽  
Author(s):  
Jonathan E. Pleim ◽  
Aijun Xiu
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Planetary Boundary Layer ◽  
Land Surface ◽  
Field Experiments ◽  
Weather Prediction ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Global Climate Models ◽  
Pbl Model

Abstract Although the development of soil, vegetation, and atmosphere interaction models has been driven primarily by the need for accurate simulations of long-term energy and moisture budgets in global climate models, the importance of these processes at smaller scales for short-term numerical weather prediction and air quality studies is becoming more appreciated. Planetary boundary layer (PBL) development is highly dependent on the partitioning of the available net radiation into sensible and latent heat fluxes. Therefore, adequate treatmentof surface properties such as soil moisture and vegetation characteristics is essential for accurate simulation of PBL development, convective and low-level cloud processes, and the temperature and humidity of boundary layer air. In this paper, the development ofa simple coupled surface and PBL model, which is planned for incorporation into the Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM4/5), is described. The soil-vegetation model is based on a simple force-restore algorithm with explicit soil moisture and evapotranspiration. The PBL model is a hybrid of nonlocal closure for convective conditions and eddy diffusion for all other conditions. A one-dimensional version of the model has been applied to several case studies from field experiments in both dry desert-like conditions (Wangara) and moist vegetated conditions(First International Satellite Land Surface Climatology Project Field Experiment) to demonstrate the model's ability to realistically simulate surface fluxes as well as PBL development. This new surface-PBL model is currently being incorporated into the MM4-MM5 system.

scholarly journals Global Estimates of Land Surface Water Fluxes from SMOS and SMAP Satellite Soil Moisture Data

2020 ◽  
Vol 21 (2) ◽  
pp. 241-253 ◽  
Author(s):  
Morteza Sadeghi ◽  
Ardeshir Ebtehaj ◽  
Wade T. Crow ◽  
Lun Gao ◽  
Adam J. Purdy ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Groundwater Resources ◽  
Water Flux ◽  
Mass Conservation ◽  
Surface Flux ◽  
Richards Equation ◽  
Future Research ◽  
Near Surface ◽  
Net Water Flux

AbstractIn-depth knowledge about the global patterns and dynamics of land surface net water flux (NWF) is essential for quantification of depletion and recharge of groundwater resources. Net water flux cannot be directly measured, and its estimates as a residual of individual surface flux components often suffer from mass conservation errors due to accumulated systematic biases of individual fluxes. Here, for the first time, we provide direct estimates of global NWF based on near-surface satellite soil moisture retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) satellites. We apply a recently developed analytical model derived via inversion of the linearized Richards’ equation. The model is parsimonious, yet yields unbiased estimates of long-term cumulative NWF that is generally well correlated with the terrestrial water storage anomaly from the Gravity Recovery and Climate Experiment (GRACE) satellite. In addition, in conjunction with precipitation and evapotranspiration retrievals, the resultant NWF estimates provide a new means for retrieving global infiltration and runoff from satellite observations. However, the efficacy of the proposed approach over densely vegetated regions is questionable, due to the uncertainty of the satellite soil moisture retrievals and the lack of explicit parameterization of transpiration by deeply rooted plants in the proposed model. Future research is needed to advance this modeling paradigm to explicitly account for plant transpiration.

scholarly journals Weakening and Shifting of the Saharan Shallow Meridional Circulation during Wet Years of the West African Monsoon

2017 ◽  
Vol 30 (18) ◽  
pp. 7399-7422 ◽  
Author(s):  
Ravi Shekhar ◽  
William R. Boos
Keyword(s):  
Surface Pressure ◽  
Land Surface ◽  
Meridional Circulation ◽  
Surface Flow ◽  
Global Climate Models ◽  
Near Surface ◽  
Low Level ◽  
Wide Range ◽  
Sahel Rainfall ◽  
Poleward Shift

Abstract The correlation between increased Sahel rainfall and reduced Saharan surface pressure is well established in observations and global climate models and has been used to imply that increased Sahel rainfall is caused by a stronger shallow meridional circulation (SMC) over the Sahara. This study uses two atmospheric reanalyses to examine interannual variability of Sahel rainfall and the Saharan SMC, which consists of northward near-surface flow across the Sahel into the Sahara and southward flow near 700 hPa out of the Sahara. During wet Sahel years, the Saharan SMC shifts poleward, producing a drop in low-level geopotential and surface pressure over the Sahara. Statistically removing the effect of the poleward shift from the low-level geopotential eliminates significant correlations between this geopotential and Sahel precipitation. As the Saharan SMC shifts poleward, its midtropospheric divergent outflow decreases, indicating a weakening of its overturning mass flux. The poleward shift and weakening of the Saharan SMC during wet Sahel years is reproduced in an idealized model of West Africa; a wide range of imposed sea surface temperature and land surface albedo perturbations in this model produce a much larger range of SMC variations that nevertheless have similar quantitative associations with Sahel rainfall, as in the reanalyses. These results disprove the idea that enhanced Sahel rainfall is caused by strengthening of the Saharan SMC. Instead, these results are consistent with the hypothesis that a stronger SMC inhibits Sahel rainfall, perhaps by advecting midtropospheric warm and dry air into the precipitation maximum.

scholarly journals The AACES field experiments: SMOS calibration and validation across the Murrumbidgee River catchment

2012 ◽  
Vol 16 (6) ◽  
pp. 1697-1708 ◽  
Author(s):  
S. Peischl ◽  
J. P. Walker ◽  
C. Rüdiger ◽  
N. Ye ◽  
Y. H. Kerr ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Field Experiments ◽  
Spectral Characteristics ◽  
Winter Season ◽  
Ancillary Data ◽  
Area Index ◽  
Near Surface ◽  
River Catchment ◽  
Calibration And Validation

Abstract. Following the launch of the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission on 2 November 2009, SMOS soil moisture products need to be rigorously validated at the satellite's approximately 45 km scale and disaggregation techniques for producing maps with finer resolutions tested. The Australian Airborne Cal/val Experiments for SMOS (AACES) provide the basis for one of the most comprehensive assessments of SMOS data world-wide by covering a range of topographic, climatic and land surface variability within an approximately 500 × 100 km2 study area, located in South-East Australia. The AACES calibration and validation activities consisted of two extensive field experiments which were undertaken across the Murrumbidgee River catchment during the Australian summer and winter season of 2010, respectively. The datasets include airborne L-band brightness temperature, thermal infrared and multi-spectral observations at 1 km resolution, as well as extensive ground measurements of near-surface soil moisture and ancillary data, such as soil temperature, soil texture, surface roughness, vegetation water content, dew amount, leaf area index and spectral characteristics of the vegetation. This paper explains the design and data collection strategy of the airborne and ground component of the two AACES campaigns and presents a preliminary analysis of the field measurements including the application and performance of the SMOS core retrieval model on the diverse land surface conditions captured by the experiments. The data described in this paper are publicly available from the website: http://www.moisturemap.monash.edu.au/aaces.

scholarly journals Quantifying the added value of high resolution climate models: A systematic comparison of WRF simulations for complex Himalayan terrain

2017 ◽  
Author(s):  
Ramchandra Karki ◽  
Shabeh Hasson ◽  
Lars Gerlitz ◽  
Udo Schickhoff ◽  
Thomas Scholten ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Regional Scale ◽  
Wrf Model ◽  
Global Climate Models ◽  
Added Value ◽  
Cold Bias ◽  
Near Surface ◽  
Monsoonal Precipitation ◽  
High Elevations

Abstract. Mesoscale dynamical refinements of global climate models or atmospheric reanalysis have shown their potential to resolve the intricate atmospheric processes, their land surface interactions, and subsequently, realistic distribution of climatic fields in complex terrains. Given that such potential is yet to be explored within the central Himalayan region of Nepal, we investigate the skill of the Weather Research and Forecasting (WRF) model with different spatial resolutions in reproducing the spatial, seasonal and diurnal characteristics of the near-surface air temperature and precipitation, as well as, the spatial shifts in the diurnal monsoonal precipitation peak over the Khumbu (Everest), Rolwaling and adjacent southern areas. Therefore, the ERA-Interim (0.75°) reanalysis has been dynamically refined to 25, 5 and 1 km (D1, D2 and D3) for one complete hydrological year (Oct 2014–Sep 2015), using the one-way nested WRF model run with mild-nudging and parameterized convection for the outer but explicitly resolved convection for the inner domains. Our results suggest that D3 realistically reproduces the monsoonal precipitation, as compared to its underestimation by D1 but overestimation by D2. All three resolutions however overestimate precipitation from the westerly disturbances, owing to simulating anomalously higher intensity of few intermittent events. Temperatures are though generally well reproduced by all resolutions, winter and pre-monsoon seasons feature a high cold bias for high elevations while lower show a simultaneous warm bias. Contrary to higher resolutions, D1 fails to realistically reproduce the regional-scale nocturnal monsoonal peak precipitation observed at the Himalayan foothills and its diurnal shift towards high elevations, whereas D2 resolves these characteristics but exhibits a limited skill in reproducing such peak at the river valley scale due to the limited representation of the narrow valleys at 5 km resolution. Nonetheless, featuring a substantial skill over D1 and D2, D3 simulates almost realistic shapes of the seasonal and diurnal precipitation and the peak timings even at valley scales. These findings clearly suggest an added value of the convective scale resolutions in realistically resolving the topo-climates over the central Himalaya, which in turn allow simulating their interactions with the synoptic scale weather systems prevailing over High Asia.

A Study on Contribution of the Advective Heat Flux to the Energy Closure near the Land Surface in the Zoige Alpine Wetland

2020 ◽  
Author(s):  
Jun Wen ◽  
Xuancheng Lu ◽  
Yue Yang ◽  
Hui Tian ◽  
Wenhui Liu ◽  
...  
Keyword(s):  
Heat Flux ◽  
Land Surface ◽  
Energy Balance Equation ◽  
Eddy Correlation ◽  
Underlying Surface ◽  
Closure Rate ◽  
Near Surface ◽  
Alpine Wetland ◽  
The Difference ◽  
Flux Energy

&lt;p&gt;The energy non-closure near the land surface has been a key topic in the land surface processes research. &amp;#160;The energy closure rate is still not high even after considering heat storage and photosynthesis energy consumption, while the contribution of advective energy to the closure rate needs to be considered further under the non-uniform underlying surface. In this paper, the advective energy caused by thermal heterogeneity of underlying surface is calculated by using the energy budget data collected from the Flower-Lake observation site in the Zoige Alpine Wetland in 2017, and the contribution of thermal advection to energy closure near the ground is estimated. The result shows: In summer of 2017, the maximum value of the advective heat flux was 23.8w/m2 at the Zoige alpine wetland. When the contribution of advective heat flux is introduced into the energy balance equation, the energy closure rate increases from 72.0% to 79.4%. With considering the contribution of horizontal heat transfer, it has a certain effect on improving energy closure rate for the flat terrain and thermal inhomogeneous underlying surface. The near surface thermal inhomogeneity leads to the accumulation of heat, which is the basic reason for the heat advection to affect the energy closure rate, and also an important reason for the difference between the wetland characteristics of water and heat exchange of the wetland with the other regions.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Key &lt;/strong&gt;&lt;strong&gt;words&lt;/strong&gt;&lt;strong&gt;&amp;#65306;&lt;/strong&gt;Alpine wetland; eddy correlation; advective&amp;#160;heat flux; energy closure&amp;#160;rate; inhomogeneous&amp;#160;land&amp;#160;surface&lt;/p&gt;

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